Phenotypic and Genetic Characterization of a Near-Isogenic Line Pair: Insights into Flowering Time in Chickpea. 

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Adrian Perez-Rial, Alejandro Carmona, Latifah Ali, Josefa Rubio, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4002926/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Jul, 2024 Read the published version in BMC Plant Biology → Version 1 posted 11 You are reading this latest preprint version Abstract Background Cicer arietinum is a significant legume crop cultivated mainly in short-season environments, where early-flowering is a desirable trait to overcome terminal constraints. Despite its agricultural significance, the genetic control of flowering time in chickpea is not fully understood. In this study, we developed, phenotyped, re-sequenced and genetically characterized a pair of near-isogenic lines (NILs) with contrasting days to flowering to identify candidate gene variants potentially associated with flowering time. Results In addition to days to flowering, noticeable differences in multiple shoot architecture traits were observed between the NILs. The re-sequencing data confirms that the NILs developed in this study serve as appropriate plant materials, effectively constraining genetic variation to specific regions and thereby establishing a valuable resource for future genetic and functional investigations in chickpea research. Leveraging bioinformatics tools and public genomic datasets, we identified homologs of flowering-related genes from Arabidopsis thaliana , including ELF3 and, for the first time in chickpea, MED16 and STO/BBX24 , with variants among the NILs. Analysis of the allelic distribution of these genes revealed their preservation within chickpea diversity and their potential association with flowering time. Variants were also identified in members of the ERF and ARF gene families. Furthermore, in silico expression analysis was conducted elucidating their putative roles in flowering. Conclusions While the gene CaELF3a is identified as a prominent candidate, this study also exposes new targets in chickpea, such as CaMED16b and LOC101499101 ( BBX24-like ), homologs of flowering-related genes in Arabidopsis , as well as ERF12 and ARF2 . The in silico expression characterization and genetic variability analysis performed could contribute to their use as specific markers for chickpea breeding programs. This study lays the groundwork for future investigations utilizing this plant material, promising further insights into the complex mechanisms governing flowering time in chickpea. Cicer arietinum early-flowering NILs sequencing SNPs Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background The domesticated chickpea ( Cicer arietinum L.) is an annual and self-pollinated legume belonging to the Papilionoideae subfamily. With an estimated genome size of ∽ 738 Mb (2 n = 2 x = 16), the reference genome CDC Frontier kabuli cultivar has been assembled into 530 Mb [1]. Chickpea is currently the second most cultivated grain legume globally, with a production of 18.1 million tons in 14.8 million ha, resulting in a yield of 1.22 t/ha in 2022 [2]. Despite its importance, global chickpea cultivation is mostly conducted in short-season environments that expose the crop to terminal stresses, consequently limiting its potential yield [3–5]. In Mediterranean and semi-arid environments, terminal drought and heat stand out as the primary causes of yield loss [6–9]. Conversely, in higher latitude areas like Canada, the growing season is affected by lower temperatures, delayed maturation, and an increased risk of frost damage [10–13]. In response to these challenges, early-flowering emerges as a desirable trait for chickpea, serving as an effective escape strategy in various environmental conditions [5, 8, 10, 11, 14]. The flowering time is also linked to fundamental decisions made by the plant about when and how to allocate resources and is therefore involved in a complex web of bidirectional interactions with other developmental processes. Thus, although the defining feature of the vegetative-to-reproductive transition is the conversion of meristems to produce flowers rather than vegetative buds, this is also accompanied by significant changes in a wide range of other developmental traits (e.g. stem elongation and lateral branching). However, despite increasing interest, the genetic control of this complex trait remains unclear [15–17]. Chickpea, along with notable legumes such as pea, lentil, and faba bean, belongs to the galegoid clade. Members of this clade are from temperate regions and exhibit long-day plant characteristics in terms of flowering control. In contrast, legumes in the phaseoloid clade, including soybean, cowpea, pigeon pea, and common bean, are mainly from lower latitudes and are identified as short-day plants [15]. Much of our current understanding of flowering time regulation originates from studies on the model long-day species Arabidopsis thaliana (L.) Heynh . , where over 300 flowering time genes, including key regulators, have been identified [18]. These genes are involved in seven major pathways governing flowering: 'photoperiod/circadian clock,' 'vernalization,' 'aging,' 'ambient temperature,' 'hormones,' 'sugar,' and 'autonomous' pathways. The key signaling integrator molecule responsible for promoting flowering is encoded by the FLOWERING LOCUS T ( FT ) gene in leaves. Upon induction, the FT protein migrates from the leaves to the shoot apex, where it activates meristem identity genes [19, 20]. In contrast, the product of the TERMINAL FLOWER1 ( TFL1 ) gene functions as an 'anti-florigen', suppressing meristem identity genes [21]. While gene families and pathways controlling flowering time in A. thaliana are generally conserved in legumes, three main differences stand out [15, 17, 22, 23]. First, variations in the number of gene copies in legumes, where numerous examples of duplication and loss events reflect the evolutionary history after the divergence of Arabidopsis and legume lineages [24]. Legumes, for instance, possess multiple FT genes organized in three subclades and multiple TFL1 genes [15, 16, 25, 26]. Second, the absence of FLC orthologs in the galegoid legume species, such as chickpea, where the vernalization response mechanism remains unknown. However, FT genes appear to be major targets of vernalization as in A. thaliana [17, 25–28]. Third, the distinct roles of CO orthologous genes in legumes, do not seem to play a central role in integrating photoperiod signaling and circadian rhythms, as observed in A. thaliana [29, 30]. Traditionally, classical genetic studies have identified four major Mendelian loci that control flowering time in chickpea. Recessive alleles at these loci confer early-flowering [31]. These loci have been designated as Early flowering1 ( Efl1 ) to Efl4 , with corresponding mutant alleles labeled as efl1 to efl4 . The initial identification of these loci occurred in specific lines: ICCV 2 ( Efl1 ; [32]), ICC 5010 ( Efl2 ; [33]), BGD-132 ( Efl3 ; [34]), and ICC 16641 and ICC 16644 ( Efl4 ;[31]). Studies have shown that these flowering time genes are non-allelic [31, 34]. In addition, numerous quantitative trait loci (QTLs) associated with flowering time have been identified through linkage analysis, with some predicted to possess minor effects. These QTLs are distributed across various linkage groups (LG), including LG1, LG2, LG3, LG4, LG5, LG6, and LG8, as reported in studies using different parental lines [7, 35–39]. Despite the identification of these major loci and QTLs, the correspondence and characterization of the underlying genes have been limited to date. [40] proposed that the Elf1 locus corresponds to CaELF3a , an ortholog of Arabidopsis ELF3 mapped on Ca5, although the possibility of other nearby genes contributing to the Efl1 phenotype cannot be definitively excluded. For the QTL in LG3, the cluster FTa1 / a2 / c has been identified as the strongest candidate [16]. To deepen our understanding of the genes governing early-flowering phenotypes in chickpea, the development of near-isogenic lines (NILs) emerges as a promising strategy. Pairs of NILs, designed to manifest variation in specific agronomic traits, have been proven invaluable for fine mapping of QTLs and characterizing underlying genes [41]. NILs are distinguished by differences in small genomic sections, effectively minimizing background genetic noise. This plant material facilitates the assessment of allelic variation at both phenotypic and molecular levels, enabling comparisons at genomic or transcriptomic scales. The characteristics of NILs not only provide a focused study of flowering time but also offer accessibility for exploring interconnected traits. In chickpea, NILs have successfully been applied in studies on growth habit [42], plant height [43], double/single pod [44, 45] , nodulation [46], Fusarium wilt resistance [47–49] as well as flowering time [50]. Advances in next-generation sequencing (NGS) technologies have enabled the generation of large-scale sequencing and genotyping data sets in chickpea, resulting in the creation of valuable genomic resources since the first sequenced genome [1]. One notable achievement is the comprehensive mapping of variation acquired through the sequencing of 3,171 cultivated and 195 wild accessions alongside phenotypic data [51], now publicly accessible via the CicerSeq repository. Additional resources like Atlas GEO chickpea complement these datasets, providing a robust foundation for comprehensive investigations into gene function and transcriptional pattern expression in various tissues through chickpea development [52]. This extensive dataset serves as a vital resource for genomic and diversity research, facilitating a deeper molecular-level understanding of traits essential for enhancing chickpea cultivation. In this study, we identified and characterized candidate genes for chickpea flowering through a combined phenotypic and genetic analysis involving re-sequencing of a pair of NILs. Utilizing bioinformatics approaches and public genomic datasets, we identified homologs to flowering-related genes in A. thaliana with variants among the NILs, including ELF3 , and, for the first time, MED16 and STO/BBX24 in chickpea. We also analyzed the allelic diversity of these novel genes and their conservation within chickpea diversity. Additionally, transcriptomic data in chickpea enable us to explore in silico expression profiles for candidate genes in vegetative tissues such as leaves and shoot apical meristem, crucial for promoting flowering, as well as in early flowering stages. Materials and Methods Plant materials and NIL development A pair of chickpea NILs distinguished by flowering time was employed: an early-flowering NIL (NF10/82-E) and a late-flowering NIL (NF10/82-L). These NILs were developed from residual heterozygosity in a F 6:7 recombinant inbred line (RIL) named RIP10–82 derived from the intraspecific cross JG62 x ILC72. This methodology is an alternative method to the traditional approach involving consecutive backcrossing followed by self-pollination, known for its effectiveness in self-pollinated crops as chickpea [53]. The parental line JG62 (syn. ICC4951) is an Indian early-flowering desi landrace maintained by ICRISAT (International Crops Research Institute for the Semi-Arid Tropics), while ILC72 (syn. CPAM88) is a late-flowering kabuli type from the former Soviet Union maintained by ICARDA (International Center for Agricultural Research in the Dry Areas). Descendants from the early-flowering individuals of RIP10–82 consistently showed early-flowering phenotype, while some from late-flowering individuals exhibited segregation for this trait. This observation suggests that early-flowering should be a recessive trait in this context. To develop the NILs, seeds from an individual heterozygous plant were collected and sowed, designated as RIP10–82/P1 ( Fig. 1 ). Subsequently, a heterozygous descendant for flowering time was selected to proceed with (RIP10–82/P1/P3). Two non-segregating progeny were selfed for both early (RIP10–82/P1/P3/P8) and late-flowering (RIP10–82/P1/P3/P12). One descendant from each one was selfed once more and considered as NILs for this trait: an early-flowering line (RIP10-82/P1/P3/P8/P5, called NF10/82-E) and a late-flowering line (RIP10-82/P1/P3/P12/P13, called NF10/82-L). This means that the NILs were obtained after at least 11 generations of self-fertilization (seven until the RIP10-82 line was obtained and four more afterwards). Growth Conditions and Phenotypic Characterization Phenotypic characterization of the pair of NILs involved the assessment of 15 plants each, sown on March 28 2022, in the field at the IFAPA site in Córdoba, Spain (latitude/longitude/altitude: 37º53’N/4º47’W/117m). The plants were arranged in two independent rows, 2.25 m apart. Days to flowering (DTF) were recorded from seedling emergence to the opening of the first flower for each plant. Subsequently, the plants were harvested, dried and phenotyped for six morphological traits: plant weight (PW, g), plant height (PH, cm), internodes per plant (IPP), internode length (IL, cm), total number of branches per plant (BPP) and the number of branches in the first three nodes (BF). Additionally, a branching index (BI) was calculated, defined as the ratio of total branch length to plant length, to normalize differences in general vigor. Statistical significance was assessed using a t-test ( P < 0.05) in RStudio v.4.2.0. DNA extraction and Resequencing Total genomic DNA was isolated from young leaves of an individual NF10/82-E and an individual NF10/82-L using the DNeasy Plant Mini Kit (Qiagen) according to the manufacturer’s instructions. DNA samples from both NILs were sequenced by Centro Nacional de Análisis Genómico (CNAG-CRG; Barcelona, Spain) using an Illumina HiSeq2000 instrument with 50x coverage. Variants (SNPs and InDels) were identified against the chickpea reference genome (CDC Frontier genome, assembly ASM33114v1; NCBI). Variants with a read depth < 10 in at least one sample were not considered. Genetic Characterization The sequence differences detected between the NILs were analyzed, distinguishing between homozygous and heterozygous positions. The identified variants (SNPs and InDels) were filtered including only those passing all quality criteria or failing to meet only one criterion. These criteria are summarized in the FILTER comments in the VCF v.4.2 file containing the variant sequencing report of the NILs (accession number PRJEB73790; European Variation Archive at EMBL-EBI). Our selection was focused exclusively on homozygous variants confidently assigned to chromosomes, determined by the absence of segregation for flowering time observed in the phenotypic data collected at the end of NIL development. Theoretical impact assessment of variants was conducted using snpEff v.4.x [54], categorizing them as modifier, low, moderate, or high impact. To assess intragenic variants, all variants with an annotation impact other than "intergenic region", "upstream gene variant" or "downstream gene variant" were selected. These variants located in loci were classified by their specific region type as mRNA (coding sequence (CDS), exon or intron), lncRNA, rRNA, snRNA, snoRNA or pseudogene/miscellaneous RNA variant according to the C. arietinum GFF data information from NCBI using a custom R script (GitHub/AGR114molecularBreeding/chickpea/SNP_PosType). The density of variants in chromosomes was visualized using SRplot tools [55]. For protein-coding genes, protein accession was obtained using the refseqR package v.1.0.1 [56]. The Gene Ontology Tool Blast2GO v.6.0 [57] was employed to assign GO identities for functional annotation of the protein-coding genes with variants in exons or CDS. The following settings were used: BLASTp against NCBI nr database, E -value filter ≤ 10 -3 , HSP length cutoff of 33, maximum 10 BLAST hits per sequence and annotation cutoff of 33. Furthermore, to enhance the annotation ability, InterProScan was conducted, results were merged to GO annotations and plant GO Slim were obtained. An enrichment analysis calculated via Fisher’s exact test was performed to compare the functional annotations of the protein-coding genes with variants in exons or CDS against the whole chickpea genome annotation. Candidate Genes From the functional annotation, candidate genes were selected based on the enriched GO terms derived from a dataset of 306 flowering-related genes in A. thaliana , obtained from the FLOR-ID database [18]. The Go Term Enrichment for Plants tool, available through TAIR and powered by PANTHER [58], was employed for this analysis. Only those child GO Slim terms within each ancestor GO Slim were considered ( Additional file 2 ). Additionally, a reciprocal BLASTp was performed to identify whether any of the candidate genes showed homology to those included in the A. thaliana FLOR-ID dataset. In silico Expression Analysis The CDS of the candidate genes were utilized to identify their corresponding matches through reciprocal BLASTn in the chickpea expression atlas during development, available in the NCBI GEO database under the accession GSE147831 [52]. The expression atlas data were then imported, classified and analyzed using a custom R script to convert the FPKM data into TPM, facilitating comparison between different tissues and genes (GitHub/AGR114molecularBreeding/chickpea/GEO). All matched genes were examined for their in silico expression pattern using data from seven different chickpea tissues: young leaf (YL), mature leaf (ML), four stages of flower-bud (FB1–4) and shoot apical meristem (SAM). The heatmap visualization plot for expression level was obtained using SRplot tools with complete-linkage cluster method and Euclidean distance [55]. Results Phenotypic Characterization The traits recorded for grown-field NILs are shown in Table 1 . The difference in flowering time between NILs was about 14 days (44.4 ± 2.8 days for NF10/82-E and 58.0 ± 1.1 days for NF10/82-L). NF10/82-E exhibited reduced vegetative biomass characterized by decreased branching (lower total number of branches and fewer branches in the initial nodes) and shorter plant height with fewer internodes ( Fig. 2 ). Nevertheless, its internode length exceeded that of the late-flowering ones (2.47 ± 0.17 for NF10/82-E vs. 2.23 ± 0.10 for NF10/82-L). Table 1 Phenotypic characterization of the NILs (Mean ± SD) Genotype DTF PW PH IPP IL BPP BF BI NF10/82-E 44.4 ± 2.8 3.79 ± 1.85 52.5 ± 6.1 22.3 ± 2.6 2.47 ± 0.17 3.91 ± 2.26 0.73 ± 0.65 1.25 ± 0.67 NF10/82-L 58.0 ± 1.1 9.14 ± 2.62 66.6 ± 3.8 30.9 ± 2.4 2.23 ± 0.10 21.5 ± 6.6 2.57 ± 1.02 6.01 ± 1.69 t-test *** *** *** *** ** *** *** *** Significant difference Student’s t-test (ns: non-significant, *0.01 < P ≤ 0.05, **0.001 < P ≤ 0.01, ***P ≤ 0.001). DTF, Days to flowering; PW, Plant weight (g); PH, Plant height (cm); IPP, Internodes per plant; IL, Internode length (cm); BPP, Branches per plant; BF, Branches in the first three nodes; BI, Branching index Genetic Characterization The sequencing data confirmed a high degree of similarity between NILs. A total of 393,670,345 positions were read, revealing 120,441 different positions constituting the detected variants ( Additional file 1 ). This indicates that the NILs differ in only 0.03% of positions between them. Additionally, for NF10/82-L, 209,276 heterozygous positions were detected, and for the NF10/82-E, 200,084, corresponding to an observed heterozygosity of 0.053% and 0.051%, respectively. Both lines underwent at least 11 generations of self-fertilization during their development ( Fig. 1 ), so the expected residual heterozygosity is 0.098% deduced from Mendelian Genetics for self-fertilizing generations. The observed values being lower than expected are reasonable because the segregating population from which these lines were obtained may have undergone prior refreshing processes to maintain seed viability. In other words, it could have undergone additional generations of self-fertilization to maintain a suitable number of viable seeds before the actual process of obtaining the NILs. Approximately 64% of the detected variants were successfully mapped to chromosomes (77,170), of which 45,481 met the applied quality criteria ( Table 2 ). Only 15,690 variants were homozygous, with 4,932 being intragenic in 432 loci (HHQ-I variants; Additional file 3 ). There are 37 variants expected to affect two loci simultaneously. Among all HHQ-I variants detected on chromosomes, 1,610 are located in CDS or exons (HHQ-I-C/E variants; 849 in CDS, 758 in exon regions and three are located in both depending on DNA strand), affecting 246 protein-coding genes ( Table 2 ). Additionally, there are 176 variants located in non-protein-coding RNA genes, including 17 uncharacterized lncRNA (168 variants), two snRNA (4), one snoRNA (1) and three tRNA (3) ( Additional file 4) . Finally, 199 variants are positioned in pseudogenes or miscellaneous RNA. Notably, six variants are classified as intragenic, affecting LOC101491595, but in a region devoid of additional features according to the GFF data of C. arietinum . As explained by NCBI staff, this discrepancy is attributed to an artificial extension of this locus resulting from an error in the annotation of the non-protein-coding transcript XR_003470270.1 (personal communication). Consequently, XR_003470270.1 has recently been suppressed by NCBI RefSeq staff. The distribution of the HHQ-I and HHQ-I-C/E variants did not follow a proportional pattern concerning chromosome size, nor was it uniform along the chromosomes ( Fig. 3 ). Most of them are positioned in a region at the beginning of chromosome 1 (Ca1: 1.78 – 3.15 Mb) and the end of chromosome 6 (Ca6: 57.2 – 58.8 Mb). These are the only two chromosomes with specific regions containing more than 200 variants per 1 Mb window. Notably, chromosome 3 lacks any HHQ-I variant. Table 2 Number of variants (SNPs and InDels) and protein-coding genes affected per chromosome in the pair of NILs Chr Size (Mb) Detected Variants HQ Variants HHQ Variants HHQ-I Variants HHQ-I-C/E Variants Protein-coding Genes with HHQ-I-C/E Ca1 48.36 31,790 23,428 12,585 4,185 1,334 165 Ca2 36.63 7,012 3,774 673 134 35 30 Ca3 39.99 5,311 2,095 9 0 0 0 Ca4 49.19 5,371 2,259 23 4 2 2 Ca5 48.17 6,843 2,936 106 17 4 4 Ca6 59.46 12,594 7,507 2,232 575 230 40 Ca7 48.96 6,598 2,625 15 3 1 1 Ca8 16.48 1,651 858 47 14 4 4 TOTAL 77,170 45,481 15,690 4,932 1,610 246 HQ, High-quality; HHQ, Homozygous high-quality; HHQ-I, Intragenic homozygous high-quality; HHQ-I-C/E, Intragenic homozygous high quality in CDS or exon of mRNA Functional annotation using Blast2GO was successfully performed on 216 out of the 246 coding genes affected by HHQ-I-C/E variants ( Additional file 5 ). The distribution of GO Slim terms among protein-coding genes across the ontologies of “molecular function”, “biological process”, and “cellular component” ( Fig. 4 ) revealed no enrichment compared to the entire chickpea annotated genome using Fisher's exact test ( P < 0.05). Candidate Genes Based on GO Slim enrichment analysis in A. thaliana for the FLOR-ID set of flowering-related genes, there are 146 genes affected by HHQ-I-C/E variants that have any of these enriched GO Slim terms (Additional file 6) . Among them, four genes seem to be homologous to those found in the FLOR-ID A. thaliana dataset according to the reciprocal BLASTp results. These genes are LOC101515142, LOC101489432 (also known as CaELF3a ), LOC101499101 and LOC101507442 ( Table 3 ). LOC101515142 (Ca1: 2,285,592 - 2,298,911, complement) is annotated as “Mediator of RNA polymerase II transcription subunit 16-like” ( MED16 ), an homologue of the A. thaliana MED16/SFR6 gene encoding a component of the Mediator complex involved in diversal aspects of gene expression regulation [59] . In chickpea, a second homologue is present on Ca6 (LOC101501202, Ca6: 16,660,218 - 16,679,432) without any detected variants between NILs. LOC101515142 is affected by 94 variants, from which 14 affect exon or CDS regions ( Table 3 ). Most alternative variant alleles are found in NF10/82-E, with only one detected in NF10/82-L (a 21 bp deletion located in an intron in Ca1: 2,297,103). This locus encodes six different isoforms, being affected by three variants in CDS with different impacts. For example, NF10/82-E has a 6 bp deletion (Ca6: 2,298,571) that affects two isoforms with a moderate impact (by the loss of two Glu), whereas another two transcriptional isoforms are affected in the 5’ UTR ( Additional file 7. Fig. S1a) . However, the other 11 HHQ-I-C/E variants affect all isoforms equally with low or modifier theoretical impacts. In any case, the high number of detected variants affecting this locus could have some implications for its functional activity. LOC101489432 ( CaELF3a , Ca5: 36,011,384 – 36,016,600, complement) is one of the two homologs of A. thaliana ELF3 identified in legumes, previously reported to be involved in the regulation of the circadian clock and to influence the flowering process in chickpea [40] . In this study, an 11 bp deletion located at Ca5: 36,016,064 was detected in NIL10/82-E. This deletion is predicted to affect the first exon of CaELF3a , resulting in six missense amino acids followed by a premature stop codon. Consequently, this alteration reduces the protein length from 699 to 13 amino acids ( Additional file 7. Fig. S1b ). The absence of other isoforms encoded by CaELF3a suggests a significant impairment in its functionality. Finally, two loci at the end of Ca6 are affected by HHQ-I-C/E variants. On one hand, LOC101499101 is a B-box finger protein homolog of STO/BBX24 , known to link the FRI/FLC and photoperiod/circadian clock pathways, affecting flowering time in A. thaliana [60] . On the other hand, LOC101507442 is a VRN1 - like transcription factor containing a B3 domain, encoding a DNA-binding protein involved in the vernalization pathway that represses FLC expression, thus promoting flowering [61] . Both loci are affected by only one SNP with modifier or low theoretical impact. LOC101499101 has a SNP affecting the 3’UTR ( Additional file 7. Fig. S1c) , while LOC101507442 has a SNP located in the third exon, influencing its two potential protein isoforms as a synonymous variant ( Additional file 7. Fig. S1d) . Table 3 Genes affected by HHQ-I-C/E variants that appear homologous to four genes included in the A. thaliana FLOR-ID dataset C. arietinum ID NCBI Homologous A. thaliana ID TAIR Number HHQ-I-C/E Variants Variant Position Ref (0) Alt (1) Variant Impacts NF10/82-L NF10/82-E LOC101515142 Mediator of RNA polymerase II transcription subunit 16-like (Ca1: 2,285,592 – 2,298,911, complement) AT4G04920 14 (+ 80 in intron regions) 2,285,696 C CAT 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,285,879 G A 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,286,112 G GA 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,286,256 A T 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,286,460 C T 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,286,488 A G 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,288,143 C T synonymous_variant [LOW], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,291,280 T G synonymous_variant [LOW], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,292,486 A C synonymous_variant [LOW], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,292,528 G A synonymous_variant [LOW], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,294,335 A G synonymous_variant [LOW], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,298,490 G T synonymous_variant [LOW], 5_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,298,571 CTCTTCT C disruptive_inframe_deletion [MODERATE], 5_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 2,298,634 T A synonymous_variant [LOW], 5_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 LOC101489432 protein EARLY FLOWERING 3a (Ca5: 36,011,384 – 36,016,600, complement) AT2G25930 1 36,016,064 ATCATCATCTTC A frameshift_variant [HIGH], non_coding_transcript_exon_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 0/0 1/1 LOC101499101 B-box zinc finger protein 24 (Ca6: 57,549,424 – 57,552,323, complement) AT1G06040 1 57,549,449 T A 3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER] 1/1 0/0 LOC101507442 B3 Domain- containing transcription factor VRN1-like (Ca6: 57,717,926 – 57,721,229) AT3G18990 1 57,720,344 C T synonymous_variant [LOW], non_coding_transcript_variant [MODIFIER] 0/0 1/1 The 11 bp deletion in CaELF3a seems to be distributed across a small proportion of chickpea germplasm, with only two haplotypes identified that specifically differ in this deletion [40] . To gain insights into the genetic variability and conservation of the variants detected in LOC101515142, LOC101499101 and LOC101507442 along chickpea diversity, we analyzed the different accessions represented in the public repository CicerSeq, which contains information about the SNPs detected in cultivated chickpea [51] . Among the 94 variants detected for LOC101515142 in the pair of NILs, 68 are SNPs, with 51 positions registered in CicerSeq. The contrasting haplotypes for LOC101515142 detected in NILs are highly conserved along the 3,171 cultivated accessions for C.arietinum registered in the pangenome ( Fig. 5 and Additional file 8 ). The NF10/82-L haplotype is conserved in approximately 70% of the accessions (H1), while the NF10/82-E is present in about 23.6% (H2). Interestingly, ~3.8% of accessions have the NF10/82-L haplotype except for one SNP variant located in Ca1: 2,295,317 (in the intron region of LOC101515142 ; H3), and 2% of accessions have an intermediate haplotype (36/51 SNPs like NF10/82-L haplotype; H4). For the SNPs in LOC101499101 (T/A) and LOC101507442 (C/T), the reference alleles are the majority (82.2% T/ 9.4% A and 83.7% C/ 7.3% T, respectively) ( Additional file 9 ). The DTF data for chickpea accessions, available in the public repository CicerSeq across six locations and two seasons (excluding the IIPR location, which only provided data for one season), were analyzed according to the SNPs present in LOC101515142 haplotype, LOC101499101, and LOC101507442 ( Additional file 9 ). Accession density distribution plots were obtained for each group ( Fig. 6 and Additional file 10 ). In accessions with contrasting haplotypes of LOC101515142, significant differences in DTF were only found in three different locations/seasons. In the other locations, the data reflect a similar DTF distribution for the different lines between the two groups of accessions with contrasting haplotypes. This pattern is also observed for the SNP in LOC101507442, where significant differences were only detected in ICARDA 2015/16. In contrast, for the SNP located in LOC101499101, interestingly significant differences are found in all locations/seasons, except RARI 2015/16. These consistent differences across locations and seasons suggest that LOC101499101 could influence flowering time along chickpea diversity. In silico Expression Analysis A total of 132 CDS from the selected 146 protein-coding genes, based on their functional annotation, were unambiguously matched with sequences in the GEO dataset. The TPM data for each transcript ID and their corresponding gene ID can be found in Additional file 11 . The TPM level heatmap categorized LOC101515142, LOC101489432, LOC101499101 and LOC101507442 into three distinct clusters ( Fig. 7) . LOC101499101 and LOC101507442 (both situated at the end of Ca6) show a similar expression pattern, closely grouped in the same subcluster, characterized by genes with higher expressions at all FB stages (Cluster I). LOC101515142 (Ca1: 2,285,592 – 2,298,911, complement) is in a neighboring cluster (Cluster III) with lower expression levels at the end of the FB stage (FB3 and FB4), but higher levels in SAM. Finally, LOC101489432 (Ca5: 36,011,384 – 36,016,600, complement) shows the most different expression profile, falling into a cluster with high expression levels in SAM and low expression in FB tissues (Cluster V). This locus is somewhat isolated from other genes in its cluster due to its lower expression level in YL and higher level in ML. The detailed description of co-expressed genes for these four genes can be found in Table 4. In Cluster I, it is remarkable LOC101513952 ( CaARF2 ), which is an auxin response factor protein (ARF). The ARF family members are considered the core of auxin signaling with important functions as regulators of plant growth and developmental processes [62, 63] . NF10/82-E exhibits 14 variants affecting this locus, of which six are located in exon or CDS with moderate and low theoretical impacts. LOC101491064 also stands out in this cluster, encoding a DNA-binding one zinc finger (DOF) protein. DOF transcription factor genes are involved in various fundamental processes in plants, including responses to light, phytohormones, as well as roles in seed maturation or germination [64] . For this locus, a total of 72 variants were detected in NF10/82-E with 13 located in exon or CDS regions. Additionally, LOC101491273 is an ethylene-responsive transcription factor (ERF) affected by four HHQ-I-C/E variants, one of them predicted to have a moderate impact as a missense variant. In Cluster III, no other gene apart from LOC101515142 seems to be prominent for flowering. Finally, LOC101492009 and LOC101510831 show the most similar expression pattern with CaELF3a in Cluster V. LOC101492009 is the TIFY5A protein, and LOC101510831 is a helicase-like transcription factor CHR28, both with the stress response GO Slim term. Moreover, in this Cluster V fall LOC101504196 (ethylene-responsive transcription factor 12) with 2 SNPs and LOC101500880, another DOF transcription factor (dof zinc finger protein DOF5.3-like) with a SNP in 3’UTR. Thus, there are two members of the ERF family and two members of the DOF family that fall into the same clusters that the genes appearing to be homologous to those found in the FLOR-ID A. thaliana dataset. Table 4 Co-expressed genes associated with the four genes affected by HHQ-I-C/E variants (highlighted in bold ) homologous to genes included in FLOR-ID Cluster Gene ID Variants GO Slim Name Gene Description I LOC101492907 8 P: lipid metabolic process enoyl-CoA delta isomerase 2, peroxisomal-like I LOC101495155 33 F: hydrolase activity GDSL esterase/lipase At5g45920 I LOC101511773 1 F: hydrolase activity ATP-dependent zinc metalloprotease FTSH 4, mitochondrial-like I LOC101497641 8 F: protein binding heterogeneous nuclear ribonucleoprotein U-like protein 1 I LOC101505696 8 P: response to biotic stimulus; P: response to external stimulus; P: response to stress putative disease resistance protein At3g14460 I LOC101507442 1 F: DNA binding B3 domain-containing transcription factor VRN1-like I LOC101513952 14 P: response to chemical; P: response to endogenous stimulus; P: biosynthetic process; P: signal transduction; F: DNA binding auxin response factor 2 I LOC101491064 72 P: biosynthetic process; F: DNA-binding transcription factor activity; F: DNA binding dof zinc finger protein DOF 4.7-like I LOC101507871 1 F: protein binding pentatricopeptide repeat-containing protein At4g20740-like I LOC101499101 1 P: post-embryonic development; P: response to light stimulus; P: biosynthetic process B-box zinc finger protein 24 I LOC101513083 10 P: biosynthetic process; F: DNA-binding transcription factor activity uncharacterized LOC101513083 I LOC101510178 6 P: biosynthetic process; F: DNA binding homeobox-DDT domain protein RLT1 I LOC101491273 4 P: response to chemical; P: response to endogenous stimulus; P: biosynthetic process; P: signal transduction; F: DNA-binding transcription factor activity; F: DNA binding ethylene-responsive transcription factor 1B III LOC101504748 1 P: biosynthetic process spermidine synthase 1 III LOC101508062 19 F: kinase activity; F: protein binding protein STRUBBELIG-RECEPTOR FAMILY 3-like III LOC101496576 29 P: biosynthetic process; F: DNA binding TATA box-binding protein-associated factor RNA polymerase I subunit B III LOC101495479 37 P: biosynthetic process THO complex subunit 7A-like III LOC101505912 1 F: kinase activity protein kinase PINOID-like III LOC101514288 37 P: biosynthetic process splicing factor U2af large subunit B-like III LOC101488340 102 P: biosynthetic process; F: protein binding proteinaceous RNase P 2 III LOC101515142 94 P: biosynthetic process mediator of RNA polymerase II transcription subunit 16-like III LOC101501305 1 P: signal transduction 14-3-3-like protein C III LOC101500879 41 P: biosynthetic process; F: protein binding pre-mRNA-splicing factor SYF1 III LOC101491071 41 F: protein binding phospholipase A-2-activating protein III LOC101501014 1 F: kinase activity; F: protein binding probable inactive leucine-rich repeat receptor-like protein kinase At3g03770 III LOC101504099 1 P: biosynthetic process; F: hydrolase activity ribosome biogenesis protein BMS1 homolog V LOC101493874 15 P: response to chemical; P: response to stress; F: protein binding E3 ubiquitin-protein ligase RMA1H1-like V LOC101515146 1 F: chromatin binding uncharacterized LOC101515146 V LOC101491385 4 F: hydrolase activity non-cyanogenic beta-glucosidase-like V LOC101503100 43 P: response to chemical; P: response to endogenous stimulus; P: signal transduction; F: transporter activity lysine histidine transporter-like 8 V LOC101506337 1 P: biosynthetic process; F: hydrolase activity U4/U6.U5 tri-snRNP-associated protein 2-like V LOC101504196 2 P: biosynthetic process; F: DNA-binding transcription factor activity; F: DNA binding ethylene-responsive transcription factor 12 V LOC101500880 1 P: biosynthetic process; F: DNA-binding transcription factor activity; F: DNA binding dof zinc finger protein DOF5.3-like V LOC101509325 2 P: response to chemical; P: response to endogenous stimulus; P: signal transduction two-component response regulator ARR17 V LOC101512564 86 F: hydrolase activity allantoinase V LOC101507112 1 P: biosynthetic process SAC3 family protein B V LOC101492009 1 P: response to chemical; P: response to endogenous stimulus; P: signal transduction; P: response to stress protein TIFY 5A V LOC101489432 1 P: post-embryonic development; P: response to light stimulus; P: reproduction protein EARLY FLOWERING 3a V LOC101510831 3 P: response to stress; P: DNA metabolic process helicase-like transcription factor CHR28 Discussion Near-isogenic lines (NILs) provide a unique advantage by confining genetic variation to specific regions of the genome while preserving genetic identity elsewhere. In this study, we characterized a pair of NILs exhibiting contrasting flowering times, aiming to discern not only major but also minor genes contributing to this complex process. Phenotyping of both NILs revealed significant differences across various morphological traits, including a notable contrast in DTF ( Table 1 ). This implies that genetic distinctions between the two NILs extend beyond the control of flowering initiation and influence over a spectrum of diverse characteristics. The association between flowering and multiple shoot architecture traits have been documented in various legume species, including chickpea [16, 35, 65–71]. Several instances of legume mutants, characterized by alterations in a specific flowering-related gene, exhibit variations in morphological features, such as changes in branching patterns and internode length [26, 30, 70]. In the case of the studied NILs, phenotype differences could arise from the action of several independent genes or the pleiotropic effects of a single or a few genes. Nevertheless, the substantial differences in DTF observed (14 days) suggest additive effects from more than one locus. The sequencing data from the pair of NILs revealed a 99.97% identity of the read positions, with variations mainly observed in specific regions, as expected [41]. This level of genomic identity is consistent with values from other legume studies involving NILs, including chickpea, where reported identities range between 90-99% [50, 72, 73]. The observed residual heterozygosity for each NIL is ~ 0.05%, falling below the theoretical 0.098% expected for 11 generations of self-fertilizing lines. Nevertheless, this also aligns with values reported for other NILs [74] and closely resembles the residual heterozygosity found in cultivated chickpea. According to data reported by [51], the detected residual heterozygosity for SNPs ranged from 0.024% (0.013% - 0.050%) for cultivar lines to 0.033% (0.011% - 0.078%) for landrace lines and 0.033% (0.009% - 0.073%) for breeding lines, relative to the total sequenced positions (533.36 Mb; Additional file 12 ). It is important to note that these estimations do not encompass other variations, such as InDels, suggesting that the actual heterozygosity may be higher. Therefore, the pair of NILs developed in our study appears to be suitable plant material, embodying the characteristics of near-isogenic lines, and providing a valuable resource for further genetic and functional studies in chickpea research. The comparison between positions sequenced in the pair of NILs revealed 15,690 homozygous variants (SNPs and InDels) mapped to chromosomes that pass all quality criteria or fail to meet only one criterion ( Table 2 ). Of these, 4,932 variants are intragenic (HHQ-I), with the highest density observed at the beginning of chromosome 1 and the end of chromosome 6 ( Fig. 3 and Additional file 3 ). Notably, no HHQ-I variants were detected on chromosome 3, where QTLs have been reported several times, and genetic variants in the FTa1/a2/c cluster seem to play an important role in relaxing the environmental constraints on flowering, permitting early-flowering in long-day legumes [15, 16]. Thus, differences in flowering time in the pair of NILs do not appear to be related to chromosome 3. A total of 1,610 variants were identified within exons or CDS (HHQ-I-C/E), affecting 246 protein-coding genes. However, functional annotation against the chickpea genome annotation did not reveal any enrichment of GO Slim terms ( Fig. 4 ). To deepen our analysis, we selected 146 of these as candidate genes, guided by enriched GO Slim terms related to flowering obtained from the model plant A. thaliana ( Additional file 6 ). Significantly, four candidate genes showed homology to A. thaliana FLOR-ID genes dataset ( Table 3 ). One of them, LOC101507442 (Ca6: 57,717,926 – 57,721,229), a B3 domain-containing transcription factor VRN1-like , is affected only by a SNP located in CDS with low impact as a synonymous variant. The analysis of the public repository CicerSeq phenotype data indicates that this SNP is not associated with DTF in chickpea germplasm (Fig. 6 and Additional file 10) . LOC101515142 (Ca1: 2,285,592 – 2,298,911, complement) is a homologue of the A. thaliana MED16/SFR6 gene, encoding a component of the Mediator complex. This complex is a large and dynamically variable multisubunit protein complex implicated in the regulation of RNA polymerase II-dependent gene expression. The Mediator complex recruits transcription factors to specific gene sites, promoting or repressing transcription initiation and elongation through protein-protein interaction modules [59, 75–77]. The Mediator is evolutionarily highly conserved across eukaryotes; out of the 34 Mediator subunits described in Arabidopsis , only four are plant-specific subunits; 25 other subunits including MED16 are structurally conserved [59]. MED16 is part of the tail module of the Mediator complex with functions in both abiotic and biotic stress pathways. Initially identified as SENSITIVE TO FREEZING 6 ( SFR6 ) for its role in cold acclimation [78–80], it is also involved in the regulation of iron homeostasis [81] and salicylic acid- and jasmonate-mediated defense response [82, 83]. Loss of MED16 disrupts transcriptional outputs beyond low-temperature gene regulation, affecting the expression of photoperiod flowering time pathway and circadian clock genes, which leads to a late-flowering phenotype in long days [84]. To our knowledge, no flowering-time-related function for MED16 has been described in legumes. A recent study in Medicago truncatula detected a mutation in a MED16 homologue (LOC25493186, MtrunA17_Chr4g0047551), referred to as MED16A by the authors, which suppresses nodulation and increases arbuscular density [85]. However, a comparison through BLASTp against C. arietinum RefSeq_Protein database reveals that MED16A seems to be the homologue to LOC101501202 (Ca6: 16,660,218 - 16,679,432) with no variants between NILs. Thus, LOC101515142, affected by 94 variants in this study, seems to be the homologue of MED16B (LOC11424919, MtrunA17_Chr2g0281921) (Additional file 13). Nevertheless, the importance of the Mediator complex in flowering time has been highlighted in a recent publication in pea, revealing that other subunits, orthologs of CYCLIN-DEPENDENT KINASE 8 (CDK8) and CYCLIN C1 (CYCC1), components of the CDK8 kinase module of the Mediator complex, are involved in promoting flowering and maintaining normal reproductive development ([70]. In chickpea, a recent study identified the role of two Mediator subunit genes, namely CaMED23 and CaMED5b , along with their naturally derived haplotypes, in the regulation of plant height [43]. This indicates that the variability of the Mediator complex could play an important role in different traits for yield improvement. Based on the nomenclature used in these legume studies involving the Mediator complex [43, 70, 85], we propose that LOC101515142 is CaMED16b . The identified SNPs in CaMED16b appear to form contrasting haplotypes, showing high conservation across cultivated chickpea germplasm ( Fig. 5 and Additional file 8 ). However, significant differences in DTF for the accessions with these contrasting haplotypes were observed in only three out of eleven different locations/seasons ( Fig. 6 and Additional file 10) . Consequently, further investigation is required to fully comprehend the functional role of CaMED16b in flowering and its contribution to DTF. CaELF3a (Ca5: 36,011,384 – 36,016,600, complement) is one of the two homologs of A. thaliana ELF3 identified in legumes [40, 86]. This gene is a major component of the Evening complex (EC) with ELF4 and LUX within the circadian clock. The EC is not only directly involved in clock function, but also plays a key role in different developmental processes by interacting with other genes, such as PIF4 or GI , in the control of photoperiodic flowering and hypocotyl elongation in A. thaliana [87–90]. In this study, an 11 bp deletion in the first exon of CaELF3a was identified in the NF10/82-E line. This deletion is predicted to cause a frameshift, reducing the encoded protein from 699 to 13 amino acids ( Additional file 7. Fig. S1b ). The same deletion was previously reported by [40] in line ICCV96029. It is noteworthy that the 11 bp constituting the deletion are followed by 10 bp that are identical to them. This sequence similarity may have facilitated the natural occurrence of the deletion at this specific position within the gene (Additional file 7. Fig. S1b) . In fact, [40] resequenced the entire CaELF3a gDNA in 109 lines and only found this sequence polymorphism. The presence of the deletion in homozygosity is associated with early-flowering in chickpea, representing the recessive allele. This aligns with the observation that the late-flowering phenotype was dominant in the developmental process of the pair of NILs used in this study (Fig. 1) . Interestingly, ELF3 acts as a negative regulator of flowering [90], so loss-of-function mutations in this locus are predicted to result in early-flowering phenotype as we observed in the pair of NILs. Mutations in ELF3 orthologs are also associated with early-flowering and reduced branching in other galegoid legumes, such as pea and lentil [69], a morphological trait also observed for the NF10/82–E line in this study. However, although CaELF3a appears to have a significant effect on flowering time and other related traits, not all of the phenotypic differences detected between the pair of NILs should be assigned to it. Other genes may likely contribute comparable positive effects on flowering time, as expected with ICCV96029 [40]. In LOC101499101 (Ca6: 57,549,424 – 57,552,323, complement), a SNP was identified in the 3’ UTR. This locus exhibits homology to the B-box finger protein of A. thaliana STO/BBX24 which is recognized for its role in connecting the FRI/FLC and the photoperiod/circadian clock pathway, ultimately influencing flowering time in this species [60]. The 3’ UTR of mRNA is recognized for its role in transcriptional control and protein targeting, affecting various physiological processes in plants, such as flowering and stress tolerance [91, 92]. Specifically, different mechanisms of 3’ RNA processing and their relevance for flowering time were investigated, with a focus on the FLC gene in A. thaliana [93, 94]. Furthermore, a study highlighted the role of post-transcriptional regulation in flowering time control through the repressed SOC1 activity in a 3′ UTR-dependent manner in A. thaliana [95]. Polymorphisms in the UTR and intronic regions were also reported to be associated with higher expression of an FT5a allele causing early-flowering in soybean [96]. While the effects of a single SNP in UTRs may not be as pronounced as those in CDS, its association with flowering time should not necessarily be dismissed. For example, a SNP in the 3′ UTR of M. truncatula FTa1 was significantly correlated with latitudinal variation, reflecting differences in photoperiod and temperature in its distribution across the Mediterranean region [97]. Notably, the analysis of accession density distribution plots based on the allele of the SNP reveals significant differences in DTF across all locations/seasons registered in the public repository CicerSeq, except for one ( Fig. 6 and Additional file 10) . Therefore, the T → A transversion detected in LOC101499101 could influence DTF differences in the NILs, suggesting a plausible association of the SNP with flowering time in the chickpea germplasm. To further characterize the 146 candidate protein-coding genes affected by HHQ-I-C/E in the pair of NILs, an in silico expression analysis was conducted. The purpose of this analysis was to gain insights into the transcription profiles in vegetative tissues with significant roles in promoting flowering (leaves and SAM), as well as the initial stages of flowering (FB1 – FB4). We focused, particularly, on the four genes detected as homologous to those in A. thaliana. The TPM values, calculated from the chickpea expression atlas [52], categorized LOC101515142 ( CaMED16b ), LOC101489432 ( CaELF3a ), LOC101499101 ( BBX24-like ) and LOC101507442 ( VRN1-like ) into three different clusters ( Fig. 7 and Additional file 11 ). The expression profile of CaMED16b indicates higher levels during the initial stages of flowering, evidenced by an increase in TPM levels between the SAM and FB1, followed by a decrease between FB1 and FB2. Subsequent FB stages (FB3 and FB4) show lower expression levels, suggesting a potential role for CaMED16b during the immediate pre-flowering period. In contrast, CaELF3a shows the highest expression levels in ML and SAM tissues, indicating its involvement in upstream transcriptional regulation pathways preceding the onset of flowering. This suggests that CaELF3a may play a role in regulating processes leading up to flowering initiation. Finally, LOC101499101 and LOC101507442 exhibit a similar expression pattern, with the highest TPM levels observed at FB1 and consistent levels across all subsequent FB stages. This suggests their involvement during the flower development rather than the initiation of flowering. According to the in silico analysis, CaMED16b and CaELF3a exhibit interesting expression patterns consistent with an expected role in flowering time regulation, with expression in leaves and SAM preceding the transition from vegetative to reproductive stages. This putative observation for CaELF3a was previously reported, identifying it as one of the key regulators responsible for early inflorescence development and early-flowering phenotype in chickpeas [98] . Interestingly, LOC101492009 (TIFY5A protein) and LOC101510831 (helicase-like transcription factor CHR28), both with the stress response GO Slim term, show a similar expression pattern with CaELF3a (Fig. 7). [98] found that stress and defense-responsive genes as well as the ethylene signaling pathway genes were to be upregulated during inflorescence development in chickpeas. Furthermore, other candidate genes, including some members of the ARF, ERF, and DOF families, exhibit co-expression with these four genes (Table 4) . These transcription factor families play important roles in various fundamental processes in plants that could influence the phenotype observed for the pair of NILs [62–64, 99–101]. Specifically, ARF2 and ERF12 were described in A. thaliana with roles in flowering. A. thaliana arf2 mutants exhibited pleiotropic development phenotypes, including delays in several processes related to plant aging such as initiation of flowering, rosette leaf senescence and floral organ abscission [102, 103]. Arabidopsis EFR12 pleiotropically affects meristem identity, floral phyllotaxy and organ initiation and seems to be conserved among angiosperms [104]. Therefore, LOC101513952 ( CaARF2; auxin response factor 2), with 14 variants detected between NILs and LOC101491273 ( CaERF12 ; ethylene-responsive transcription factor 12), affected by four HHQ-I-C/E variants, are potential candidate genes that could play a role in the observed phenotypic differences. Conclusion The development of the NIL pair in this study represents a valuable resource for advancing research on chickpea flowering time. This study offers a complementary approach to association analyses by phenotyping and re-sequencing the NILs, enabling the identification of candidate gene variants that could have both major and minor effects on flowering time. While CaELF3a emerges as the most prominent candidate gene, our study also uncovered other targets for the first time in chickpea, including CaMED16b and LOC101499101 ( BBX24-like ), which are homologs to flowering-related genes in A. thaliana . This suggests their potential contribution in modeling this trait. Furthermore, ERF and ARF family members potentially associated with flowering time were also detected. The in silico expression characterization and genetic variability analysis carried out in this study for these loci could contribute to the development of specific markers for chickpea breeding programs. This study lays the foundation for future research on this plant material. Subsequent studies, including analysis of the F2 progeny resulting from the NIL cross and expression analysis, hold the potential to unveil new insights into the intricate mechanisms governing flowering time in chickpea. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The dataset generated and analyzed during the current study is available in the European Variation Archive (EVA) at EMBL-EBI under accession number PRJEB73790, https://urldefense.com/v3/__https://www.ebi.ac.uk/eva/?eva-study=PRJEB73790__;!!D9dNQwwGXtA!UdDPickLBLigeaKK1uTr009AH7xm-vup0ndN_fMEwYr8Ay_ik2ooSI7MDZSsXYi4d24v4nT4KWYkv8qN57t0o20q$. The custom scripts used for the analysis of the data during the current study are available in the GitHub repository https://github.com/AGR114molecularBreeding/chickpea. Competing interests The authors declare that they have no competing interests. Funding This research was funded by the following projects and programs: PID2020-114952RRI00 funded by MCIN/AEI/10.13039/501100011033; European Union’s Horizon Europe research and innovation program under grant agreement BELIS (No 101081878); PR.AVA23.INV2023.009 co-financed by European Regional Development Fund (ERDF). APR is a FPU Fellow funded by the Spanish Ministry of Science, Innovation and Universities through the National Program FPU “Formación de Profesorado Universitario” (Ref. FPU22/02101). AC acknowledges the FPI grant associated with the JVD’s Ramón y Cajal program (University of Cordoba). JVD is a Ramón y Cajal Fellow funded by the program MCIN/AEI/10.13039/501100011033 (Ref. RYC2019-028188-I). Authors’ contributions J.R., T.M. and P.C. contributed to the study conception and design. J.R., T.M. and J.V.D. acquired funding for the study. J.R., L.A., T.M. and P.C. developed the plant material. A.P.R., L.A., J.R. and T.M. participated in field characterization. A.P.R., A.C. and J.V.D. analyzed the data. P.C. and J.V.D. supervised the study. A.P.R. wrote the first draft of the manuscript. A.C., P.C. and J.V.D. reviewed and edited the manuscript. All authors read and approved the final manuscript. Acknowledgments We would like to express our sincere appreciation to Prof. Juan Gil for his invaluable contributions to the study. His critical review and insightful feedback have greatly enriched the content and quality of the manuscript. References Varshney RK, Song C, Saxena RK, Azam S, Yu S, Sharpe AG, et al. Draft genome sequence of chickpea ( Cicer arietinum ) provides a resource for trait improvement. Nat Biotechnol. 2013;31:240–6. FAOSTAT FAO. FAOSTAT. 2022. https://www.fao.org/faostat/en/#data. Accessed 11 Jan 2024. Kumar J, Abbo S. Genetics of flowering time in chickpea and its bearing on productivity in semiarid environments. Elsevier; 2001. p. 107–38. Gaur PM, Jukanti AK, Varshney RK. Impact of genomic technologies on chickpea breeding strategies. Agronomy. 2012;2:199–221. Arriagada O, Cacciuttolo F, Cabeza RA, Carrasco B, Schwember AR. A comprehensive review on chickpea ( Cicer arietinum L.) breeding for abiotic stress tolerance and climate change resilience. Int J Mol Sci. 2022;23:6794. Zhang H, Pala M, Oweis T, Harris H. Water use and water-use efficiency of chickpea and lentil in a Mediterranean environment. Aust J Agric Res. 2000;51:295. Varshney RK, Thudi M, Nayak SN, Gaur PM, Kashiwagi J, Krishnamurthy L, et al. Genetic dissection of drought tolerance in chickpea ( Cicer arietinum L.). Theor Appl Genet. 2014;127:445–62. Siddique KHM, Loss SP, Thomson BD. Cool season grain legumes in dryland Mediterranean environments of Western Australia: significance of early flowering. Management of agricultural drought: Agronomic and genetic options. 2003;151–62. Berger JD, Turner NC. The ecology of chickpea. In: Yadav SS, Redden RJ, Chen W, Sharma B, editors. Chickpea breeding and management. UK: CABI; 2007. p. 47–71. Daba K, Tar’an B, Bueckert R, Warkentin TD. Effect of temperature and photoperiod on time to flowering in chickpea. Crop Sci. 2016;56:200. Berger JD, Turner NC, Siddique KHM, Knights EJ, Brinsmead RB, Mock I, et al. Genotype by environment studies across Australia reveal the importance of phenology for chickpea ( Cicer arietinum L.) improvement. Aust J Agric Res. 2004;55:1071. Croser JS, Clarke HJ, Siddique KHM, Khan TN. Low-temperature stress: implications for chickpea ( Cicer arietinum L.) improvement. CRC Crit Rev Plant Sci. 2003;22:185–219. Clarke HJ, Siddique KHM. Response of chickpea genotypes to low temperature stress during reproductive development. Field Crops Res. 2004;90:323–34. Berger JD, Ali M, Basu PS, Chaudhary BD, Chaturvedi SK, Deshmukh PS, et al. Genotype by environment studies demonstrate the critical role of phenology in adaptation of chickpea ( Cicer arietinum L.) to high and low yielding environments of India. Field Crops Res. 2006;98:230–44. Weller JL, Ortega R. Genetic control of flowering time in legumes. Front Plant Sci. 2015;6:207. Ortega R, Hecht VFG, Freeman JS, Rubio J, Carrasquilla-Garcia N, Mir RR, et al. Altered Expression of an FT Cluster Underlies a Major Locus Controlling Domestication-Related Changes to Chickpea Phenology and Growth Habit. Front Plant Sci. 2019;10:824. Gretsova M, Surkova S, Kanapin A, Samsonova A, Logacheva M, Shcherbakov A, et al. Transcriptomic analysis of flowering time genes in cultivated chickpea and wild cicer. ijms. 2023;24:2692. Bouché F, Lobet G, Tocquin P, Périlleux C. FLOR-ID: an interactive database of flowering-time gene networks in Arabidopsis thaliana . Nucleic Acids Res. 2016;44:D1167-71. Jaeger KE, Wigge PA. FT protein acts as a long-range signal in Arabidopsis . Curr Biol. 2007;17:1050–4. Andrés F, Coupland G. The genetic basis of flowering responses to seasonal cues. Nat Rev Genet. 2012;13:627–39. Hanano S, Goto K. Arabidopsis TERMINAL FLOWER1 is involved in the regulation of flowering time and inflorescence development through transcriptional repression. Plant Cell. 2011;23:3172–84. Hecht V, Foucher F, Ferrándiz C, Macknight R, Navarro C, Morin J, et al. Conservation of Arabidopsis flowering genes in model legumes. Plant Physiol. 2005;137:1420–34. Kim MY, Kang YJ, Lee T, Lee S-H. Divergence of Flowering-Related Genes in Three Legume Species. Plant Genome. 2013;6:0. Young ND, Bharti AK. Genome-enabled insights into legume biology. Annu Rev Plant Biol. 2012;63:283–305. Hecht V, Laurie RE, Vander Schoor JK, Ridge S, Knowles CL, Liew LC, et al. The pea GIGAS gene is a FLOWERING LOCUS T homolog necessary for graft-transmissible specification of flowering but not for responsiveness to photoperiod. Plant Cell. 2011;23:147–61. Laurie RE, Diwadkar P, Jaudal M, Zhang L, Hecht V, Wen J, et al. The Medicago FLOWERING LOCUS T homolog, MtFTa1 , is a key regulator of flowering time. Plant Physiol. 2011;156:2207–24. Nelson MN, Książkiewicz M, Rychel S, Besharat N, Taylor CM, Wyrwa K, et al. The loss of vernalization requirement in narrow-leafed lupin is associated with a deletion in the promoter and de-repressed expression of a Flowering Locus T ( FT ) homologue. New Phytol. 2017;213:220–32. Surkova SY, Samsonova MG. Mechanisms of vernalization-induced flowering in legumes. Int J Mol Sci. 2022;23. Wong ACS, Hecht VFG, Picard K, Diwadkar P, Laurie RE, Wen J, et al. Isolation and functional analysis of CONSTANS-LIKE genes suggests that a central role for CONSTANS in flowering time control is not evolutionarily conserved in Medicago truncatula . Front Plant Sci. 2014;5:486. Ridge S, Sussmilch FC, Hecht V, Vander Schoor JK, Lee R, Aubert G, et al. Identification of LATE BLOOMER2 as a CYCLING DOF FACTOR homolog reveals conserved and divergent features of the flowering response to photoperiod in pea. Plant Cell. 2016;28:2545–59. Gaur PM, Samineni S, Tripathi S, Varshney RK, Gowda CLL. Allelic relationships of flowering time genes in chickpea. Euphytica. 2015;203:295–308. Kumar J, van Rheenen HA. Brief communication. A major gene for time of flowering in chickpea. J Hered. 2000;91:67–8. Or E, Hovav R, Abbo S. A major gene for flowering time in chickpea. Crop Sci. 1999;39:315–22. Hegde VS. Genetics of flowering time in chickpea in a semi-arid environment. Plant Breeding. 2010;129:683–7. Lichtenzveig J, Bonfil DJ, Zhang H-B, Shtienberg D, Abbo S. Mapping quantitative trait loci in chickpea associated with time to flowering and resistance to Didymella rabiei the causal agent of Ascochyta blight. Theor Appl Genet. 2006;113:1357–69. Rehman AU, Malhotra RS, Bett K, Tar’an B, Bueckert R, Warkentin TD. Mapping QTL associated with traits affecting grain yield in chickpea ( Cicer arietinum L.) under terminal drought stress. Crop Sci. 2011;51:450–63. Mallikarjuna BP, Samineni S, Thudi M, Sajja SB, Khan AW, Patil A, et al. Molecular mapping of flowering time major genes and QTLs in chickpea ( Cicer arietinum L.). Front Plant Sci. 2017;8:1140. Daba K, Deokar A, Banniza S, Warkentin TD, Tar’an B. QTL mapping of early flowering and resistance to ascochyta blight in chickpea. Genome. 2016;59:413–25. Upadhyaya HD, Bajaj D, Das S, Saxena MS, Badoni S, Kumar V, et al. A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea. Plant Mol Biol. 2015;89:403–20. Ridge S, Deokar A, Lee R, Daba K, Macknight RC, Weller JL, et al. The chickpea E arly flowering 1 ( E fl1 ) locus is an ortholog of A rabidopsis ELF3 . Plant Physiol. 2017;175:802–15. Yan G, Liu H, Wang H, Lu Z, Wang Y, Mullan D, et al. Accelerated generation of selfed pure line plants for gene identification and crop breeding. Front Plant Sci. 2017;8:1786. Ali L, Azam S, Rubio J, Kudapa H, Madrid E, Varshney RK, et al. Detection of a new QTL/gene for growth habit in chickpea CaLG1 using wide and narrow crosses. Euphytica. 2015;204:473–85. Malik N, Basu U, Srivastava R, Daware A, Ranjan R, Sharma A, et al. Natural alleles of Mediator subunit genes modulate plant height in chickpea. Plant J. 2023;116:1271–92. Caballo C, Berbel A, Ortega R, Gil J, Millán T, Rubio J, et al. The SINGLE FLOWER ( SFL ) gene encodes a MYB transcription factor that regulates the number of flowers produced by the inflorescence of chickpea. New Phytol. 2022;234:827–36. Ali L, Deokar A, Caballo C, Tar’an B, Gil J, Chen W, et al. Fine mapping for double podding gene in chickpea. Theor Appl Genet. 2016;129:77–86. Ali L, Madrid E, Varshney RK, Azam S, Millan T, Rubio J, et al. Mapping and identification of a Cicer arietinum NSP2 gene involved in nodulation pathway. Theor Appl Genet. 2014;127:481–8. Castro P, Pistón F, Madrid E, Millán T, Gil J, Rubio J. Development of chickpea near-isogenic lines for Fusarium wilt. Theor Appl Genet. 2010;121:1519–26. Caballo C, Castro P, Gil J, Millan T, Rubio J, Die JV. Candidate genes expression profiling during wilting in chickpea caused by Fusarium oxysporum f. sp. ciceris race 5. PLoS ONE. 2019;14:e0224212. Jendoubi W, Bouhadida M, Millan T, Kharrat M, Gil J, Rubio J, et al. Identification of the target region including the Foc0 1 /foc0 1 gene and development of near isogenic lines for resistance to Fusarium Wilt race 0 in chickpea. Euphytica. 2016;210:119–33. Basu U, Narnoliya L, Srivastava R, Sharma A, Bajaj D, Daware A, et al. CLAVATA signaling pathway genes modulating flowering time and flower number in chickpea. Theor Appl Genet. 2019;132:2017–38. Varshney RK, Roorkiwal M, Sun S, Bajaj P, Chitikineni A, Thudi M, et al. A chickpea genetic variation map based on the sequencing of 3,366 genomes. Nature. 2021;599:622–7. Jain M, Bansal J, Rajkumar MS, Garg R. An integrated transcriptome mapping the regulatory network of coding and long non-coding RNAs provides a genomics resource in chickpea. Commun Biol. 2022;5:1106. Tuinstra MR, Ejeta G, Goldsbrough PB. Heterogeneous inbred family (HIF) analysis: a method for developing near-isogenic lines that differ at quantitative trait loci. Theor Appl Genet. 1997;95:1005–11. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012;6:80–92. Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, et al. SRplot: A free online platform for data visualization and graphing. PLoS ONE. 2023;18:e0294236. Die JV. Jdieramon/Refseqr V1.0.1. Zenodo. 2018. Conesa A, Götz S. Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics. 2008;2008:619832. Mi H, Muruganujan A, Huang X, Ebert D, Mills C, Guo X, et al. Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc. 2019;14:703–21. Dolan WL, Chapple C. Conservation and Divergence of Mediator Structure and Function: Insights from Plants. Plant Cell Physiol. 2016. Li F, Sun J, Wang D, Bai S, Clarke AK, Holm M. The B-box family gene STO ( BBX24 ) in Arabidopsis thaliana regulates flowering time in different pathways. PLoS ONE. 2014;9:e87544. Levy YY, Mesnage S, Mylne JS, Gendall AR, Dean C. Multiple roles of Arabidopsis VRN1 in vernalization and flowering time control. Science. 2002;297:243–6. Die JV, Gil J, Millan T. Genome-wide identification of the auxin response factor gene family in Cicer arietinum . BMC Genomics. 2018;19:301. Chapman EJ, Estelle M. Mechanism of auxin-regulated gene expression in plants. Annu Rev Genet. 2009;43:265–85. Noguero M, Atif RM, Ochatt S, Thompson RD. The role of the DNA-binding One Zinc Finger (DOF) transcription factor family in plants. Plant Sci. 2013;209:32–45. Julier B, Huguet T, Chardon F, Ayadi R, Pierre J-B, Prosperi J-M, et al. Identification of quantitative trait loci influencing aerial morphogenesis in the model legume Medicago truncatula . Theor Appl Genet. 2007;114:1391–406. Espinoza L del CL, Huguet T, Julier B. Multi-population QTL detection for aerial morphogenetic traits in the model legume Medicago truncatula . Theor Appl Genet. 2012;124:739–54. González AM, Yuste-Lisbona FJ, Saburido S, Bretones S, De Ron AM, Lozano R, et al. Major contribution of flowering time and vegetative growth to plant production in common bean as deduced from a comparative genetic mapping. Front Plant Sci. 2016;7:1940. Yang G, Zhai H, Wu H, Zhang X, Lü S, Wang Y, et al. QTL effects and epistatic interaction for flowering time and branch number in a soybean mapping population of Japanese×Chinese cultivars. J Integr Agric. 2017;16:1900–12. Weller JL, Liew LC, Hecht VFG, Rajandran V, Laurie RE, Ridge S, et al. A conserved molecular basis for photoperiod adaptation in two temperate legumes. Proc Natl Acad Sci USA. 2012;109:21158–63. Hasan ASMM, Vander Schoor JK, Hecht V, Weller JL. The CYCLIN-DEPENDENT KINASE module of the Mediator complex promotes flowering and reproductive development in pea. Plant Physiol. 2020;182:1375–86. Anbessa Y, Warkentin T, Bueckert R, Vandenberg A. Short internode, double podding and early flowering effects on maturity and other agronomic characters in chickpea. Field Crops Res. 2007;102:43–50. Jacques S, Sperschneider J, Garg G, Thatcher LF, Gao L-L, Kamphuis LG, et al. A functional genomics approach to dissect spotted alfalfa aphid resistance in Medicago truncatula . Sci Rep. 2020;10:22159. Thakro V, Malik N, Basu U, Srivastava R, Narnoliya L, Daware A, et al. A superior gene allele involved in abscisic acid signaling enhances drought tolerance and yield in chickpea. Plant Physiol. 2023;191:1884–912. Pea G, Aung HH, Frascaroli E, Landi P, Pè ME. Extensive genomic characterization of a set of near-isogenic lines for heterotic QTL in maize ( Zea mays L.). BMC Genomics. 2013;14:61. Allen BL, Taatjes DJ. The Mediator complex: a central integrator of transcription. Nat Rev Mol Cell Biol. 2015;16:155–66. Jeronimo C, Robert F. The mediator complex: at the nexus of RNA polymerase II transcription. Trends Cell Biol. 2017;27:765–83. Zhang L, Guo C. The important function of mediator complex in controlling the developmental transitions in plants. Int J Mol Sci. 2020;21. Knight H, Veale EL, Warren GJ, Knight MR. The sfr6 mutation in Arabidopsis suppresses low-temperature induction of genes dependent on the CRT/DRE sequence motif. Plant Cell. 1999;11:875–86. Knight H, Mugford SG, Ulker B, Gao D, Thorlby G, Knight MR. Identification of SFR6 , a key component in cold acclimation acting post-translationally on CBF function. Plant J. 2009;58:97–108. Hemsley PA, Hurst CH, Kaliyadasa E, Lamb R, Knight MR, De Cothi EA, et al. The Arabidopsis mediator complex subunits MED16, MED14, and MED2 regulate mediator and RNA polymerase II recruitment to CBF-responsive cold-regulated genes. Plant Cell. 2014;26:465–84. Yang Y, Ou B, Zhang J, Si W, Gu H, Qin G, et al. The Arabidopsis Mediator subunit MED16 regulates iron homeostasis by associating with EIN3/EIL1 through subunit MED25. Plant J. 2014;77:838–51. Wathugala DL, Hemsley PA, Moffat CS, Cremelie P, Knight MR, Knight H. The Mediator subunit SFR6/MED16 controls defence gene expression mediated by salicylic acid and jasmonate responsive pathways. New Phytol. 2012;195:217–30. Zhang X, Yao J, Zhang Y, Sun Y, Mou Z. The Arabidopsis Mediator complex subunits MED14/SWP and MED16/SFR6/IEN1 differentially regulate defense gene expression in plant immune responses. Plant J. 2013;75:484–97. Knight H, Thomson AJW, McWatters HG. Sensitive to freezing6 integrates cellular and environmental inputs to the plant circadian clock. Plant Physiol. 2008;148:293–303. Chaulagain D, Schnabel E, Crook A, Bashyal S, Müller LM, Frugoli J. A mutation in Mediator subunit MED16A suppresses nodulation and increases arbuscule density in Medicago truncatula . J Plant Growth Regul. 2023;42:7004–22. Rubenach AJS, Hecht V, Vander Schoor JK, Liew LC, Aubert G, Burstin J, et al. EARLY FLOWERING3 redundancy fine-tunes photoperiod sensitivity. Plant Physiol. 2017;173:2253–64. Nusinow DA, Helfer A, Hamilton EE, King JJ, Imaizumi T, Schultz TF, et al. The ELF4-ELF3-LUX complex links the circadian clock to diurnal control of hypocotyl growth. Nature. 2011;475:398–402. Shim JS, Kubota A, Imaizumi T. Circadian clock and photoperiodic flowering in A rabidopsis : CONSTANS is a hub for signal integration. Plant Physiol. 2017;173:5–15. Anwer MU, Davis A, Davis SJ, Quint M. Photoperiod sensing of the circadian clock is controlled by EARLY FLOWERING 3 and GIGANTEA . Plant J. 2020;101:1397–410. Zhao H, Xu D, Tian T, Kong F, Lin K, Gan S, et al. Molecular and functional dissection of EARLY-FLOWERING 3 ( ELF3 ) and ELF4 in Arabidopsis . Plant Sci. 2021;303:110786. Srivastava AK, Lu Y, Zinta G, Lang Z, Zhu J-K. UTR-dependent control of gene expression in plants. Trends Plant Sci. 2018;23:248–59. Bernardes WS, Menossi M. Plant 3’ Regulatory Regions From mRNA-encoding genes and their uses to modulate expression. Front Plant Sci. 2020;11:1252. Rataj K, Simpson GG. Message ends: RNA 3’ processing and flowering time control. J Exp Bot. 2014;65:353–63. Sun B, Bhati KK, Song P, Edwards A, Petri L, Kruusvee V, et al. FIONA1-mediated methylation of the 3’UTR of FLC affects FLC transcript levels and flowering in Arabidopsis . PLoS Genet. 2022;18:e1010386. Kim H-S, Abbasi N, Choi S-B. Bruno-like proteins modulate flowering time via 3’ UTR-dependent decay of SOC1 mRNA. New Phytol. 2013;198:747–56. Takeshima R, Hayashi T, Zhu J, Zhao C, Xu M, Yamaguchi N, et al. A soybean quantitative trait locus that promotes flowering under long days is identified as FT5a , a FLOWERING LOCUS T ortholog. J Exp Bot. 2016;67:5247–58. Burgarella C, Chantret N, Gay L, Prosperi J-M, Bonhomme M, Tiffin P, et al. Adaptation to climate through flowering phenology: a case study in Medicago truncatula . Mol Ecol. 2016;25:3397–415. Basu U, Hegde VS, Daware A, Jha UC, Parida SK. Transcriptome landscape of early inflorescence developmental stages identifies key flowering time regulators in chickpea. Plant Mol Biol. 2022;108:565–83. Deokar AA, Kondawar V, Kohli D, Aslam M, Jain PK, Karuppayil SM, et al. The CarERF genes in chickpea ( Cicer arietinum L.) and the identification of CarERF116 as abiotic stress responsive transcription factor. Funct Integr Genomics. 2015;15:27–46. Srivastava R, Kumar R. The expanding roles of APETALA2/Ethylene Responsive Factors and their potential applications in crop improvement. Brief Funct Genomics. 2018;18:240–54. Die JV, Elmassry MM, LeBlanc KH, Awe OI, Dillman A, Busby B. geneHummus: an R package to define gene families and their expression in legumes and beyond. BMC Genomics. 2019;20:591. Ellis CM, Nagpal P, Young JC, Hagen G, Guilfoyle TJ, Reed JW. AUXIN RESPONSE FACTOR1 and AUXIN RESPONSE FACTOR2 regulate senescence and floral organ abscission in Arabidopsis thaliana . Development. 2005;132:4563–74. Okushima Y, Mitina I, Quach HL, Theologis A. AUXIN RESPONSE FACTOR 2 ( ARF2 ): a pleiotropic developmental regulator. Plant J. 2005;43:29–46. Chandler JW, Werr W. A phylogenetically conserved APETALA2/ETHYLENE RESPONSE FACTOR , ERF12 , regulates Arabidopsis floral development. Plant Mol Biol. 2020;102:39–54. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4002926","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278886395,"identity":"debceef5-0d36-4d1a-971e-158b55838966","order_by":0,"name":"Adrian Perez-Rial","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACZuYDQFKCgZ94LexsCWAtkg1Ea+HnMQDTBgeI1SHfzGD24OMeC3njG8kPHzBU1BHWwtjMkG4445mE4bYbacYGDGcOE9bCzMxwTJrngATjths5bBKMbUQ4j42ZsU36zwEJ+80zQFr+EeEwHmZmNmmGAxKJGyRAWhqYCWuRYGZjN+w5IJE848wzY4OEY0T4Rb7//LcHPw7U2fa3A0PsQw0RDgMCNgQzgSgNKFpGwSgYBaNgFGADACLKMnpqDt/TAAAAAElFTkSuQmCC","orcid":"","institution":"University of Córdoba","correspondingAuthor":true,"prefix":"","firstName":"Adrian","middleName":"","lastName":"Perez-Rial","suffix":""},{"id":278886396,"identity":"d6ce4b40-ec97-46a0-8806-347992dcdea7","order_by":1,"name":"Alejandro Carmona","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"prefix":"","firstName":"Alejandro","middleName":"","lastName":"Carmona","suffix":""},{"id":278886397,"identity":"df101172-caa7-4696-ae70-fff2d31bbd91","order_by":2,"name":"Latifah Ali","email":"","orcid":"","institution":"Tishreen University","correspondingAuthor":false,"prefix":"","firstName":"Latifah","middleName":"","lastName":"Ali","suffix":""},{"id":278886398,"identity":"6774e941-5c61-4960-b8aa-9ea4c22a5db3","order_by":3,"name":"Josefa Rubio","email":"","orcid":"","institution":"Andalusian Institute of Agricultural and Fisheries Research and Training","correspondingAuthor":false,"prefix":"","firstName":"Josefa","middleName":"","lastName":"Rubio","suffix":""},{"id":278886399,"identity":"3325fc4e-4853-4f81-88a4-40931cd6e500","order_by":4,"name":"Teresa Millan","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"prefix":"","firstName":"Teresa","middleName":"","lastName":"Millan","suffix":""},{"id":278886400,"identity":"b7f74f53-49ec-4edc-a5c1-72c5ff7c41b9","order_by":5,"name":"Patricia Castro","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"prefix":"","firstName":"Patricia","middleName":"","lastName":"Castro","suffix":""},{"id":278886401,"identity":"66ee4ebf-2c55-4572-b7ed-a4e54528cae1","order_by":6,"name":"Jose V. Die","email":"","orcid":"","institution":"University of Córdoba","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"V.","lastName":"Die","suffix":""}],"badges":[],"createdAt":"2024-03-01 10:46:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4002926/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4002926/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-024-05411-y","type":"published","date":"2024-07-25T16:16:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52594631,"identity":"cc71f3a9-ee02-4fe1-80cf-0265c8334274","added_by":"auto","created_at":"2024-03-13 11:22:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83657,"visible":true,"origin":"","legend":"\u003cp\u003eScheme followed in the present study to develop the pair of NILs for flowering time. NILs were obtained from the residual heterozygosity in the recombinant inbred line RIP10-82. The different plants (P) used during development are numbered and represented by a symbol according to their phenotype; those selected to obtain the NILs are outlined in red\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/14ed32e152c263e3cb39aaea.png"},{"id":52592685,"identity":"310be051-c028-4526-baf1-a64a82390fea","added_by":"auto","created_at":"2024-03-13 11:06:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":711900,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative phenotypes of NF10/82-E and NF10/82-L plants grown in the field. \u003cstrong\u003e(a) \u003c/strong\u003eComparison of vegetative biomass characterized by contrasting branching and plant height. \u003cstrong\u003e(b) \u003c/strong\u003eNF10/82-L plant characterized by increased branching (more total number of branches and more branches in the initial nodes)\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/edbb43db3262181bf2323fc9.png"},{"id":52592679,"identity":"f95d0c70-c692-4164-805f-7216910f0568","added_by":"auto","created_at":"2024-03-13 11:06:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46482,"visible":true,"origin":"","legend":"\u003cp\u003eDensity in 1 Mb window size over the chickpea chromosomes in the NILsfor the \u003cstrong\u003e(a) \u003c/strong\u003e4,932 HHQ-I variants and \u003cstrong\u003e(b) \u003c/strong\u003e1,610 HHQ-I-C/E variants\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/a86719b8002ed104bb193629.png"},{"id":52592849,"identity":"067bf1b5-4a20-4373-8a86-cd97268de217","added_by":"auto","created_at":"2024-03-13 11:14:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":203973,"visible":true,"origin":"","legend":"\u003cp\u003eGO Slim terms distribution in the category \u003cstrong\u003e(a) \u003c/strong\u003ebiological process, \u003cstrong\u003e(b) \u003c/strong\u003emolecular function and \u003cstrong\u003e(c) \u003c/strong\u003ecellular component for the protein-coding genes affected by HHQ-I-C/E variants in the NILs\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/2b195c2fa489505a9cfdea2b.png"},{"id":52592850,"identity":"ec24ca8a-a862-4bcd-a10f-9a25950fb4ea","added_by":"auto","created_at":"2024-03-13 11:14:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":91427,"visible":true,"origin":"","legend":"\u003cp\u003eConservation of the LOC101515142 haplotypes detected in the NIL pair across some cultivated \u003cem\u003eC. arietinum\u003c/em\u003e accessions (data obtained from 51 SNPs registered in the CicerSeq pangenome public repository). The NF10/82-L haplotype (H1) is conserved in 2,219 accessions (~70%), while the NF10/82-E (H2) is present in 749 (23.6%)\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/04486e6bfb3876b3debfb5ac.png"},{"id":52592684,"identity":"2986ed5b-8a46-470c-87b1-8e2b60b7a129","added_by":"auto","created_at":"2024-03-13 11:06:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":214562,"visible":true,"origin":"","legend":"\u003cp\u003eDensity plot of cultivated chickpea accessions distribution based on days to flowering (DTF) in three locations (ICARDA 2015/16; ICRISAT 2015/16; RARI 2014/15) according to \u003cstrong\u003e(a) \u003c/strong\u003eLOC101515142 haplotype, \u003cstrong\u003e(b) \u003c/strong\u003eLOC101499101 SNP (Ca6: 57,549,449), and \u003cstrong\u003e(c) \u003c/strong\u003eLOC101507442 SNP (Ca6: 57,720,344). The DTF data were acquired from the public repository CicerSeq . Vertical lines represent the global mean (black) and the means for each group (salmon and turquoise). Significant differences were assessed using Student’s t-test (ns: non-significant, *0.01 \u0026lt; \u003cem\u003eP\u003c/em\u003e ≤ 0.05, **0.001 \u0026lt; \u003cem\u003eP\u003c/em\u003e ≤ 0.01, ***\u003cem\u003eP\u003c/em\u003e ≤ 0.001). The number of individuals taken into account for each location/season depending on the SNPs they present is indicated in the upper left corner of each of the plots. Additional data for other locations can be found in \u003cstrong\u003eAdditional file 10\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/2f821c49a31250962b933690.png"},{"id":52592687,"identity":"c568c10c-b784-469c-8a3a-5d9566914f8d","added_by":"auto","created_at":"2024-03-13 11:06:11","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":627822,"visible":true,"origin":"","legend":"\u003cp\u003eThe heatmap expression level of the 132 matched genes with HHQ-I-C/E variants in NILs. The four genes homologous to those included in the FLOR-ID \u003cem\u003eA. thaliana\u003c/em\u003e dataset appear in three clusters. LOC101499101 and LOC101507442 appear in Cluster I. LOC101515142 appears in Cluster III, close to those genes, whereas LOC101489432 shows the most different expression profiles (Cluster V). Tissue Samples: YL, young leaf; ML, mature leaf; SAM, shoot apical meristem; FB (1 – 4), flower bud (different development stages 1 to 4). The TPM data for each transcript ID and their corresponding gene ID can be found in \u003cstrong\u003eAdditional file 11\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/bb2eb1e358f3e192d2725f0e.png"},{"id":61596450,"identity":"f43e9f0f-d638-4efa-9c3e-44800ff44d97","added_by":"auto","created_at":"2024-08-01 17:27:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3209063,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/01981d23-9634-4f1d-bccf-641a7061e8ab.pdf"},{"id":52592700,"identity":"361f7c5c-493f-4038-b57c-969b59cba060","added_by":"auto","created_at":"2024-03-13 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11:14:12","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":14456,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile13.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4002926/v1/481d3a9469b68406fca7513a.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Phenotypic and Genetic Characterization of a Near-Isogenic Line Pair: Insights into Flowering Time in Chickpea. ","fulltext":[{"header":"Background","content":"\u003cp\u003eThe domesticated chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.) is an annual and self-pollinated legume belonging to the Papilionoideae subfamily. With an estimated genome size of ∽ 738 Mb (2\u003cem\u003en \u003c/em\u003e= 2\u003cem\u003ex\u003c/em\u003e = 16), the reference genome CDC Frontier kabuli cultivar has been assembled into 530 Mb [1]. Chickpea is currently the second most cultivated grain legume globally, with a production of 18.1 million tons in 14.8 million ha, resulting in a yield of 1.22 t/ha in 2022 [2]. Despite its importance, global chickpea cultivation is mostly conducted in short-season environments that expose the crop to terminal stresses, consequently limiting its potential yield [3\u0026ndash;5]. In Mediterranean and semi-arid environments, terminal drought and heat stand out as the primary causes of yield loss [6\u0026ndash;9]. Conversely, in higher latitude areas like Canada, the growing season is affected by lower temperatures, delayed maturation, and an increased risk of frost damage [10\u0026ndash;13]. In response to these challenges, early-flowering emerges as a desirable trait for chickpea, serving as an effective escape strategy in various environmental conditions [5, 8, 10, 11, 14]. The flowering time is also linked to fundamental decisions made by the plant about when and how to allocate resources and is therefore involved in a complex web of bidirectional interactions with other developmental processes. Thus, although the defining feature of the vegetative-to-reproductive transition is the conversion of meristems to produce flowers rather than vegetative buds, this is also accompanied by significant changes in a wide range of other developmental traits (e.g. stem elongation and lateral branching). However, despite increasing interest, the genetic control of this complex trait remains unclear [15\u0026ndash;17]. \u003c/p\u003e\n\u003cp\u003eChickpea, along with notable legumes such as pea, lentil, and faba bean, belongs to the galegoid clade. Members of this clade are from temperate regions and exhibit long-day plant characteristics in terms of flowering control. In contrast, legumes in the phaseoloid clade, including soybean, cowpea, pigeon pea, and common bean, are mainly from lower latitudes and are identified as short-day plants [15]. Much of our current understanding of flowering time regulation originates from studies on the model long-day species \u003cem\u003eArabidopsis thaliana \u003c/em\u003e(L.) Heynh\u003cem\u003e.\u003c/em\u003e, where over 300 flowering time genes, including key regulators, have been identified [18]. These genes are involved in seven major pathways governing flowering: \u0026apos;photoperiod/circadian clock,\u0026apos; \u0026apos;vernalization,\u0026apos; \u0026apos;aging,\u0026apos; \u0026apos;ambient temperature,\u0026apos; \u0026apos;hormones,\u0026apos; \u0026apos;sugar,\u0026apos; and \u0026apos;autonomous\u0026apos; pathways. The key signaling integrator molecule responsible for promoting flowering is encoded by the \u003cem\u003eFLOWERING LOCUS T\u003c/em\u003e (\u003cem\u003eFT\u003c/em\u003e) gene in leaves. Upon induction, the FT protein migrates from the leaves to the shoot apex, where it activates meristem identity genes [19, 20]. In contrast, the product of the \u003cem\u003eTERMINAL FLOWER1\u003c/em\u003e (\u003cem\u003eTFL1\u003c/em\u003e) gene functions as an \u0026apos;anti-florigen\u0026apos;, suppressing meristem identity genes [21]. While gene families and pathways controlling flowering time in \u003cem\u003eA. thaliana\u003c/em\u003e are generally conserved in legumes, three main differences stand out [15, 17, 22, 23]. First, variations in the number of gene copies in legumes, where numerous examples of duplication and loss events reflect the evolutionary history after the divergence of \u003cem\u003eArabidopsis \u003c/em\u003eand legume lineages [24]. Legumes, for instance, possess multiple \u003cem\u003eFT \u003c/em\u003egenes organized in three subclades and multiple \u003cem\u003eTFL1 \u003c/em\u003egenes [15, 16, 25, 26]. Second, the absence of \u003cem\u003eFLC \u003c/em\u003eorthologs in the galegoid legume species, such as chickpea, where the vernalization response mechanism remains unknown. However, \u003cem\u003eFT \u003c/em\u003egenes appear to be major targets of vernalization as in \u003cem\u003eA. thaliana\u003c/em\u003e [17, 25\u0026ndash;28]. Third, the distinct roles of \u003cem\u003eCO \u003c/em\u003eorthologous genes in legumes, do not seem to play a central role in integrating photoperiod signaling and circadian rhythms, as observed in \u003cem\u003eA. thaliana\u003c/em\u003e [29, 30]. \u003c/p\u003e\n\u003cp\u003eTraditionally, classical genetic studies have identified four major Mendelian loci that control flowering time in chickpea. Recessive alleles at these loci confer early-flowering [31]. These loci have been designated as \u003cem\u003eEarly flowering1\u003c/em\u003e (\u003cem\u003eEfl1\u003c/em\u003e) to \u003cem\u003eEfl4\u003c/em\u003e, with corresponding mutant alleles labeled as \u003cem\u003eefl1 \u003c/em\u003eto \u003cem\u003eefl4\u003c/em\u003e. The initial identification of these loci occurred in specific lines: ICCV 2 (\u003cem\u003eEfl1\u003c/em\u003e; [32]), ICC 5010 (\u003cem\u003eEfl2\u003c/em\u003e; [33]), BGD-132 (\u003cem\u003eEfl3\u003c/em\u003e; [34]), and ICC 16641 and ICC 16644 (\u003cem\u003eEfl4\u003c/em\u003e;[31]). Studies have shown that these flowering time genes are non-allelic [31, 34]. In addition, numerous quantitative trait loci (QTLs) associated with flowering time have been identified through linkage analysis, with some predicted to possess minor effects. These QTLs are distributed across various linkage groups (LG), including LG1, LG2, LG3, LG4, LG5, LG6, and LG8, as reported in studies using different parental lines [7, 35\u0026ndash;39]. Despite the identification of these major loci and QTLs, the correspondence and characterization of the underlying genes have been limited to date. [40] proposed that the \u003cem\u003eElf1 \u003c/em\u003elocus corresponds to \u003cem\u003eCaELF3a\u003c/em\u003e, an ortholog of \u003cem\u003eArabidopsis ELF3 \u003c/em\u003emapped on Ca5, although the possibility of other nearby genes contributing to the \u003cem\u003eEfl1 \u003c/em\u003ephenotype cannot be definitively excluded. For the QTL in LG3, the cluster \u003cem\u003eFTa1\u003c/em\u003e/\u003cem\u003ea2\u003c/em\u003e/\u003cem\u003ec\u003c/em\u003e has been identified as the strongest candidate [16]. \u003c/p\u003e\n\u003cp\u003eTo deepen our understanding of the genes governing early-flowering phenotypes in chickpea, the development of near-isogenic lines (NILs) emerges as a promising strategy. Pairs of NILs, designed to manifest variation in specific agronomic traits, have been proven invaluable for fine mapping of QTLs and characterizing underlying genes [41]. NILs are distinguished by differences in small genomic sections, effectively minimizing background genetic noise. This plant material facilitates the assessment of allelic variation at both phenotypic and molecular levels, enabling comparisons at genomic or transcriptomic scales. The characteristics of NILs not only provide a focused study of flowering time but also offer accessibility for exploring interconnected traits. In chickpea, NILs have successfully been applied in studies on growth habit [42], plant height [43], double/single pod [44, 45]\u003cem\u003e, \u003c/em\u003enodulation [46],\u003cem\u003e Fusarium \u003c/em\u003ewilt resistance [47\u0026ndash;49] as well as flowering time [50]. \u003c/p\u003e\n\u003cp\u003eAdvances in next-generation sequencing (NGS) technologies have enabled the generation of large-scale sequencing and genotyping data sets in chickpea, resulting in the creation of valuable genomic resources since the first sequenced genome [1]. One notable achievement is the comprehensive mapping of variation acquired through the sequencing of 3,171 cultivated and 195 wild accessions alongside phenotypic data [51], now publicly accessible via the CicerSeq repository. Additional resources like Atlas GEO chickpea complement these datasets, providing a robust foundation for comprehensive investigations into gene function and transcriptional pattern expression in various tissues through chickpea development [52]. This extensive dataset serves as a vital resource for genomic and diversity research, facilitating a deeper molecular-level understanding of traits essential for enhancing chickpea cultivation.\u003c/p\u003e\n\u003cp\u003eIn this study, we identified and characterized candidate genes for chickpea flowering through a combined phenotypic and genetic analysis involving re-sequencing of a pair of NILs. Utilizing bioinformatics approaches and public genomic datasets, we identified homologs to flowering-related genes in \u003cem\u003eA. thaliana\u003c/em\u003e with variants among the NILs, including \u003cem\u003eELF3\u003c/em\u003e, and, for the first time, \u003cem\u003eMED16 \u003c/em\u003eand \u003cem\u003eSTO/BBX24\u003c/em\u003e in chickpea. We also analyzed the allelic diversity of these novel genes and their conservation within chickpea diversity. Additionally, transcriptomic data in chickpea enable us to explore \u003cem\u003ein silico\u003c/em\u003e expression profiles for candidate genes in vegetative tissues such as leaves and shoot apical meristem, crucial for promoting flowering, as well as in early flowering stages.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch2\u003ePlant materials and NIL development\u003c/h2\u003e\n\u003cp\u003eA pair of chickpea NILs distinguished by flowering time was employed: an early-flowering NIL (NF10/82-E) and a late-flowering NIL (NF10/82-L). These NILs were developed from residual heterozygosity in a F\u003csub\u003e6:7\u0026nbsp;\u003c/sub\u003erecombinant inbred line (RIL) named RIP10\u0026ndash;82 derived from the intraspecific cross JG62 x ILC72. This methodology is an alternative method to the traditional approach involving consecutive backcrossing followed by self-pollination, known for its effectiveness in self-pollinated crops as chickpea [53]. The parental line JG62 (syn. ICC4951) is an Indian early-flowering desi landrace maintained by ICRISAT (International Crops Research Institute for the Semi-Arid Tropics), while ILC72 (syn. CPAM88) is a late-flowering kabuli type from the former Soviet Union maintained by ICARDA (International Center for Agricultural Research in the Dry Areas). Descendants from the early-flowering individuals of RIP10\u0026ndash;82 consistently showed early-flowering phenotype, while some from late-flowering individuals exhibited segregation for this trait. This observation suggests that early-flowering should be a recessive trait in this context.\u003c/p\u003e\n\u003cp\u003eTo develop the NILs, seeds from an individual heterozygous plant were collected and sowed, designated as RIP10\u0026ndash;82/P1 (\u003cstrong\u003eFig. 1\u003c/strong\u003e). Subsequently, a heterozygous descendant for flowering time was selected to proceed with (RIP10\u0026ndash;82/P1/P3). Two non-segregating progeny were selfed for both early (RIP10\u0026ndash;82/P1/P3/P8) and late-flowering (RIP10\u0026ndash;82/P1/P3/P12). One descendant from each one was selfed once more and considered as NILs for this trait: an early-flowering line (RIP10-82/P1/P3/P8/P5, called NF10/82-E) and a late-flowering line (RIP10-82/P1/P3/P12/P13, called NF10/82-L). This means that the NILs were obtained after at least 11 generations of self-fertilization (seven until the RIP10-82 line was obtained and four more afterwards).\u003c/p\u003e\n\u003ch2\u003eGrowth Conditions and Phenotypic Characterization\u003c/h2\u003e\n\u003cp\u003ePhenotypic characterization of the pair of NILs involved the assessment of 15 plants each, sown on March 28 2022, in the field at the IFAPA site in C\u0026oacute;rdoba, Spain (latitude/longitude/altitude: 37\u0026ordm;53\u0026rsquo;N/4\u0026ordm;47\u0026rsquo;W/117m). The plants were arranged in two independent rows, 2.25 m apart. Days to flowering (DTF) were recorded from seedling emergence to the opening of the first flower for each plant. Subsequently, the plants were harvested, dried and phenotyped for six morphological traits: plant weight (PW, g), plant height (PH, cm), internodes per plant (IPP), internode length (IL, cm), total number of branches per plant (BPP) and the number of branches in the first three nodes (BF). Additionally, a branching index (BI) was calculated, defined as the ratio of total branch length to plant length, to normalize differences in general vigor. Statistical significance was assessed using a t-test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) in RStudio v.4.2.0.\u003c/p\u003e\n\u003ch2\u003eDNA extraction and Resequencing\u003c/h2\u003e\n\u003cp\u003eTotal genomic DNA was isolated from young leaves of an individual NF10/82-E and an individual NF10/82-L using the DNeasy Plant Mini Kit (Qiagen) according to the manufacturer\u0026rsquo;s instructions. DNA samples from both NILs were sequenced by \u003cem\u003eCentro Nacional de An\u0026aacute;lisis Gen\u0026oacute;mico\u0026nbsp;\u003c/em\u003e(CNAG-CRG; Barcelona, Spain) using an \u003cem\u003eIllumina\u003c/em\u003e \u003cem\u003eHiSeq2000\u003c/em\u003e instrument with 50x coverage. Variants (SNPs and InDels) were identified against the chickpea reference genome (CDC Frontier genome, assembly ASM33114v1; NCBI). Variants with a read depth \u0026lt; 10 in at least one sample were not considered.\u003c/p\u003e\n\u003ch2\u003eGenetic Characterization\u003c/h2\u003e\n\u003cp\u003eThe sequence differences detected between the NILs were analyzed, distinguishing between homozygous and heterozygous positions. The identified variants (SNPs and InDels) were filtered including only those passing all quality criteria or failing to meet only one criterion. These criteria are summarized in the FILTER comments in the VCF v.4.2 file containing the variant sequencing report of the NILs (accession number PRJEB73790; European Variation Archive at EMBL-EBI). Our selection was focused exclusively on homozygous variants confidently assigned to chromosomes, determined by the absence of segregation for flowering time observed in the phenotypic data collected at the end of NIL development. Theoretical impact assessment of variants was conducted using snpEff v.4.x\u003cem\u003e\u0026nbsp;\u003c/em\u003e[54], categorizing them as modifier, low, moderate, or high impact. To assess intragenic variants, all variants with an annotation impact other than \u0026quot;intergenic region\u0026quot;, \u0026quot;upstream gene variant\u0026quot; or \u0026quot;downstream gene variant\u0026quot; were selected. These variants located in loci were classified by their specific region type as mRNA (coding sequence (CDS), exon or intron), lncRNA, rRNA, snRNA, snoRNA or pseudogene/miscellaneous RNA variant according to the \u003cem\u003eC. arietinum\u0026nbsp;\u003c/em\u003eGFF data information from NCBI using a custom R script (GitHub/AGR114molecularBreeding/chickpea/SNP_PosType). The density of variants in chromosomes was visualized using SRplot tools [55]. For protein-coding genes, protein accession was obtained using the \u003cem\u003erefseqR\u003c/em\u003e package v.1.0.1 [56]. The Gene Ontology Tool Blast2GO v.6.0 [57] was employed to assign GO identities for functional annotation of the protein-coding genes with variants in exons or CDS. The following settings were used: BLASTp against NCBI nr database, \u003cem\u003eE\u003c/em\u003e-value filter \u0026le; 10\u003csup\u003e-3\u003c/sup\u003e, HSP length cutoff of 33, maximum 10 BLAST hits per sequence and annotation cutoff of 33. Furthermore, to enhance the annotation ability, InterProScan was conducted, results were merged to GO annotations and plant GO Slim were obtained. An enrichment analysis calculated via Fisher\u0026rsquo;s exact test was performed to compare the functional annotations of the protein-coding genes with variants in exons or CDS against the whole chickpea genome annotation.\u003c/p\u003e\n\u003ch2\u003eCandidate Genes\u003c/h2\u003e\n\u003cp\u003eFrom the functional annotation, candidate genes were selected based on the enriched GO terms derived from a dataset of 306 flowering-related genes in \u003cem\u003eA. thaliana\u003c/em\u003e, obtained from the FLOR-ID database [18]. The Go Term Enrichment for Plants tool, available through TAIR and powered by PANTHER [58], was employed for this analysis. Only those child GO Slim terms within each ancestor GO Slim were considered (\u003cstrong\u003eAdditional file 2\u003c/strong\u003e). Additionally, a reciprocal BLASTp was performed to identify whether any of the candidate genes showed homology to those included in the \u003cem\u003eA. thaliana\u003c/em\u003e FLOR-ID dataset.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eIn silico\u003c/em\u003e Expression Analysis\u003c/h2\u003e\n\u003cp\u003eThe CDS of the candidate genes were utilized to identify their corresponding matches through reciprocal BLASTn in the chickpea expression atlas during development, available in the NCBI GEO database under the accession GSE147831 [52]. The expression atlas data were then imported, classified and analyzed using a custom R script to convert the FPKM data into TPM, facilitating comparison between different tissues and genes (GitHub/AGR114molecularBreeding/chickpea/GEO). All matched genes were examined for their \u003cem\u003ein silico\u003c/em\u003e expression pattern using data from seven different chickpea tissues: young leaf (YL), mature leaf (ML), four stages of flower-bud (FB1\u0026ndash;4) and shoot apical meristem (SAM). The heatmap visualization plot for expression level was obtained using SRplot tools with complete-linkage cluster method and Euclidean distance [55].\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003ePhenotypic Characterization\u003c/h2\u003e\n\u003cp\u003eThe traits recorded for grown-field NILs are shown in \u003cstrong\u003eTable 1\u003c/strong\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eThe difference in flowering time between NILs was about 14 days (44.4 \u0026plusmn; 2.8 days for NF10/82-E and 58.0 \u0026plusmn; 1.1 days for NF10/82-L). NF10/82-E exhibited reduced vegetative biomass characterized by decreased branching (lower total number of branches and fewer branches in the initial nodes) and shorter plant height with fewer internodes (\u003cstrong\u003eFig. 2\u003c/strong\u003e). Nevertheless, its internode length exceeded that of the late-flowering ones (2.47 \u0026plusmn; 0.17 for NF10/82-E vs. 2.23 \u0026plusmn; 0.10 for NF10/82-L).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Phenotypic characterization of the NILs (Mean \u0026plusmn; SD)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"650\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDTF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIPP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBPP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eBI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNF10/82-E\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e44.4 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e3.79 \u0026plusmn; 1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e52.5 \u0026plusmn; 6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e22.3 \u0026plusmn; 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e2.47 \u0026plusmn; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e3.91 \u0026plusmn; 2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e0.73 \u0026plusmn; 0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e1.25 \u0026plusmn; 0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNF10/82-L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e58.0 \u0026plusmn; 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e9.14 \u0026plusmn; 2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e66.6 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e30.9 \u0026plusmn; 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e2.23 \u0026plusmn; 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e21.5 \u0026plusmn; 6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e2.57 \u0026plusmn; 1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e6.01 \u0026plusmn; 1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et-test\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSignificant difference Student\u0026rsquo;s \u003cem\u003et-test\u003c/em\u003e (ns: non-significant, *0.01 \u0026lt; P \u0026le; 0.05, **0.001 \u0026lt; P \u0026le; 0.01, ***P \u0026le; 0.001). DTF, Days to flowering; PW, Plant weight (g); PH, Plant height (cm); IPP, Internodes per plant; IL, Internode length (cm); BPP, Branches per plant; BF, Branches in the first three nodes; BI, Branching index\u003c/p\u003e\n\u003ch2\u003eGenetic Characterization\u003c/h2\u003e\n\u003cp\u003eThe sequencing data confirmed a high degree of similarity between NILs. A total of 393,670,345 positions were read, revealing 120,441 different positions constituting the detected variants (\u003cstrong\u003eAdditional file 1\u003c/strong\u003e). This indicates that the NILs differ in only 0.03% of positions between them. Additionally, for NF10/82-L, 209,276 heterozygous positions were detected, and for the NF10/82-E, 200,084, corresponding to an observed heterozygosity of 0.053% and 0.051%, respectively. Both lines underwent at least 11 generations of self-fertilization during their development (\u003cstrong\u003eFig. 1\u003c/strong\u003e), so the expected residual heterozygosity is 0.098% deduced from Mendelian Genetics for self-fertilizing generations. The observed values being lower than expected are reasonable because the segregating population from which these lines were obtained may have undergone prior refreshing processes to maintain seed viability. In other words, it could have undergone additional generations of self-fertilization to maintain a suitable number of viable seeds before the actual process of obtaining the NILs.\u003c/p\u003e\n\u003cp\u003eApproximately 64% of the detected variants were successfully mapped to chromosomes (77,170), of which 45,481 met the applied quality criteria (\u003cstrong\u003eTable 2\u003c/strong\u003e). Only 15,690 variants were homozygous, with 4,932 being intragenic in 432 loci (HHQ-I variants; \u003cstrong\u003eAdditional file 3\u003c/strong\u003e). There are 37 variants expected to affect two loci simultaneously.\u003c/p\u003e\n\u003cp\u003eAmong all HHQ-I variants detected on chromosomes, 1,610 are located in CDS or exons (HHQ-I-C/E variants; 849 in CDS, 758 in exon regions and three are located in both depending on DNA strand), affecting 246 protein-coding genes (\u003cstrong\u003eTable 2\u003c/strong\u003e). Additionally, there are 176 variants located in non-protein-coding RNA genes, including 17 uncharacterized lncRNA (168 variants), two snRNA (4), one snoRNA (1) and three tRNA (3) (\u003cstrong\u003eAdditional file 4)\u003c/strong\u003e. Finally, 199 variants are positioned in pseudogenes or miscellaneous RNA. Notably, six variants are classified as intragenic, affecting LOC101491595, but in a region devoid of additional features according to the GFF data of \u003cem\u003eC. arietinum\u003c/em\u003e. As explained by NCBI staff, this discrepancy is attributed to an artificial extension of this locus resulting from an error in the annotation of the non-protein-coding transcript XR_003470270.1 (personal communication). Consequently, XR_003470270.1 has recently been suppressed by NCBI RefSeq staff.\u003c/p\u003e\n\u003cp\u003eThe distribution of the HHQ-I and HHQ-I-C/E variants did not follow a proportional pattern concerning chromosome size, nor was it uniform along the chromosomes (\u003cstrong\u003eFig. 3\u003c/strong\u003e). Most of them are positioned in a region at the beginning of chromosome 1 (Ca1: 1.78 \u0026ndash; 3.15 Mb) and the end of chromosome 6 (Ca6: 57.2 \u0026ndash; 58.8 Mb). These are the only two chromosomes with specific regions containing more than 200 variants per 1 Mb window. Notably, chromosome 3 lacks any HHQ-I variant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Number of variants (SNPs and InDels) and protein-coding genes affected per chromosome in the pair of NILs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eChr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003eSize (Mb)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003eDetected Variants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003eHQ Variants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003eHHQ Variants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003eHHQ-I\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Variants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003eHHQ-I-C/E Variants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003eProtein-coding Genes with HHQ-I-C/E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e48.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e31,790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e23,428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e12,585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e4,185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e1,334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e36.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e7,012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e3,774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e39.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e5,311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e2,095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e49.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e5,371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e2,259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e48.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e6,843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e2,936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e59.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e12,594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e7,507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e2,232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e48.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e6,598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e2,625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003eCa8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e16.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e1,651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.220779220779221%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003eTOTAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.96103896103896%\"\u003e\n \u003cp\u003e77,170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.714285714285714%\"\u003e\n \u003cp\u003e45,481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.337662337662337%\"\u003e\n \u003cp\u003e15,690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e4,932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.746753246753247%\"\u003e\n \u003cp\u003e1,610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01948051948052%\"\u003e\n \u003cp\u003e246\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHQ, High-quality; HHQ, Homozygous high-quality; HHQ-I, Intragenic homozygous high-quality;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHHQ-I-C/E, Intragenic homozygous high quality in CDS or exon of mRNA\u003c/p\u003e\n\u003cp\u003eFunctional annotation using Blast2GO was successfully performed on 216 out of the 246 coding genes affected by HHQ-I-C/E variants (\u003cstrong\u003eAdditional file 5\u003c/strong\u003e). The distribution of GO Slim terms among protein-coding genes across the ontologies of \u0026ldquo;molecular function\u0026rdquo;, \u0026ldquo;biological process\u0026rdquo;, and \u0026ldquo;cellular component\u0026rdquo; (\u003cstrong\u003eFig. 4\u003c/strong\u003e) revealed no enrichment compared to the entire chickpea annotated genome using Fisher\u0026apos;s exact test (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003ch2\u003eCandidate Genes\u003c/h2\u003e\n\u003cp\u003eBased on GO Slim enrichment analysis in \u003cem\u003eA. thaliana\u003c/em\u003e for the FLOR-ID set of flowering-related genes, there are 146 genes affected by HHQ-I-C/E variants that have any of these enriched GO Slim terms \u003cstrong\u003e(Additional file 6)\u003c/strong\u003e. Among them, four genes seem to be homologous to those found in the FLOR-ID \u003cem\u003eA. thaliana\u003c/em\u003e dataset according to the reciprocal BLASTp results. These genes are LOC101515142, LOC101489432 (also known as \u003cem\u003eCaELF3a\u003c/em\u003e), LOC101499101 and LOC101507442 (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eLOC101515142 (Ca1: 2,285,592 - 2,298,911, complement) is annotated as \u0026ldquo;Mediator of RNA polymerase II transcription subunit 16-like\u0026rdquo; (\u003cem\u003eMED16\u003c/em\u003e), an homologue of the \u003cem\u003eA. thaliana MED16/SFR6\u003c/em\u003e gene encoding a component of the Mediator complex involved in diversal aspects of gene expression regulation \u003ca href=\"https://sciwheel.com/work/citation?ids=3692745\u0026pre=\u0026suf=\u0026sa=0\"\u003e[59]\u003c/a\u003e. In chickpea, a second homologue is present on Ca6 (LOC101501202, Ca6: 16,660,218 - 16,679,432) without any detected variants between NILs. LOC101515142 is affected by 94 variants, from which 14 affect exon or CDS regions (\u003cstrong\u003eTable 3\u003c/strong\u003e). Most alternative variant alleles are found in NF10/82-E, with only one detected in NF10/82-L (a 21 bp deletion located in an intron in Ca1: 2,297,103). This locus encodes six different isoforms, being affected by three variants in CDS with different impacts. For example, NF10/82-E has a 6 bp deletion (Ca6: 2,298,571) that affects two isoforms with a moderate impact (by the loss of two Glu), whereas another two transcriptional isoforms are affected in the 5\u0026rsquo; UTR (\u003cstrong\u003eAdditional file 7. Fig. S1a)\u003c/strong\u003e. However, the other 11 HHQ-I-C/E variants affect all isoforms equally with low or modifier theoretical impacts. In any case, the high number of detected variants affecting this locus could have some implications for its functional activity.\u003c/p\u003e\n\u003cp\u003eLOC101489432 (\u003cem\u003eCaELF3a\u003c/em\u003e, Ca5: 36,011,384 \u0026ndash; 36,016,600, complement) is one of the two homologs of \u003cem\u003eA. thaliana\u003c/em\u003e \u003cem\u003eELF3\u003c/em\u003e identified in legumes, previously reported to be involved in the regulation of the circadian clock and to influence the flowering process in chickpea \u003ca href=\"https://sciwheel.com/work/citation?ids=4410923\u0026pre=\u0026suf=\u0026sa=0\"\u003e[40]\u003c/a\u003e. In this study, an 11 bp deletion located at Ca5: 36,016,064 was detected in NIL10/82-E. This deletion is predicted to affect the first exon of \u003cem\u003eCaELF3a\u003c/em\u003e, resulting in six missense amino acids followed by a premature stop codon. Consequently, this alteration reduces the protein length from 699 to 13 amino acids (\u003cstrong\u003eAdditional file 7. Fig. S1b\u003c/strong\u003e).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe absence of other isoforms encoded by \u003cem\u003eCaELF3a\u0026nbsp;\u003c/em\u003esuggests a significant impairment in its functionality.\u003c/p\u003e\n\u003cp\u003eFinally, two loci at the end of Ca6 are affected by HHQ-I-C/E variants. On one hand, LOC101499101 is a B-box finger protein homolog of \u003cem\u003eSTO/BBX24\u003c/em\u003e, known to link the \u003cem\u003eFRI/FLC\u003c/em\u003e and photoperiod/circadian clock pathways, affecting flowering time in \u003cem\u003eA. thaliana\u003c/em\u003e \u003ca href=\"https://sciwheel.com/work/citation?ids=794430\u0026pre=\u0026suf=\u0026sa=0\"\u003e[60]\u003c/a\u003e. On the other hand, LOC101507442 is a \u003cem\u003eVRN1\u003c/em\u003e-\u003cem\u003elike\u003c/em\u003e transcription factor containing a B3 domain, encoding a DNA-binding protein involved in the vernalization pathway that represses \u003cem\u003eFLC\u0026nbsp;\u003c/em\u003eexpression, thus promoting flowering \u003ca href=\"https://sciwheel.com/work/citation?ids=1355086\u0026pre=\u0026suf=\u0026sa=0\"\u003e[61]\u003c/a\u003e. Both loci are affected by only one SNP with modifier or low theoretical impact. LOC101499101 has a SNP affecting the 3\u0026rsquo;UTR (\u003cstrong\u003eAdditional file 7. Fig. S1c)\u003c/strong\u003e, while LOC101507442 has a SNP located in the third exon, influencing its two potential protein isoforms as a synonymous variant (\u003cstrong\u003eAdditional file 7. Fig. S1d)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Genes affected by HHQ-I-C/E variants that appear homologous to four genes included in the \u003cem\u003eA. thaliana\u003c/em\u003e FLOR-ID dataset\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.15629522431259%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eC. arietinum\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eID NCBI\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.696092619392186%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHomologous \u003cem\u003eA. thaliana\u003c/em\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eID TAIR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143270622286542%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHHQ-I-C/E Variants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.827785817655572%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant Position\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.209840810419681%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRef (0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.643994211287988%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlt (1)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.6410998552822%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant Impacts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNF10/82-L\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNF10/82-E\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.15629522431259%\" rowspan=\"14\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101515142\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMediator of RNA polymerase II transcription subunit 16-like\u003c/p\u003e\n \u003cp\u003e(Ca1: 2,285,592 \u0026ndash; 2,298,911, complement)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.696092619392186%\" rowspan=\"14\"\u003e\n \u003cp\u003eAT4G04920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143270622286542%\" rowspan=\"14\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e(+ 80 in intron regions)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.827785817655572%\"\u003e\n \u003cp\u003e2,285,696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.209840810419681%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.643994211287988%\"\u003e\n \u003cp\u003eCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.6410998552822%\" valign=\"bottom\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,285,879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,286,112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,286,256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,286,460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,286,488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,288,143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,291,280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,292,486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,292,528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,294,335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,298,490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], 5_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,298,571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eCTCTTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003edisruptive_inframe_deletion [MODERATE], 5_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.174946004319654%\"\u003e\n \u003cp\u003e2,298,634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.775377969762419%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.423326133909287%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.25269978401728%\" valign=\"bottom\"\u003e\n \u003cp\u003esynonymous_variant [LOW], 5_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.68682505399568%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.15629522431259%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101489432\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eprotein EARLY FLOWERING 3a\u003c/p\u003e\n \u003cp\u003e(Ca5: 36,011,384 \u0026ndash; 36,016,600, complement)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.696092619392186%\"\u003e\n \u003cp\u003eAT2G25930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143270622286542%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.827785817655572%\"\u003e\n \u003cp\u003e36,016,064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.209840810419681%\"\u003e\n \u003cp\u003eATCATCATCTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.643994211287988%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.6410998552822%\"\u003e\n \u003cp\u003eframeshift_variant [HIGH], non_coding_transcript_exon_variant [MODIFIER], \u0026nbsp;non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.15629522431259%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101499101\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eB-box zinc finger protein 24\u003c/p\u003e\n \u003cp\u003e(Ca6: 57,549,424 \u0026ndash; 57,552,323, complement)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.696092619392186%\"\u003e\n \u003cp\u003eAT1G06040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143270622286542%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.827785817655572%\"\u003e\n \u003cp\u003e57,549,449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.209840810419681%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.643994211287988%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.6410998552822%\"\u003e\n \u003cp\u003e3_prime_UTR_variant [MODIFIER], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.15629522431259%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101507442\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eB3 Domain-\u003c/p\u003e\n \u003cp\u003econtaining transcription factor VRN1-like\u003c/p\u003e\n \u003cp\u003e(Ca6: 57,717,926 \u0026ndash; 57,721,229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.696092619392186%\"\u003e\n \u003cp\u003eAT3G18990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.143270622286542%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.827785817655572%\"\u003e\n \u003cp\u003e57,720,344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.209840810419681%\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.643994211287988%\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.6410998552822%\"\u003e\n \u003cp\u003esynonymous_variant [LOW], non_coding_transcript_variant [MODIFIER]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.84081041968162%\"\u003e\n \u003cp\u003e1/1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe 11 bp deletion in \u003cem\u003eCaELF3a\u0026nbsp;\u003c/em\u003eseems to be distributed across a small proportion of chickpea germplasm, with only two haplotypes identified that specifically differ in this deletion \u0026nbsp;\u003ca href=\"https://sciwheel.com/work/citation?ids=4410923\u0026pre=\u0026suf=\u0026sa=0\"\u003e[40]\u003c/a\u003e. To gain insights into the genetic variability and conservation of the variants detected in LOC101515142, LOC101499101 and LOC101507442 along chickpea diversity, we analyzed the different accessions represented in the public repository CicerSeq, which contains information about the SNPs detected in cultivated chickpea \u003ca href=\"https://sciwheel.com/work/citation?ids=11999657\u0026pre=\u0026suf=\u0026sa=0\"\u003e[51]\u003c/a\u003e. Among the 94 variants detected for LOC101515142 in the pair of NILs, 68 are SNPs, with 51 positions registered in CicerSeq. The contrasting haplotypes for LOC101515142 detected in NILs are highly conserved along the 3,171 cultivated accessions for \u003cem\u003eC.arietinum\u0026nbsp;\u003c/em\u003eregistered in the pangenome (\u003cstrong\u003eFig. 5 and Additional file 8\u003c/strong\u003e). The NF10/82-L haplotype is conserved in approximately 70% of the accessions (H1), while the NF10/82-E is present in about 23.6% (H2). Interestingly, ~3.8% of accessions have the NF10/82-L haplotype except for one SNP variant located in Ca1: 2,295,317 (in the intron region of LOC101515142\u003cem\u003e;\u0026nbsp;\u003c/em\u003eH3), and 2% of accessions have an intermediate haplotype (36/51 SNPs like NF10/82-L haplotype; H4). For the SNPs in LOC101499101 (T/A) \u0026nbsp;and LOC101507442 (C/T), the reference alleles are the majority (82.2% T/ 9.4% A \u0026nbsp; and \u0026nbsp;83.7% C/ 7.3% T, respectively) (\u003cstrong\u003eAdditional file 9\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eThe DTF data for chickpea accessions, available in the public repository CicerSeq across six locations and two seasons (excluding the IIPR location, which only provided data for one season), were analyzed according to the SNPs present in LOC101515142 haplotype, LOC101499101, and LOC101507442 (\u003cstrong\u003eAdditional file 9\u003c/strong\u003e). Accession density distribution plots were obtained for each group (\u003cstrong\u003eFig. 6 and Additional file 10\u003c/strong\u003e). In accessions with contrasting haplotypes of LOC101515142, significant differences in DTF were only found in three different locations/seasons. In the other locations, the data reflect a similar DTF distribution for the different lines between the two groups of accessions with contrasting haplotypes. This pattern is also observed for the SNP in LOC101507442, where significant differences were only detected in ICARDA 2015/16. In contrast, for the SNP located in LOC101499101, interestingly significant differences are found in all locations/seasons, except RARI 2015/16. These consistent differences across locations and seasons suggest that LOC101499101 could influence flowering time along chickpea diversity.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eIn silico\u003c/em\u003e Expression Analysis\u003c/h2\u003e\n\u003cp\u003eA total of 132 CDS from the selected 146 protein-coding genes, based on their functional annotation, were unambiguously matched with sequences in the GEO dataset. The TPM data for each transcript ID and their corresponding gene ID can be found in \u003cstrong\u003eAdditional file 11\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe TPM level heatmap categorized LOC101515142, LOC101489432, LOC101499101 and LOC101507442 into three distinct clusters (\u003cstrong\u003eFig. 7)\u003c/strong\u003e. LOC101499101 and LOC101507442 (both situated at the end of Ca6) show a similar expression pattern, closely grouped in the same subcluster, characterized by genes with higher expressions at all FB stages (Cluster I). LOC101515142 (Ca1: 2,285,592 \u0026ndash; 2,298,911, complement) is in a neighboring cluster (Cluster III) with lower expression levels at the end of the FB stage (FB3 and FB4), but higher levels in SAM. Finally, LOC101489432 (Ca5: 36,011,384 \u0026ndash; 36,016,600, complement) shows the most different expression profile, falling into a cluster with high expression levels in SAM and low expression in FB tissues (Cluster V). This locus is somewhat isolated from other genes in its cluster due to its lower expression level in YL and higher level in ML. The detailed description of co-expressed genes for these four genes can be found in \u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Cluster I, it is remarkable LOC101513952 (\u003cem\u003eCaARF2\u003c/em\u003e), which is an auxin response factor protein (ARF). The ARF family members are considered the core of auxin signaling with important functions as regulators of plant growth and developmental processes \u003ca href=\"https://sciwheel.com/work/citation?ids=5463618,52098\u0026pre=\u0026pre=\u0026suf=\u0026suf=\u0026sa=0,0\"\u003e[62, 63]\u003c/a\u003e. NF10/82-E exhibits 14 variants affecting this locus, of which six are located in exon or CDS with moderate and low theoretical impacts. LOC101491064 also stands out in this cluster, encoding a DNA-binding one zinc finger (DOF) protein. DOF transcription factor genes are involved in various fundamental processes in plants, including responses to light, phytohormones, as well as roles in seed maturation or germination \u003ca href=\"https://sciwheel.com/work/citation?ids=15859082\u0026pre=\u0026suf=\u0026sa=0\"\u003e[64]\u003c/a\u003e. For this locus, a total of 72 variants were detected in NF10/82-E with 13 located in exon or CDS regions. Additionally, LOC101491273 is an ethylene-responsive transcription factor (ERF) affected by four HHQ-I-C/E variants, one of them predicted to have a moderate impact as a missense variant. In Cluster III, no other gene apart from LOC101515142 seems to be prominent for flowering.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, LOC101492009 and LOC101510831 show the most similar expression pattern with \u003cem\u003eCaELF3a\u0026nbsp;\u003c/em\u003ein Cluster V. LOC101492009 is the TIFY5A protein, and LOC101510831 is a helicase-like transcription factor CHR28, both with the stress response GO Slim term. Moreover, in this Cluster V fall LOC101504196 (ethylene-responsive transcription factor 12) with 2 SNPs and LOC101500880, another DOF transcription factor (dof zinc finger protein DOF5.3-like) with a SNP in 3\u0026rsquo;UTR. Thus, there are two members of the ERF family and two members of the DOF family that fall into the same clusters that the genes appearing to be homologous to those found in the FLOR-ID \u003cem\u003eA. thaliana\u003c/em\u003e dataset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eCo-expressed genes associated with the four genes affected by HHQ-I-C/E variants (highlighted in \u003cstrong\u003ebold\u003c/strong\u003e) homologous to genes included in FLOR-ID\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"949\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCluster\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Variants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGO Slim Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGene Description\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101492907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: lipid metabolic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eenoyl-CoA delta isomerase 2, peroxisomal-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101495155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: hydrolase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eGDSL esterase/lipase At5g45920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101511773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: hydrolase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eATP-dependent zinc metalloprotease FTSH 4, mitochondrial-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101497641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eheterogeneous nuclear ribonucleoprotein U-like protein 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101505696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to biotic stimulus; P: response to external stimulus; P: response to stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eputative disease resistance protein At3g14460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101507442\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF: DNA binding\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB3 domain-containing transcription factor VRN1-like\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101513952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to chemical; P: response to endogenous stimulus; P: biosynthetic process; P: signal transduction; F: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eauxin response factor 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101491064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: DNA-binding transcription factor activity; F: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003edof zinc finger protein DOF 4.7-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101507871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003epentatricopeptide repeat-containing protein At4g20740-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101499101\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP: post-embryonic development; P: response to light stimulus; P: biosynthetic process\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB-box zinc finger protein 24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101513083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: DNA-binding transcription factor activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003euncharacterized LOC101513083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101510178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003ehomeobox-DDT domain protein RLT1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101491273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to chemical; P: response to endogenous stimulus; P: biosynthetic process; P: signal transduction; F: DNA-binding transcription factor activity;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eF: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eethylene-responsive transcription factor 1B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101504748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003espermidine synthase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101508062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: kinase activity; F: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eprotein STRUBBELIG-RECEPTOR FAMILY 3-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101496576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eTATA box-binding protein-associated factor RNA polymerase I subunit B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101495479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eTHO complex subunit 7A-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101505912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: kinase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eprotein kinase PINOID-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101514288\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003esplicing factor U2af large subunit B-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101488340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eproteinaceous RNase P 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIII\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101515142\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP: biosynthetic process\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emediator of RNA polymerase II transcription subunit 16-like\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101501305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: signal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e14-3-3-like protein C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101500879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003epre-mRNA-splicing factor SYF1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101491071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003ephospholipase A-2-activating protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101501014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: kinase activity; F: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eprobable inactive leucine-rich repeat receptor-like protein kinase At3g03770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101504099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: hydrolase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eribosome biogenesis protein BMS1 homolog\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101493874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to chemical; P: response to stress; F: protein binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eE3 ubiquitin-protein ligase RMA1H1-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101515146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: chromatin binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003euncharacterized LOC101515146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101491385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: hydrolase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003enon-cyanogenic beta-glucosidase-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101503100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to chemical; P: response to endogenous stimulus; P: signal transduction; \u0026nbsp; F: transporter activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003elysine histidine transporter-like 8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101506337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: hydrolase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eU4/U6.U5 tri-snRNP-associated protein 2-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101504196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: DNA-binding transcription factor activity; F: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eethylene-responsive transcription factor 12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101500880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process; F: DNA-binding transcription factor activity; F: DNA binding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003edof zinc finger protein DOF5.3-like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101509325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to chemical; P: response to endogenous stimulus; P: signal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003etwo-component response regulator ARR17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101512564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eF: hydrolase activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eallantoinase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101507112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: biosynthetic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eSAC3 family protein B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101492009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to chemical; P: response to endogenous stimulus; P: signal transduction; P: response to stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003eprotein TIFY 5A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOC101489432\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP: post-embryonic development; P: response to light stimulus; P: reproduction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eprotein EARLY FLOWERING 3a\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.105263157894737%\" valign=\"top\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.157894736842104%\" valign=\"top\"\u003e\n \u003cp\u003eLOC101510831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003eP: response to stress; P: DNA metabolic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.8421052631579%\" valign=\"top\"\u003e\n \u003cp\u003ehelicase-like transcription factor CHR28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"},{"header":"Discussion","content":"\u003cp\u003eNear-isogenic lines (NILs) provide a unique advantage by confining genetic variation to specific regions of the genome while preserving genetic identity elsewhere. In this study, we characterized a pair of NILs exhibiting contrasting flowering times, aiming to discern not only major but also minor genes contributing to this complex process.\u003c/p\u003e\n\u003cp\u003ePhenotyping of both NILs revealed significant differences across various morphological traits, including a notable contrast in DTF (\u003cstrong\u003eTable 1\u003c/strong\u003e). This implies that genetic distinctions between the two NILs extend beyond the control of flowering initiation and influence over a spectrum of diverse characteristics. The association between flowering and multiple shoot architecture traits have been documented in various legume species, including chickpea [16, 35, 65\u0026ndash;71]. Several instances of legume mutants, characterized by alterations in a specific flowering-related gene, exhibit variations in morphological features, such as changes in branching patterns and internode length [26, 30, 70]. In the case of the studied NILs, phenotype differences could arise from the action of several independent genes or the pleiotropic effects of a single or a few genes. Nevertheless, the substantial differences in DTF observed (14 days) suggest additive effects from more than one locus.\u003c/p\u003e\n\u003cp\u003eThe sequencing data from the pair of NILs revealed a 99.97% identity of the read positions, with variations mainly observed in specific regions, as expected [41]. This level of genomic identity is consistent with values from other legume studies involving NILs, including chickpea, where reported identities range between 90-99% [50, 72, 73]. The observed residual heterozygosity for each NIL is ~ 0.05%, falling below the theoretical 0.098% expected for 11 generations of self-fertilizing lines. Nevertheless, this also aligns with values reported for other NILs [74] and closely resembles the residual heterozygosity found in cultivated chickpea. According to data reported by [51], the detected residual heterozygosity for SNPs ranged from 0.024% (0.013% - 0.050%) for cultivar lines to 0.033% (0.011% - 0.078%) for landrace lines and 0.033% (0.009% - 0.073%) for breeding lines, relative to the total sequenced positions (533.36 Mb; \u003cstrong\u003eAdditional file 12\u003c/strong\u003e). It is important to note that these estimations do not encompass other variations, such as InDels, suggesting that the actual heterozygosity may be higher. Therefore, the pair of NILs developed in our study appears to be suitable plant material, embodying the characteristics of near-isogenic lines, and providing a valuable resource for further genetic and functional studies in chickpea research.\u003c/p\u003e\n\u003cp\u003eThe comparison between positions sequenced in the pair of NILs revealed 15,690 homozygous variants (SNPs and InDels) mapped to chromosomes that pass all quality criteria or fail to meet only one criterion (\u003cstrong\u003eTable 2\u003c/strong\u003e). Of these, 4,932 variants are intragenic (HHQ-I), with the highest density observed at the beginning of chromosome 1 and the end of chromosome 6 (\u003cstrong\u003eFig. 3 and\u003c/strong\u003e \u003cstrong\u003eAdditional file 3\u003c/strong\u003e). Notably, no HHQ-I variants were detected on chromosome 3, where QTLs have been reported several times, and genetic variants in the \u003cem\u003eFTa1/a2/c\u003c/em\u003e cluster seem to play an important role in relaxing the environmental constraints on flowering, permitting early-flowering in long-day legumes [15, 16]. Thus, differences in flowering time in the pair of NILs do not appear to be related to chromosome 3.\u003c/p\u003e\n\u003cp\u003eA total of 1,610 variants were identified within exons or CDS (HHQ-I-C/E), affecting 246 protein-coding genes. However, functional annotation against the chickpea genome annotation did not reveal any enrichment of GO Slim terms (\u003cstrong\u003eFig. 4\u003c/strong\u003e). To deepen our analysis, we selected 146 of these as candidate genes, guided by enriched GO Slim terms related to flowering obtained from the model plant \u003cem\u003eA. thaliana \u003c/em\u003e(\u003cstrong\u003eAdditional file 6\u003c/strong\u003e). Significantly, four candidate genes showed homology to \u003cem\u003eA. thaliana\u003c/em\u003e FLOR-ID genes dataset (\u003cstrong\u003eTable 3\u003c/strong\u003e). One of them, LOC101507442 (Ca6: 57,717,926 \u0026ndash; 57,721,229), a B3 domain-containing transcription factor \u003cem\u003eVRN1-like\u003c/em\u003e, is affected only by a SNP located in CDS with low impact as a synonymous variant. The analysis of the public repository CicerSeq phenotype data indicates that this SNP is not associated with DTF in chickpea germplasm \u003cstrong\u003e(Fig. 6 and Additional file 10)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eLOC101515142 (Ca1: 2,285,592 \u0026ndash; 2,298,911, complement) is a homologue of the \u003cem\u003eA. thaliana MED16/SFR6\u003c/em\u003e gene, encoding a component of the Mediator complex. This complex is a large and dynamically variable multisubunit protein complex implicated in the regulation of RNA polymerase II-dependent gene expression. The Mediator complex recruits transcription factors to specific gene sites, promoting or repressing transcription initiation and elongation through protein-protein interaction modules [59, 75\u0026ndash;77]. The Mediator is evolutionarily highly conserved across eukaryotes; out of the 34 Mediator subunits described in \u003cem\u003eArabidopsis\u003c/em\u003e, only four are plant-specific subunits; 25 other subunits including \u003cem\u003eMED16 \u003c/em\u003eare structurally conserved [59]. \u003cem\u003eMED16 \u003c/em\u003eis part of the tail module of the Mediator complex with functions in both abiotic and biotic stress pathways. Initially identified as \u003cem\u003eSENSITIVE TO FREEZING 6\u003c/em\u003e (\u003cem\u003eSFR6\u003c/em\u003e) for its role in cold acclimation [78\u0026ndash;80], it is also involved in the regulation of iron homeostasis [81] and salicylic acid- and jasmonate-mediated defense response [82, 83]. Loss of \u003cem\u003eMED16 \u003c/em\u003edisrupts transcriptional outputs beyond low-temperature gene regulation, affecting the expression of photoperiod flowering time pathway and circadian clock genes, which leads to a late-flowering phenotype in long days [84]. \u003c/p\u003e\n\u003cp\u003eTo our knowledge, no flowering-time-related function for \u003cem\u003eMED16\u003c/em\u003e has been described in legumes. A recent study in \u003cem\u003eMedicago truncatula \u003c/em\u003edetected a mutation in a \u003cem\u003eMED16 \u003c/em\u003ehomologue (LOC25493186, MtrunA17_Chr4g0047551), referred to as \u003cem\u003eMED16A \u003c/em\u003eby the authors, which suppresses nodulation and increases arbuscular density [85]. However, a comparison through BLASTp against \u003cem\u003eC. arietinum \u003c/em\u003eRefSeq_Protein database reveals that \u003cem\u003eMED16A\u003c/em\u003e seems to be the homologue to LOC101501202 (Ca6: 16,660,218 - 16,679,432) with no variants between NILs. Thus, LOC101515142, affected by 94 variants in this study, seems to be the homologue of \u003cem\u003eMED16B\u003c/em\u003e (LOC11424919, MtrunA17_Chr2g0281921) \u003cstrong\u003e(Additional file 13). \u003c/strong\u003eNevertheless, the importance of the Mediator complex in flowering time has been highlighted in a recent publication in pea, revealing that other subunits, orthologs of CYCLIN-DEPENDENT KINASE 8 (CDK8) and CYCLIN C1 (CYCC1), components of the CDK8 kinase module of the Mediator complex, are involved in promoting flowering and maintaining normal reproductive development ([70]. In chickpea, a recent study identified the role of two Mediator subunit genes, namely \u003cem\u003eCaMED23 \u003c/em\u003eand \u003cem\u003eCaMED5b\u003c/em\u003e, along with their naturally derived haplotypes, in the regulation of plant height [43]. This indicates that the variability of the Mediator complex could play an important role in different traits for yield improvement.\u003c/p\u003e\n\u003cp\u003eBased on the nomenclature used in these legume studies involving the Mediator complex [43, 70, 85], we propose that LOC101515142 is \u003cem\u003eCaMED16b\u003c/em\u003e. The identified SNPs in \u003cem\u003eCaMED16b \u003c/em\u003eappear to form contrasting haplotypes, showing high conservation across cultivated chickpea germplasm (\u003cstrong\u003eFig. 5 and Additional file 8\u003c/strong\u003e). However, significant differences in DTF for the accessions with these contrasting haplotypes were observed in only three out of eleven different locations/seasons (\u003cstrong\u003eFig. 6 and Additional file 10)\u003c/strong\u003e. Consequently, further investigation is required to fully comprehend the functional role of \u003cem\u003eCaMED16b \u003c/em\u003ein flowering and its contribution to DTF.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCaELF3a \u003c/em\u003e(Ca5: 36,011,384 \u0026ndash; 36,016,600, complement) is one of the two homologs of \u003cem\u003eA. thaliana\u003c/em\u003e \u003cem\u003eELF3 \u003c/em\u003eidentified in legumes [40, 86]. This gene is a major component of the Evening complex\u003cem\u003e \u003c/em\u003e(EC)\u003cem\u003e \u003c/em\u003ewith \u003cem\u003eELF4 \u003c/em\u003eand \u003cem\u003eLUX \u003c/em\u003ewithin the circadian clock. The EC is not only directly involved in clock function, but also plays a key role in different developmental processes by interacting with other genes, such as \u003cem\u003ePIF4 \u003c/em\u003eor \u003cem\u003eGI\u003c/em\u003e, in the control of photoperiodic flowering and hypocotyl elongation in \u003cem\u003eA. thaliana\u003c/em\u003e [87\u0026ndash;90]. \u003c/p\u003e\n\u003cp\u003eIn this study, an 11 bp deletion in the first exon of \u003cem\u003eCaELF3a \u003c/em\u003ewas identified in the NF10/82-E line. This deletion is predicted to cause a frameshift, reducing the encoded protein from 699 to 13 amino acids (\u003cstrong\u003eAdditional file 7. Fig. S1b\u003c/strong\u003e). The same deletion was previously reported by [40] in line ICCV96029. It is noteworthy that the 11 bp constituting the deletion are followed by 10 bp that are identical to them. This sequence similarity may have facilitated the natural occurrence of the deletion at this specific position within the gene \u003cstrong\u003e(Additional file 7. Fig. S1b)\u003c/strong\u003e. In fact, [40] resequenced the entire \u003cem\u003eCaELF3a \u003c/em\u003egDNA in 109 lines and only found this sequence polymorphism. The presence of the deletion in homozygosity is associated with early-flowering in chickpea, representing the recessive allele. This aligns with the observation that the late-flowering phenotype was dominant in the developmental process of the pair of NILs used in this study \u003cstrong\u003e(Fig. 1)\u003c/strong\u003e. Interestingly, \u003cem\u003eELF3\u003c/em\u003e acts as a negative regulator of flowering [90], so loss-of-function mutations in this locus are predicted to result in early-flowering phenotype as we observed in the pair of NILs.\u003c/p\u003e\n\u003cp\u003eMutations in \u003cem\u003eELF3 \u003c/em\u003eorthologs are also associated with early-flowering and reduced branching in other galegoid legumes, such as pea and lentil [69], a morphological trait also observed for the NF10/82\u0026ndash;E line in this study. However, although \u003cem\u003eCaELF3a \u003c/em\u003eappears to have a significant effect on flowering time and other related traits, not all of the phenotypic differences detected between the pair of NILs should be assigned to it. Other genes may likely contribute comparable positive effects on flowering time, as expected with ICCV96029 [40].\u003c/p\u003e\n\u003cp\u003eIn LOC101499101 (Ca6: 57,549,424 \u0026ndash; 57,552,323, complement), a SNP was identified in the 3\u0026rsquo; UTR. This locus exhibits homology to the B-box finger protein of \u003cem\u003eA. thaliana \u003c/em\u003eSTO/BBX24 which is recognized for its role in connecting the \u003cem\u003eFRI/FLC\u003c/em\u003e and the photoperiod/circadian clock pathway, ultimately influencing flowering time in this species\u003cem\u003e \u003c/em\u003e[60]. The 3\u0026rsquo; UTR of mRNA is recognized for its role in transcriptional control and protein targeting, affecting various physiological processes in plants, such as flowering and stress tolerance [91, 92]. Specifically, different mechanisms of 3\u0026rsquo; RNA processing and their relevance for flowering time were investigated, with a focus on the \u003cem\u003eFLC \u003c/em\u003egene in \u003cem\u003eA. thaliana\u003c/em\u003e [93, 94]. Furthermore, a study highlighted the role of post-transcriptional regulation in flowering time control through the repressed \u003cem\u003eSOC1 \u003c/em\u003eactivity in a 3\u0026prime; UTR-dependent manner in \u003cem\u003eA. thaliana\u003c/em\u003e [95]. Polymorphisms in the UTR and intronic regions were also reported to be associated with higher expression of an \u003cem\u003eFT5a \u003c/em\u003eallele causing early-flowering in soybean [96]. \u003c/p\u003e\n\u003cp\u003eWhile the effects of a single SNP in UTRs may not be as pronounced as those in CDS, its association with flowering time should not necessarily be dismissed. For example, a SNP in the 3\u0026prime; UTR of \u003cem\u003eM. truncatula FTa1\u003c/em\u003e was significantly correlated with latitudinal variation, reflecting differences in photoperiod and temperature in its distribution across the Mediterranean region [97]. Notably, the analysis of accession density distribution plots based on the allele of the SNP reveals significant differences in DTF across all locations/seasons registered in the public repository CicerSeq, except for one (\u003cstrong\u003eFig. 6 and Additional file 10)\u003c/strong\u003e. Therefore, the T \u0026rarr; A transversion detected in LOC101499101 could influence DTF differences in the NILs, suggesting a plausible association of the SNP with flowering time in the chickpea germplasm.\u003c/p\u003e\n\u003cp\u003eTo further characterize the 146 candidate protein-coding genes affected by HHQ-I-C/E in the pair of NILs, an \u003cem\u003ein silico\u003c/em\u003e expression analysis was conducted. The purpose of this analysis was to gain insights into the transcription profiles in vegetative tissues with significant roles in promoting flowering (leaves and SAM), as well as the initial stages of flowering (FB1 \u0026ndash; FB4). We focused, particularly, on the four genes detected as homologous to those in \u003cem\u003eA. thaliana.\u003c/em\u003e The TPM values, calculated from the chickpea expression atlas [52], categorized LOC101515142 (\u003cem\u003eCaMED16b\u003c/em\u003e), LOC101489432 (\u003cem\u003eCaELF3a\u003c/em\u003e), LOC101499101 (\u003cem\u003eBBX24-like\u003c/em\u003e) and LOC101507442 (\u003cem\u003eVRN1-like\u003c/em\u003e) into three different clusters (\u003cstrong\u003eFig. 7 and Additional file 11\u003c/strong\u003e). \u003c/p\u003e\n\u003cp\u003eThe expression profile of \u003cem\u003eCaMED16b\u003c/em\u003e indicates higher levels during the initial stages of flowering, evidenced by an increase in TPM levels between the SAM and FB1, followed by a decrease between FB1 and FB2. Subsequent FB stages (FB3 and FB4) show lower expression levels, suggesting a potential role for \u003cem\u003eCaMED16b \u003c/em\u003eduring the immediate pre-flowering period. In contrast, \u003cem\u003eCaELF3a \u003c/em\u003eshows the highest expression levels in ML and SAM tissues, indicating its involvement in upstream transcriptional regulation pathways preceding the onset of flowering. This suggests that \u003cem\u003eCaELF3a \u003c/em\u003emay play a role in regulating processes leading up to flowering initiation. Finally, LOC101499101 and LOC101507442 exhibit a similar expression pattern, with the highest TPM levels observed at FB1 and consistent levels across all subsequent FB stages. This suggests their involvement during the flower development rather than the initiation of flowering. According to the \u003cem\u003ein silico \u003c/em\u003eanalysis, \u003cem\u003eCaMED16b \u003c/em\u003eand \u003cem\u003eCaELF3a \u003c/em\u003eexhibit interesting expression patterns consistent with an expected role in flowering time regulation, with expression in leaves and SAM preceding the transition from vegetative to reproductive stages. This putative observation for \u003cem\u003eCaELF3a\u003c/em\u003e was previously reported, identifying it as one of the key regulators responsible for early inflorescence development and early-flowering phenotype in chickpeas [98]\u003cem\u003e. \u003c/em\u003eInterestingly, LOC101492009 (TIFY5A protein) and LOC101510831 (helicase-like transcription factor CHR28), both with the stress response GO Slim term, show a similar expression pattern with \u003cem\u003eCaELF3a \u003c/em\u003e\u003cstrong\u003e(Fig. 7).\u003c/strong\u003e [98] found that stress and defense-responsive genes as well as the ethylene signaling pathway genes were to be upregulated during inflorescence development in chickpeas.\u003c/p\u003e\n\u003cp\u003eFurthermore, other candidate genes, including some members of the ARF, ERF, and DOF families, exhibit co-expression with these four genes \u003cstrong\u003e(Table 4)\u003c/strong\u003e. These transcription factor families play important roles in various fundamental processes in plants that could influence the phenotype observed for the pair of NILs [62\u0026ndash;64, 99\u0026ndash;101]. Specifically, \u003cem\u003eARF2 \u003c/em\u003eand \u003cem\u003eERF12 \u003c/em\u003ewere described in \u003cem\u003eA. thaliana \u003c/em\u003ewith roles in flowering. \u003cem\u003eA. thaliana arf2 \u003c/em\u003emutants exhibited pleiotropic development phenotypes, including delays in several processes related to plant aging such as initiation of flowering, rosette leaf senescence and floral organ abscission [102, 103]. \u003cem\u003eArabidopsis EFR12 \u003c/em\u003epleiotropically affects meristem identity, floral phyllotaxy and organ initiation and seems to be conserved among angiosperms [104]. Therefore, LOC101513952 (\u003cem\u003eCaARF2;\u003c/em\u003e auxin response factor 2), with 14 variants detected between NILs and LOC101491273 (\u003cem\u003eCaERF12\u003c/em\u003e; ethylene-responsive transcription factor 12), affected by four HHQ-I-C/E variants, are potential candidate genes that could play a role in the observed phenotypic differences. \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe development of the NIL pair in this study represents a valuable resource for advancing research on chickpea flowering time. This study offers a complementary approach to association analyses by phenotyping and re-sequencing the NILs, enabling the identification of candidate gene variants that could have both major and minor effects on flowering time. While \u003cem\u003eCaELF3a\u0026nbsp;\u003c/em\u003eemerges as the most prominent candidate gene, our study also uncovered other targets for the first time in chickpea, including \u003cem\u003eCaMED16b\u0026nbsp;\u003c/em\u003eand LOC101499101 (\u003cem\u003eBBX24-like\u003c/em\u003e), which are homologs to flowering-related genes in \u003cem\u003eA. thaliana\u003c/em\u003e. This suggests their potential contribution in modeling this trait. Furthermore, ERF and ARF family members potentially associated with flowering time were also detected. The \u003cem\u003ein silico\u0026nbsp;\u003c/em\u003eexpression characterization and genetic variability analysis carried out in this study for these loci could contribute to the development of specific markers for chickpea breeding programs. This study lays the foundation for future research on this plant material. Subsequent studies, including analysis of the F2 progeny resulting from the NIL cross and expression analysis, hold the potential to unveil new insights into the intricate mechanisms governing flowering time in chickpea.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset generated and analyzed during the current study is available in the European Variation Archive (EVA) at EMBL-EBI under accession number PRJEB73790, https://urldefense.com/v3/__https://www.ebi.ac.uk/eva/?eva-study=PRJEB73790__;!!D9dNQwwGXtA!UdDPickLBLigeaKK1uTr009AH7xm-vup0ndN_fMEwYr8Ay_ik2ooSI7MDZSsXYi4d24v4nT4KWYkv8qN57t0o20q$.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe custom scripts used for the analysis of the data during the current study are available in the GitHub repository https://github.com/AGR114molecularBreeding/chickpea.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was funded by the following projects and programs: PID2020-114952RRI00\u003c/p\u003e\n\u003cp\u003efunded by MCIN/AEI/10.13039/501100011033; European Union\u0026rsquo;s Horizon Europe research and innovation program under grant agreement BELIS (No 101081878); PR.AVA23.INV2023.009 co-financed by European Regional Development Fund (ERDF). APR is a FPU Fellow funded by the Spanish Ministry of Science, Innovation and Universities through the National Program FPU \u0026ldquo;Formaci\u0026oacute;n de Profesorado Universitario\u0026rdquo; (Ref. FPU22/02101). AC acknowledges the FPI grant associated with the JVD\u0026rsquo;s Ram\u0026oacute;n y Cajal program (University of Cordoba). JVD is a Ram\u0026oacute;n y Cajal Fellow funded by the program MCIN/AEI/10.13039/501100011033 (Ref. RYC2019-028188-I). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.R., T.M. and P.C. contributed to the study conception and design. J.R., T.M. and J.V.D. acquired funding for the study. J.R., L.A., T.M. and P.C. developed the plant material. A.P.R., L.A., J.R. and T.M. participated in field characterization. A.P.R., A.C. and J.V.D. analyzed the data. P.C. and J.V.D. supervised the study. A.P.R. wrote the first draft of the manuscript. A.C., P.C. and J.V.D. reviewed and edited the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere appreciation to Prof. Juan Gil for his invaluable contributions to the study. His critical review and insightful feedback have greatly enriched the content and quality of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVarshney RK, Song C, Saxena RK, Azam S, Yu S, Sharpe AG, et al. Draft genome sequence of chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e) provides a resource for trait improvement. Nat Biotechnol. 2013;31:240\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eFAOSTAT FAO. FAOSTAT. 2022. https://www.fao.org/faostat/en/#data. Accessed 11 Jan 2024.\u003c/li\u003e\n\u003cli\u003eKumar J, Abbo S. Genetics of flowering time in chickpea and its bearing on productivity in semiarid environments. Elsevier; 2001. p. 107\u0026ndash;38.\u003c/li\u003e\n\u003cli\u003eGaur PM, Jukanti AK, Varshney RK. Impact of genomic technologies on chickpea breeding strategies. Agronomy. 2012;2:199\u0026ndash;221.\u003c/li\u003e\n\u003cli\u003eArriagada O, Cacciuttolo F, Cabeza RA, Carrasco B, Schwember AR. A comprehensive review on chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.) breeding for abiotic stress tolerance and climate change resilience. Int J Mol Sci. 2022;23:6794.\u003c/li\u003e\n\u003cli\u003eZhang H, Pala M, Oweis T, Harris H. Water use and water-use efficiency of chickpea and lentil in a Mediterranean environment. Aust J Agric Res. 2000;51:295.\u003c/li\u003e\n\u003cli\u003eVarshney RK, Thudi M, Nayak SN, Gaur PM, Kashiwagi J, Krishnamurthy L, et al. Genetic dissection of drought tolerance in chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.). Theor Appl Genet. 2014;127:445\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eSiddique KHM, Loss SP, Thomson BD. Cool season grain legumes in dryland Mediterranean environments of Western Australia: significance of early flowering. Management of agricultural drought: Agronomic and genetic options. 2003;151\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eBerger JD, Turner NC. The ecology of chickpea. In: Yadav SS, Redden RJ, Chen W, Sharma B, editors. Chickpea breeding and management. UK: CABI; 2007. p. 47\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eDaba K, Tar\u0026rsquo;an B, Bueckert R, Warkentin TD. Effect of temperature and photoperiod on time to flowering in chickpea. Crop Sci. 2016;56:200.\u003c/li\u003e\n\u003cli\u003eBerger JD, Turner NC, Siddique KHM, Knights EJ, Brinsmead RB, Mock I, et al. Genotype by environment studies across Australia reveal the importance of phenology for chickpea (\u003cem\u003eCicer arietinum \u003c/em\u003eL.) improvement. Aust J Agric Res. 2004;55:1071.\u003c/li\u003e\n\u003cli\u003eCroser JS, Clarke HJ, Siddique KHM, Khan TN. Low-temperature stress: implications for chickpea ( \u003cem\u003eCicer arietinum\u003c/em\u003e L.) improvement. CRC Crit Rev Plant Sci. 2003;22:185\u0026ndash;219.\u003c/li\u003e\n\u003cli\u003eClarke HJ, Siddique KHM. Response of chickpea genotypes to low temperature stress during reproductive development. Field Crops Res. 2004;90:323\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eBerger JD, Ali M, Basu PS, Chaudhary BD, Chaturvedi SK, Deshmukh PS, et al. Genotype by environment studies demonstrate the critical role of phenology in adaptation of chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.) to high and low yielding environments of India. Field Crops Res. 2006;98:230\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eWeller JL, Ortega R. Genetic control of flowering time in legumes. Front Plant Sci. 2015;6:207.\u003c/li\u003e\n\u003cli\u003eOrtega R, Hecht VFG, Freeman JS, Rubio J, Carrasquilla-Garcia N, Mir RR, et al. Altered Expression of an \u003cem\u003eFT \u003c/em\u003eCluster Underlies a Major Locus Controlling Domestication-Related Changes to Chickpea Phenology and Growth Habit. Front Plant Sci. 2019;10:824.\u003c/li\u003e\n\u003cli\u003eGretsova M, Surkova S, Kanapin A, Samsonova A, Logacheva M, Shcherbakov A, et al. Transcriptomic analysis of flowering time genes in cultivated chickpea and wild cicer. ijms. 2023;24:2692.\u003c/li\u003e\n\u003cli\u003eBouch\u0026eacute; F, Lobet G, Tocquin P, P\u0026eacute;rilleux C. FLOR-ID: an interactive database of flowering-time gene networks in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e. Nucleic Acids Res. 2016;44:D1167-71.\u003c/li\u003e\n\u003cli\u003eJaeger KE, Wigge PA. FT protein acts as a long-range signal in \u003cem\u003eArabidopsis\u003c/em\u003e. Curr Biol. 2007;17:1050\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eAndr\u0026eacute;s F, Coupland G. The genetic basis of flowering responses to seasonal cues. Nat Rev Genet. 2012;13:627\u0026ndash;39.\u003c/li\u003e\n\u003cli\u003eHanano S, Goto K. \u003cem\u003eArabidopsis TERMINAL FLOWER1\u003c/em\u003e is involved in the regulation of flowering time and inflorescence development through transcriptional repression. Plant Cell. 2011;23:3172\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eHecht V, Foucher F, Ferr\u0026aacute;ndiz C, Macknight R, Navarro C, Morin J, et al. Conservation of \u003cem\u003eArabidopsis \u003c/em\u003eflowering genes in model legumes. Plant Physiol. 2005;137:1420\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eKim MY, Kang YJ, Lee T, Lee S-H. Divergence of Flowering-Related Genes in Three Legume Species. Plant Genome. 2013;6:0.\u003c/li\u003e\n\u003cli\u003eYoung ND, Bharti AK. Genome-enabled insights into legume biology. Annu Rev Plant Biol. 2012;63:283\u0026ndash;305.\u003c/li\u003e\n\u003cli\u003eHecht V, Laurie RE, Vander Schoor JK, Ridge S, Knowles CL, Liew LC, et al. The pea \u003cem\u003eGIGAS \u003c/em\u003egene is a\u003cem\u003e FLOWERING LOCUS T\u003c/em\u003e homolog necessary for graft-transmissible specification of flowering but not for responsiveness to photoperiod. Plant Cell. 2011;23:147\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eLaurie RE, Diwadkar P, Jaudal M, Zhang L, Hecht V, Wen J, et al. The Medicago \u003cem\u003eFLOWERING LOCUS T\u003c/em\u003e homolog, \u003cem\u003eMtFTa1\u003c/em\u003e, is a key regulator of flowering time. Plant Physiol. 2011;156:2207\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eNelson MN, Książkiewicz M, Rychel S, Besharat N, Taylor CM, Wyrwa K, et al. The loss of vernalization requirement in narrow-leafed lupin is associated with a deletion in the promoter and de-repressed expression of a \u003cem\u003eFlowering Locus T\u003c/em\u003e (\u003cem\u003eFT\u003c/em\u003e) homologue. New Phytol. 2017;213:220\u0026ndash;32.\u003c/li\u003e\n\u003cli\u003eSurkova SY, Samsonova MG. Mechanisms of vernalization-induced flowering in legumes. Int J Mol Sci. 2022;23.\u003c/li\u003e\n\u003cli\u003eWong ACS, Hecht VFG, Picard K, Diwadkar P, Laurie RE, Wen J, et al. Isolation and functional analysis of \u003cem\u003eCONSTANS-LIKE\u003c/em\u003e genes suggests that a central role for \u003cem\u003eCONSTANS \u003c/em\u003ein flowering time control is not evolutionarily conserved in \u003cem\u003eMedicago truncatula\u003c/em\u003e. Front Plant Sci. 2014;5:486.\u003c/li\u003e\n\u003cli\u003eRidge S, Sussmilch FC, Hecht V, Vander Schoor JK, Lee R, Aubert G, et al. Identification of \u003cem\u003eLATE BLOOMER2\u003c/em\u003e as a CYCLING DOF FACTOR homolog reveals conserved and divergent features of the flowering response to photoperiod in pea. Plant Cell. 2016;28:2545\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eGaur PM, Samineni S, Tripathi S, Varshney RK, Gowda CLL. Allelic relationships of flowering time genes in chickpea. Euphytica. 2015;203:295\u0026ndash;308.\u003c/li\u003e\n\u003cli\u003eKumar J, van Rheenen HA. Brief communication. A major gene for time of flowering in chickpea. J Hered. 2000;91:67\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eOr E, Hovav R, Abbo S. A major gene for flowering time in chickpea. Crop Sci. 1999;39:315\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eHegde VS. Genetics of flowering time in chickpea in a semi-arid environment. Plant Breeding. 2010;129:683\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eLichtenzveig J, Bonfil DJ, Zhang H-B, Shtienberg D, Abbo S. Mapping quantitative trait loci in chickpea associated with time to flowering and resistance to \u003cem\u003eDidymella rabiei\u003c/em\u003e the causal agent of Ascochyta blight. Theor Appl Genet. 2006;113:1357\u0026ndash;69.\u003c/li\u003e\n\u003cli\u003eRehman AU, Malhotra RS, Bett K, Tar\u0026rsquo;an B, Bueckert R, Warkentin TD. Mapping QTL associated with traits affecting grain yield in chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.) under terminal drought stress. Crop Sci. 2011;51:450\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eMallikarjuna BP, Samineni S, Thudi M, Sajja SB, Khan AW, Patil A, et al. Molecular mapping of flowering time major genes and QTLs in chickpea (\u003cem\u003eCicer arietinum \u003c/em\u003eL.). Front Plant Sci. 2017;8:1140.\u003c/li\u003e\n\u003cli\u003eDaba K, Deokar A, Banniza S, Warkentin TD, Tar\u0026rsquo;an B. QTL mapping of early flowering and resistance to ascochyta blight in chickpea. Genome. 2016;59:413\u0026ndash;25.\u003c/li\u003e\n\u003cli\u003eUpadhyaya HD, Bajaj D, Das S, Saxena MS, Badoni S, Kumar V, et al. A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea. Plant Mol Biol. 2015;89:403\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eRidge S, Deokar A, Lee R, Daba K, Macknight RC, Weller JL, et al. The chickpea \u003cem\u003eE\u003c/em\u003e\u003cem\u003early flowering 1 \u003c/em\u003e(\u003cem\u003eE\u003c/em\u003e\u003cem\u003efl1\u003c/em\u003e) locus is an ortholog of \u003cem\u003eA\u003c/em\u003e\u003cem\u003erabidopsis ELF3\u003c/em\u003e. Plant Physiol. 2017;175:802\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eYan G, Liu H, Wang H, Lu Z, Wang Y, Mullan D, et al. Accelerated generation of selfed pure line plants for gene identification and crop breeding. Front Plant Sci. 2017;8:1786.\u003c/li\u003e\n\u003cli\u003eAli L, Azam S, Rubio J, Kudapa H, Madrid E, Varshney RK, et al. Detection of a new QTL/gene for growth habit in chickpea CaLG1 using wide and narrow crosses. Euphytica. 2015;204:473\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eMalik N, Basu U, Srivastava R, Daware A, Ranjan R, Sharma A, et al. Natural alleles of Mediator subunit genes modulate plant height in chickpea. Plant J. 2023;116:1271\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eCaballo C, Berbel A, Ortega R, Gil J, Mill\u0026aacute;n T, Rubio J, et al. The \u003cem\u003eSINGLE FLOWER\u003c/em\u003e (\u003cem\u003eSFL\u003c/em\u003e) gene encodes a MYB transcription factor that regulates the number of flowers produced by the inflorescence of chickpea. New Phytol. 2022;234:827\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003eAli L, Deokar A, Caballo C, Tar\u0026rsquo;an B, Gil J, Chen W, et al. Fine mapping for double podding gene in chickpea. Theor Appl Genet. 2016;129:77\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eAli L, Madrid E, Varshney RK, Azam S, Millan T, Rubio J, et al. Mapping and identification of a \u003cem\u003eCicer arietinum NSP2\u003c/em\u003e gene involved in nodulation pathway. Theor Appl Genet. 2014;127:481\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eCastro P, Pist\u0026oacute;n F, Madrid E, Mill\u0026aacute;n T, Gil J, Rubio J. Development of chickpea near-isogenic lines for Fusarium wilt. Theor Appl Genet. 2010;121:1519\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eCaballo C, Castro P, Gil J, Millan T, Rubio J, Die JV. Candidate genes expression profiling during wilting in chickpea caused by \u003cem\u003eFusarium oxysporum\u003c/em\u003e f. sp. \u003cem\u003eciceris \u003c/em\u003erace 5. PLoS ONE. 2019;14:e0224212.\u003c/li\u003e\n\u003cli\u003eJendoubi W, Bouhadida M, Millan T, Kharrat M, Gil J, Rubio J, et al. Identification of the target region including the \u003cem\u003eFoc0\u003c/em\u003e\u003cem\u003e\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e/foc0\u003c/em\u003e\u003cem\u003e\u003csub\u003e1\u003c/sub\u003e\u003c/em\u003e gene and development of near isogenic lines for resistance to Fusarium Wilt race 0 in chickpea. Euphytica. 2016;210:119\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eBasu U, Narnoliya L, Srivastava R, Sharma A, Bajaj D, Daware A, et al. CLAVATA signaling pathway genes modulating flowering time and flower number in chickpea. Theor Appl Genet. 2019;132:2017\u0026ndash;38.\u003c/li\u003e\n\u003cli\u003eVarshney RK, Roorkiwal M, Sun S, Bajaj P, Chitikineni A, Thudi M, et al. A chickpea genetic variation map based on the sequencing of 3,366 genomes. Nature. 2021;599:622\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eJain M, Bansal J, Rajkumar MS, Garg R. An integrated transcriptome mapping the regulatory network of coding and long non-coding RNAs provides a genomics resource in chickpea. Commun Biol. 2022;5:1106.\u003c/li\u003e\n\u003cli\u003eTuinstra MR, Ejeta G, Goldsbrough PB. Heterogeneous inbred family (HIF) analysis: a method for developing near-isogenic lines that differ at quantitative trait loci. Theor Appl Genet. 1997;95:1005\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eCingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of \u003cem\u003eDrosophila melanogaster\u003c/em\u003e strain w1118; iso-2; iso-3. Fly (Austin). 2012;6:80\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eTang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, et al. SRplot: A free online platform for data visualization and graphing. PLoS ONE. 2023;18:e0294236.\u003c/li\u003e\n\u003cli\u003eDie JV. Jdieramon/Refseqr V1.0.1. Zenodo. 2018.\u003c/li\u003e\n\u003cli\u003eConesa A, G\u0026ouml;tz S. Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics. 2008;2008:619832.\u003c/li\u003e\n\u003cli\u003eMi H, Muruganujan A, Huang X, Ebert D, Mills C, Guo X, et al. Protocol Update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc. 2019;14:703\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eDolan WL, Chapple C. Conservation and Divergence of Mediator Structure and Function: Insights from Plants. Plant Cell Physiol. 2016.\u003c/li\u003e\n\u003cli\u003eLi F, Sun J, Wang D, Bai S, Clarke AK, Holm M. The B-box family gene \u003cem\u003eSTO \u003c/em\u003e(\u003cem\u003eBBX24\u003c/em\u003e) in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e regulates flowering time in different pathways. PLoS ONE. 2014;9:e87544.\u003c/li\u003e\n\u003cli\u003eLevy YY, Mesnage S, Mylne JS, Gendall AR, Dean C. Multiple roles of \u003cem\u003eArabidopsis VRN1 \u003c/em\u003ein vernalization and flowering time control. Science. 2002;297:243\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eDie JV, Gil J, Millan T. Genome-wide identification of the auxin response factor gene family in \u003cem\u003eCicer arietinum\u003c/em\u003e. BMC Genomics. 2018;19:301.\u003c/li\u003e\n\u003cli\u003eChapman EJ, Estelle M. Mechanism of auxin-regulated gene expression in plants. Annu Rev Genet. 2009;43:265\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eNoguero M, Atif RM, Ochatt S, Thompson RD. The role of the DNA-binding One Zinc Finger (DOF) transcription factor family in plants. Plant Sci. 2013;209:32\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eJulier B, Huguet T, Chardon F, Ayadi R, Pierre J-B, Prosperi J-M, et al. Identification of quantitative trait loci influencing aerial morphogenesis in the model legume \u003cem\u003eMedicago truncatula\u003c/em\u003e. Theor Appl Genet. 2007;114:1391\u0026ndash;406.\u003c/li\u003e\n\u003cli\u003eEspinoza L del CL, Huguet T, Julier B. Multi-population QTL detection for aerial morphogenetic traits in the model legume \u003cem\u003eMedicago truncatula\u003c/em\u003e. Theor Appl Genet. 2012;124:739\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eGonz\u0026aacute;lez AM, Yuste-Lisbona FJ, Saburido S, Bretones S, De Ron AM, Lozano R, et al. Major contribution of flowering time and vegetative growth to plant production in common bean as deduced from a comparative genetic mapping. Front Plant Sci. 2016;7:1940.\u003c/li\u003e\n\u003cli\u003eYang G, Zhai H, Wu H, Zhang X, L\u0026uuml; S, Wang Y, et al. QTL effects and epistatic interaction for flowering time and branch number in a soybean mapping population of Japanese\u0026times;Chinese cultivars. J Integr Agric. 2017;16:1900\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eWeller JL, Liew LC, Hecht VFG, Rajandran V, Laurie RE, Ridge S, et al. A conserved molecular basis for photoperiod adaptation in two temperate legumes. Proc Natl Acad Sci USA. 2012;109:21158\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eHasan ASMM, Vander Schoor JK, Hecht V, Weller JL. The CYCLIN-DEPENDENT KINASE module of the Mediator complex promotes flowering and reproductive development in pea. Plant Physiol. 2020;182:1375\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eAnbessa Y, Warkentin T, Bueckert R, Vandenberg A. Short internode, double podding and early flowering effects on maturity and other agronomic characters in chickpea. Field Crops Res. 2007;102:43\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eJacques S, Sperschneider J, Garg G, Thatcher LF, Gao L-L, Kamphuis LG, et al. A functional genomics approach to dissect spotted alfalfa aphid resistance in \u003cem\u003eMedicago truncatula\u003c/em\u003e. Sci Rep. 2020;10:22159.\u003c/li\u003e\n\u003cli\u003eThakro V, Malik N, Basu U, Srivastava R, Narnoliya L, Daware A, et al. A superior gene allele involved in abscisic acid signaling enhances drought tolerance and yield in chickpea. Plant Physiol. 2023;191:1884\u0026ndash;912.\u003c/li\u003e\n\u003cli\u003ePea G, Aung HH, Frascaroli E, Landi P, P\u0026egrave; ME. Extensive genomic characterization of a set of near-isogenic lines for heterotic QTL in maize (\u003cem\u003eZea mays\u003c/em\u003e L.). BMC Genomics. 2013;14:61.\u003c/li\u003e\n\u003cli\u003eAllen BL, Taatjes DJ. The Mediator complex: a central integrator of transcription. Nat Rev Mol Cell Biol. 2015;16:155\u0026ndash;66.\u003c/li\u003e\n\u003cli\u003eJeronimo C, Robert F. The mediator complex: at the nexus of RNA polymerase II transcription. Trends Cell Biol. 2017;27:765\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eZhang L, Guo C. The important function of mediator complex in controlling the developmental transitions in plants. Int J Mol Sci. 2020;21.\u003c/li\u003e\n\u003cli\u003eKnight H, Veale EL, Warren GJ, Knight MR. The \u003cem\u003esfr6 \u003c/em\u003emutation in \u003cem\u003eArabidopsis \u003c/em\u003esuppresses low-temperature induction of genes dependent on the CRT/DRE sequence motif. Plant Cell. 1999;11:875\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eKnight H, Mugford SG, Ulker B, Gao D, Thorlby G, Knight MR. Identification of \u003cem\u003eSFR6\u003c/em\u003e, a key component in cold acclimation acting post-translationally on CBF function. Plant J. 2009;58:97\u0026ndash;108.\u003c/li\u003e\n\u003cli\u003eHemsley PA, Hurst CH, Kaliyadasa E, Lamb R, Knight MR, De Cothi EA, et al. The \u003cem\u003eArabidopsis \u003c/em\u003emediator complex subunits MED16, MED14, and MED2 regulate mediator and RNA polymerase II recruitment to CBF-responsive cold-regulated genes. Plant Cell. 2014;26:465\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eYang Y, Ou B, Zhang J, Si W, Gu H, Qin G, et al. The \u003cem\u003eArabidopsis \u003c/em\u003eMediator subunit MED16 regulates iron homeostasis by associating with EIN3/EIL1 through subunit MED25. Plant J. 2014;77:838\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eWathugala DL, Hemsley PA, Moffat CS, Cremelie P, Knight MR, Knight H. The Mediator subunit \u003cem\u003eSFR6/MED16\u003c/em\u003e controls defence gene expression mediated by salicylic acid and jasmonate responsive pathways. New Phytol. 2012;195:217\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eZhang X, Yao J, Zhang Y, Sun Y, Mou Z. The \u003cem\u003eArabidopsis \u003c/em\u003eMediator complex subunits\u003cem\u003e MED14/SWP\u003c/em\u003e and \u003cem\u003eMED16/SFR6/IEN1\u003c/em\u003e differentially regulate defense gene expression in plant immune responses. Plant J. 2013;75:484\u0026ndash;97.\u003c/li\u003e\n\u003cli\u003eKnight H, Thomson AJW, McWatters HG. \u003cem\u003eSensitive to freezing6\u003c/em\u003e integrates cellular and environmental inputs to the plant circadian clock. Plant Physiol. 2008;148:293\u0026ndash;303.\u003c/li\u003e\n\u003cli\u003eChaulagain D, Schnabel E, Crook A, Bashyal S, M\u0026uuml;ller LM, Frugoli J. A mutation in Mediator subunit \u003cem\u003eMED16A \u003c/em\u003esuppresses nodulation and increases arbuscule density in \u003cem\u003eMedicago truncatula\u003c/em\u003e. J Plant Growth Regul. 2023;42:7004\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eRubenach AJS, Hecht V, Vander Schoor JK, Liew LC, Aubert G, Burstin J, et al. \u003cem\u003eEARLY FLOWERING3\u003c/em\u003e redundancy fine-tunes photoperiod sensitivity. Plant Physiol. 2017;173:2253\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eNusinow DA, Helfer A, Hamilton EE, King JJ, Imaizumi T, Schultz TF, et al. The ELF4-ELF3-LUX complex links the circadian clock to diurnal control of hypocotyl growth. Nature. 2011;475:398\u0026ndash;402.\u003c/li\u003e\n\u003cli\u003eShim JS, Kubota A, Imaizumi T. Circadian clock and photoperiodic flowering in \u003cem\u003eA\u003c/em\u003e\u003cem\u003erabidopsis\u003c/em\u003e: \u003cem\u003eCONSTANS \u003c/em\u003eis a hub for signal integration. Plant Physiol. 2017;173:5\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eAnwer MU, Davis A, Davis SJ, Quint M. Photoperiod sensing of the circadian clock is controlled by \u003cem\u003eEARLY FLOWERING 3\u003c/em\u003e and \u003cem\u003eGIGANTEA\u003c/em\u003e. Plant J. 2020;101:1397\u0026ndash;410.\u003c/li\u003e\n\u003cli\u003eZhao H, Xu D, Tian T, Kong F, Lin K, Gan S, et al. Molecular and functional dissection of \u003cem\u003eEARLY-FLOWERING 3 \u003c/em\u003e(\u003cem\u003eELF3\u003c/em\u003e) and \u003cem\u003eELF4 \u003c/em\u003ein \u003cem\u003eArabidopsis\u003c/em\u003e. Plant Sci. 2021;303:110786.\u003c/li\u003e\n\u003cli\u003eSrivastava AK, Lu Y, Zinta G, Lang Z, Zhu J-K. UTR-dependent control of gene expression in plants. Trends Plant Sci. 2018;23:248\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eBernardes WS, Menossi M. Plant 3\u0026rsquo; Regulatory Regions From mRNA-encoding genes and their uses to modulate expression. Front Plant Sci. 2020;11:1252.\u003c/li\u003e\n\u003cli\u003eRataj K, Simpson GG. Message ends: RNA 3\u0026rsquo; processing and flowering time control. J Exp Bot. 2014;65:353\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eSun B, Bhati KK, Song P, Edwards A, Petri L, Kruusvee V, et al. FIONA1-mediated methylation of the 3\u0026rsquo;UTR of \u003cem\u003eFLC \u003c/em\u003eaffects \u003cem\u003eFLC \u003c/em\u003etranscript levels and flowering in \u003cem\u003eArabidopsis\u003c/em\u003e. PLoS Genet. 2022;18:e1010386.\u003c/li\u003e\n\u003cli\u003eKim H-S, Abbasi N, Choi S-B. Bruno-like proteins modulate flowering time via 3\u0026rsquo; UTR-dependent decay of SOC1 mRNA. New Phytol. 2013;198:747\u0026ndash;56.\u003c/li\u003e\n\u003cli\u003eTakeshima R, Hayashi T, Zhu J, Zhao C, Xu M, Yamaguchi N, et al. A soybean quantitative trait locus that promotes flowering under long days is identified as \u003cem\u003eFT5a\u003c/em\u003e, a \u003cem\u003eFLOWERING LOCUS T\u003c/em\u003e ortholog. J Exp Bot. 2016;67:5247\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eBurgarella C, Chantret N, Gay L, Prosperi J-M, Bonhomme M, Tiffin P, et al. Adaptation to climate through flowering phenology: a case study in \u003cem\u003eMedicago truncatula\u003c/em\u003e. Mol Ecol. 2016;25:3397\u0026ndash;415.\u003c/li\u003e\n\u003cli\u003eBasu U, Hegde VS, Daware A, Jha UC, Parida SK. Transcriptome landscape of early inflorescence developmental stages identifies key flowering time regulators in chickpea. Plant Mol Biol. 2022;108:565\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eDeokar AA, Kondawar V, Kohli D, Aslam M, Jain PK, Karuppayil SM, et al. The \u003cem\u003eCarERF \u003c/em\u003egenes in chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.) and the identification of \u003cem\u003eCarERF116 \u003c/em\u003eas abiotic stress responsive transcription factor. Funct Integr Genomics. 2015;15:27\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eSrivastava R, Kumar R. The expanding roles of APETALA2/Ethylene Responsive Factors and their potential applications in crop improvement. Brief Funct Genomics. 2018;18:240\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eDie JV, Elmassry MM, LeBlanc KH, Awe OI, Dillman A, Busby B. geneHummus: an R package to define gene families and their expression in legumes and beyond. BMC Genomics. 2019;20:591.\u003c/li\u003e\n\u003cli\u003eEllis CM, Nagpal P, Young JC, Hagen G, Guilfoyle TJ, Reed JW. \u003cem\u003eAUXIN RESPONSE FACTOR1\u003c/em\u003e and \u003cem\u003eAUXIN RESPONSE FACTOR2\u003c/em\u003e regulate senescence and floral organ abscission in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e. Development. 2005;132:4563\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eOkushima Y, Mitina I, Quach HL, Theologis A. \u003cem\u003eAUXIN RESPONSE FACTOR 2 \u003c/em\u003e(\u003cem\u003eARF2\u003c/em\u003e): a pleiotropic developmental regulator. Plant J. 2005;43:29\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eChandler JW, Werr W. A phylogenetically conserved \u003cem\u003eAPETALA2/ETHYLENE RESPONSE FACTOR\u003c/em\u003e, \u003cem\u003eERF12\u003c/em\u003e, regulates \u003cem\u003eArabidopsis \u003c/em\u003efloral development. Plant Mol Biol. 2020;102:39\u0026ndash;54.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cicer arietinum, early-flowering, NILs, sequencing, SNPs","lastPublishedDoi":"10.21203/rs.3.rs-4002926/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4002926/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCicer arietinum \u003c/em\u003eis a significant legume crop cultivated mainly in short-season environments, where early-flowering is a desirable trait to overcome terminal constraints. Despite its agricultural significance, the genetic control of flowering time in chickpea is not fully understood. In this study, we developed, phenotyped, re-sequenced and genetically characterized a pair of near-isogenic lines (NILs) with contrasting days to flowering to identify candidate gene variants potentially associated with flowering time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn addition to days to flowering, noticeable differences in multiple shoot architecture traits were observed between the NILs. The re-sequencing data confirms that the NILs developed in this study serve as appropriate plant materials, effectively constraining genetic variation to specific regions and thereby establishing a valuable resource for future genetic and functional investigations in chickpea research. Leveraging bioinformatics tools and public genomic datasets, we identified homologs of flowering-related genes from \u003cem\u003eArabidopsis thaliana\u003c/em\u003e, including \u003cem\u003eELF3 \u003c/em\u003eand, for the first time in chickpea, \u003cem\u003eMED16 \u003c/em\u003eand \u003cem\u003eSTO/BBX24\u003c/em\u003e, with variants among the NILs. Analysis of the allelic distribution of these genes revealed their preservation within chickpea diversity and their potential association with flowering time. Variants were also identified in members of the ERF and ARF gene families. Furthermore, \u003cem\u003ein silico\u003c/em\u003e expression analysis was conducted elucidating their putative roles in flowering.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile the gene \u003cem\u003eCaELF3a \u003c/em\u003eis identified as a prominent candidate, this study also exposes new targets in chickpea, such as \u003cem\u003eCaMED16b \u003c/em\u003eand LOC101499101 (\u003cem\u003eBBX24-like\u003c/em\u003e), homologs of flowering-related genes in \u003cem\u003eArabidopsis\u003c/em\u003e, as well as \u003cem\u003eERF12 \u003c/em\u003eand \u003cem\u003eARF2\u003c/em\u003e. The \u003cem\u003ein silico\u003c/em\u003e expression characterization and genetic variability analysis performed could contribute to their use as specific markers for chickpea breeding programs. This study lays the groundwork for future investigations utilizing this plant material, promising further insights into the complex mechanisms governing flowering time in chickpea.\u003c/p\u003e","manuscriptTitle":"Phenotypic and Genetic Characterization of a Near-Isogenic Line Pair: Insights into Flowering Time in Chickpea. 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