Identification and characterization of four novel xiaomi alleles to facilitate foxtail millet as a C4 model plant

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In this paper, four novel xiaomi -like mutants, named xiaomi3 , xiaomi4 , xiaomi5 , and xiaomi6 , were identified and characterized in different genetic backgrounds. These mutants exhibited an extremely early heading phenotype, with heading occurring around 30-40 days after sowing under natural long-day conditions. Significant reductions in plant height, leaf length, leaf width, panicle length, and panicle diameter were observed in the mutants compared to their corresponding wild-types. Notably, these mutants displayed diverse panicle architectures and hull colors, effectively preventing seed mixing between them. Subsequent investigation under controlled short-day and long-day conditions confirmed the significant early heading phenotype of the mutants. Molecular characterization revealed mutations in the Phytochrome C ( SiPHYC ) gene, including transposon insertions and a frame shift mutation, were responsible for the extremely early heading phenotype. RNA-sequencing (RNA-Seq) analysis identified 19 differentially expressed genes associated with the extremely early heading phenotype. Additionally, genome-wide InDels and SNPs were identified, providing valuable resources for marker-assisted breeding and genetic studies. These findings advance our comprehension of the genetic and molecular mechanisms underlying SiPHYC mediated photoperiod flowering, and provide valuable resources that will push xiaomi as a C 4 model plant. Setaria italica C4 model plant xiaomi allele Phytochrome C miniature short life cycle Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction According to the different initial products of carbon assimilation of photosynthesis, higher plants can be categorized as C 3 plants, C 4 plants and Sedum acid metabolism plants. Compared to C 3 plants, C 4 plants exhibit relatively high photosynthetic efficiency, nitrogen- and water-use efficiency, as well as enhanced environmental adaptability (Stefanov et al. 2022 ; Peng and Zhang 2021 ; Sage 2004 ). These exceptional capabilities of C 4 plants hold promise for significantly boosting the yields of major C 3 crops to meet to meet the increasing global demands for bioenergy and food production (Zhu et al. 2010 ). However, despite the importance of C 4 plants, the lack of a representative model plant remains a challenge. Foxtail millet ( Setaria italica ), a diploid C 4 grain crop, was domesticated around 11,000 years ago from its wild progenitor, green foxtail ( Setaria viridis ) (Yang et al. 2012 ). These two species are closely related to the major crops such as maize ( Zea mays ), sorghum ( Sorghum bicolor ), and sugarcane ( Saccharum officinarum ), and the major biofuel feedstock switchgrass ( Panicum virgatum ). Due to the excellent drought and barren tolerance, foxtail millet is widely cultured in arid and semi-arid regions and plays crucial roles in global agricultural grain and biofuel production. Its wild ancestor, green foxtail, is considered a noxious weed in Asia, Europe, North America and North Africa. Furthermore, foxtail millet boasts abundant phenotypic variation resources, as well as cultivated and wild-type germplasm resources, providing valuable resources for gene-function dissection and elite-allele mining (He et al. 2023a ). These attributes together with the relatively small genome (~ 430 Mb), self-pollination and prolific seed production, foxtail millet emerges as an ideal model plant for functional genomics of the Panicoideae, especially in the study of C 4 photosynthesis (Diao et al. 2014 ; Yang et al. 2020 ; Doust et al. 2009 ; Lata et al. 2013 ). The modern era of foxtail millet research commenced in 2012 with the assembly of Yugu1 and Zhanggu genomes (Bennetzen et al. 2012 ; Zhang et al. 2012 ). Since then, significant efforts have been dedicated to developing foxtail millet into an exemplary model plant for C 4 grasses. In March 2014, the first International Setaria Genetics Conference was held in Beijing, where 230 Setaria scientists from 9 countries converged, officially proposing foxtail millet as a C 4 model plant (Diao et al. 2014 ). However, research in foxtail millet has been hindered by its large stature and long growth period, making large-scale indoor cultivation challenging. To address this limitation, a large-scale ethyl methanesulfonate (EMS)-mutagenesis using Jingu21 was conducted, leading to the identification of a miniature mutant, xiaomi (Yang et al. 2020 ). Notably, xiaomi shares several unique features with Arabidopsis thaliana , including reduced size and shortened life cycle. Furthermore, a highly efficient Agrobacterium-mediated genetic transformation system, a high-quality genome assembly and an online multi-omics database were developed (Yang et al. 2020 ; Li et al. 2023 ), laying a robust foundation for establishing foxtail millet as a C 4 model plant. In 2013, Diao's group constructed a haplotype map of foxtail millet (Jia et al. 2013 ), providing an overview of the genomic variations of foxtail millet. Recently, they further developed a graph-based genome and performed pan-genome variation analysis (He et al. 2023a ). The haplotype map, particularly the graph-based genome, provides an extensive dataset for gene discovery, functional dissection and genetic enhancement in foxtail millet, and also significantly advance its potential as a C 4 model plant. The quality of the reference genome profoundly impacts both fundamental biology studies and practical agricultural applications. More recently, a complete telomere-to-telomere (T2T) assembly of the Yugu1 genome was accomplished, providing an even more comprehensive and accurate representation of the foxtail millet genome (He et al. 2023b ). These achievements underscore the maturity of foxtail millet as a functional genomic model system for C 4 cereal. In Arabidopsis , the most successful model plant, many different ecotypes (accessions), including Columbia and Landsberg, are available for experimental analysis (Meinke et al. 1998 ). However, it is worth noting that both xiaomi and xiaomi2 were derived from the Jingu21 accession, which somewhat limits their utility as a model for genetic analysis. In this study, we identified four novel xiaomi alleles in four different accessions. All of these alleles exhibited a xiaomi- like rapid-cycling mini phenotype. Nevertheless, significant differences in panicle architecture and hull color were observed among these four alleles, which effectively avoids seed mixing between them. These alleles, along with xiaomi , will usher in a new era for functional genomic research and crop improvement, particularly for C 4 plants. Materials and methods Plant materials and growth condition xiaomi3 , xiaomi4 , xiaomi5 and xiaomi6 are natural mutants derived from Huangsu (HS), Datonghonggu (DTHG), Taixuangu29 (TXG) and Jingu60 (JG), respectively. HS and DTHG are landraces from Jiangxi and Shanxi Provinces in China, while TXG and JG are modern cultivars from Shanxi province in China. To observe the phenotype under natural long-day (LD) conditions, plants were grown in the experimental field in Taigu, Shanxi, China (37° 25′ 13″ N, 112° 35′ 26″ E). For phenotypic analysis under controlled photoperiod treatment, they were grown in auto-controlled growth chambers or culture rooms, as described previously (Yang et al. 2020 ). Heading date was measured as the number of days from sowing to panicle emergence. Map-based cloning of XIAOMI4 gene The F 1 plants were produced from a cross between xiaomi4 and G1, a landrace with a heading date of approximately 75 DAS under natural LD conditions. The F 2 seeds were collected from self-pollination of the F 1 plants and planted to generate the F 2 mapping population. The DNA of 55 recessive F 2 plants, exhibiting the typical early heading and miniature phenotype, was extracted and mixed equally. Then, the mixture of DNA was used for bulk segregation analysis using the primers listed in Table S1 . Genome re-sequencing and molecular marker development Young leaves of the xiaomi alleles were collected, and genomic DNA was extracted using cetyltrimethylammonium bromide (CTAB) method. Approximately 5 µg of extracted DNA was fragmented randomly to construct sequencing libraries following standard protocols provided by Illumina. The libraries were paired-end sequenced on an Illumina HiSeq X Ten sequencing platform at Biomarker Technologies, generating raw reads of 2 × 150 bp for downstream analyses. To identify InDel and SNP polymorphisms between xiaomi alleles and xiaomi , the raw reads were qualified and filtered using Trimmomatic (ver. 0.39) (Bolger et al. 2014 ) to generate clean reads. Clean reads were then aligned to the xiaomi reference genome (Yang et al. 2020 ) using Burrows-Wheeler aligner software (Li and Durbin 2009 ) (ver. 0.7.17) with default parameters. The alignment results in SAM format were transformed into Binary Alignment Map (BAM) format files using SAMtools (Li et al. 2009 ). Duplicate reads were removed with the MarkDuplicates program (ver. 2.18.9) in Picard ( https://broadinstitute.github.io/picard/ ) to avoid any influence on variant detection. After removing duplicate reads, SNPs and InDels were detected using GATK (ver. 3.8.0) (McKenna et al. 2010 ). InDel primers were designed by selecting the InDel site with 13 ~ 50 bp base difference, and the amplified fragments were 100 ~ 250 bp in length. Amplification was carried out as follows: 3 min at 94 ℃ for initial denaturation, followed by 30 cycles of 30 s at 94 ℃, 30 s at 56 ℃ and 30 s at 72 ℃ and a final extension at 72 ℃ for 10 min in a T100™ Thermal Cycler (Bio-Rad Laboratories). Identification and validation of the transposon insertions The BAM files generated above were displayed using Integrative Genomics Viewer (IGV, v2.12.3) (Robinson et al. 2011 ), and variations in the SiPHYC gene were manually inspected. The reads aligned to both the transposon insertion and flanking sequences were extracted and utilized to design transposon border primers. PCR was employed to confirm the transposon insertions in xiaomi4 , xiaomi5 , and xiaomi6 , using the primers listed in Table S1 . Finally, the PCR product was separated on a 1.0% agarose gel via electrophoresis, and the DNA band image was photographed. RNA extraction, RNA-Seq and RT-qPCR The second leaf from the top (the first fully unfolded leaflet) was harvested from the plants grown for 21 days LD (16 h: 8 h, light: dark) conditions after 2 hours of light, and then immediately frozen in liquid nitrogen. Total RNA was extracted from the collected samples using an RNA extraction kit (OMEGA, Guangzhou, # R6827-01). For RNA-Seq analysis, cDNA libraries were constructed and sequenced as previously reported (Yang et al. 2020 ). Transcripts per million reads (TPM) were calculated based on the length of the longest transcript of each gene. DESeq2 R package was used to perform differential expression analyses (Love et al. 2014 ). Genes with log 2 FC (fold change) ≥ 1 or ≤ 1 with p -value < 0.05 were considered as differentially expressed ones for further analysis. For RT-qPCR, the first strand of cDNA was synthesized from 1 µg total RNA using the PrimeScript™ RT reagent Kit with gDNA Eraser (Takara, Beijing, # RR047A) according to the manufacturer’s instructions. Finally, RT-qPCR was performed in a 96-well plate using TB Green® Premix Ex Taq™ II FAST qPCR (Takara, Beijing, # CN830A) on a CFX 96™ real-time PCR detection system (Bio-Rad, USA). The histone superfamily gene SiH3.3 ( Si9G37480 ) was used as an internal control. Primers used for RT-qPCR are listed in Table S1 . Results Identification and Phenotype characterization of four novel xiaomi- like natural mutants in different background During grain production in the field, we discovered four natural xiaomi- like mutants, hereby named xiaomi3 , xiaomi4 , xiaomi5 and xiaomi6 in the HS, DTHG, TXG and JG backgrounds, respectively (Fig. 1 ). Under natural LD conditions, these xiaomi- like mutants exhibited an extremely early heading phenotype, heading around 30–40 DAS. In contrast, the heading dates of the corresponding wild-types were 80–90 DAS (Table 1). Additionally, the mutant plants showed a significant decrease in plant height, leaf length, leaf width, panicle length, and panicle diameter (Fig. 1 ). Despite these similarities, significant differences were observed in panicle architecture and hull color among these four mutants. The panicle of xiaomi3 of exhibited a spindle shape and was relatively loose, while the panicles of the xiaomi4-6 were relatively compact cylinders (Fig. 1 e-h). Furthermore, the hull color of xiaomi4 was reddish brown, while the others were yellow (Fig. 1 e-h). Photoperiod is one of the most critical environmental factors that influences the transition from vegetative to reproductive development in flowering plants. To further explore the photoperiodic response of these xiaomi -like mutants, they were cultivated in growth chambers under SD or LD conditions, respectively. Consistent with the extremely early heading phenotype under natural LD conditions, the heading dates of xiaomi3 , xiaomi4 , xiaomi5 and xiaomi6 were significantly earlier than those of their wild-type varieties HS, DTHG, TXG and JG under artificial LD conditions in growth chambers (Fig. 2 ). Under SD conditions, xiaomi6 also flowered earlier than JG, xiaomi3 flowered at the same time to HS, while xiaomi4 and xiaomi5 flowered even later than their wild accessions, DTHG and TXG (Fig. 2 ). Molecular characterization of the xiaomi- like mutants To identify the mutation responsible for the xiaomi- like phenotype, we conducted a cross between xiaomi4 and G1, a landrace with a heading date of ~ 75 DAS under the long-day conditions. All 10 F 1 plants exhibited a G1-like late heading phenotype, indicating that the xiaomi- like phenotype of xiaomi4 was caused by recessive mutation (s). The mutation was then mapped using 55 homozygous recessive F 2 individuals via bulked segregant analysis. In the initial mapping, two markers, M3374 and M8819 on chromosome 9, were found to be linked to the mutation in an initial mapping (Fig. 3 a and b). Coincidently, we discovered the SiPHYC gene located in this interval. Genome re-sequencing analysis revealed that the insertion of a transposon at the 2,222th nucleotide (the first nucleotide of the translation start codon is referred to as + 1) in the second exon of SiPHYC , indicating the xiaomi- like early-heading phenotype might result from the mutation at the PHYC locus (Fig. 3 c). To confirm the presence of the transposon in xiaomi4 , we conducted PCR analysis using SiPHYC -specific primers in combination with transposon boarder specific primers. As shown in Fig. 3 c, DTHG, the wild-type of xiaomi4 , produced an expected 1306 bp band with SiPHYC specific primers xioami4F and xiaomi4R, but no bands could be visible in xiaomi4 mutant due to the large transposon insertion. In contrast, xiaomi4 generated 554 bp or 797 bp band with primer pairs xiaomi4F/xiaomi4TR or xiaomi4R/xiaomi4TF, which were absent in DTHG (Fig. 3 d). Furthermore, allelic analysis provided additional confirmation that xiaomi4 is a novel allelic mutant of xiaomi , as all 9 individual F 1 plants and 165 F 2 plants from a cross between xiaomi4 and xiaomi exhibited a xiaomi -like early heading phenotype. Given that xiaomi3 , xiaomi5 and xiaomi6 also displayed a xiaomi -like phenotype similar to xiaomi4 , we suspected that these mutants were also xiaomi alleles. To test this hypothesis, we analyzed the genome resequencing data, and found a single nucleotide deletion in xiaomi3 at the 1,348th nucleotide in the first exon of SiPHYC , causing a frame shift mutation (Fig. 4 a, 4 b and Fig. S1 a). In the xiaomi5 and xiaomi6 mutants, a transposon was inserted in the first exon at the 213th and 1453th nucleotide, respectively (Fig. 4 a and Fig. S1 b, S1c). These transposon insertions were further confirmed by PCR (Fig. 2 c and 2 d). To examine the effect of these SiPHYC mutations on its expression, reverse transcription-PCR (RT-PCR) was performed. As shown in Fig. 4 , there was no significant difference in SiPHYC expression level between xiaomi3 and the wild-type plants. However, no expression was detected in the three transposon insertion mutants, xiaomi4 , xiaomi5 and xiaomi6 (Fig. 4 e). Effects of SiPHYC mutation on photoperiod pathway gene expression in different accessions Previously, we found that mutation of SiPHYC dramatically altered expression of genes linked to photoperiodic pathway (Jingu21 background) (Yang et al. 2020 ). To gain a deeper understanding of the impact of the SiPHYC mutation on gene expression and its interaction with the background, transcriptomic variations of the xiaomi alleles were analyzed using RNA-Seq approach. A total of 1048, 1489, and 4319 differentially expressed genes (DEGs) were identified between xiaomi3 , xiaomi4 , xiaomi5 , xiaomi6 and their corresponding wild-types (Dataset 1). Among these DEGs, 19 were exhibited similar expression patterns in all the four xiaomi alleles, including well-characterized ortholog flowering time genes in other plants, such as SiEhd1 ( Si9g22570 ), SiMADS14 ( Si9g09160 ), SiMADS15 ( Si2g01630 ), SiMADS18 ( Si2g38170 ), SiFTL2 ( Si4g07330 ), and SiFT9 ( Si5g32220 ), which might be responsible for the extremely early heading phenotype of these xiaomi alleles (Fig. 5 ). Furthermore, to verify RNA-Seq results and to understand the influence of background on gene expression, the expression level of six flowering time related genes, including SiMADS14 、 SiMADS18 and SiFT9 mentioned above, were analyzed using RT-qPCR. Consistent to the RNA-Seq results, the expression of SiPRR7 ( Si2G43940 ) was downregulated, while the expression of the other five genes was upregulated (Fig. 5 ). Moreover, the expression levels of these genes vary among different xiaomi alleles, which might be responsible for variation of the heading date of the xiaomi alleles. Genome-wide development of InDels and SNPs in xiaomi alleles Molecular markers, particularly InDels, are valuable resources for map-based cloning, marker-assisted breeding and germplasm genotyping. To identify molecular markers genome widely, we conducted genome re-sequencing of the xiaomi alleles with an average coverage depth of 30×. Molecular markers, including InDels and SNPs, were identified by comparing the re-sequencing data with the xiaomi reference genome. A total of 508235 InDels were detected in the genome of the four xiaomi alleles (Dataset 1). Of these InDels, 64171 located in upstream, 52792 were in downstream, 317622 were in intergenic regions, 66353 were in introns, 20496 were in exons and were in 14970 3' untranslated regions (UTR) and 9729 in 5' UTR (Dataset 2). Additionally, 3216261 SNPs were identified in these four xiaomi alleles, with 231609 in upstream, 201110 in downstream, 2310533 in the intergenic regions, 292563 in introns, 182078 in exons, 48794 in 3'UTR and 26937 in 5'UTR, respectively (Dataset 3). To facilitate the use of these InDels, we screened out high-quality homozygous InDels ranging from 14 to 200 bp in length. These variations could serve as promising candidates for designing molecular markers that can be easily examined through PCR and agarose gel electrophoresis. In total, we identified 37,682 InDels distributed across the 9 chromosomes of the xiaomi genome, with an average of 87.63 InDels per mega base (Fig. 6 a and Dataset 4). Among these InDels, 7452, 7136, 5358, and 4911 were unique to xiaomi3 , xiaomi4 , xiaomi5 and xiaomi6 , respectively. Only 1468 were shared by all the four xiaomi alleles (Fig. 7 a). To validate the accuracy of the candidate InDel markers, we screened and designed 10 pairs of representative InDel marker primers based on their distribution on chromosomes (Table S1 ). All 10 pairs of primers successfully amplified specific bands and exhibited expected polymorphisms between the xiaomi alleles (Fig. 7 b). Discussion The utilization of diverse genetic backgrounds allows for a more comprehensive understanding of trait variation, gene discovery, and the elucidation of complex genetic interactions. Here, four novel xiaomi alleles ( xiaomi3 , xiaomi4 , xiaomi5 , and xiaomi6 ) were isolated from different genetic backgrounds and extensively characterized, providing valuable supplements to establish xiaomi as a C 4 model plant. The PHYC is a crucial photoreceptor for red and far-red light in plants and plays essential roles in photomorphogenesis. Our findings show that siphyc mutants in foxtail millet flower approximately 2 months earlier than the wild-types under noninductive LD conditions (Fig. 2 a, see also Yang et al. 2020 ; Wang et al. 2022), indicating the SiPHYC gene plays a significant role as a flowering time repressor and a determinator in foxtail millet under LD conditions. Notably, unlike Arabidopsis and rice phyc mutants, which exhibit similar flowering time to the wild-type under inductive conditions (Monte et al. 2003 ; Takano et al. 2005 ). xiaomi , xiaomi4 and xiaomi5 flowered even later than their corresponding wild-types under SD conditions. Furthermore, the plant height was also dramatically decreased in xiaomi alleles, while the number of tillers/ branches significantly increased in xiaomi alleles (Fig. 1 and Yang et al. 2020 ; Wang et al. 2022), which were not observed in either Arabidopsis or rice (Monte et al. 2003 ; Takano et al. 2005 ; Li et al. 2021 ). These results suggested that the PHYC gene may have different functions in flowering time regulation and photomorphogenesis in different species, although further verification of these conjectures is needed in the future. In rice, a facultative SD plant, multiple genes regulate the photoperiodic flowering pathway. Core genes in this pathway include Heading date 1 ( Hd1 ) and Early heading date 1 ( Ehd1 ), Grain number , plant height , and heading date 7 ( Ghd7 ), Days to heading on chromosome8 ( DTH8 ). Hd1 is a homolog of CONSTANS ( CO ) in Arabidopsis , while Ehd1 is a unique flowering time gene in rice without homologs in Arabidopsis (Doi et al. 2004 ). Under LD conditions, Hd1 synergistically suppresses flowering with Ghd7 or Ghd7 - DTH8 , while under SD conditions, Hd1 competes with the suppressor Ghd7 , DTH8 , or Ghd7 - DTH8 , to promote flowering (Sun et al. 2022 ). The transcriptomic results revealed that the four xiaomi alleles shared 19 DEGs, including SiEhd1 , the homologue of Ehd1 in rice, suggesting that SiPHYC functions in photoperiodic flowering mainly through the Ehd1 -dependent pathway. In addition to the well-characterized flowering time genes, there are several DEGs with unknown functions shared among the xiaomi alleles which might represent unique flowering time genes in foxtail millet and require further study to comprehensively understand the regulatory networks involved in the photoperiodic response in foxtail millet. Conclusion In this study, we have identified four novel xiaomi alleles in various genetic backgrounds. All of these mutants exhibited xiaomi -like early heading and miniature phenotypes, demonstrating their potential to establish an efficient indoor cultivation system. The phenotypes observed were caused by a single nucleotide deletion or transposon insertion in the SiPHYC gene. These mutations resulted in the absence or frame-shift of SiPHYC , which in turn affected the photoperiodic response of the mutants and leading to their early flowering. Additionally, genome-wide molecular markers, including InDels and SNPs, were identified in the xiaomi alleles, providing valuable resources for map-based cloning and marker-assisted breeding. Declarations Author contributions Xingchun Wang designed the experiments, coordinated the study, performed map-based cloning of the XIAOMI4 gene and wrote the manuscript. Meng Shan, Mengmeng Duan, Huimin Shen, Yujing Wang and Zhirong Yang characterized the xiaomi allele phenotype. Yiru Zhang and Xingchun Wang identified the xiaomi3 mutant. Yuanhuai Han identified the xiaomi3 mutant. Kai Zhao identified the xiaomi5 and xiaomi6 mutants. Xukai Li analyzed genome resequencing data and identified the InDels and SNPs. Data availability The raw sequence data have been deposited in the Beijing Institute of Genomics Data Center (https://bigd.big.ac.cn/) under the BioProject accession PRJCA022856. Acknowledgements This work was financially supported by National Key R&D Program of China (2022YFC3400300, 2022YFC3400301), Shanxi Province Science and Technology Major Special Project (202101140601027), the Central Government Guides the Local Science and Technology Development Fund Project (YDZJSX2021B010), Fundamental Research Program of Shanxi Province (20210302123423, 20210302123385) and Graduate Research and Innovation Projects of Shanxi Province (2023KY319) and China Agriculture Research System of MOF and MARA (CARS-06-14.5-B8). 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Dataset3SNPsofthexiaomialleles.vcf Dataset 3 SNPs identified in xiaomi alleles. Dataset4InDelssuitablefordevelopingmolecularmarkers.xlsx Dataset 4 InDels suitable for developing molecular markers. SupplementaryInformation.docx Cite Share Download PDF Status: Published Journal Publication published 13 Mar, 2024 Read the published version in Plant Growth Regulation → Version 1 posted Editorial decision: Minor revisions 03 Feb, 2024 Reviewers agreed at journal 25 Jan, 2024 Reviewers invited by journal 24 Jan, 2024 Editor invited by journal 24 Jan, 2024 Editor assigned by journal 19 Jan, 2024 First submitted to journal 18 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-3869721","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269356252,"identity":"9c3631d1-b252-4532-a827-a45ec0a7912d","order_by":0,"name":"Meng 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12:10:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3869721/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3869721/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10725-024-01134-0","type":"published","date":"2024-03-13T11:11:30+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50350943,"identity":"b71f7ec0-0a94-41c6-a17b-608fd5540a01","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9578683,"visible":true,"origin":"","legend":"\u003cp\u003ePhenotype of four novel \u003cem\u003exiaomi-\u003c/em\u003elike mutants. \u003cstrong\u003ea \u003c/strong\u003ePlants of HS (Left) and \u003cem\u003exiaomi3\u003c/em\u003e(Right) at 70 DAS; \u003cstrong\u003eb\u003c/strong\u003e Plants of DTHG (Left) and \u003cem\u003exiaomi4\u003c/em\u003e (Right) at 70 DAS; \u003cstrong\u003ec \u003c/strong\u003ePlants of TXG (Left) and \u003cem\u003exiaomi5\u003c/em\u003e (Right) at 70 DAS; \u003cstrong\u003ed\u003c/strong\u003ePlants of JG (Left) and \u003cem\u003exiaomi6\u003c/em\u003e (Right) at 70 DAS; Note: The main panicles of \u003cem\u003exiaomi3-6\u003c/em\u003e mutants matured at 70 DAS, while the wild-type, HS, TXG and JG didn’t head, and DTHG headed approximate 2 days. \u003cstrong\u003ee\u003c/strong\u003e Panicles of HS (Left) and \u003cem\u003exiaomi3\u003c/em\u003e (Right); \u003cstrong\u003ef\u003c/strong\u003e Panicles of DTHG (Left) and \u003cem\u003exiaomi4\u003c/em\u003e(Right); \u003cstrong\u003eg\u003c/strong\u003e Panicles of TXG (Left) and \u003cem\u003exiaomi5\u003c/em\u003e (Right); \u003cstrong\u003eh\u003c/strong\u003ePanicles of JG (Left) and \u003cem\u003exiaomi6\u003c/em\u003e (Right). Scale bar: \u003cstrong\u003ea\u003c/strong\u003e-\u003cstrong\u003ed\u003c/strong\u003e20 cm, \u003cstrong\u003ee\u003c/strong\u003e-\u003cstrong\u003eh\u003c/strong\u003e 5 cm.\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/7033b6c5b580e21b1021d6e0.jpg"},{"id":50350937,"identity":"5258ed13-f1f9-41bd-a1ba-f0dd2c814847","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1160880,"visible":true,"origin":"","legend":"\u003cp\u003eHeading dates of \u003cem\u003exiaomi-\u003c/em\u003elike mutants. Heading dates of \u003cem\u003exiaomi\u003c/em\u003e-like mutants and their corresponding wild-type plants under LD (\u003cstrong\u003ea\u003c/strong\u003e) or SD (\u003cstrong\u003eb\u003c/strong\u003e) conditions. The heading dates of at least 30 plants were measured. Data are presented as mean values ±standard error (n≥ 30).\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/ed7be40b29c2349c7c8c39e9.jpg"},{"id":50351758,"identity":"230a79b8-1f0d-4e9a-a7b2-0ecd7f0835f7","added_by":"auto","created_at":"2024-01-30 08:03:04","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1935276,"visible":true,"origin":"","legend":"\u003cp\u003eMap-based cloning of \u003cem\u003eXIAOMI4\u003c/em\u003e. \u003cstrong\u003ea \u003c/strong\u003eand\u003cstrong\u003eb \u003c/strong\u003eBSA of \u003cem\u003exiaomi4\u003c/em\u003e with molecular marker\u003cstrong\u003e \u003c/strong\u003eM3374 and M8819. \u003cstrong\u003ec \u003c/strong\u003eAn IGV display of genome sequencing reads from DTHG (top) or \u003cem\u003exiaomi4\u003c/em\u003e(bottom) spanning the transposon insertion site on \u003cem\u003eSiPHYC\u003c/em\u003e gene. The break point caused by the insertion was marked by an arrow. The numbers above the graph correspond to the positions on the chromosomes. \u003cstrong\u003ed\u003c/strong\u003e PCR confirmation of the insertion transposon site in \u003cem\u003exiaomi4\u003c/em\u003e. The upper panels were PCR products amplified using primers flanking the transposon, thus the wild-type got a band but not the mutant. The middle panels were PCR products amplified using forward \u003cem\u003eSiPHYC\u003c/em\u003e primers of and left transposon boarder primers, thus the mutant got a band but not the wild-type. Similarly, the bottom panel were PCR products amplified using reverse \u003cem\u003eSiPHYC\u003c/em\u003eprimers of and right transposon boarder primers, thus the mutant got a band but not the wild-type.\u003c/p\u003e","description":"","filename":"floatimage3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/e46d259b958fc0636bf2d696.jpg"},{"id":50351759,"identity":"9193b634-b2d3-4985-9d0b-3f3a2562fc35","added_by":"auto","created_at":"2024-01-30 08:03:04","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3793789,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular characterization of the \u003cem\u003exiaomi\u003c/em\u003e alleles.\u003cstrong\u003e a \u003c/strong\u003eStructure of the \u003cem\u003eSiPHYC\u003c/em\u003egene with indication of the nature of the \u003cem\u003exiaomi\u003c/em\u003e alleles. Exons and introns are denoted by filled boxes and lines, respectively. Positions of the start (ATG) and stop (TGA) codons are also indicated. \u003cstrong\u003eb \u003c/strong\u003eSequencing results of PCR products spanning base deletion sites, showing the wild-type HS (top) and \u003cem\u003exiaomi3\u003c/em\u003e (bottom). The deletion nucleotide was marked by a purple arrow. \u003cstrong\u003ec\u003c/strong\u003e and\u003cstrong\u003e d\u003c/strong\u003e. The validation of transposon insertions in \u003cem\u003exiaomi5\u003c/em\u003e (\u003cstrong\u003ec\u003c/strong\u003e) and \u003cem\u003exiaomi6 \u003c/em\u003e(\u003cstrong\u003ed\u003c/strong\u003e) genomes. \u003cstrong\u003ee\u003c/strong\u003e. Comparison of \u003cem\u003eSiPHYC \u003c/em\u003etranscript levels in \u003cem\u003exiaomi \u003c/em\u003ealleles and their corresponding wild-type plants by RT-PCR. PCR products with the gene-specific primer pair (top), the gene-specific primer pair and forward (middle) or reverse (bottom) transposon binding primer were separated on a 1.0% agarose gel via electrophoresis.\u003c/p\u003e","description":"","filename":"floatimage4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/be664d4d9d3824109895dbae.jpg"},{"id":50350941,"identity":"1b0aefec-6362-4fab-a8eb-0cc66db55b8a","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1016438,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams of the DEGs in \u003cem\u003exiaomi\u003c/em\u003ealleles\u003c/p\u003e","description":"","filename":"floatimage5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/6ec3bc2de62b612c2ef03c7d.jpg"},{"id":50350938,"identity":"8c734cd1-9c45-4513-82c2-636ae3ecb271","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3786008,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpressions of key photoperiod pathway genes measured by RT-qPCR. \u003c/strong\u003eThe relative expression level to the reference gene is plotted. Values are the means ± standard error of three independent samples.\u003c/p\u003e","description":"","filename":"floatimage6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/e3399bcc3a51b105b259767e.jpg"},{"id":50350942,"identity":"21a12da7-6db4-4c88-9730-1f388bc90e83","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2986935,"visible":true,"origin":"","legend":"\u003cp\u003eInDels suitable for designing molecular markers.\u003cstrong\u003e a \u003c/strong\u003eVenn diagrams of the InDel numbers in \u003cem\u003exiaomi\u003c/em\u003e alleles; \u003cstrong\u003eb \u003c/strong\u003ePolymorphism analysis of InDel markers between \u003cem\u003exiaomi\u003c/em\u003e alleles using PCR. Primers were listed in Table S1.\u003c/p\u003e","description":"","filename":"floatimage7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/14166948e575c8bae3102c46.jpg"},{"id":52813416,"identity":"d70a8388-835f-4474-ac2e-56ce4f690320","added_by":"auto","created_at":"2024-03-16 11:11:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1157811,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/5763a09a-101f-4435-acce-15c18bf0d65f.pdf"},{"id":50350945,"identity":"6011b1e4-6d71-4437-a92e-d041e1965908","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1350069,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDataset 1 \u003c/strong\u003eDifferentially expressed gene in \u003cem\u003exiaomi\u003c/em\u003ealleles.\u003c/p\u003e","description":"","filename":"Dataset1Differentiallyexpressedgeneinxiaomialleles.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/d8d8e25108c59fb32c8041ba.xlsx"},{"id":50350975,"identity":"ebbefa66-d847-45fc-b05d-d8d32bc2969d","added_by":"auto","created_at":"2024-01-30 07:55:14","extension":"vcf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":159869966,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDataset 2\u003c/strong\u003e InDels identified in \u003cem\u003exiaomi \u003c/em\u003ealleles.\u003c/p\u003e","description":"","filename":"Dataset2InDelsofthexiaomialleles.vcf","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/c1af52b02faacfe7fefd754f.vcf"},{"id":50351018,"identity":"3934033d-ed42-4bf2-b9eb-228c8f861a8d","added_by":"auto","created_at":"2024-01-30 07:56:06","extension":"vcf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":999711683,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDataset 3\u003c/strong\u003e SNPs identified in \u003cem\u003exiaomi \u003c/em\u003ealleles.\u003c/p\u003e","description":"","filename":"Dataset3SNPsofthexiaomialleles.vcf","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/54c2af51714fcb9b46c16888.vcf"},{"id":50351760,"identity":"9b679fb3-65bc-4dca-b002-f223ee1221fa","added_by":"auto","created_at":"2024-01-30 08:03:04","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5063131,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDataset 4\u003c/strong\u003e InDels suitable for developing molecular markers.\u003c/p\u003e","description":"","filename":"Dataset4InDelssuitablefordevelopingmolecularmarkers.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/2cd02e4fa398732560e77d00.xlsx"},{"id":50350947,"identity":"1151714b-7a20-44ec-8755-3a40bb4c6683","added_by":"auto","created_at":"2024-01-30 07:55:04","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1862502,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-3869721/v1/71a86fc8842c87bb78725d52.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eIdentification and characterization of four novel \u003cem\u003exiaomi \u003c/em\u003ealleles to facilitate foxtail millet as a C\u003csub\u003e4\u003c/sub\u003e model plant\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the different initial products of carbon assimilation of photosynthesis, higher plants can be categorized as C\u003csub\u003e3\u003c/sub\u003e plants, C\u003csub\u003e4\u003c/sub\u003e plants and Sedum acid metabolism plants. Compared to C\u003csub\u003e3\u003c/sub\u003e plants, C\u003csub\u003e4\u003c/sub\u003e plants exhibit relatively high photosynthetic efficiency, nitrogen- and water-use efficiency, as well as enhanced environmental adaptability (Stefanov et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Peng and Zhang \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sage \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). These exceptional capabilities of C\u003csub\u003e4\u003c/sub\u003e plants hold promise for significantly boosting the yields of major C\u003csub\u003e3\u003c/sub\u003e crops to meet to meet the increasing global demands for bioenergy and food production (Zhu et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). However, despite the importance of C\u003csub\u003e4\u003c/sub\u003e plants, the lack of a representative model plant remains a challenge.\u003c/p\u003e \u003cp\u003eFoxtail millet (\u003cem\u003eSetaria italica\u003c/em\u003e), a diploid C\u003csub\u003e4\u003c/sub\u003e grain crop, was domesticated around 11,000 years ago from its wild progenitor, green foxtail (\u003cem\u003eSetaria viridis\u003c/em\u003e) (Yang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These two species are closely related to the major crops such as maize (\u003cem\u003eZea mays\u003c/em\u003e), sorghum (\u003cem\u003eSorghum bicolor\u003c/em\u003e), and sugarcane (\u003cem\u003eSaccharum officinarum\u003c/em\u003e), and the major biofuel feedstock switchgrass (\u003cem\u003ePanicum virgatum\u003c/em\u003e). Due to the excellent drought and barren tolerance, foxtail millet is widely cultured in arid and semi-arid regions and plays crucial roles in global agricultural grain and biofuel production. Its wild ancestor, green foxtail, is considered a noxious weed in Asia, Europe, North America and North Africa. Furthermore, foxtail millet boasts abundant phenotypic variation resources, as well as cultivated and wild-type germplasm resources, providing valuable resources for gene-function dissection and elite-allele mining (He et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). These attributes together with the relatively small genome (~\u0026thinsp;430 Mb), self-pollination and prolific seed production, foxtail millet emerges as an ideal model plant for functional genomics of the Panicoideae, especially in the study of C\u003csub\u003e4\u003c/sub\u003e photosynthesis (Diao et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Doust et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Lata et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe modern era of foxtail millet research commenced in 2012 with the assembly of Yugu1 and Zhanggu genomes (Bennetzen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Since then, significant efforts have been dedicated to developing foxtail millet into an exemplary model plant for C\u003csub\u003e4\u003c/sub\u003e grasses. In March 2014, the first International Setaria Genetics Conference was held in Beijing, where 230 Setaria scientists from 9 countries converged, officially proposing foxtail millet as a C\u003csub\u003e4\u003c/sub\u003e model plant (Diao et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, research in foxtail millet has been hindered by its large stature and long growth period, making large-scale indoor cultivation challenging. To address this limitation, a large-scale ethyl methanesulfonate (EMS)-mutagenesis using Jingu21 was conducted, leading to the identification of a miniature mutant, \u003cem\u003exiaomi\u003c/em\u003e (Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, \u003cem\u003exiaomi\u003c/em\u003e shares several unique features with \u003cem\u003eArabidopsis thaliana\u003c/em\u003e, including reduced size and shortened life cycle. Furthermore, a highly efficient Agrobacterium-mediated genetic transformation system, a high-quality genome assembly and an online multi-omics database were developed (Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), laying a robust foundation for establishing foxtail millet as a C\u003csub\u003e4\u003c/sub\u003e model plant. In 2013, Diao's group constructed a haplotype map of foxtail millet (Jia et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), providing an overview of the genomic variations of foxtail millet. Recently, they further developed a graph-based genome and performed pan-genome variation analysis (He et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). The haplotype map, particularly the graph-based genome, provides an extensive dataset for gene discovery, functional dissection and genetic enhancement in foxtail millet, and also significantly advance its potential as a C\u003csub\u003e4\u003c/sub\u003e model plant. The quality of the reference genome profoundly impacts both fundamental biology studies and practical agricultural applications. More recently, a complete telomere-to-telomere (T2T) assembly of the Yugu1 genome was accomplished, providing an even more comprehensive and accurate representation of the foxtail millet genome (He et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). These achievements underscore the maturity of foxtail millet as a functional genomic model system for C\u003csub\u003e4\u003c/sub\u003e cereal.\u003c/p\u003e \u003cp\u003eIn \u003cem\u003eArabidopsis\u003c/em\u003e, the most successful model plant, many different ecotypes (accessions), including Columbia and Landsberg, are available for experimental analysis (Meinke et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). However, it is worth noting that both \u003cem\u003exiaomi\u003c/em\u003e and \u003cem\u003exiaomi2\u003c/em\u003e were derived from the Jingu21 accession, which somewhat limits their utility as a model for genetic analysis. In this study, we identified four novel \u003cem\u003exiaomi\u003c/em\u003e alleles in four different accessions. All of these alleles exhibited a \u003cem\u003exiaomi-\u003c/em\u003elike rapid-cycling mini phenotype. Nevertheless, significant differences in panicle architecture and hull color were observed among these four alleles, which effectively avoids seed mixing between them. These alleles, along with \u003cem\u003exiaomi\u003c/em\u003e, will usher in a new era for functional genomic research and crop improvement, particularly for C\u003csub\u003e4\u003c/sub\u003e plants.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials and growth condition\u003c/h2\u003e \u003cp\u003e \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e are natural mutants derived from Huangsu (HS), Datonghonggu (DTHG), Taixuangu29 (TXG) and Jingu60 (JG), respectively. HS and DTHG are landraces from Jiangxi and Shanxi Provinces in China, while TXG and JG are modern cultivars from Shanxi province in China. To observe the phenotype under natural long-day (LD) conditions, plants were grown in the experimental field in Taigu, Shanxi, China (37° 25′ 13″ N, 112° 35′ 26″ E). For phenotypic analysis under controlled photoperiod treatment, they were grown in auto-controlled growth chambers or culture rooms, as described previously (Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Heading date was measured as the number of days from sowing to panicle emergence.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMap-based cloning of\u003c/b\u003e \u003cb\u003eXIAOMI4\u003c/b\u003e \u003cb\u003egene\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe F\u003csub\u003e1\u003c/sub\u003e plants were produced from a cross between \u003cem\u003exiaomi4\u003c/em\u003e and G1, a landrace with a heading date of approximately 75 DAS under natural LD conditions. The F\u003csub\u003e2\u003c/sub\u003e seeds were collected from self-pollination of the F\u003csub\u003e1\u003c/sub\u003e plants and planted to generate the F\u003csub\u003e2\u003c/sub\u003e mapping population. The DNA of 55 recessive F\u003csub\u003e2\u003c/sub\u003e plants, exhibiting the typical early heading and miniature phenotype, was extracted and mixed equally. Then, the mixture of DNA was used for bulk segregation analysis using the primers listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eGenome re-sequencing and molecular marker development\u003c/h2\u003e \u003cp\u003eYoung leaves of the \u003cem\u003exiaomi\u003c/em\u003e alleles were collected, and genomic DNA was extracted using cetyltrimethylammonium bromide (CTAB) method. Approximately 5 µg of extracted DNA was fragmented randomly to construct sequencing libraries following standard protocols provided by Illumina. The libraries were paired-end sequenced on an Illumina HiSeq X Ten sequencing platform at Biomarker Technologies, generating raw reads of 2 × 150 bp for downstream analyses.\u003c/p\u003e \u003cp\u003eTo identify InDel and SNP polymorphisms between \u003cem\u003exiaomi\u003c/em\u003e alleles and \u003cem\u003exiaomi\u003c/em\u003e, the raw reads were qualified and filtered using Trimmomatic (ver. 0.39) (Bolger et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) to generate clean reads. Clean reads were then aligned to the \u003cem\u003exiaomi\u003c/em\u003e reference genome (Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) using Burrows-Wheeler aligner software (Li and Durbin \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) (ver. 0.7.17) with default parameters. The alignment results in SAM format were transformed into Binary Alignment Map (BAM) format files using SAMtools (Li et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Duplicate reads were removed with the MarkDuplicates program (ver. 2.18.9) in Picard (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://broadinstitute.github.io/picard/\u003c/span\u003e\u003cspan address=\"https://broadinstitute.github.io/picard/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to avoid any influence on variant detection. After removing duplicate reads, SNPs and InDels were detected using GATK (ver. 3.8.0) (McKenna et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). InDel primers were designed by selecting the InDel site with 13 ~ 50 bp base difference, and the amplified fragments were 100 ~ 250 bp in length. Amplification was carried out as follows: 3 min at 94 ℃ for initial denaturation, followed by 30 cycles of 30 s at 94 ℃, 30 s at 56 ℃ and 30 s at 72 ℃ and a final extension at 72 ℃ for 10 min in a T100™ Thermal Cycler (Bio-Rad Laboratories).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and validation of the transposon insertions\u003c/h2\u003e \u003cp\u003eThe BAM files generated above were displayed using Integrative Genomics Viewer (IGV, v2.12.3) (Robinson et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and variations in the \u003cem\u003eSiPHYC\u003c/em\u003e gene were manually inspected. The reads aligned to both the transposon insertion and flanking sequences were extracted and utilized to design transposon border primers. PCR was employed to confirm the transposon insertions in \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e, and \u003cem\u003exiaomi6\u003c/em\u003e, using the primers listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Finally, the PCR product was separated on a 1.0% agarose gel via electrophoresis, and the DNA band image was photographed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction, RNA-Seq and RT-qPCR\u003c/h2\u003e \u003cp\u003eThe second leaf from the top (the first fully unfolded leaflet) was harvested from the plants grown for 21 days LD (16 h: 8 h, light: dark) conditions after 2 hours of light, and then immediately frozen in liquid nitrogen. Total RNA was extracted from the collected samples using an RNA extraction kit (OMEGA, Guangzhou, # R6827-01).\u003c/p\u003e \u003cp\u003eFor RNA-Seq analysis, cDNA libraries were constructed and sequenced as previously reported (Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Transcripts per million reads (TPM) were calculated based on the length of the longest transcript of each gene. DESeq2 R package was used to perform differential expression analyses (Love et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Genes with log\u003csub\u003e2\u003c/sub\u003eFC (fold change) ≥ 1 or ≤ 1 with \u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.05 were considered as differentially expressed ones for further analysis.\u003c/p\u003e \u003cp\u003eFor RT-qPCR, the first strand of cDNA was synthesized from 1 µg total RNA using the PrimeScript™ RT reagent Kit with gDNA Eraser (Takara, Beijing, # RR047A) according to the manufacturer’s instructions. Finally, RT-qPCR was performed in a 96-well plate using TB Green® Premix Ex Taq™ II FAST qPCR (Takara, Beijing, # CN830A) on a CFX 96™ real-time PCR detection system (Bio-Rad, USA). The histone superfamily gene \u003cem\u003eSiH3.3\u003c/em\u003e (\u003cem\u003eSi9G37480\u003c/em\u003e) was used as an internal control. Primers used for RT-qPCR are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eIdentification and Phenotype characterization of four novel\u003c/b\u003e \u003cb\u003exiaomi-\u003c/b\u003e\u003cb\u003elike natural mutants in different background\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDuring grain production in the field, we discovered four natural \u003cem\u003exiaomi-\u003c/em\u003elike mutants, hereby named \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e in the HS, DTHG, TXG and JG backgrounds, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Under natural LD conditions, these \u003cem\u003exiaomi-\u003c/em\u003elike mutants exhibited an extremely early heading phenotype, heading around 30–40 DAS. In contrast, the heading dates of the corresponding wild-types were 80–90 DAS (Table\u0026nbsp;1). Additionally, the mutant plants showed a significant decrease in plant height, leaf length, leaf width, panicle length, and panicle diameter (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Despite these similarities, significant differences were observed in panicle architecture and hull color among these four mutants. The panicle of \u003cem\u003exiaomi3\u003c/em\u003e of exhibited a spindle shape and was relatively loose, while the panicles of the \u003cem\u003exiaomi4-6\u003c/em\u003e were relatively compact cylinders (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee-h). Furthermore, the hull color of \u003cem\u003exiaomi4\u003c/em\u003e was reddish brown, while the others were yellow (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee-h).\u003c/p\u003e\u003cp\u003ePhotoperiod is one of the most critical environmental factors that influences the transition from vegetative to reproductive development in flowering plants. To further explore the photoperiodic response of these \u003cem\u003exiaomi\u003c/em\u003e-like mutants, they were cultivated in growth chambers under SD or LD conditions, respectively. Consistent with the extremely early heading phenotype under natural LD conditions, the heading dates of \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e were significantly earlier than those of their wild-type varieties HS, DTHG, TXG and JG under artificial LD conditions in growth chambers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Under SD conditions, \u003cem\u003exiaomi6\u003c/em\u003e also flowered earlier than JG, \u003cem\u003exiaomi3\u003c/em\u003e flowered at the same time to HS, while \u003cem\u003exiaomi4\u003c/em\u003e and \u003cem\u003exiaomi5\u003c/em\u003e flowered even later than their wild accessions, DTHG and TXG (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e \u003cb\u003eMolecular characterization of the\u003c/b\u003e \u003cb\u003exiaomi-\u003c/b\u003e\u003cb\u003elike mutants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify the mutation responsible for the \u003cem\u003exiaomi-\u003c/em\u003elike phenotype, we conducted a cross between \u003cem\u003exiaomi4\u003c/em\u003e and G1, a landrace with a heading date of ~ 75 DAS under the long-day conditions. All 10 F\u003csub\u003e1\u003c/sub\u003e plants exhibited a G1-like late heading phenotype, indicating that the \u003cem\u003exiaomi-\u003c/em\u003elike phenotype of \u003cem\u003exiaomi4\u003c/em\u003e was caused by recessive mutation (s). The mutation was then mapped using 55 homozygous recessive F\u003csub\u003e2\u003c/sub\u003e individuals via bulked segregant analysis. In the initial mapping, two markers, M3374 and M8819 on chromosome 9, were found to be linked to the mutation in an initial mapping (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and b). Coincidently, we discovered the \u003cem\u003eSiPHYC\u003c/em\u003e gene located in this interval. Genome re-sequencing analysis revealed that the insertion of a transposon at the 2,222th nucleotide (the first nucleotide of the translation start codon is referred to as + 1) in the second exon of \u003cem\u003eSiPHYC\u003c/em\u003e, indicating the \u003cem\u003exiaomi-\u003c/em\u003elike early-heading phenotype might result from the mutation at the \u003cem\u003ePHYC\u003c/em\u003e locus (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003eTo confirm the presence of the transposon in \u003cem\u003exiaomi4\u003c/em\u003e, we conducted PCR analysis using \u003cem\u003eSiPHYC\u003c/em\u003e-specific primers in combination with transposon boarder specific primers. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, DTHG, the wild-type of \u003cem\u003exiaomi4\u003c/em\u003e, produced an expected 1306 bp band with \u003cem\u003eSiPHYC\u003c/em\u003e specific primers xioami4F and xiaomi4R, but no bands could be visible in \u003cem\u003exiaomi4\u003c/em\u003e mutant due to the large transposon insertion. In contrast, \u003cem\u003exiaomi4\u003c/em\u003e generated 554 bp or 797 bp band with primer pairs xiaomi4F/xiaomi4TR or xiaomi4R/xiaomi4TF, which were absent in DTHG (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). Furthermore, allelic analysis provided additional confirmation that \u003cem\u003exiaomi4\u003c/em\u003e is a novel allelic mutant of \u003cem\u003exiaomi\u003c/em\u003e, as all 9 individual F\u003csub\u003e1\u003c/sub\u003e plants and 165 F\u003csub\u003e2\u003c/sub\u003e plants from a cross between \u003cem\u003exiaomi4\u003c/em\u003e and \u003cem\u003exiaomi\u003c/em\u003e exhibited a \u003cem\u003exiaomi\u003c/em\u003e-like early heading phenotype.\u003c/p\u003e\u003cp\u003eGiven that \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e also displayed a \u003cem\u003exiaomi\u003c/em\u003e-like phenotype similar to \u003cem\u003exiaomi4\u003c/em\u003e, we suspected that these mutants were also \u003cem\u003exiaomi\u003c/em\u003e alleles. To test this hypothesis, we analyzed the genome resequencing data, and found a single nucleotide deletion in \u003cem\u003exiaomi3\u003c/em\u003e at the 1,348th nucleotide in the first exon of \u003cem\u003eSiPHYC\u003c/em\u003e, causing a frame shift mutation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea). In the \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e mutants, a transposon was inserted in the first exon at the 213th and 1453th nucleotide, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eb, S1c). These transposon insertions were further confirmed by PCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e\u003cp\u003eTo examine the effect of these \u003cem\u003eSiPHYC\u003c/em\u003e mutations on its expression, reverse transcription-PCR (RT-PCR) was performed. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e, there was no significant difference in \u003cem\u003eSiPHYC\u003c/em\u003e expression level between \u003cem\u003exiaomi3\u003c/em\u003e and the wild-type plants. However, no expression was detected in the three transposon insertion mutants, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ee).\u003c/p\u003e\u003cp\u003e \u003cb\u003eEffects of\u003c/b\u003e \u003cb\u003eSiPHYC\u003c/b\u003e \u003cb\u003emutation on photoperiod pathway gene expression in different accessions\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePreviously, we found that mutation of \u003cem\u003eSiPHYC\u003c/em\u003e dramatically altered expression of genes linked to photoperiodic pathway (Jingu21 background) (Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To gain a deeper understanding of the impact of the \u003cem\u003eSiPHYC\u003c/em\u003e mutation on gene expression and its interaction with the background, transcriptomic variations of the \u003cem\u003exiaomi\u003c/em\u003e alleles were analyzed using RNA-Seq approach. A total of 1048, 1489, and 4319 differentially expressed genes (DEGs) were identified between \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e, \u003cem\u003exiaomi6\u003c/em\u003e and their corresponding wild-types (Dataset 1). Among these DEGs, 19 were exhibited similar expression patterns in all the four \u003cem\u003exiaomi\u003c/em\u003e alleles, including well-characterized ortholog flowering time genes in other plants, such as \u003cem\u003eSiEhd1\u003c/em\u003e (\u003cem\u003eSi9g22570\u003c/em\u003e), \u003cem\u003eSiMADS14\u003c/em\u003e (\u003cem\u003eSi9g09160\u003c/em\u003e), \u003cem\u003eSiMADS15\u003c/em\u003e (\u003cem\u003eSi2g01630\u003c/em\u003e), \u003cem\u003eSiMADS18\u003c/em\u003e (\u003cem\u003eSi2g38170\u003c/em\u003e), \u003cem\u003eSiFTL2\u003c/em\u003e (\u003cem\u003eSi4g07330\u003c/em\u003e), and \u003cem\u003eSiFT9\u003c/em\u003e (\u003cem\u003eSi5g32220\u003c/em\u003e), which might be responsible for the extremely early heading phenotype of these \u003cem\u003exiaomi\u003c/em\u003e alleles (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, to verify RNA-Seq results and to understand the influence of background on gene expression, the expression level of six flowering time related genes, including \u003cem\u003eSiMADS14\u003c/em\u003e、\u003cem\u003eSiMADS18\u003c/em\u003e and \u003cem\u003eSiFT9\u003c/em\u003e mentioned above, were analyzed using RT-qPCR. Consistent to the RNA-Seq results, the expression of \u003cem\u003eSiPRR7\u003c/em\u003e (\u003cem\u003eSi2G43940\u003c/em\u003e) was downregulated, while the expression of the other five genes was upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Moreover, the expression levels of these genes vary among different \u003cem\u003exiaomi\u003c/em\u003e alleles, which might be responsible for variation of the heading date of the \u003cem\u003exiaomi\u003c/em\u003e alleles.\u003c/p\u003e\u003cp\u003e \u003cb\u003eGenome-wide development of InDels and SNPs in\u003c/b\u003e \u003cb\u003exiaomi\u003c/b\u003e \u003cb\u003ealleles\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMolecular markers, particularly InDels, are valuable resources for map-based cloning, marker-assisted breeding and germplasm genotyping. To identify molecular markers genome widely, we conducted genome re-sequencing of the \u003cem\u003exiaomi\u003c/em\u003e alleles with an average coverage depth of 30×. Molecular markers, including InDels and SNPs, were identified by comparing the re-sequencing data with the \u003cem\u003exiaomi\u003c/em\u003e reference genome. A total of 508235 InDels were detected in the genome of the four \u003cem\u003exiaomi\u003c/em\u003e alleles (Dataset 1). Of these InDels, 64171 located in upstream, 52792 were in downstream, 317622 were in intergenic regions, 66353 were in introns, 20496 were in exons and were in 14970 3' untranslated regions (UTR) and 9729 in 5' UTR (Dataset 2). Additionally, 3216261 SNPs were identified in these four \u003cem\u003exiaomi\u003c/em\u003e alleles, with 231609 in upstream, 201110 in downstream, 2310533 in the intergenic regions, 292563 in introns, 182078 in exons, 48794 in 3'UTR and 26937 in 5'UTR, respectively (Dataset 3).\u003c/p\u003e\u003cp\u003eTo facilitate the use of these InDels, we screened out high-quality homozygous InDels ranging from 14 to 200 bp in length. These variations could serve as promising candidates for designing molecular markers that can be easily examined through PCR and agarose gel electrophoresis. In total, we identified 37,682 InDels distributed across the 9 chromosomes of the \u003cem\u003exiaomi\u003c/em\u003e genome, with an average of 87.63 InDels per mega base (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003ea and Dataset 4). Among these InDels, 7452, 7136, 5358, and 4911 were unique to \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e, respectively. Only 1468 were shared by all the four \u003cem\u003exiaomi\u003c/em\u003e alleles (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). To validate the accuracy of the candidate InDel markers, we screened and designed 10 pairs of representative InDel marker primers based on their distribution on chromosomes (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All 10 pairs of primers successfully amplified specific bands and exhibited expected polymorphisms between the \u003cem\u003exiaomi\u003c/em\u003e alleles (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eb).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe utilization of diverse genetic backgrounds allows for a more comprehensive understanding of trait variation, gene discovery, and the elucidation of complex genetic interactions. Here, four novel \u003cem\u003exiaomi\u003c/em\u003e alleles (\u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e, and \u003cem\u003exiaomi6\u003c/em\u003e) were isolated from different genetic backgrounds and extensively characterized, providing valuable supplements to establish \u003cem\u003exiaomi\u003c/em\u003e as a C\u003csub\u003e4\u003c/sub\u003e model plant.\u003c/p\u003e \u003cp\u003eThe PHYC is a crucial photoreceptor for red and far-red light in plants and plays essential roles in photomorphogenesis. Our findings show that \u003cem\u003esiphyc\u003c/em\u003e mutants in foxtail millet flower approximately 2 months earlier than the wild-types under noninductive LD conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, see also Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang et al. 2022), indicating the \u003cem\u003eSiPHYC\u003c/em\u003e gene plays a significant role as a flowering time repressor and a determinator in foxtail millet under LD conditions. Notably, unlike \u003cem\u003eArabidopsis\u003c/em\u003e and rice \u003cem\u003ephyc\u003c/em\u003e mutants, which exhibit similar flowering time to the wild-type under inductive conditions (Monte et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Takano et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). \u003cem\u003exiaomi\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e and \u003cem\u003exiaomi5\u003c/em\u003e flowered even later than their corresponding wild-types under SD conditions. Furthermore, the plant height was also dramatically decreased in \u003cem\u003exiaomi\u003c/em\u003e alleles, while the number of tillers/ branches significantly increased in \u003cem\u003exiaomi\u003c/em\u003e alleles (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Yang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wang et al. 2022), which were not observed in either \u003cem\u003eArabidopsis\u003c/em\u003e or rice (Monte et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Takano et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These results suggested that the \u003cem\u003ePHYC\u003c/em\u003e gene may have different functions in flowering time regulation and photomorphogenesis in different species, although further verification of these conjectures is needed in the future.\u003c/p\u003e \u003cp\u003eIn rice, a facultative SD plant, multiple genes regulate the photoperiodic flowering pathway. Core genes in this pathway include \u003cem\u003eHeading date 1\u003c/em\u003e (\u003cem\u003eHd1\u003c/em\u003e) and \u003cem\u003eEarly heading date 1\u003c/em\u003e (\u003cem\u003eEhd1\u003c/em\u003e), \u003cem\u003eGrain number\u003c/em\u003e, \u003cem\u003eplant height\u003c/em\u003e, \u003cem\u003eand heading date 7\u003c/em\u003e (\u003cem\u003eGhd7\u003c/em\u003e), \u003cem\u003eDays to heading on chromosome8\u003c/em\u003e (\u003cem\u003eDTH8\u003c/em\u003e). \u003cem\u003eHd1\u003c/em\u003e is a homolog of \u003cem\u003eCONSTANS\u003c/em\u003e (\u003cem\u003eCO\u003c/em\u003e) in \u003cem\u003eArabidopsis\u003c/em\u003e, while \u003cem\u003eEhd1\u003c/em\u003e is a unique flowering time gene in rice without homologs in \u003cem\u003eArabidopsis\u003c/em\u003e (Doi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Under LD conditions, \u003cem\u003eHd1\u003c/em\u003e synergistically suppresses flowering with \u003cem\u003eGhd7\u003c/em\u003e or \u003cem\u003eGhd7\u003c/em\u003e-\u003cem\u003eDTH8\u003c/em\u003e, while under SD conditions, \u003cem\u003eHd1\u003c/em\u003e competes with the suppressor \u003cem\u003eGhd7\u003c/em\u003e, \u003cem\u003eDTH8\u003c/em\u003e, or \u003cem\u003eGhd7\u003c/em\u003e-\u003cem\u003eDTH8\u003c/em\u003e, to promote flowering (Sun et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The transcriptomic results revealed that the four \u003cem\u003exiaomi\u003c/em\u003e alleles shared 19 DEGs, including \u003cem\u003eSiEhd1\u003c/em\u003e, the homologue of \u003cem\u003eEhd1\u003c/em\u003e in rice, suggesting that \u003cem\u003eSiPHYC\u003c/em\u003e functions in photoperiodic flowering mainly through the \u003cem\u003eEhd1\u003c/em\u003e-dependent pathway. In addition to the well-characterized flowering time genes, there are several DEGs with unknown functions shared among the \u003cem\u003exiaomi\u003c/em\u003e alleles which might represent unique flowering time genes in foxtail millet and require further study to comprehensively understand the regulatory networks involved in the photoperiodic response in foxtail millet.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we have identified four novel \u003cem\u003exiaomi\u003c/em\u003e alleles in various genetic backgrounds. All of these mutants exhibited \u003cem\u003exiaomi\u003c/em\u003e-like early heading and miniature phenotypes, demonstrating their potential to establish an efficient indoor cultivation system. The phenotypes observed were caused by a single nucleotide deletion or transposon insertion in the \u003cem\u003eSiPHYC\u003c/em\u003e gene. These mutations resulted in the absence or frame-shift of \u003cem\u003eSiPHYC\u003c/em\u003e, which in turn affected the photoperiodic response of the mutants and leading to their early flowering. Additionally, genome-wide molecular markers, including InDels and SNPs, were identified in the \u003cem\u003exiaomi\u003c/em\u003e alleles, providing valuable resources for map-based cloning and marker-assisted breeding.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eXingchun Wang designed the experiments, coordinated the study, performed map-based cloning of the \u003cem\u003eXIAOMI4\u003c/em\u003e gene and wrote the manuscript. Meng Shan, Mengmeng Duan, Huimin Shen, Yujing Wang and Zhirong Yang characterized the \u003cem\u003exiaomi\u003c/em\u003e allele phenotype. Yiru Zhang and Xingchun Wang identified the \u003cem\u003exiaomi3\u003c/em\u003e mutant. Yuanhuai Han identified the \u003cem\u003exiaomi3\u003c/em\u003e mutant. Kai Zhao identified the \u003cem\u003exiaomi5\u003c/em\u003e and \u003cem\u003exiaomi6\u003c/em\u003e mutants. Xukai Li analyzed genome resequencing data and identified the InDels and SNPs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequence data have been deposited in the Beijing Institute of Genomics Data Center (https://bigd.big.ac.cn/) under the BioProject accession PRJCA022856.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThis work was financially supported by National Key R\u0026amp;D Program of China (2022YFC3400300, 2022YFC3400301), Shanxi Province Science and Technology Major Special Project (202101140601027), the Central Government Guides the Local Science and Technology Development Fund Project (YDZJSX2021B010), Fundamental Research Program of Shanxi Province (20210302123423, 20210302123385) and Graduate Research and Innovation Projects of Shanxi Province (2023KY319) and China Agriculture Research System of MOF and MARA (CARS-06-14.5-B8).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors have no competing interests to declare that are relevant to the content of this article\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003eThe manuscript has been seen and approved by all authors, and has not been submitted to anywhere else for consideration.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBennetzen JL, Schmutz J, Wang H, Percifield R, Hawkins J, Pontaroli AC, Estep M, Feng L, Vaughn JN, Grimwood J, Jenkins J, Barry K, Lindquist E, Hellsten U, Deshpande S, Wang X, Wu X, Mitros T, Triplett J, Yang X, Ye C, Mauro-Herrera M, Wang L, Li P, Sharma M, Sharma R, Ronald PC, Panaud O, Kellogg EA, Brutnell TP, Doust AN, Tuskan GA, Rokhsar D, Devos KM (2012) Reference genome sequence of the model plant\u003cem\u003e Setaria\u003c/em\u003e. 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In this paper, four novel \u003cem\u003exiaomi\u003c/em\u003e-like mutants, named \u003cem\u003exiaomi3\u003c/em\u003e, \u003cem\u003exiaomi4\u003c/em\u003e, \u003cem\u003exiaomi5\u003c/em\u003e, and \u003cem\u003exiaomi6\u003c/em\u003e, were identified and characterized in different genetic backgrounds. These mutants exhibited an extremely early heading phenotype, with heading occurring around 30-40 days after sowing under natural long-day conditions. Significant reductions in plant height, leaf length, leaf width, panicle length, and panicle diameter were observed in the mutants compared to their corresponding wild-types. Notably, these mutants displayed diverse panicle architectures and hull colors, effectively preventing seed mixing between them. Subsequent investigation under controlled short-day and long-day conditions confirmed the significant early heading phenotype of the mutants. Molecular characterization revealed mutations in the \u003cem\u003ePhytochrome C \u003c/em\u003e(\u003cem\u003eSiPHYC\u003c/em\u003e) gene, including transposon insertions and a frame shift mutation, were responsible for the extremely early heading phenotype. RNA-sequencing (RNA-Seq) analysis identified 19 differentially expressed genes associated with the extremely early heading phenotype. Additionally, genome-wide InDels and SNPs were identified, providing valuable resources for marker-assisted breeding and genetic studies. These findings advance our comprehension of the genetic and molecular mechanisms underlying \u003cem\u003eSiPHYC \u003c/em\u003emediated photoperiod flowering, and provide valuable resources that will push \u003cem\u003exiaomi \u003c/em\u003eas a C\u003csub\u003e4 \u003c/sub\u003emodel plant.\u003c/p\u003e","manuscriptTitle":"Identification and characterization of four novel xiaomi alleles to facilitate foxtail millet as a C4 model plant","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-30 07:54:59","doi":"10.21203/rs.3.rs-3869721/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revisions","date":"2024-02-04T02:35:03+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-01-25T10:08:36+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-25T02:25:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant Growth Regulation","date":"2024-01-25T00:06:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-19T17:07:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant Growth Regulation","date":"2024-01-18T19:38:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-growth-regulation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"grow","sideBox":"Learn more about [Plant Growth Regulation](https://www.springer.com/journal/10725)","snPcode":"10725","submissionUrl":"https://submission.nature.com/new-submission/10725/3","title":"Plant Growth Regulation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"940d237c-5f19-40bf-836b-819bd7367ac2","owner":[],"postedDate":"January 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-16T11:11:30+00:00","versionOfRecord":{"articleIdentity":"rs-3869721","link":"https://doi.org/10.1007/s10725-024-01134-0","journal":{"identity":"plant-growth-regulation","isVorOnly":false,"title":"Plant Growth Regulation"},"publishedOn":"2024-03-13 11:11:30","publishedOnDateReadable":"March 13th, 2024"},"versionCreatedAt":"2024-01-30 07:54:59","video":"","vorDoi":"10.1007/s10725-024-01134-0","vorDoiUrl":"https://doi.org/10.1007/s10725-024-01134-0","workflowStages":[]},"version":"v1","identity":"rs-3869721","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3869721","identity":"rs-3869721","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}