Transcriptomic and the Pectinase Gene Family analysis reveals a particular pathway on malformed tomato development

Transcriptomic and the Pectinase Gene Family analysis reveals a particular pathway on malformed tomato development | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Transcriptomic and the Pectinase Gene Family analysis reveals a particular pathway on malformed tomato development Junqin Wen, Chaofan Yan, Quanhui Li, Shubo Bi, Qiwen Zhong This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6365605/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Fruit malformation severely reduces the yield and quality of tomatoes, resulting in significant economic losses. However, the molecular mechanisms underlying malformed tomato fruit are far from being fully understood. Here, we first investigated the phenotypic characterization between the wild type "QT57" and the malformed fruit "QT2". Significant differences in flower organization were found. The expression of genes related to the CLAVATA-WUSCHEL pathway suggested that SlCRCa and SlCRCb are involved in the formation of QT2 misshapen fruits by acting in a compensatory manner. RNA-Seq analysis identified six pectinase genes as key candidate genes for misshapen fruit. They were significantly expressed and their expression was higher in "QT57" than in "QT2", suggesting a negative regulation of malformed fruit formation. Gene family analysis of pectinase genes was also performed. A total of 34 pectinase genes, including 6 PL, 15 PG and 13 PME genes, were used for in-depth bioinformatic analysis. We found that all genes except SlPL2 , SlPL11 and SlPG56-2 had gibberellin homeopathic effect elements; pectin lyase and pectin esterase were closely related and functioned in similar microenvironments. The results provide new insights into tomato fruit deformation. Transcriptomic analysis Malformed Pectinase gene Tomato Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Tomato ( Solanum lycopersicum L.) is an important vegetable crop worldwide with high yield, unique fruit flavor, rich nutrition and various edible ways [ 1 ]. Occurrences of catfacing fruits, a deformity that develops at the blossom end, often cause a huge loss in the market value of tomatoes [ 2 ]. The survey in the Shanghai, Jilin, Liaoning and other places of China, displaied that the incidence of malformed tomatoes was generally more than 20%, and the highest was 70–80% in winter and spring protection areas, seriously limited the quality and economic value of tomatoes [ 3 ]. Malformed tomato fruit is an important problem in tomato production. Malformed tomato fruit, this physiological defect is generally thought to be caused by unfavorable growing conditions, particularly the high and low temperature. The molecular mechanisms underlying malformed tomato fruit are of agronomic interest. Wu et al. [ 4 ] found that the transport of SlWUS in cell-to-cell was delayed reinstatement under cold stress, thus preventing the activation of SlCLV3 and TAG1 , resulting the interrupted feedback inhibition of SlWUS , and eventually leading to the expanded stem cell population and fruit malformation. Short-term high or low temperature reduced pollen germination of Strawberry plants and poor pollen germination correlated to high fruit malformation (Flower development and fruit malformation in strawberries after short-term exposure to high or low temperature). Plant hormones and ventricular number are also the effecting factors of fruit malformation. The application of exogenous NAA reduced endogenous hormone content by regulating the expression of differential genes YUCCA11 , YUCCA14 , GA2ox7 , and CKX4 , as well as down-regulating ARR expression, thus affecting stem meristem cell activity, resulting in lower tomato ventricles and malformation [ 4 ]. Knockdown of CYP735A , a key enzyme in cytokinin synthesis, reduced tomato deformity from 28.95–11.11% [ 5 ]. Sun et al. [ 6 ] identified 2 candidate genes involved in the number of floral organs and fruit ventricles by clv3 mutants. Tomato SlCRCa and SlCRCb operate as positive regulators of floral meristems determinacy by acting in a compensatory and partially redundant manner to safeguard the proper formation of flowers and fruits [ 7 ]. Pectinase is a complex of several enzymes including pectin lyase (PL), pectin methylesterase (PME) and polygalacturonase (PG), and play a major role in pollen development and tube elongation [ 8 , 9 , 10 , 11 ]. The inhibition of PL in Brassica pekinensis exhibited irregular and short pollen tubes, and abnormal accumulations near the pollen germination grooves were found [ 12 ]. Palusa et al. [ 13 ] found that all AtPLL genes were expressed in Arabidopsis thaliana flowers, and several AtPLL genes were highly expressed in pollen. Thirty PME were identified in tobacco and NtPME1 were confirmed preferentially expressed in the stigma and ovary and highly expressed in the pollen tube, and it exhibited collapsed pollen grains and damaged pollen tubes while silenced [ 14 ]. Tang et al. [ 15 ] found 81 PbrPMEs in pear, and the inhibition of PbrPME44 , PbrPME59 , and PbrPME11 resulted in the aberrant methyl esterification of pectin in the tip of pollen tubes, preventing the growth of pollen tube. OsFOR1 , a polygalacturonase inhibitory protein-coding gene (PGIP), increased the number of stamens, carpels, paleas/lemmas, stigmas, and scales when it suppressed [ 16 ]. The complete bioinformatics analysis of the PG genes has been conducted, but only preliminary analyses have been carried out for the PL and PME gene families, and the molecular mechanisms underlying malformed tomato fruit were developed around the CLAVATA-WUSCHEL pathway, however, availability of other regulatory pathways involved in deformed fruit are far from fully understood. Here, we investigated changes in the wild-type (WT) and malformed fruit with phenotypic characterization and transcriptomics, and pectinase genes whose expression might lead to malformed fruit were further analyzed. The study gives a particular focus on malformed tomato fruit mediated in pectinase genes, providing a novel insight into the malformation of fruit regulation. 2. Materials and methods 2.1 Plant material and growth conditions The tomato "Jindi363" ( Solanum lycopersicum L.), named "QT57", was used as wild-type (WT) for this study, and the malformed fruit was identified from tomato "1636", named "QT2". The tomato materials were preserved in Key Laboratory of Vegetable Genetics and Physiology of Qinghai University. The tomato plants were grown in Horticultural Innovation Base of Qinghai University with general field management. 2.2 Phenotypic characterization of tomato flowers and fruits The number of floral organs was evaluated in at least six flowers at anthesis stage in "QT57" and "QT2". Flower bud transverse diameter, bud longitudinal meridian, sepal number, petal number, stamen transverse diameter, stamen longitudinal meridian, ovary transverse diameter, style longitudinal and transverse, pollen tube transverse diameter and pollen tube longitudinal meridian were collected and used to calculate the average. Optical microscopy analyses were performed as described in Lozano et al.[ 17 ]. 2.3 RNA-seq analysis Tomato unopened flower buds (earlier than 8 d before anthesis), half- unopened flower buds (earlier than 4 d before anthesis), and fully-opened flowers were used to extract total RNA for expression detection. Three biological replicates were used for each sample, and five mixed samples were taken for each replicate. The same plants were not used for repeated sampling and a total of 18 samples were used for RNA-seq analysis with three replicates. Total RNA was extracted using Plant RNA Purifcation Reagent (Invitrogen, Carlsbad, USA), and qualified with NanoDrop 2000 (Thermo Scientific, USA). Qualified RNA samples were used to construct the cDNA library sequenced using llumina Novaseq 6000 platform (Ouyi Biological Company, Shanghai, China). The disembarking data was filtered by the fastp software [ 18 ], and then, the clean data were further mapped to the reference tomato ITAG3.1.0 SL3.1 genome using HISAT2 (v2.0.4, http://www.ccb.jhu.edu/software/hisat/index.shtml ). Differential expression analysis was performed using DESeq2 (v1.4.5, www.bioconductor.org/packages/release/bioc/html/ DESeq2.html) with q 2. Differentially expressed genes (DEGs) were further analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases based on the hypergeometric distribution algorithm to assess their functional enrichment. 2.4 qRT-PCR analyses The total RNA was extracted using TaKaRa MiniBEST Plant RNA Extraction Kit (TaKaRa, Shanghai, China). Quality and purity of RNA were checked using NanoDrop 2000 (Thermo Scientific, USA). qRT-PCR analysis was performed with Eppendorf real-time PCR machine (Hamburg, Germany) using ABI (Shanghai, China) TOROIVD ® qRT Master Mix (2 \(\:\times\:\) ) kits according to the manufacturer’s instructions. Relative gene expression levels were calculated using 2 −ΔΔCt method [ 19 ] and employing tomato actin as a standard. The cds sequences for qRT-PCR analysis were listed in Table S1 . 2.5 Bioinformatics analysis The gene IDs of Pectin lyase (PL), pectin methylesterase (PME) and polygalacturonase (PG) were obtained from the studies carried by Yang et al. [ 20 ], Jeong et al. [ 21 ], and Ke et al. [ 22 ]. Their protein sequences, CDS sequences, tomato genome CDS sequences and GFF3 annotation files were downloaded from the Ensembl Plants database ( https://plants.ensembl.org/index.html ). The chromosomal localisation was performed using TBtools. The MEME website ( https://meme-suite.org/meme/ ) was used to identify the conserved motifs of Pectinase genes with the number of motifs set to 12. The protein structural domain was predicted using the SMART website ( https://smart.embl.de/ ). To analysis the cis-acting elements in the promoter regions, the 2 kb upstream nucleotide sequences of PL, PME and PG genes were selected, and submitted to the online software Plant CARE ( http://bioinformatics.psb.ugent.be/webtools/plantcare/html ) through clicking ‘search for care’ to identify the promoters, and finally, TBtools was used to visualise the gene structures, protein structure domains and cis-acting elements with the Gene Structure View (Advanced) function. The ClustalW program with default parameters was performed to multiple sequence alignments, then the phylogenetic tree was constructed using Molecular Evolutionary Genetics Analysis (MEGA) software version 6.0 and Optimised by iTOL ( https://itol.embl.de/ ). Amino acid length, molecular weight, isoelectric point, instability coefficient, aliphatic amino acid index, and protein hydrophobicity analyses were performed on ExPASy ( https://www.expasy.org/ ). WoLF PSORT ( https://wolfpsort.hgc.jp ) software was applied for subcellular localization prediction. The secondary and tertiary structures of proteins were predicted with SWISS-MODEL ( https://swissmodel.expasy.org/ ) and SOPMA ( https://npsa.lyon.inserm.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html ), and STRING ( https://cn.string-db.org/ ) was used for protein network interactions analysis. 2.6 Subcellular localization subcellular localizations were assessed by fusing each protein to the green fluorescent protein (GFP). Thus, coding sequences were cloned into the PCAMBIA2300-GFP vector double digested with Sac Ⅰ and Xba Ⅰ using homologous recombination. Constructs were transformed in A. tumefaciens GV3101 strain and infiltrated into Nicothiana benthamiana leaves from 2- to 3-wk-old plants according to the procedure of Robertson [ 23 ]. Plants were kept in long-day (16 h : 8 h, light : dark) conditions at 22°C for two days, then, fluorescent signal was detected using a fluorescence microscope (Zeiss, Observer Z1, Germany). 3. Results 3.1 Morphological identification of deformed fruit The deformed flower bud was early characteristics for development of catfacing in tomato (Fig. 1 A). To understand the characteristics of deformed flower formation, the ten traits involved in "QT2" and "QT57" at 4 periods (initial bud stage: buds more conspicuous, length about 4mm; later bud stage: buds more conspicuous than initial bud stage, sepals not yet separated; bloom stage: sepals slightly separated, exposing petals and stamens, full bloom stage: petals fully unfolded, perpendicular to the style) in flower formation, as bud transverse diameter, bud longitudinal meridian, number of sepals, number of petals, stamen transverse diameter, stamen longitudinal meridian, ovary transverse diameter, style longitudinal and transverse, pollen tube transverse diameter, pollen tube longitudinal meridian, were further analysised (Fig. 1 B). The results showed that only the number of sepals and petals differed significantly between "QT2" and "QT57" at the primordial bud stage, with the mean number of sepals and petals being 5 in "QT57", while the mean number of "QT2" were 9 and 9.25, respectively. The differences in longitudinal diameter of buds, number of sepals and petals, transverse diameter of stamens, transverse diameter of ovary, transverse diameter of pollen tube, and longitudinal diameter of pollen tube at the post-bud stage were significant between the two varieties. The mean values of bud transverse diameter, sepal number, petal number, stamen transverse diameter, stamen longitudinal meridian, ovary transverse diameter, style longitudinal meridian, pollen tube transverse diameter and pollen tube longitudinal meridian at bract stage differed significantly between the two varieties, with the mean values of "QT57" being 3.10mm, 5.25, 5.75, 2.72mm, 7.77mm, 1.81mm, 6.19mm, 0.52mm, 4.52mm, while the mean values for "QT2" were 6.96mm, 10, 10.25, 6.72mm, 11.15mm, 4.71mm, 10.26mm, 2.45mm and 6.86mm, respectively. The differences between the "QT2" and "QT57" were significant for bud transverse diameter, bud longitudinal meridian, sepal number, petal number, stamen transverse diameter, ovary transverse diameter, pollen tube transverse diameter and pollen tube longitudinal meridian at full flowering. 3.2 Transcriptome sequencing analysis of malformed tomato fruit To investigate the molecular responses to malformed tomato fruit, tomato unopened flower buds (UP, earlier than 8 d before anthesis), half- unopened flower buds (HP, earlier than 4 d before anthesis), and fully-opened flowers (FP) of "QT57" (WT) and "QT2" (malformed fruit) were used for RNA-Seq analysis. The total raw and clean reads in each sample ranged from 44.36 to 53.35 Mb and 42.01 to 49.76 Mb, respectively. The Q30% was ranged from 94.68–95.33%, and the GC contents ranged from 42.8–43.82% (Table S2 ). Differentially expressed genes (DEG) were screened with the criterion of FDR 2. The 1133, 1115 and 2319 differential genes were up-regulated, and 1512, 1732 and 3256 genes were down-regulated in the three comparison groups of QT2_UP - vs - QT57_UP, QT2_HP - vs - QT57_HP and QT2_FP - vs - QT57_FP, respectively (Fig. 2 A; Fig. 2 C). Among them, 819 genes were co-expressed, and 3294, 687 and 939 genes were expressed only in QT2_UP - vs - QT57_UP, QT2_HP - vs - QT57_HP and QT2_FP - vs - QT57_FP, respectively (Fig. 2 A). The DEGs were functionally annotated to GO and KEGG pathways to assess their functional enrichment (Fig. 2 D; Fig. 2 E). The top 30 and top 20 entries with the most significant DEGs were subjected to GO and KEGG analysis in the "QT2" and "QT57" upon UP, HP and FP periods, respectively. The GO functional annotation showed that the differential genes were involved in a series of biological processes, mainly including chitin response, pollen ectoderm formation, sporopollen biosynthesis process, pollen tube growth regulation, defense responses and pectinolytic processes. The DEGs also played biological functions such as DNA-binding transcription factor activity, aldehyde oxidase activity, oxidoreductase activity, calmodulin binding, actin binding, and microtubule binding. The DEGs were also components of cell wall, cytoplasm plasma membrane and pollen tubes. The KEGG enrichment analysis indicated that DEGs were significantly enriched in the processes of phytohormone signalling, pentose and glucuronide interconversion, and MAPK signalling pathway, and 96, 53, and 28 differential genes were identified in the three KEGG pathways, respectively. Furthermore, 9, 19, and 3 differential genes were detected with |log 2 FC| > 2 in UP, HP and FP periods, respectively. 3.3 Expression analysis of differentially expressed genes The top 23 differential genes with |Log 2 FC| > 2 in the "QT2" and "QT57" upon UP, HP and FP periods were clustered, and 12 genes were down-regulated and 11 genes were up-regulated (Fig. 2 B). Furthermore, 16 candidate genes with differential expression related to phytohormones, pectinases, mitosis, elongation factors, FAS proteins, and disease-causing proteins were screened based on the KEGG analysis (Table S3 ). The expression of 16 candidate genes were analyzed using RNA-seq and qRT-PCR analysis (Fig. 3 C). The RNA-seq analysis was in accordance with qRT-PCR results. The MPK3 and LOC101257474 exhibited significantly expression in the"QT2" and "QT57" upon UP, HP and FP periods, the expression of MPK3 up-regulated by 0.25, 10.69 and 1.43-folds in "QT2" compared with "QT57", respectively, and the expression of LOC101257474 up-regulated by 4.22, 9.77 and 24.05-folds in malformed tomato fruit compared with "QT57", respectively. The expression of LOC101249702 and EREB in "QT2" was significantly higher than that of "QT57" under UP and FP periods, and the expression of LOC101268544 in "QT2" was significantly higher than that of "QT57" under HP and FP periods. Other than that, the rest of the 11 genes exhibited significantly higher expression in "QT57" than that of "QT2",they were hardly expressed in "QT2". Nine genes have been reported in tomato deformed fruit regulatory (Table S3 ), and their expression were detected to verify whether they are involved in the formation of "QT2" deformed fruits (Fig. 3 A; Fig. 3 B). The expression of SlCRCa up-regulated by 10.94 and 84.55-folds in "QT2" compared with "QT57" upon HP and FP periods, respectively. The SlCRCb was significantly differed from "QT2" and "QT57" upon UP and FP periods, with the relative expression of "QT57" being 1, and the relative expression of "QT2" being 35.96 and 34.1, respectively. SlWUS and SlTPL was only significantly expressed in the HP period. SlIMA exhibited significantly expression at UP, HP and FP periods in "QT2" and "QT57". The SlKNU , SlTAG1 and SlTAG1 significantly expressed in UP and FP periods, and the SlHDA1 significantly expressed in HP and FP periods. The expression of SlCLV3 up-regulated by 50-folds at UP period in deformed fruit "QT2". 3.4 Pectinase biosynthesis pathway involved in the formation of malformed tomato fruit Six pectinase genes, including LAT56 as PL gene, LOC101260471 , LOC101244677 , LOC101267809 , LAT59 as PME genes, and LOC101263150 as PG gene, were identified in the 16 candidate genes screened in the study, and they were significantly different in "QT2" and "QT57" upon UP, HP and FP periods. In addition to the above six pectinase genes, there were 28 genes that are specifically expressed in the flowers in the pectinase gene family (Table S4 ). Thus, we further detected the expression profile of 28 pectinase genes in our transcriptome data. The heat map analysis found that the 28 pectinase genes were all differential expressed, and of them, SlPG24-9 , SlPG24-1 , SlPG24-8 , SlPG15 , SlPG24-4 , SlPG17-2 , and SlPG24-6 , were highly expressed in aberrant flowers, and the remaining genes were highly expressed in normal flowers (Fig. 4 A). The qRT-PCR results showed that, among the 28 pectinase genes, 19 genes were significantly different in "QT2" and "QT57" upon UP, HP and FP periods, eight genes were significantly expressed in two periods, and one gene was significantly different in one period, suggesting the pectinase genes may be as key candidate genes involved in the regulation of deformed flower formation in tomato (Fig. 4 B). 3.5 Pectinase gene family identification A total of 34 pectinase genes, including six genes found in our study and 28 genes in previous study, were used for deeper bioinformatics analysis. Of the 34 genes, including 6 PLs, 15 PGs and 13 PMEs. The gene information of 34 genes were listed in Table S5 . 3.5.1 Chromosomal Localization Chromosomal Localization revealed that PL genes were distributed on chromosomes 2, 3, and 5, PME genes on chromosomes 1, 3, 5, 6, 7, and 12, and PG genes on chromosomes 2, 3, 4, 6, 7, 10, and 12. The chromosomes 8, 9, and 11 did not found pectinase genes (Fig. 5 A). 3.5.2 Protein physicochemical property analysis The results of the protein physicochemical properties showed that the number of amino acids of the PL gene ranged from 398 to 616, the molecular weights ranged from 44277.08 to 68766.17 Da, the isoelectric points ranged from 6.92 to 8.68, the coefficients of instability ranged from 29.52 to 36.22, the aliphatic indexes ranged from 72.54 to 84.32, and the average values of hydrophilicity ranged from − 0.446 to -0.264. The PME genes had an amino acid number of 102–652, a molecular weight of 11505.02-69716.4 Da, an isoelectric point of 5.22–9.32, an instability coefficient of 23.77–40.25, an aliphaticity index of 59.41–89.49, and a hydrophilicity average of -0.604 to -0.107. The amino acid number of PG genes was 246 ~ 467, the molecular weight was 27096.2 ~ 50954.28 Da, the isoelectric point was 5.9 ~ 9.19, the instability coefficient was 21.95 ~ 40.55, the aliphatic index was 78.14 ~ 95.89, and the hydrophilicity mean value was − 0.294 ~ 0.006 (Table S6 ). 3.5.3 Subcellular localization analysis Subcellular localization predicted that PL and PME genes were mostly distributed in the extracellular matrix, with a few in the cytoplasm, mitochondria, chloroplasts, vesicles and endoplasmic reticulum, and PG genes were mostly distributed in the nucleus, with a few in the vesicles, cytoplasm, and extracellular matrix. While experiments subsequently confirmed that SlPL7 was distributed in the nucleus, SolycPME9 was distributed in the cell membrane and endoplasmic reticulum, in general agreement with the predicted results (Fig. 5 B). 3.5.4 Protein structural analysis The results of secondary structure prediction showed that the α-helix, extended strand, β-turn, and irregular curl of PL genes ranged from 14.96 to 25.39%, 20.49 to 26.62%, 2.26 to 5.84%, and 48.21 to 58.1%, respectively (Table S7 ). The PME genes ranged between 13.73 and 41.23%, 14.88 and 25.73%, 4.2 and 7.84%, and 36.4 and 59.8%, respectively, and the PG genes ranged from 4.59 to 16.26%, 12.13 to 40.83%, 3.64 to 12.13% and 46.34 to 54.18%, respectively. The tertiary structure found that the α-helix and β-folding numbers of PL ranged from 8 to 14 and 31 to 51, respectively; the PME ranged from 5 to 22 and 8 to 37, respectively; and PG ranged from 3 to 9 and 23 to 43, respectively (Fig. 5 C). 3.5.5 Evolutionary analyses The evolutionary tree was constructed by removing one non-conserved sequence after multiple sequence comparison (Fig. 5 D). The results showed that. The evolutionary tree classified 33 genes into 4 classes, consisting of 10, 3, 2 and 18 genes, respectively. Among them, PG was classified into three taxa Ⅰ, Ⅱ, and Ⅲ, and PL and PME were classified in the Ⅳ taxa, which indicated that PL and PME were closely related and might have similar functions 3.5.6 Gene structure and promoter analyses The gene structure showed that PL genes characterized 3 to 13 exons and 2 to 12 introns, while PME genes featured 1 to 8 exons and 0 to 7 introns, and the exons and introns of PG ranged from 4 to 9 and 3 to 8, respectively. Twelve Motifs were identified using the MEME. PL genes consisted of Motif 12, Motif 7, Motif 4 and Motif 9, forming the Pec_lyase_N and Amb_all domains, and the PME genes consisted of Motif 8, Motif 9, Motif 1 and Motif 6, possessing the PMEI and Pectinesterase domains. PG genes contained PbH1 domain, specially including Motif 9, Motif 11, Motif 2, Motif 10, Motif 3, Motif 5, and Motif 7. The cis-acting promoter elements of pectinase genes could be divided into four categories. The first acting elements were related to hormone response, including GARE-motif, ABRE and TATC-box involved in gibberellin response, AuxRE, AuxRR-core and TGA-element in response to growth hormone, and CGTCA-motif in response to methyl jasmonate, and SARE in response to salicylate, respectively. The second category were some elements related to meristematic organisation, seed-specific regulation, chloroplast mesophyll cell differentiation and endosperm expression, such as CAT-box, RY-element, HD-Zip 1, GCN4_motif, and AACA_motif. The third category is related to low temperature, drought stress and anaerobic induction responsiveness, such asLTR, MBS, GC-motif and ARE. The fourth type elements were related to light responsiveness, such as MRE, ATC-motif, G-Box, ACE, Box II, AE-box, 3-AF1 binding site and CAG-motif (Fig. 5 E). 3.5.7 Protein network interaction analysis The results of protein network interactions showed (Fig. 5 F) that there were 98 pairs of protein interactions between PL and PME, of which SlPG15 had 16 pairs of interactions with other proteins, SlPL2 , SlPL4 , SlPL7 , and SlPL11 all had 11 pairs of interactions with other proteins, and SolycPME5 , SolycPME9 , and SolycPME42 , SolycPME47 , SolycPME79 , SlPG24-6 , and SlPG24-1 existed 10 pairs of interactions with other proteins, SlPL6 , SolycPME12 , SolycPME18 , and SolycPME48 existed 9 pairs of interactions with other proteins, and SolycPME40 and SlPG24-4 8 pairs of interactions with other proteins, SolycPME4 7 pairs of interactions with other proteins, SlPG24-9 6 pairs of interactions with other proteins, SlPL12 interactions with SlPG15 , SolycPME30 , SolycPME39 , SolycPME78 , SlPG38-1 , SlPG44 , SlPG24-8 , SlPG56-2 , SlPG56-3 , SlPG45 , SlPG17-2 , SlPG8 , SlPG38-2 , and SlPG36 were not interacting with other proteins. 4. Discussion Fruit malformation is a major constrain in fruit production worldwide resulting in substantial economic losses. The molecular mechanisms underlying malformed tomato fruit were developed around the CLAVATA-WUSCHEL pathway, however, availability of other regulatory pathways involved in deformed fruit are far from fully understood. Here, we first investigated phenotypic characterization between the wild-type "QT57" and malformed fruit "QT2". The significant differences in floral organisation were found, with deformed flowers mainly displaying characteristics such as large buds, many sepals and petals, and thick and irregular styles compared to normal flowers, and those phenotypics becoming more pronounced with the development of floral organs, suggesting that certain genes regulate the formation of deformed flowers, and consequently result in deformed fruits. Some of the genes that mediate the formation of malformed fruit by regulating carpel development have been reported. Tomato SlCRCa and SlCRCb positively regulated the floral meristems by acting in a compensatory and partially redundant manner, furthermore, SlCRCa and SlCRCb , SlIMA and SlKNU interact with SlHDA1 and SlTPL1 to form a chromatin remodelling complex that represses SlWUS expression to terminate floral stem cell activity once carpel primordia are initiated, finally, safeguarding the proper formation of flowers and fruits [ 7 ]. The delayed reinstatement of cell-to-cell transport of SlWUS prevented the activation of SlCLV3 and TAG1 , causing the interrupted feedback inhibition of SlWUS expression, leading to the expanded stem cell population and malformed fruits under cold stress [ 2 ]. To further verify whether the formation of "QT2" deformed fruit was regulated by the CLAVATA-WUSCHEL pathway genes reported in the studies of Castañeda [ 7 ] and Wu [ 2 ], nine genes were used for expression analysis in "QT57" and "QT2" under UP, HP and FP periods. The results showed that SlCRCa was expressed at high levels in "QT2" during the FP periods, whereas SlCRCb was expressed at high levels in "QT2" during the UP and HP periods. This is consistent with a compensatory mechanism reported in the study by Castañeda [ 7 ]. Thus, we suspected that SlCRCa and SlCRCb involved in the formation of "QT2" aberrant fruits by acting in a compensatory manner. Tomato unopened flower buds (UP, earlier than 8 d before anthesis), half- unopened flower buds (HP, earlier than 4 d before anthesis), and fully-opened flowers (FP) of "QT57" (WT) and "QT2" (malformed fruit) were used for RNA-Seq analysis to identify new regulatory pathways underlying malformed tomato fruit. The 1133, 1115 and 2319 up-regulated differential genes, and 1512, 1732 and 3256 down-regulated differential genes were identified using RNA-Seq analysis in UP, HP and FP periods, respectively. The number of down-regulated genes was all higher than the number of up-regulated genes, speculating that those down-regulated genes may play a key role in the formation of deformed fruit. Liu et al. [ 24 ] identified flowering and hormone-related DEGs underlying deformed flowers with the expression of most genes down-regulated in sugar apple, which was consistent with the results of this study. 16 key candidate genes were further found and analyzed using qRT-PCR analysis. The results found that 16 candidate genes were all significantly expressed between "QT57" and "QT2", suggesting they may be involved in the formation of "QT2" deformed fruit. Six pectinase genes, including LAT56 as PL gene, LOC101260471 , LOC101244677 , LOC101267809 , LAT59 as PME genes, and LOC101263150 as PG gene, were identified in the 16 candidate genes, and their expression in "QT57" was higher than in "QT2", suggesting negatively regulate of deformed fruit formation. six pectinase genes in the study were found to be specifically highly expressed in floral tissues [ 20 , 21 , 22 ], and the results of Jang et al. [ 16 ] and Li et al. [ 8 ] also confirmed that PG genes lead to fruit malformation by overexpression and silencing analysis. Pectinase genes are involved in the formation of malformed fruits in tomato, and the molecular mechanism on pectinase genes involved in deformed fruit are far from fully understood, therefore, pectinase was considered as key candidate genes for further gene family analysis. Promoter analysis revealed that all pectinase genes, except SlPL2 , SlPL11 and SlPG56-2 , have gibberellin homeopathic effect elements, suggesting gibberellin may influence pectinase gene expression and malformed fruits. Wu et al. [ 4 ] showed that the increase of gibberellin promoted the WUS gene expression, leading to an increase in the number of ventricles and the formation of malformed fruits. The results of Wu et al [ 4 ] indicated that the increase of ABA under short-term cold stress enhanced the accumulation of callus, while the application of exogenous GA could reduce the accumulation of callus, restore the intercellular movement of WUS, and lead to the normal development of the FM, reducing the fruit malformation. The phylogenetic tree classified the PL and PME genes into the same taxon, suggesting that they are closely related and play similar functions. The protein network interaction found a large number of interactions between pectinases, mainly enriched in the pectin catabolic process, carbohydrate metabolic process and pentose glucuronide interconversion pathway. Andrés et al. [ 25 ] found that nutrient decline altered the number of deformed fruits in coffee beans, suggesting that inhibition of the pectinase gene resulted in the inability to degrade pectin, leading to nutrient deficiencies in tomatoes, and consequently the formation of deformed fruits. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by funds from The Key Laboratory Project of Qinghai Science & Technology Department (Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources 2025), The Project of Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources (2024-SYS-06), and National Natural Science Foundation of China (No. 32460771). Author Contribution JQW and QWZ designed the experiments. CFY performed the experiments. JQW and CFY analyzed the data and wrote the paper. QHL and SBB revised the paper. All authors read and approved the final manuscript. Data Availability Data is provided within the manuscript or supplementary information files and RNA sequence data that support the findings of this study will be submitted to the NCBI sequence read archive (SRA) after manuscript acceptance. References Camejo G, Rodriguéz LM, Östergren LG, et al. W04-IS-001 Fatty acid-induced alterations of extracellular matrix proteoglycans may link insulin resistance and atherogenesis. Atherosclerosis (Supplements) (Component). 2005;6(1):16–16. Wu J, Sun W, Sun C, et al. Cold stress induces malformed tomato fruits by breaking the feedback loops of stem cell regulation in floral meristem. New Phytol. 2023;237(6):2268–83. Li TL. Comprehensive preventive measures for the deformed fruits of tomato with multiple centers in sunlight greenhouse. Rural Practical Eng Technol, 1999, (05): 12–3. Wu ZB. Mechanism analysis of growth hormone to alleviate the occurrence of multiventricular deformed fruits in tomato under low night temperature. Shenyang Agricultural University; 2022. Wu XL. Effect of Cytokinins on Tomato Multi-loculeMalformation Fruit. Shenyang Agricultural University; 2020. Sun MH. Gene analysis of fasciated locus regulating the loculenumber of tomato. Shenyang Agricultural University; 2020. Castañeda L, Giménez E, Pineda B, et al. Tomato CRABS CLAW paralogues interact with chromatin remodelling factors to mediate carpel development and floral determinacy. New Phytol. 2022;234(3):1059–74. Li H, Cao JS, Zhang AH, et al. The polygalacturonase gene BcMF2 from Brassica campestris is associated with intine development. J Exp Bot. 2009;60(1):301–13. Oskar M, Štefan J. Pectin methylesterases: sequence-structural features and phylogenetic relationships. Carbohydr Res. 2004;339(13):2281–95. Wakeley P, Rogers H, Rozycka M, et al. A maize pectin methylesterase-like gene, ZmC5 , specifically expressed in pollen. Plant Mol Biol. 1998;37:187–92. Louvet R, Cavel E, Gutierrez L, et al. Comprehensive expression profiling of the pectin methylesterase gene family during silique development in Arabidopsis thaliana . Planta. 2006;224:782–91. Jiang JJ, Yao LN, Yu YJ, et al. PECTATE LYASE-LIKE 9 from Brassica campestris is associated with intine formation. Plant Sci. 2014;229:66–75. Palusa SG, Golovkin M, Shin SB, et al. Organ-specific, developmental, hormonal and stress regulation of expression of putative pectate lyase genes in Arabidopsis . New Phytol. 2007;174:537–50. Lubini G, Ferreira PB, Quiapim AC, et al. Silencing of a Pectin Acetylesterase (PAE) Gene Highly Expressed in Tobacco Pistils Negatively Affects Pollen Tube Growth. Plants. 2023;12:329. Tang C, Zhu X, Qiao X, et al. Characterization of the pectin methyl-esterase gene family and its function in controlling pollen tube growth in pear ( Pyrus bretschneideri ). Genomics. 2020;112(3):2467–77. Jang S, Lee B, Kim C, et al. The OsFOR1 gene encodes a polygalacturonase-inhibiting protein (PGIP) that regulates floral organ number in rice. Plant Mol Biol. 2003;53:357–72. Lozano R, Angosto T, Gomez P, et al. Tomato flower abnormalities induced by low temperatures are associated with changes of expression of MADS-Box genes. Plant Physiol. 1998;117(1):91–100. Shifu C, Yanqing Z, Yaru C, et al. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884–90. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25(4):402–8. Yang L, Huang W, Xiong F, et al. Silencing of SlPL , which encodes a pectate lyase in tomato, confers enhanced fruit firmness, prolonged shelf-life and reduced susceptibility to grey mould. Plant Biotechnol J. 2017;15(12):1544–55. Jeong HY, Nguyen HP, Eom SH, et al. Integrative analysis of pectin methylesterase (PME) and PME inhibitors in tomato ( Solanum lycopersicum ): Identification, tissue-specific expression, and biochemical characterization. Plant Physiol Biochem. 2018;132:557–65. Ke X, Wang H, Li Y, et al. Genome-Wide Identification and Analysis of Polygalacturonase Genes in Solanum lycopersicum . Int J Mol Sci. 2018;19(8):2290. Robertson D. VIGS vectors for gene silencing: many targets, many tools. Annu Rev Plant Biol. 2004;55:495–519. Liu K, Li H, Li W, et al. Comparative transcriptomic analyses of normal and malformed flowers in sugar apple ( Annona squamosa L.) to identify the differential expressed genes between normal and malformed flowers. BMC Plant Biol. 2017;17:170. Andrés FL, José RRS, Luis CIQ, et al. Varying fruit loads modified leaf nutritional status, photosynthetic performance, and bean biochemical composition of coffee trees. Sci Hort. 2024;329:113005. Additional Declarations No competing interests reported. Supplementary Files FigureS1.docx TableS1.xlsx TableS2.xlsx TableS3.xlsx TableS4.xlsx TableS5.xlsx TableS6.xlsx TableS7.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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-6365605","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442111800,"identity":"ea66c638-e35e-4226-8016-39db5586ff4b","order_by":0,"name":"Junqin Wen","email":"","orcid":"","institution":"Academy of Agriculture and Forestry Sciences of Qinghai University (Qinghai Academy of Agriculture and Forestry Sciences), Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources","correspondingAuthor":false,"prefix":"","firstName":"Junqin","middleName":"","lastName":"Wen","suffix":""},{"id":442111801,"identity":"b0aadffe-040e-40f9-8283-c96069d0ee34","order_by":1,"name":"Chaofan Yan","email":"","orcid":"","institution":"Academy of Agriculture and Forestry Sciences of Qinghai University (Qinghai Academy of Agriculture and Forestry Sciences), Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources","correspondingAuthor":false,"prefix":"","firstName":"Chaofan","middleName":"","lastName":"Yan","suffix":""},{"id":442111802,"identity":"8edd4457-4b59-4514-811c-dc5e09ec66b3","order_by":2,"name":"Quanhui Li","email":"","orcid":"","institution":"Academy of Agriculture and Forestry Sciences of Qinghai University (Qinghai Academy of Agriculture and Forestry Sciences), Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources","correspondingAuthor":false,"prefix":"","firstName":"Quanhui","middleName":"","lastName":"Li","suffix":""},{"id":442111804,"identity":"a600105a-8b19-4a20-a3d7-d2a7c9077f54","order_by":3,"name":"Shubo Bi","email":"","orcid":"","institution":"Normal College for Nationalities, Qinghai Normal University","correspondingAuthor":false,"prefix":"","firstName":"Shubo","middleName":"","lastName":"Bi","suffix":""},{"id":442111805,"identity":"c99966f0-bc45-4de7-a752-dcf923b06296","order_by":4,"name":"Qiwen Zhong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACNv7mg4//GNTU298///BBQkUNYS18EseSDXgKjiUw3OBhNnhw5hhhLXIMOWYSPB+YQVrYJB+2MBPhMIYzZhISBmx5jLN7j1UkNrAx8Ld3J+DXwtxWbGFgIFPMLHMu7UbiDhkGiTNnNxCw5fDGGwkGbIxtDAlmNxLPsDEYSOQS0pJgIHHAgJmxB6ilILGNmRgtKUaSDQbMiTMkcswYiNMCDGRjBoNjxgY8x5IlEs4c4yHoF/l+YFQy/KmRM2BvPvjxR0WNHH97L34tGICHNOWjYBSMglEwCrACAP56SOgBpAEDAAAAAElFTkSuQmCC","orcid":"","institution":"Academy of Agriculture and Forestry Sciences of Qinghai University (Qinghai Academy of Agriculture and Forestry Sciences), Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources","correspondingAuthor":true,"prefix":"","firstName":"Qiwen","middleName":"","lastName":"Zhong","suffix":""}],"badges":[],"createdAt":"2025-04-03 03:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6365605/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6365605/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80575294,"identity":"8a79bd08-a5bc-4b10-9508-6f1ebe95e5ea","added_by":"auto","created_at":"2025-04-14 21:32:48","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":703003,"visible":true,"origin":"","legend":"\u003cp\u003ePhenotype and of flower buds in \"QT57\" and \"QT2\". A: Bud and fruit phenotypes at different time points, B: Bud phenotypic characteristics. Where, OB-Original bud stage; PB-Postbud stage; BS-Bud stage; PF-Pluminal stage; FBW-Flower bud transverse diameter (mm); FBL-Flower bud longitudinal meridian (mm); SN-Sepal number (no.); PN-Petal number (no.); SNW-Stamen transverse diameter (mm); SNL-Stamen longitudinal meridian (mm).); SNW-Stamen transverse diameter (mm); SNL-Stamen longitudinal meridian (mm); OW-Ovary transverse diameter (mm); OSL-Ostyle longitudinal meridian (mm); SEW-Pollen tube transverse diameter (mm); SEL-Pollen tube longitudinal meridian (mm).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/f970432cccb9bc022810e920.jpeg"},{"id":80576154,"identity":"a2ea4095-9b24-44e2-9f38-1f6ed8415e61","added_by":"auto","created_at":"2025-04-14 21:56:48","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":871678,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential gene screening. A: differential gene Wayne plots; B: differential gene expression level clustering analysis; C: differential gene volcano plots; D: GO functional annotation; E: KEGG functional annotation.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/799c17c1ddee94f55b837e60.jpeg"},{"id":80575583,"identity":"2faa2a1f-ff3a-40be-b627-dd86eae8c348","added_by":"auto","created_at":"2025-04-14 21:40:48","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1271686,"visible":true,"origin":"","legend":"\u003cp\u003eCandidate gene expression analysis. A: Transcriptome heatmap of the candidate genes and the nine genes in the studies by Castañeda et al. (2022) and Wu et al. (2022); B: RT-qPCR of the nine genes in the studies by Castañeda et al. (2022) and Wu et al. (2022); C: RT-qPCR of the candidate genes.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/2483f3ee7bbb52ed9afa15e3.jpeg"},{"id":80575305,"identity":"283f6524-9fea-4060-b138-d643880704e5","added_by":"auto","created_at":"2025-04-14 21:32:48","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":814055,"visible":true,"origin":"","legend":"\u003cp\u003ePectinase gene expression analysis. A: Heatmap of the pectinase gene transcriptome; B: RT-qPCR of the pectinase gene, where the red box is pectinolytic enzyme, the blue box is pectin esterase and the purple box is polygalacturonase.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/0f68a8d5649e0e5ffd671c54.jpeg"},{"id":80575806,"identity":"9e0edd94-bade-4b76-bb77-a5f94a3a9934","added_by":"auto","created_at":"2025-04-14 21:48:48","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1733378,"visible":true,"origin":"","legend":"\u003cp\u003eBioinformatics analysis of pectinases. A: chromosomal localisation; B: subcellular localisation, GFP for green fluorescence array, CHI for chloroplast autofluorescence array, DAPI for DAPI array (cytosolic staining), DIC for bright field and Merge for merged array; C: partial pectinase tertiary structure prediction, and all pectinase tertiary structures are shown in Figure S1; D: phylogenetic tree; E: prediction of gene structure, protein structural domains and cis-acting elements; F: protein network interactions.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/c0a00faceb13ec8997892a6b.jpeg"},{"id":81963184,"identity":"f1779b62-7713-4ab3-bba4-e2f68799e6da","added_by":"auto","created_at":"2025-05-05 11:16:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6241161,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/e5c1287e-c176-4a35-8be4-ab72b3801ba0.pdf"},{"id":80575296,"identity":"b7b4ddf6-3b0c-46a6-b0d1-89ac115d137a","added_by":"auto","created_at":"2025-04-14 21:32:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":202216,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/f4037d2760ec321e65ed86da.docx"},{"id":80575299,"identity":"4efbf8b5-de4e-42ae-b3f2-800cfe852a5e","added_by":"auto","created_at":"2025-04-14 21:32:48","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34886,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/348590cd411c632287c63164.xlsx"},{"id":80575581,"identity":"69050056-a9c7-4e01-b215-2a12ff5ffdb0","added_by":"auto","created_at":"2025-04-14 21:40:48","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11578,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/39ca4dd23d77031616dc2b55.xlsx"},{"id":80575807,"identity":"b20943d5-e336-4569-aac8-8a5801771a19","added_by":"auto","created_at":"2025-04-14 21:48:48","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":12999,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/97594eee5dbfe91be7636034.xlsx"},{"id":80575301,"identity":"b657b41d-6fa0-4d21-ae8f-c7bfb7e0bd46","added_by":"auto","created_at":"2025-04-14 21:32:48","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11476,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/799dd61b7a5368f7bef75b55.xlsx"},{"id":80575586,"identity":"598fb584-448b-49be-8d59-97881887b633","added_by":"auto","created_at":"2025-04-14 21:40:48","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":43118,"visible":true,"origin":"","legend":"","description":"","filename":"TableS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/17344bef714ca6899b06304c.xlsx"},{"id":80575808,"identity":"83495630-bfeb-4223-b6ce-c8d059bb66cf","added_by":"auto","created_at":"2025-04-14 21:48:49","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":12996,"visible":true,"origin":"","legend":"","description":"","filename":"TableS6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/97ff91307889097c8d8f6f4b.xlsx"},{"id":80575322,"identity":"bc94f731-acbf-4929-a35e-c9bac6649249","added_by":"auto","created_at":"2025-04-14 21:32:49","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":12140,"visible":true,"origin":"","legend":"","description":"","filename":"TableS7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6365605/v1/08ce4f2178dd1fc748237c56.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transcriptomic and the Pectinase Gene Family analysis reveals a particular pathway on malformed tomato development","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTomato (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e L.) is an important vegetable crop worldwide with high yield, unique fruit flavor, rich nutrition and various edible ways [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Occurrences of catfacing fruits, a deformity that develops at the blossom end, often cause a huge loss in the market value of tomatoes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The survey in the Shanghai, Jilin, Liaoning and other places of China, displaied that the incidence of malformed tomatoes was generally more than 20%, and the highest was 70\u0026ndash;80% in winter and spring protection areas, seriously limited the quality and economic value of tomatoes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Malformed tomato fruit is an important problem in tomato production.\u003c/p\u003e \u003cp\u003eMalformed tomato fruit, this physiological defect is generally thought to be caused by unfavorable growing conditions, particularly the high and low temperature. The molecular mechanisms underlying malformed tomato fruit are of agronomic interest. Wu et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] found that the transport of \u003cem\u003eSlWUS\u003c/em\u003e in cell-to-cell was delayed reinstatement under cold stress, thus preventing the activation of \u003cem\u003eSlCLV3\u003c/em\u003e and \u003cem\u003eTAG1\u003c/em\u003e, resulting the interrupted feedback inhibition of \u003cem\u003eSlWUS\u003c/em\u003e, and eventually leading to the expanded stem cell population and fruit malformation. Short-term high or low temperature reduced pollen germination of Strawberry plants and poor pollen germination correlated to high fruit malformation (Flower development and fruit malformation in strawberries after short-term exposure to high or low temperature).\u003c/p\u003e \u003cp\u003ePlant hormones and ventricular number are also the effecting factors of fruit malformation. The application of exogenous NAA reduced endogenous hormone content by regulating the expression of differential genes \u003cem\u003eYUCCA11\u003c/em\u003e, \u003cem\u003eYUCCA14\u003c/em\u003e, \u003cem\u003eGA2ox7\u003c/em\u003e, and \u003cem\u003eCKX4\u003c/em\u003e, as well as down-regulating \u003cem\u003eARR\u003c/em\u003e expression, thus affecting stem meristem cell activity, resulting in lower tomato ventricles and malformation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Knockdown of \u003cem\u003eCYP735A\u003c/em\u003e, a key enzyme in cytokinin synthesis, reduced tomato deformity from 28.95\u0026ndash;11.11% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Sun et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] identified 2 candidate genes involved in the number of floral organs and fruit ventricles by \u003cem\u003eclv3\u003c/em\u003e mutants. Tomato \u003cem\u003eSlCRCa\u003c/em\u003e and \u003cem\u003eSlCRCb\u003c/em\u003e operate as positive regulators of floral meristems determinacy by acting in a compensatory and partially redundant manner to safeguard the proper formation of flowers and fruits [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePectinase is a complex of several enzymes including pectin lyase (PL), pectin methylesterase (PME) and polygalacturonase (PG), and play a major role in pollen development and tube elongation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The inhibition of PL in \u003cem\u003eBrassica pekinensis\u003c/em\u003e exhibited irregular and short pollen tubes, and abnormal accumulations near the pollen germination grooves were found [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Palusa et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] found that all \u003cem\u003eAtPLL\u003c/em\u003e genes were expressed in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e flowers, and several \u003cem\u003eAtPLL\u003c/em\u003e genes were highly expressed in pollen. Thirty PME were identified in tobacco and \u003cem\u003eNtPME1\u003c/em\u003e were confirmed preferentially expressed in the stigma and ovary and highly expressed in the pollen tube, and it exhibited collapsed pollen grains and damaged pollen tubes while silenced [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Tang et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] found 81 \u003cem\u003ePbrPMEs\u003c/em\u003e in pear, and the inhibition of \u003cem\u003ePbrPME44\u003c/em\u003e, \u003cem\u003ePbrPME59\u003c/em\u003e, and \u003cem\u003ePbrPME11\u003c/em\u003e resulted in the aberrant methyl esterification of pectin in the tip of pollen tubes, preventing the growth of pollen tube. \u003cem\u003eOsFOR1\u003c/em\u003e, a polygalacturonase inhibitory protein-coding gene (PGIP), increased the number of stamens, carpels, paleas/lemmas, stigmas, and scales when it suppressed [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe complete bioinformatics analysis of the PG genes has been conducted, but only preliminary analyses have been carried out for the PL and PME gene families, and the molecular mechanisms underlying malformed tomato fruit were developed around the CLAVATA-WUSCHEL pathway, however, availability of other regulatory pathways involved in deformed fruit are far from fully understood. Here, we investigated changes in the wild-type (WT) and malformed fruit with phenotypic characterization and transcriptomics, and pectinase genes whose expression might lead to malformed fruit were further analyzed. The study gives a particular focus on malformed tomato fruit mediated in pectinase genes, providing a novel insight into the malformation of fruit regulation.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Plant material and growth conditions\u003c/h2\u003e \u003cp\u003eThe tomato \"Jindi363\" (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e L.), named \"QT57\", was used as wild-type (WT) for this study, and the malformed fruit was identified from tomato \"1636\", named \"QT2\". The tomato materials were preserved in Key Laboratory of Vegetable Genetics and Physiology of Qinghai University. The tomato plants were grown in Horticultural Innovation Base of Qinghai University with general field management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 \u003cem\u003ePhenotypic characterization of tomato flowers and fruits\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe number of floral organs was evaluated in at least six flowers at anthesis stage in \"QT57\" and \"QT2\". Flower bud transverse diameter, bud longitudinal meridian, sepal number, petal number, stamen transverse diameter, stamen longitudinal meridian, ovary transverse diameter, style longitudinal and transverse, pollen tube transverse diameter and pollen tube longitudinal meridian were collected and used to calculate the average. Optical microscopy analyses were performed as described in Lozano et al.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.3 RNA-seq\u003c/em\u003e analysis\u003c/h2\u003e \u003cp\u003eTomato unopened flower buds (earlier than 8 d before anthesis), half- unopened flower buds (earlier than 4 d before anthesis), and fully-opened flowers were used to extract total RNA for expression detection. Three biological replicates were used for each sample, and five mixed samples were taken for each replicate. The same plants were not used for repeated sampling and a total of 18 samples were used for RNA-seq analysis with three replicates.\u003c/p\u003e \u003cp\u003eTotal RNA was extracted using Plant RNA Purifcation Reagent (Invitrogen, Carlsbad, USA), and qualified with NanoDrop 2000 (Thermo Scientific, USA). Qualified RNA samples were used to construct the cDNA library sequenced using llumina Novaseq 6000 platform (Ouyi Biological Company, Shanghai, China). The disembarking data was filtered by the fastp software [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and then, the clean data were further mapped to the reference tomato ITAG3.1.0 SL3.1 genome using HISAT2 (v2.0.4, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ccb.jhu.edu/software/hisat/index.shtml\u003c/span\u003e\u003cspan address=\"http://www.ccb.jhu.edu/software/hisat/index.shtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Differential expression analysis was performed using DESeq2 (v1.4.5, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.bioconductor.org/packages/release/bioc/html/\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.bioconductor.org/packages/release/bioc/html/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e DESeq2.html) with q\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log\u003csub\u003e2\u003c/sub\u003eFC|\u0026gt;2. Differentially expressed genes (DEGs) were further analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases based on the hypergeometric distribution algorithm to assess their functional enrichment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 qRT-PCR analyses\u003c/h2\u003e \u003cp\u003eThe total RNA was extracted using TaKaRa MiniBEST Plant RNA Extraction Kit (TaKaRa, Shanghai, China). Quality and purity of RNA were checked using NanoDrop 2000 (Thermo Scientific, USA). qRT-PCR analysis was performed with Eppendorf real-time PCR machine (Hamburg, Germany) using ABI (Shanghai, China) TOROIVD \u0026reg; qRT Master Mix (2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\)\u003c/span\u003e\u003c/span\u003e) kits according to the manufacturer\u0026rsquo;s instructions. Relative gene expression levels were calculated using 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and employing tomato \u003cem\u003eactin\u003c/em\u003e as a standard. The cds sequences for qRT-PCR analysis were listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.5 Bioinformatics analysis\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe gene IDs of Pectin lyase (PL), pectin methylesterase (PME) and polygalacturonase (PG) were obtained from the studies carried by Yang et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Jeong et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and Ke et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Their protein sequences, CDS sequences, tomato genome CDS sequences and GFF3 annotation files were downloaded from the Ensembl Plants database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://plants.ensembl.org/index.html\u003c/span\u003e\u003cspan address=\"https://plants.ensembl.org/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The chromosomal localisation was performed using TBtools. The MEME website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://meme-suite.org/meme/\u003c/span\u003e\u003cspan address=\"https://meme-suite.org/meme/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to identify the conserved motifs of \u003cem\u003ePectinase\u003c/em\u003e genes with the number of motifs set to 12. The protein structural domain was predicted using the SMART website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://smart.embl.de/\u003c/span\u003e\u003cspan address=\"https://smart.embl.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To analysis the cis-acting elements in the promoter regions, the 2 kb upstream nucleotide sequences of PL, PME and PG genes were selected, and submitted to the online software Plant CARE (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.psb.ugent.be/webtools/plantcare/html\u003c/span\u003e\u003cspan address=\"http://bioinformatics.psb.ugent.be/webtools/plantcare/html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) through clicking \u0026lsquo;search for care\u0026rsquo; to identify the promoters, and finally, TBtools was used to visualise the gene structures, protein structure domains and cis-acting elements with the Gene Structure View (Advanced) function. The ClustalW program with default parameters was performed to multiple sequence alignments, then the phylogenetic tree was constructed using Molecular Evolutionary Genetics Analysis (MEGA) software version 6.0 and Optimised by iTOL (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://itol.embl.de/\u003c/span\u003e\u003cspan address=\"https://itol.embl.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Amino acid length, molecular weight, isoelectric point, instability coefficient, aliphatic amino acid index, and protein hydrophobicity analyses were performed on ExPASy (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.expasy.org/\u003c/span\u003e\u003cspan address=\"https://www.expasy.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). WoLF PSORT (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://wolfpsort.hgc.jp\u003c/span\u003e\u003cspan address=\"https://wolfpsort.hgc.jp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) software was applied for subcellular localization prediction. The secondary and tertiary structures of proteins were predicted with SWISS-MODEL (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://swissmodel.expasy.org/\u003c/span\u003e\u003cspan address=\"https://swissmodel.expasy.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and SOPMA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://npsa.lyon.inserm.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html\u003c/span\u003e\u003cspan address=\"https://npsa.lyon.inserm.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and STRING (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org/\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for protein network interactions analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.6 Subcellular localization\u003c/em\u003e\u003c/h2\u003e \u003cp\u003esubcellular localizations were assessed by fusing each protein to the green fluorescent protein (GFP). Thus, coding sequences were cloned into the PCAMBIA2300-GFP vector double digested with \u003cem\u003eSac\u003c/em\u003eⅠ and \u003cem\u003eXba\u003c/em\u003eⅠ using homologous recombination. Constructs were transformed in A. tumefaciens GV3101 strain and infiltrated into Nicothiana benthamiana leaves from 2- to 3-wk-old plants according to the procedure of Robertson [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Plants were kept in long-day (16 h : 8 h, light : dark) conditions at 22\u0026deg;C for two days, then, fluorescent signal was detected using a fluorescence microscope (Zeiss, Observer Z1, Germany).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Morphological identification of deformed fruit\u003c/h2\u003e \u003cp\u003eThe deformed flower bud was early characteristics for development of catfacing in tomato (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). To understand the characteristics of deformed flower formation, the ten traits involved in \"QT2\" and \"QT57\" at 4 periods (initial bud stage: buds more conspicuous, length about 4mm; later bud stage: buds more conspicuous than initial bud stage, sepals not yet separated; bloom stage: sepals slightly separated, exposing petals and stamens, full bloom stage: petals fully unfolded, perpendicular to the style) in flower formation, as bud transverse diameter, bud longitudinal meridian, number of sepals, number of petals, stamen transverse diameter, stamen longitudinal meridian, ovary transverse diameter, style longitudinal and transverse, pollen tube transverse diameter, pollen tube longitudinal meridian, were further analysised (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The results showed that only the number of sepals and petals differed significantly between \"QT2\" and \"QT57\" at the primordial bud stage, with the mean number of sepals and petals being 5 in \"QT57\", while the mean number of \"QT2\" were 9 and 9.25, respectively. The differences in longitudinal diameter of buds, number of sepals and petals, transverse diameter of stamens, transverse diameter of ovary, transverse diameter of pollen tube, and longitudinal diameter of pollen tube at the post-bud stage were significant between the two varieties. The mean values of bud transverse diameter, sepal number, petal number, stamen transverse diameter, stamen longitudinal meridian, ovary transverse diameter, style longitudinal meridian, pollen tube transverse diameter and pollen tube longitudinal meridian at bract stage differed significantly between the two varieties, with the mean values of \"QT57\" being 3.10mm, 5.25, 5.75, 2.72mm, 7.77mm, 1.81mm, 6.19mm, 0.52mm, 4.52mm, while the mean values for \"QT2\" were 6.96mm, 10, 10.25, 6.72mm, 11.15mm, 4.71mm, 10.26mm, 2.45mm and 6.86mm, respectively. The differences between the \"QT2\" and \"QT57\" were significant for bud transverse diameter, bud longitudinal meridian, sepal number, petal number, stamen transverse diameter, ovary transverse diameter, pollen tube transverse diameter and pollen tube longitudinal meridian at full flowering.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Transcriptome sequencing analysis of malformed tomato fruit\u003c/h2\u003e \u003cp\u003eTo investigate the molecular responses to malformed tomato fruit, tomato unopened flower buds (UP, earlier than 8 d before anthesis), half- unopened flower buds (HP, earlier than 4 d before anthesis), and fully-opened flowers (FP) of \"QT57\" (WT) and \"QT2\" (malformed fruit) were used for RNA-Seq analysis. The total raw and clean reads in each sample ranged from 44.36 to 53.35 Mb and 42.01 to 49.76 Mb, respectively. The Q30% was ranged from 94.68\u0026ndash;95.33%, and the GC contents ranged from 42.8\u0026ndash;43.82% (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferentially expressed genes (DEG) were screened with the criterion of FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log\u003csub\u003e2\u003c/sub\u003eFC| \u0026gt; 2. The 1133, 1115 and 2319 differential genes were up-regulated, and 1512, 1732 and 3256 genes were down-regulated in the three comparison groups of QT2_UP - vs - QT57_UP, QT2_HP - vs - QT57_HP and QT2_FP - vs - QT57_FP, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Among them, 819 genes were co-expressed, and 3294, 687 and 939 genes were expressed only in QT2_UP - vs - QT57_UP, QT2_HP - vs - QT57_HP and QT2_FP - vs - QT57_FP, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eThe DEGs were functionally annotated to GO and KEGG pathways to assess their functional enrichment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). The top 30 and top 20 entries with the most significant DEGs were subjected to GO and KEGG analysis in the \"QT2\" and \"QT57\" upon UP, HP and FP periods, respectively. The GO functional annotation showed that the differential genes were involved in a series of biological processes, mainly including chitin response, pollen ectoderm formation, sporopollen biosynthesis process, pollen tube growth regulation, defense responses and pectinolytic processes. The DEGs also played biological functions such as DNA-binding transcription factor activity, aldehyde oxidase activity, oxidoreductase activity, calmodulin binding, actin binding, and microtubule binding. The DEGs were also components of cell wall, cytoplasm plasma membrane and pollen tubes. The KEGG enrichment analysis indicated that DEGs were significantly enriched in the processes of phytohormone signalling, pentose and glucuronide interconversion, and MAPK signalling pathway, and 96, 53, and 28 differential genes were identified in the three KEGG pathways, respectively. Furthermore, 9, 19, and 3 differential genes were detected with |log\u003csub\u003e2\u003c/sub\u003eFC| \u0026gt; 2 in UP, HP and FP periods, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Expression analysis of differentially expressed genes\u003c/h2\u003e \u003cp\u003eThe top 23 differential genes with |Log\u003csub\u003e2\u003c/sub\u003eFC| \u0026gt; 2 in the \"QT2\" and \"QT57\" upon UP, HP and FP periods were clustered, and 12 genes were down-regulated and 11 genes were up-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Furthermore, 16 candidate genes with differential expression related to phytohormones, pectinases, mitosis, elongation factors, FAS proteins, and disease-causing proteins were screened based on the KEGG analysis (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe expression of 16 candidate genes were analyzed using RNA-seq and qRT-PCR analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The RNA-seq analysis was in accordance with qRT-PCR results. The \u003cem\u003eMPK3\u003c/em\u003e and \u003cem\u003eLOC101257474\u003c/em\u003e exhibited significantly expression in the\"QT2\" and \"QT57\" upon UP, HP and FP periods, the expression of \u003cem\u003eMPK3\u003c/em\u003e up-regulated by 0.25, 10.69 and 1.43-folds in \"QT2\" compared with \"QT57\", respectively, and the expression of \u003cem\u003eLOC101257474\u003c/em\u003e up-regulated by 4.22, 9.77 and 24.05-folds in malformed tomato fruit compared with \"QT57\", respectively. The expression of \u003cem\u003eLOC101249702\u003c/em\u003e and \u003cem\u003eEREB\u003c/em\u003e in \"QT2\" was significantly higher than that of \"QT57\" under UP and FP periods, and the expression of \u003cem\u003eLOC101268544\u003c/em\u003e in \"QT2\" was significantly higher than that of \"QT57\" under HP and FP periods. Other than that, the rest of the 11 genes exhibited significantly higher expression in \"QT57\" than that of \"QT2\",they were hardly expressed in \"QT2\".\u003c/p\u003e \u003cp\u003eNine genes have been reported in tomato deformed fruit regulatory (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e), and their expression were detected to verify whether they are involved in the formation of \"QT2\" deformed fruits (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The expression of \u003cem\u003eSlCRCa\u003c/em\u003e up-regulated by 10.94 and 84.55-folds in \"QT2\" compared with \"QT57\" upon HP and FP periods, respectively. The \u003cem\u003eSlCRCb\u003c/em\u003e was significantly differed from \"QT2\" and \"QT57\" upon UP and FP periods, with the relative expression of \"QT57\" being 1, and the relative expression of \"QT2\" being 35.96 and 34.1, respectively. \u003cem\u003eSlWUS\u003c/em\u003e and \u003cem\u003eSlTPL\u003c/em\u003e was only significantly expressed in the HP period. \u003cem\u003eSlIMA\u003c/em\u003e exhibited significantly expression at UP, HP and FP periods in \"QT2\" and \"QT57\". The \u003cem\u003eSlKNU\u003c/em\u003e, \u003cem\u003eSlTAG1\u003c/em\u003e and \u003cem\u003eSlTAG1\u003c/em\u003e significantly expressed in UP and FP periods, and the \u003cem\u003eSlHDA1\u003c/em\u003e significantly expressed in HP and FP periods. The expression of \u003cem\u003eSlCLV3\u003c/em\u003e up-regulated by 50-folds at UP period in deformed fruit \"QT2\".\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Pectinase biosynthesis pathway involved in the formation of malformed tomato fruit\u003c/h2\u003e \u003cp\u003eSix pectinase genes, including \u003cem\u003eLAT56\u003c/em\u003e as PL gene, \u003cem\u003eLOC101260471\u003c/em\u003e, \u003cem\u003eLOC101244677\u003c/em\u003e, \u003cem\u003eLOC101267809\u003c/em\u003e, \u003cem\u003eLAT59\u003c/em\u003e as PME genes, and \u003cem\u003eLOC101263150\u003c/em\u003e as PG gene, were identified in the 16 candidate genes screened in the study, and they were significantly different in \"QT2\" and \"QT57\" upon UP, HP and FP periods. In addition to the above six pectinase genes, there were 28 genes that are specifically expressed in the flowers in the pectinase gene family (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). Thus, we further detected the expression profile of 28 pectinase genes in our transcriptome data. The heat map analysis found that the 28 pectinase genes were all differential expressed, and of them, \u003cem\u003eSlPG24-9\u003c/em\u003e, \u003cem\u003eSlPG24-1\u003c/em\u003e, \u003cem\u003eSlPG24-8\u003c/em\u003e, \u003cem\u003eSlPG15\u003c/em\u003e, \u003cem\u003eSlPG24-4\u003c/em\u003e, \u003cem\u003eSlPG17-2\u003c/em\u003e, and \u003cem\u003eSlPG24-6\u003c/em\u003e, were highly expressed in aberrant flowers, and the remaining genes were highly expressed in normal flowers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The qRT-PCR results showed that, among the 28 pectinase genes, 19 genes were significantly different in \"QT2\" and \"QT57\" upon UP, HP and FP periods, eight genes were significantly expressed in two periods, and one gene was significantly different in one period, suggesting the pectinase genes may be as key candidate genes involved in the regulation of deformed flower formation in tomato (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Pectinase gene family identification\u003c/h2\u003e \u003cp\u003eA total of 34 pectinase genes, including six genes found in our study and 28 genes in previous study, were used for deeper bioinformatics analysis. Of the 34 genes, including 6 PLs, 15 PGs and 13 PMEs. The gene information of 34 genes were listed in Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1 Chromosomal Localization\u003c/h2\u003e \u003cp\u003eChromosomal Localization revealed that PL genes were distributed on chromosomes 2, 3, and 5, PME genes on chromosomes 1, 3, 5, 6, 7, and 12, and PG genes on chromosomes 2, 3, 4, 6, 7, 10, and 12. The chromosomes 8, 9, and 11 did not found pectinase genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2 Protein physicochemical property analysis\u003c/h2\u003e \u003cp\u003eThe results of the protein physicochemical properties showed that the number of amino acids of the PL gene ranged from 398 to 616, the molecular weights ranged from 44277.08 to 68766.17 Da, the isoelectric points ranged from 6.92 to 8.68, the coefficients of instability ranged from 29.52 to 36.22, the aliphatic indexes ranged from 72.54 to 84.32, and the average values of hydrophilicity ranged from \u0026minus;\u0026thinsp;0.446 to -0.264. The PME genes had an amino acid number of 102\u0026ndash;652, a molecular weight of 11505.02-69716.4 Da, an isoelectric point of 5.22\u0026ndash;9.32, an instability coefficient of 23.77\u0026ndash;40.25, an aliphaticity index of 59.41\u0026ndash;89.49, and a hydrophilicity average of -0.604 to -0.107. The amino acid number of PG genes was 246\u0026thinsp;~\u0026thinsp;467, the molecular weight was 27096.2\u0026thinsp;~\u0026thinsp;50954.28 Da, the isoelectric point was 5.9\u0026thinsp;~\u0026thinsp;9.19, the instability coefficient was 21.95\u0026thinsp;~\u0026thinsp;40.55, the aliphatic index was 78.14\u0026thinsp;~\u0026thinsp;95.89, and the hydrophilicity mean value was \u0026minus;\u0026thinsp;0.294\u0026thinsp;~\u0026thinsp;0.006 (Table \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.5.3 Subcellular localization analysis\u003c/h2\u003e \u003cp\u003eSubcellular localization predicted that PL and PME genes were mostly distributed in the extracellular matrix, with a few in the cytoplasm, mitochondria, chloroplasts, vesicles and endoplasmic reticulum, and PG genes were mostly distributed in the nucleus, with a few in the vesicles, cytoplasm, and extracellular matrix. While experiments subsequently confirmed that \u003cem\u003eSlPL7\u003c/em\u003e was distributed in the nucleus, \u003cem\u003eSolycPME9\u003c/em\u003e was distributed in the cell membrane and endoplasmic reticulum, in general agreement with the predicted results (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.5.4 Protein structural analysis\u003c/h2\u003e \u003cp\u003eThe results of secondary structure prediction showed that the α-helix, extended strand, β-turn, and irregular curl of PL genes ranged from 14.96 to 25.39%, 20.49 to 26.62%, 2.26 to 5.84%, and 48.21 to 58.1%, respectively (Table \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003e). The PME genes ranged between 13.73 and 41.23%, 14.88 and 25.73%, 4.2 and 7.84%, and 36.4 and 59.8%, respectively, and the PG genes ranged from 4.59 to 16.26%, 12.13 to 40.83%, 3.64 to 12.13% and 46.34 to 54.18%, respectively. The tertiary structure found that the α-helix and β-folding numbers of PL ranged from 8 to 14 and 31 to 51, respectively; the PME ranged from 5 to 22 and 8 to 37, respectively; and PG ranged from 3 to 9 and 23 to 43, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.5.5 Evolutionary analyses\u003c/h2\u003e \u003cp\u003eThe evolutionary tree was constructed by removing one non-conserved sequence after multiple sequence comparison (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The results showed that. The evolutionary tree classified 33 genes into 4 classes, consisting of 10, 3, 2 and 18 genes, respectively. Among them, PG was classified into three taxa Ⅰ, Ⅱ, and Ⅲ, and PL and PME were classified in the Ⅳ taxa, which indicated that PL and PME were closely related and might have similar functions\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.5.6 Gene structure and promoter analyses\u003c/h2\u003e \u003cp\u003eThe gene structure showed that PL genes characterized 3 to 13 exons and 2 to 12 introns, while PME genes featured 1 to 8 exons and 0 to 7 introns, and the exons and introns of PG ranged from 4 to 9 and 3 to 8, respectively. Twelve Motifs were identified using the MEME. PL genes consisted of Motif 12, Motif 7, Motif 4 and Motif 9, forming the Pec_lyase_N and Amb_all domains, and the PME genes consisted of Motif 8, Motif 9, Motif 1 and Motif 6, possessing the PMEI and Pectinesterase domains. PG genes contained PbH1 domain, specially including Motif 9, Motif 11, Motif 2, Motif 10, Motif 3, Motif 5, and Motif 7. The cis-acting promoter elements of pectinase genes could be divided into four categories. The first acting elements were related to hormone response, including GARE-motif, ABRE and TATC-box involved in gibberellin response, AuxRE, AuxRR-core and TGA-element in response to growth hormone, and CGTCA-motif in response to methyl jasmonate, and SARE in response to salicylate, respectively. The second category were some elements related to meristematic organisation, seed-specific regulation, chloroplast mesophyll cell differentiation and endosperm expression, such as CAT-box, RY-element, HD-Zip 1, GCN4_motif, and AACA_motif. The third category is related to low temperature, drought stress and anaerobic induction responsiveness, such asLTR, MBS, GC-motif and ARE. The fourth type elements were related to light responsiveness, such as MRE, ATC-motif, G-Box, ACE, Box II, AE-box, 3-AF1 binding site and CAG-motif (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.5.7 Protein network interaction analysis\u003c/h2\u003e \u003cp\u003eThe results of protein network interactions showed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF) that there were 98 pairs of protein interactions between PL and PME, of which SlPG15 had 16 pairs of interactions with other proteins, \u003cem\u003eSlPL2\u003c/em\u003e, \u003cem\u003eSlPL4\u003c/em\u003e, \u003cem\u003eSlPL7\u003c/em\u003e, and \u003cem\u003eSlPL11\u003c/em\u003e all had 11 pairs of interactions with other proteins, and \u003cem\u003eSolycPME5\u003c/em\u003e, \u003cem\u003eSolycPME9\u003c/em\u003e, and \u003cem\u003eSolycPME42\u003c/em\u003e, \u003cem\u003eSolycPME47\u003c/em\u003e, \u003cem\u003eSolycPME79\u003c/em\u003e, \u003cem\u003eSlPG24-6\u003c/em\u003e, and \u003cem\u003eSlPG24-1\u003c/em\u003e existed 10 pairs of interactions with other proteins, \u003cem\u003eSlPL6\u003c/em\u003e, \u003cem\u003eSolycPME12\u003c/em\u003e, \u003cem\u003eSolycPME18\u003c/em\u003e, and \u003cem\u003eSolycPME48\u003c/em\u003e existed 9 pairs of interactions with other proteins, and \u003cem\u003eSolycPME40\u003c/em\u003e and \u003cem\u003eSlPG24-4\u003c/em\u003e 8 pairs of interactions with other proteins, \u003cem\u003eSolycPME4\u003c/em\u003e 7 pairs of interactions with other proteins, \u003cem\u003eSlPG24-9\u003c/em\u003e 6 pairs of interactions with other proteins, \u003cem\u003eSlPL12\u003c/em\u003e interactions with \u003cem\u003eSlPG15\u003c/em\u003e, \u003cem\u003eSolycPME30\u003c/em\u003e, \u003cem\u003eSolycPME39\u003c/em\u003e, \u003cem\u003eSolycPME78\u003c/em\u003e, \u003cem\u003eSlPG38-1\u003c/em\u003e, \u003cem\u003eSlPG44\u003c/em\u003e, \u003cem\u003eSlPG24-8\u003c/em\u003e, \u003cem\u003eSlPG56-2\u003c/em\u003e, \u003cem\u003eSlPG56-3\u003c/em\u003e, \u003cem\u003eSlPG45\u003c/em\u003e, \u003cem\u003eSlPG17-2\u003c/em\u003e, \u003cem\u003eSlPG8\u003c/em\u003e, \u003cem\u003eSlPG38-2\u003c/em\u003e, and \u003cem\u003eSlPG36\u003c/em\u003e were not interacting with other proteins.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eFruit malformation is a major constrain in fruit production worldwide resulting in substantial\u003c/p\u003e \u003cp\u003eeconomic losses. The molecular mechanisms underlying malformed tomato fruit were developed around the CLAVATA-WUSCHEL pathway, however, availability of other regulatory pathways involved in deformed fruit are far from fully understood. Here, we first investigated phenotypic characterization between the wild-type \"QT57\" and malformed fruit \"QT2\". The significant differences in floral organisation were found, with deformed flowers mainly displaying characteristics such as large buds, many sepals and petals, and thick and irregular styles compared to normal flowers, and those phenotypics becoming more pronounced with the development of floral organs, suggesting that certain genes regulate the formation of deformed flowers, and consequently result in deformed fruits.\u003c/p\u003e \u003cp\u003eSome of the genes that mediate the formation of malformed fruit by regulating carpel development have been reported. Tomato \u003cem\u003eSlCRCa\u003c/em\u003e and \u003cem\u003eSlCRCb\u003c/em\u003e positively regulated the floral meristems by acting in a compensatory and partially redundant manner, furthermore, \u003cem\u003eSlCRCa\u003c/em\u003e and \u003cem\u003eSlCRCb\u003c/em\u003e, \u003cem\u003eSlIMA\u003c/em\u003e and \u003cem\u003eSlKNU\u003c/em\u003e interact with \u003cem\u003eSlHDA1\u003c/em\u003e and \u003cem\u003eSlTPL1\u003c/em\u003e to form a chromatin remodelling complex that represses \u003cem\u003eSlWUS\u003c/em\u003e expression to terminate floral stem cell activity once carpel primordia are initiated, finally, safeguarding the proper formation of flowers and fruits [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The delayed reinstatement of cell-to-cell transport of \u003cem\u003eSlWUS\u003c/em\u003e prevented the activation of \u003cem\u003eSlCLV3\u003c/em\u003e and \u003cem\u003eTAG1\u003c/em\u003e, causing the interrupted feedback inhibition of \u003cem\u003eSlWUS\u003c/em\u003e expression, leading to the expanded stem cell population and malformed fruits under cold stress [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. To further verify whether the formation of \"QT2\" deformed fruit was regulated by the CLAVATA-WUSCHEL pathway genes reported in the studies of Casta\u0026ntilde;eda [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and Wu [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], nine genes were used for expression analysis in \"QT57\" and \"QT2\" under UP, HP and FP periods. The results showed that SlCRCa was expressed at high levels in \"QT2\" during the FP periods, whereas SlCRCb was expressed at high levels in \"QT2\" during the UP and HP periods. This is consistent with a compensatory mechanism reported in the study by Casta\u0026ntilde;eda [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, we suspected that SlCRCa and SlCRCb involved in the formation of \"QT2\" aberrant fruits by acting in a compensatory manner.\u003c/p\u003e \u003cp\u003eTomato unopened flower buds (UP, earlier than 8 d before anthesis), half- unopened flower buds (HP, earlier than 4 d before anthesis), and fully-opened flowers (FP) of \"QT57\" (WT) and \"QT2\" (malformed fruit) were used for RNA-Seq analysis to identify new regulatory pathways underlying malformed tomato fruit. The 1133, 1115 and 2319 up-regulated differential genes, and 1512, 1732 and 3256 down-regulated differential genes were identified using RNA-Seq analysis in UP, HP and FP periods, respectively. The number of down-regulated genes was all higher than the number of up-regulated genes, speculating that those down-regulated genes may play a key role in the formation of deformed fruit. Liu et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] identified flowering and hormone-related DEGs underlying deformed flowers with the expression of most genes down-regulated in sugar apple, which was consistent with the results of this study. 16 key candidate genes were further found and analyzed using qRT-PCR analysis. The results found that 16 candidate genes were all significantly expressed between \"QT57\" and \"QT2\", suggesting they may be involved in the formation of \"QT2\" deformed fruit. Six pectinase genes, including \u003cem\u003eLAT56\u003c/em\u003e as PL gene, \u003cem\u003eLOC101260471\u003c/em\u003e, \u003cem\u003eLOC101244677\u003c/em\u003e, \u003cem\u003eLOC101267809\u003c/em\u003e, \u003cem\u003eLAT59\u003c/em\u003e as PME genes, and \u003cem\u003eLOC101263150\u003c/em\u003e as PG gene, were identified in the 16 candidate genes, and their expression in \"QT57\" was higher than in \"QT2\", suggesting negatively regulate of deformed fruit formation. six pectinase genes in the study were found to be specifically highly expressed in floral tissues [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and the results of Jang et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and Li et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] also confirmed that PG genes lead to fruit malformation by overexpression and silencing analysis.\u003c/p\u003e \u003cp\u003ePectinase genes are involved in the formation of malformed fruits in tomato, and the molecular mechanism on pectinase genes involved in deformed fruit are far from fully understood, therefore, pectinase was considered as key candidate genes for further gene family analysis. Promoter analysis revealed that all pectinase genes, except \u003cem\u003eSlPL2\u003c/em\u003e, \u003cem\u003eSlPL11\u003c/em\u003e and \u003cem\u003eSlPG56-2\u003c/em\u003e, have gibberellin homeopathic effect elements, suggesting gibberellin may influence pectinase gene expression and malformed fruits. Wu et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] showed that the increase of gibberellin promoted the \u003cem\u003eWUS\u003c/em\u003e gene expression, leading to an increase in the number of ventricles and the formation of malformed fruits. The results of Wu et al [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] indicated that the increase of ABA under short-term cold stress enhanced the accumulation of callus, while the application of exogenous GA could reduce the accumulation of callus, restore the intercellular movement of WUS, and lead to the normal development of the FM, reducing the fruit malformation. The phylogenetic tree classified the PL and PME genes into the same taxon, suggesting that they are closely related and play similar functions. The protein network interaction found a large number of interactions between pectinases, mainly enriched in the pectin catabolic process, carbohydrate metabolic process and pentose glucuronide interconversion pathway. Andr\u0026eacute;s et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] found that nutrient decline altered the number of deformed fruits in coffee beans, suggesting that inhibition of the pectinase gene resulted in the inability to degrade pectin, leading to nutrient deficiencies in tomatoes, and consequently the formation of deformed fruits.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by funds from The Key Laboratory Project of Qinghai Science \u0026amp; Technology Department (Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources 2025), The Project of Laboratory for Research and Utilization of Qinghai Tibet Plateau Germplasm Resources (2024-SYS-06), and National Natural Science Foundation of China (No. 32460771).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJQW and QWZ designed the experiments. CFY performed the experiments. JQW and CFY analyzed the data and wrote the paper. QHL and SBB revised the paper. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files and RNA sequence data that support the findings of this study will be submitted to the NCBI sequence read archive (SRA) after manuscript acceptance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCamejo G, Rodrigu\u0026eacute;z LM, \u0026Ouml;stergren LG, et al. W04-IS-001 Fatty acid-induced alterations of extracellular matrix proteoglycans may link insulin resistance and atherogenesis. Atherosclerosis (Supplements) (Component). 2005;6(1):16\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Sun W, Sun C, et al. 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Sci Hort. 2024;329:113005.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Transcriptomic analysis, Malformed, Pectinase gene, Tomato","lastPublishedDoi":"10.21203/rs.3.rs-6365605/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6365605/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFruit malformation severely reduces the yield and quality of tomatoes, resulting in significant economic losses. However, the molecular mechanisms underlying malformed tomato fruit are far from being fully understood. Here, we first investigated the phenotypic characterization between the wild type \"QT57\" and the malformed fruit \"QT2\". Significant differences in flower organization were found. The expression of genes related to the CLAVATA-WUSCHEL pathway suggested that \u003cem\u003eSlCRCa\u003c/em\u003e and \u003cem\u003eSlCRCb\u003c/em\u003e are involved in the formation of QT2 misshapen fruits by acting in a compensatory manner. RNA-Seq analysis identified six pectinase genes as key candidate genes for misshapen fruit. They were significantly expressed and their expression was higher in \"QT57\" than in \"QT2\", suggesting a negative regulation of malformed fruit formation. Gene family analysis of pectinase genes was also performed. A total of 34 pectinase genes, including 6 PL, 15 PG and 13 PME genes, were used for in-depth bioinformatic analysis. We found that all genes except \u003cem\u003eSlPL2\u003c/em\u003e, \u003cem\u003eSlPL11\u003c/em\u003e and \u003cem\u003eSlPG56-2\u003c/em\u003e had gibberellin homeopathic effect elements; pectin lyase and pectin esterase were closely related and functioned in similar microenvironments. The results provide new insights into tomato fruit deformation.\u003c/p\u003e","manuscriptTitle":"Transcriptomic and the Pectinase Gene Family analysis reveals a particular pathway on malformed tomato development","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 21:32:43","doi":"10.21203/rs.3.rs-6365605/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"233d67ef-cdf5-4982-bfc1-de6f69c0a5dd","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T11:08:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-14 21:32:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6365605","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6365605","identity":"rs-6365605","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}