Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population

Yield-related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton

Salinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield-component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D-value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY-Chr6-2, qBNP-Chr4-1, qBNP-Chr12-1, qBNP-Chr15-5, qLP-Chr19-2) detected in both in E1 and D-value were salt related QTL, and three stable QTL (qLP-Chr5-3, qLP-Chr13-1, qBW-Chr5-5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP-Chr5-3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor-effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP-Chr4-1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.

Aspartyl proteases identified as candidate genes of a fiber length QTL, qFLD05, that regulates fiber length in cotton (Gossypium hirsutum L.)

KEY MESSAGE

GhAP genes were identified as the candidates involved in cotton fiber length under the scope of fine mapping a stable fiber length QTL, qFLD05. Moreover, the transcription factor GhWRKY40 positively regulated GhAP3 to decrease fiber length. Fiber length (FL) is an economically important fiber quality trait. Although several genes controlling cotton fiber development have been identified, our understanding of this process remains limited. In this study, an FL QTL (qFLD05) was fine-mapped to a 216.9-kb interval using a secondary F2:3 population derived from the upland hybrid cultivar Ji1518. This mapped genomic segment included 15 coding genes, four of which were annotated as aspartyl proteases (GhAP1-GhAP4). GhAPs were identified as candidates for qFLD05 as the sequence variations in GhAPs were associated with FL deviations in the mapping population, and functional validation of GhAP3 and GhAP4 indicated a longer FL following decreases in their expression levels through virus-induced gene silencing (VIGS). Subsequently, the potential involvement of GhWRKY40 in the regulatory network was revealed: GhWRKY40 positively regulated GhAP3's expression according to transcriptional profiling, VIGS, yeast one-hybrid assays and dual-luciferase experiments. Furthermore, alterations in the expression of the eight previously reported cotton FL-responsive genes from the above three VIGS lines (GhAP3, GhAP4 and GhWRKY40) implied that MYB5_A12 was involved in the GhWRKY40-GhAP network. In short, we unveiled the unprecedented FL regulation roles of GhAPs in cotton, which was possibly further regulated by GhWRKY40. These findings will reveal the genetic basis of FL development associated with qFLD05 and be beneficial for the marker-assisted selection of long-staple cotton.

Genetic linkage analysis of stable QTLs in Gossypium hirsutum RIL population revealed function of GhCesA4 in fiber development

INTRODUCTION

Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations.

OBJECTIVES

The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield.

METHODS

A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies.

RESULTS

An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage.

CONCLUSION

Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.

Genome-wide association study for boll weight in Gossypium hirsutum races

High yield has always been an essential target in almost all of the cotton breeding programs. Boll weight (BW) is a key component of cotton yield. Numerous linkage mapping and genome-wide association studies (GWAS) have been performed to understand the genetic mechanism of BW, but information on the markers/genes controlling BW remains limited. In this study, we conducted a GWAS for BW using 51,268 high-quality single-nucleotide polymorphisms (SNPs) and 189 Gossypium hirsutum accessions across five different environments. A total of 55 SNPs significantly associated with BW were detected, of which 29 and 26 were distributed in the A and D subgenomes, respectively. Five SNPs were simultaneously detected in two environments. For TM5655, TM8662, TM36371, and TM50258, the BW grouped by alleles of each SNP was significantly different. The ± 550 kb regions around these four key SNPs contained 262 genes. Of them, Gh_A02G1473, Gh_A10G1765, and Gh_A02G1442 were expressed highly at 0 to 1 days post-anthesis (dpa), - 3 to 0 dpa, and - 3 to 0 dpa in ovule of TM-1, respectively. They were presumed as the candidate genes for fiber cell differentiation, initiation, or elongation based on gene annotation of their homologs. Overall, these results supplemented valuable information for dissecting the genetic architecture of BW and might help to improve cotton yield through molecular marker-assisted selection breeding and molecular design breeding.

Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits

INTRODUCTION

The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield.

OBJECTIVES

This study was to identify superior loci for the improvement of fiber quality and yield.

METHODS

Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci.

RESULTS

A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population.

CONCLUSION

The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

QTL Verification and Candidate Gene Screening of Fiber Quality and Lint Percentage in the Secondary Segregating Population of Gossypium hirsutum

Fiber quality traits, especially fiber strength, length, and micronaire (FS, FL, and FM), have been recognized as critical fiber attributes in the textile industry, while the lint percentage (LP) was an important indicator to evaluate the cotton lint yield. So far, the genetic mechanism behind the formation of these traits is still unclear. Quantitative trait loci (QTL) identification and candidate gene validation provide an effective methodology to uncover the genetic and molecular basis of FL, FS, FM, and LP. A previous study identified three important QTL/QTL cluster loci, harboring at least one of the above traits on chromosomes A01, A07, and D12 via a recombinant inbred line (RIL) population derived from a cross of Lumianyan28 (L28) × Xinluzao24 (X24). A secondary segregating population (F2) was developed from a cross between L28 and an RIL, RIL40 (L28 × RIL40). Based on the population, genetic linkage maps of the previous QTL cluster intervals on A01 (6.70-10.15 Mb), A07 (85.48-93.43 Mb), and D12 (0.40-1.43 Mb) were constructed, which span 12.25, 15.90, and 5.56 cM, with 2, 14, and 4 simple sequence repeat (SSR) and insertion/deletion (Indel) markers, respectively. QTLs of FL, FS, FM, and LP on these three intervals were verified by composite interval mapping (CIM) using WinQTL Cartographer 2.5 software via phenotyping of F2 and its derived F2:3 populations. The results validated the previous primary QTL identification of FL, FS, FM, and LP. Analysis of the RNA-seq data of the developing fibers of L28 and RIL40 at 10, 20, and 30 days post anthesis (DPA) identified seven differentially expressed genes (DEGs) as potential candidate genes. qRT-PCR verified that five of them were consistent with the RNA-seq result. These genes may be involved in regulating fiber development, leading to the formation of FL, FS, FM, and LP. This study provides an experimental foundation for further exploration of these functional genes to dissect the genetic mechanism of cotton fiber development.

Mapping intron retention events contributing to complex traits using splice quantitative trait locus

BACKGROUND

Alternative splicing (AS) of mRNA plays an important roles in transcriptome diversity, involving regulation of plant growth and stress response. Understanding the variation of AS events underlying GWAS loci in a crop population can provide insight into the molecular mechanisms of complex agronomic traits. To date, genome-wide association studies relating AS events to agronomic traits have rarely been conducted at the population level in crops.

RESULTS

Here, a pipeline was constructed to identify candidate AS events related to complex traits. Firstly, ovule transcriptome data were used to characterize intron retention (IR), the predominant type of AS in plants, on a genome-wide scale. This was done in a natural population consisting of 279 upland cotton lines. Secondly, splice quantitative trait locus (sQTL) analysis was carried out, which yielded a total of 2295 sQTLs involving 1607 genes. Of these, 14.25% (n = 427) were cis-regulatory loci. Integration with expression quantitative trait loci (eQTL) revealed that 53 (21.4%) cis-sGenes were regulated by both cis-sQTLs and cis-eQTLs. Finally, co-localization analysis integrated with GWAS loci in this population showed 32 cis-QTLs to be co-located with genetic regulatory loci related to fiber yield and quality traits, indicating that sQTLs are likely to participate in regulating cotton fiber yield and quality. An in-depth evaluation confirmed that differences in the IR rates of sQTL-regulated candidate genes such as GhLRRK1 and GhGC1 are associated with lint percentage (LP), which has potential in breeding applications.

CONCLUSION

This study provides a clue that AS of mRNA has an impact on crop yield, along with functional sQTLs are new genetic resources for cotton precision breeding.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60

BACKGROUND

Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield.

RESULTS

Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation.

CONCLUSIONS

A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

Fine mapping and candidate gene analysis of qFL-A12-5: a fiber length-related QTL introgressed from Gossypium barbadense into Gossypium hirsutum

The fiber length-related qFL-A12-5 identified in CSSLs introgressed from Gossypium barbadense into Gossypium hirsutum was fine-mapped to an 18.8 kb region on chromosome A12, leading to the identification of the GhTPR gene as a potential regulator of cotton fiber length. Fiber length is a key determinant of fiber quality in cotton, and it is a key target of artificial selection for breeding and domestication. Although many fiber length-related quantitative trait loci have been identified, there are few reports on their fine mapping or candidate gene validation, thus hampering efforts to understand the mechanistic basis of cotton fiber development. Our previous study identified the qFL-A12-5 associated with superior fiber quality on chromosome A12 in the chromosome segment substitution line (CSSL) MBI7747 (BC₄F_3:5). A single segment substitution line (CSSL-106) screened from BC₆F₂ was backcrossed to construct a larger segregation population with its recurrent parent CCRI45, thus enabling the fine mapping of 2852 BC₇F₂ individuals using denser simple sequence repeat markers to narrow the qFL-A12-5 to an 18.8 kb region of the genome, in which six annotated genes were identified in Gossypium hirsutum. Quantitative real-time PCR and comparative analyses led to the identification of GH_A12G2192 (GhTPR) encoding a tetratricopeptide repeat-like superfamily protein as a promising candidate gene for qFL-A12-5. A comparative analysis of the protein-coding regions of GhTPR among Hai1, MBI7747, and CCRI45 revealed two non-synonymous mutations. The overexpression of GhTPR resulted in longer roots in Arabidopsis, suggesting that GhTPR may regulate cotton fiber development. These results provide a foundation for future efforts to improve cotton fiber length.

Recent advances and future perspectives in early-maturing cotton research

Cotton's fundamental requirements for long periods of growth and specific seasonal temperatures limit the global arable areas that can be utilized to cultivate cotton. This constraint can be alleviated by breeding for early-maturing varieties. By delaying the sowing dates without impacting the boll-opening time, early-maturing varieties not only mitigate the yield losses brought on by unfavorable weathers in early spring and late autumn but also help reducing the competition between cotton and other crops for arable land, thereby optimizing the cropping system. This review presents studies and breeding efforts for early-maturing cotton, which efficiently pyramid early maturity, high-quality, multiresistance traits, and suitable plant architecture by leveraging pleiotropic genes. Attempts are also made to summarize our current understanding of the molecular mechanisms underlying early maturation, which involves many pathways such as epigenetic, circadian clock, and hormone signaling pathways. Moreover, new avenues and effective measures are proposed for fine-scale breeding of early-maturing crops to ensure the healthy development of the agricultural industry.

Identification of elite fiber quality loci in upland cotton based on the genotyping-by-target-sequencing technology

Genome-wide association studies (GWAS) of fiber quality traits of upland cotton were conducted to identify the single-nucleotide polymorphic (SNP) loci associated with cotton fiber quality, which lays the foundation for the mining of elite] cotton fiber gene resources and its application in molecular breeding. A total of 612 upland cotton accessions were genotyped using the ZJU Cotton Chip No. 1 40K chip array via the liquid-phase probe hybridization-based genotyping-by-target-sequencing (GBTS) technology. In the present study, five fiber quality traits, namely fiber length, fiber strength, micronaire, uniformity and elongation, showed different degrees of variation in different environments. The average coefficient of variation of fiber strength was the greatest, whereas the average coefficient of variation of uniformity was the least. Significant or extremely significant correlations existed among the five fiber quality traits, especially fiber length, strength, uniformity and elongation all being significantly negative correlated with micronaire. Population cluster analysis divided the 612 accessions into four groups: 73 assigned to group I, 226 to group II, 220 to group III and 93 to group IV. Genome-wide association studies of five fiber quality traits in five environments was performed and a total of 42 SNP loci associated with target traits was detected, distributed on 19 chromosomes, with eight loci associated with fiber length, five loci associated with fiber strength, four loci associated with micronaire, twelve loci associated with fiber uniformity and thirteen loci associated with fiber elongation. Of them, seven loci were detected in more than two environments. Nine SNP loci related to fiber length, fiber strength, uniformity and elongation were found on chromosome A07, seven loci related to fiber length, fiber strength, micronaire and elongation were detected on chromosome D01, and five loci associated with fiber length, uniformity and micronaire were detected on chromosome D11. The results from this study could provide more precise molecular markers and genetic resources for cotton breeding for better fiber quality in the future.

A consensus map for quality traits in durum wheat based on genome-wide association studies and detection of ortho-meta QTL across cereal species

The present work focused on the identification of durum wheat QTL hotspots from a collection of genome-wide association studies, for quality traits, such as grain protein content and composition, yellow color, fiber, grain microelement content (iron, magnesium, potassium, selenium, sulfur, calcium, cadmium), kernel vitreousness, semolina, and dough quality test. For the first time a total of 10 GWAS studies, comprising 395 marker-trait associations (MTA) on 57 quality traits, with more than 1,500 genotypes from 9 association panels, were used to investigate consensus QTL hotspots representative of a wide durum wheat genetic variation. MTA were found distributed on all the A and B genomes chromosomes with minimum number of MTA observed on chromosome 5B (15) and a maximum of 45 on chromosome 7A, with an average of 28 MTA per chromosome. The MTA were equally distributed on A (48%) and B (52%) genomes and allowed the identification of 94 QTL hotspots. Synteny maps for QTL were also performed in Zea mays, Brachypodium, and Oryza sativa, and candidate gene identification allowed the association of genes involved in biological processes playing a major role in the control of quality traits.

Genome-wide identification, expression and evolution analysis of OVATE family proteins in cotton (Gossypium spp.)

OVATE family proteins (OFPs) are plant-specific transcription factors with a conserved OVATE domain. Although OFPs have been reported to regulate many aspects of plant growth and development, little is known about their evolution, structure, and function in fiber development in cotton. In this study, 174 OFPs were identified from four species of Gossypium namely, G. hirsutum, G. barbadense, G. arboreum, and G. raimondii. These OFPs were grouped into 6 sub-families by using phylogenetic analysis, and members within the same sub-family had similar conserved motifs. Chromosomal localization revealed that OFPs are distributed in cotton genome unevenly. Gene structure analysis showed that most of OFPs were intronless. Moreover, Ka/Ks analysis exhibited that OFPs were gone through purifying selection processes during evolution. Multiple cis-acting elements were observed in promoter region of OFPs, which are responsive to light, phytohormone, biotic stresses, growth and developmental related cis-acting elements. In addition, OFPs play important role in fiber and ovule development. In conclusion, this study provides a systematic analysis of cotton OFPs and provides the foundation for further studies on biological functioning of cotton OFPs.

UDP-glucose pyrophosphorylase: genome-wide identification, expression and functional analyses in Gossypium hirsutum

In this study, a total of 66 UDP-glucose pyrophosphorylase (UGP) (EC 2.7.7.9) genes were identified from the genomes of four cotton species, which are the members of Pfam glycosyltransferase family (PF01702) and catalyze the reaction between glucose-1-phosphate and UTP to produce UDPG. The analysis of evolutionary relationship, gene structure, and expression provides the basis for studies on function of UGP genes in cotton. The evolutionary tree and gene structure analysis revealed that the UGP gene family is evolutionarily conserved. Collinearity and Ka/Ks analysis indicated that amplification of UGP genes is due to repetitive crosstalk generating between new family genes, while being under strong selection pressure. The analysis of cis-acting elements exhibited that UGP genes play important role in cotton growth, development, abiotic and hormonal stresses. Six UGP genes that were highly expressed in cotton fiber at 15 DPA were screened by transcriptome data and qRT-PCR analysis. The addition of low concentrations of IAA and GA3 to ovule cultures revealed that energy efficiency promoted the development of ovules and fiber clusters, and qRT-PCR showed that expression of these six UGP genes was differentially increased. These results suggest that the UGP gene may play an important role in fiber development, and provides the opportunity to plant researchers to explore the mechanisms involve in fiber development in cotton.

Identification of Candidate Genes for Lint Percentage and Fiber Quality Through QTL Mapping and Transcriptome Analysis in an Allotetraploid Interspecific Cotton CSSLs Population

Upland cotton (Gossypium hirsutum) has long been an important fiber crop, but the narrow genetic diversity of modern G. hirsutum limits the potential for simultaneous improvement of yield and fiber quality. It is an effective approach to broaden the genetic base of G. hirsutum through introgression of novel alleles from G. barbadense with excellent fiber quality. In the present study, an interspecific chromosome segment substitution lines (CSSLs) population was established using G. barbadense cultivar Pima S-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. A total of 105 quantitative trait loci (QTL), including 85 QTL for fiber quality and 20 QTL for lint percentage (LP), were identified based on phenotypic data collected from four environments. Among these QTL, 25 stable QTL were detected in two or more environments, including four for LP, eleven for fiber length (FL), three for fiber strength (FS), six for fiber micronaire (FM), and one for fiber elongation (FE). Eleven QTL clusters were observed on nine chromosomes, of which seven QTL clusters harbored stable QTL. Moreover, eleven major QTL for fiber quality were verified through analysis of introgressed segments of the eight superior lines with the best comprehensive phenotypes. A total of 586 putative candidate genes were identified for 25 stable QTL associated with lint percentage and fiber quality through transcriptome analysis. Furthermore, three candidate genes for FL, GH_A08G1681 (GhSCPL40), GH_A12G2328 (GhPBL19), and GH_D02G0370 (GhHSP22.7), and one candidate gene for FM, GH_D05G1346 (GhAPG), were identified through RNA-Seq and qRT-PCR analysis. These results lay the foundation for understanding the molecular regulatory mechanism of fiber development and provide valuable information for marker-assisted selection (MAS) in cotton breeding.

Construction of a high-density genetic map and identification of QTLs related to agronomic and physiological traits in an interspecific (Gossypium hirsutum × Gossypium barbadense) F2 population

Background

Advances in genome sequencing technology, particularly restriction-site associated DNA sequence (RAD-seq) and whole-genome resequencing, have greatly aided the construction of cotton interspecific genetic maps based on single nucleotide polymorphism (SNPs), Indels, and other types of markers. High-density genetic maps can improve accuracy of quantitative trait locus (QTL) mapping, narrow down location intervals, and facilitate identification of the candidate genes.

Result

In this study, 249 individuals from an interspecific F2 population (TM-1 and Hai7124) were re-sequenced, yielding 6303 high-confidence bin markers spanning 5057.13 cM across 26 cotton chromosomes. A total of 3380 recombination hot regions RHRs were identified which unevenly distributed on the 26 chromosomes. Based on this map, 112 QTLs relating to agronomic and physiological traits from seedling to boll opening stage were identified, including 15 loci associated with 14 traits that contained genes harboring nonsynonymous SNPs. We analyzed the sequence and expression of these ten candidate genes and discovered that GhRHD3 (GH_D10G0500) may affect fiber yield while GhGPAT6 (GH_D04G1426) may affect photosynthesis efficiency.

Conclusion

Our research illustrates the efficiency of constructing a genetic map using binmap and QTL mapping on the basis of a certain size of the early-generation population. High-density genetic map features high recombination exchanges in number and distribution. The QTLs and the candidate genes identified based on this high-density genetic map may provide important gene resources for the genetic improvement of cotton.

TIP41L, a putative candidate gene conferring both seed size and boll weight, was fine-mapped in an introgression line of Gossypium hirsutum-Gossypium arboreum

QTLs for yield-related traits in tetraploid cotton have been widely mapped, but QTLs introduced from diploid species into tetraploid cotton background remain uninvolved. Here, a stable introgression line with the traits of small boll and seed on Chr. A12, IL197 derived from Gossypium hirsutum (2n = AADD = 52) × Gossypium arboreum (2n = AA = 26), was employed to construct the F₂ and F₃ secondary populations for fine-mapping QTLs of yield-related traits. QTL analysis showed eight QTLs were detected for three traits, boll weight (BW), seed index (SI, one-hundred-seed weight in g), and lint percentage, with 3.94-28.13 % of the phenotypic variance explained. Of them, a stable major QTL, q(BW + SI)-A12-1 controlling both BW and SI and covering the shortest region in Chr. A12, was further narrowed into a 60.09 kb-interval through substitution mapping. Finally, five candidate genes were detected in the interval. The qRT-PCR analysis revealed only TIP41-like family protein (TIP41L) kept up-regulated expression and significantly lower in TM-1 than that in IL197 from -1 DPA to 15 DPA during cotton boll rapid developmental stage. Therefore, TIP41L gene is speculated as the most likely candidate gene. Comparative analysis with the other four allotetraploid species showed TIP41L gene was probably diverged after the formation of allotetraploid cotton, which may be selected and swept during domestication of modern upland cotton because small boll and seed are detrimental to fibre yield of cotton. This research would lay a solid foundation for further elucidating the molecular mechanism of cotton boll and seed development.

Linkage and association analyses reveal that hub genes in energy-flow and lipid biosynthesis pathways form a cluster in upland cotton

Upland cotton is an important allotetraploid crop that provides both natural fiber for the textile industry and edible vegetable oil for the food or feed industry. To better understand the genetic mechanism that regulates the biosynthesis of storage oil in cottonseed, we identified the genes harbored in the major quantitative trait loci/nucleotides (QTLs/QTNs) of kernel oil content (KOC) in cottonseed via both multiple linkage analyses and genome-wide association studies (GWAS). In ‘CCRI70′ RILs, six stable QTLs were simultaneously identified by linkage analysis of CHIP and SLAF-seq strategies. In ‘0-153′ RILs, eight stable QTLs were detected by consensus linkage analysis integrating multiple strategies. In the natural panel, thirteen and eight loci were associated across multiple environments with two algorithms of GWAS. Within the confidence interval of a major common QTL on chromosome 3, six genes were identified as participating in the interaction network highly correlated with cottonseed KOC. Further observations of gene differential expression showed that four of the genes, LtnD, PGK, LPLAT1, and PAH2, formed hub genes and two of them, FER and RAV1, formed the key genes in the interaction network. Sequence variations in the coding regions of LtnD, FER, PGK, LPLAT1, and PAH2 genes may support their regulatory effects on oil accumulation in mature cottonseed. Taken together, clustering of the hub genes in the lipid biosynthesis interaction network provides new insights to understanding the mechanism of fatty acid biosynthesis and TAG assembly and to further genetic improvement projects for the KOC in cottonseeds.

Inheritance, QTLs, and Candidate Genes of Lint Percentage in Upland Cotton

Cotton (Gossypium spp.) is an important natural fiber plant. Lint percentage (LP) is one of the most important determinants of cotton yield and is a typical quantitative trait with high variation and heritability. Many cotton LP genetic linkages and association maps have been reported. This work summarizes the inheritance, quantitative trait loci (QTLs), and candidate genes of LP to facilitate LP genetic study and molecular breeding. More than 1439 QTLs controlling LP have been reported. Excluding replicate QTLs, 417 unique QTLs have been identified on 26 chromosomes, including 243 QTLs identified at LOD >3. More than 60 are stable, major effective QTLs that can be used in marker-assisted selection (MAS). More than 90 candidate genes for LP have been reported. These genes encode MYB, HOX, NET, and other proteins, and most are preferentially expressed during fiber initiation and elongation. A putative molecular regulatory model of LP was constructed and provides the foundation for the genetic study and molecular breeding of LP.

The Pivotal Role of Major Chromosomes of Sub-Genomes A and D in Fiber Quality Traits of Cotton

Lack of precise information about the candidate genes involved in a complex quantitative trait is a major obstacle in the cotton fiber quality improvement, and thus, overall genetic gain in conventional phenotypic selection is low. Recent molecular interventions and advancements in genome sequencing have led to the development of high-throughput molecular markers, quantitative trait locus (QTL) fine mapping, and single nucleotide polymorphisms (SNPs). These advanced tools have resolved the existing bottlenecks in trait-specific breeding. This review demonstrates the significance of chromosomes 3, 7, 9, 11, and 12 of sub-genomes A and D carrying candidate genes for fiber quality. However, chromosome 7 carrying SNPs for stable and potent QTLs related to fiber quality provides great insights for fiber quality-targeted research. This information can be validated by marker-assisted selection (MAS) and transgene in Arabidopsis and subsequently in cotton.

Identification and analysis of oil candidate genes reveals the molecular basis of cottonseed oil accumulation in Gossypium hirsutum L

Based on the integration of QTL-mapping and regulatory network analyses, five high-confidence stable QTL regions, six candidate genes and two microRNAs that potentially affect the cottonseed oil content were discovered. Cottonseed oil is increasingly becoming a promising target for edible oil with its high content of unsaturated fatty acids. In this study, a recombinant inbred line (RIL) cotton population was constructed to detect quantitative trait loci (QTLs) for the cottonseed oil content. A total of 39 QTLs were detected across eight different environments, of which five QTLs were stable. Forty-three candidate genes potentially involved in carbon metabolism, fatty acid synthesis and triacylglycerol biosynthesis processes were further obtained in the stable QTL regions. Transcriptome analysis showed that nineteen of these candidate genes expressed during  the developing cottonseed ovules and may affect the cottonseed oil content. Besides, transcription factor (TF) and microRNA (miRNA) co-regulatory network analyses based on the nineteen candidate genes suggested that six genes, two core miRNAs (ghr-miR2949b and ghr-miR2949c), and one TF GhHSL1 were considered to be closely associated with the cottonseed oil content. Moreover, four vital genes were validated by quantitative real-time PCR (qRT-PCR). These results provide insights into the oil accumulation mechanism in developing cottonseed ovules through the construction of a detailed oil accumulation model.

Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum

Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.

Whole-genome resequencing of 240 Gossypium barbadense accessions reveals genetic variation and genes associated with fiber strength and lint percentage

KEY MESSAGE

Genetic variation in a G. barbadense population was revealed using resquencing. GWAS on G.barbadense population identified several candidate genes associated with fiber strength and lint percentage. Gossypium barbadense is the second-largest cultivated cotton species planted in the world, which is characterized by high fiber quality. Here, we described the global pattern of genetic polymorphisms for 240 G. barbadense accessions based on the whole-genome resequencing. A total of 3,632,231 qualified single-nucleotide polymorphisms (SNPs) and 221,354 insertion-deletions (indels) were obtained. We conducted a genome-wide association study (GWAS) on 12 traits under four environments. Two traits with more stable associated variants, fiber strength and lint percentage, were chosen for further analysis. Three putative candidate genes, HD16 orthology (GB_D11G3437), WDL2 orthology (GB_D11G3460) and TUBA1 orthology (GB_D11G3471), on chromosome D11 were found to be associated with fiber strength, and one gene orthologous to Arabidopsis Receptor-like protein kinase HERK 1 (GB_A07G1034) was predicated to be the candidate gene for the lint percentage improvement. The identified genes may serve as promising targets for genetic engineering to accelerate the breeding process for G. barbadense and the high-density genome variation map constructed in this work may facilitate our understanding of the genetic architecture of cotton traits.

Genome-Wide Introgression and Quantitative Trait Locus Mapping Reveals the Potential of Asian Cotton (Gossypium arboreum) in Improving Upland Cotton (Gossypium hirsutum)

Gossypium arboreum (2n=2x=26, A₂), the putative progenitor of the A_t-subgenome of Gossypium hirsutum (2n=4x=52, AD), is a repository of genes of interesting that have been eliminated during evolution/domestication of G. hirsutum. However, its valuable genes remain untapped so far due to species isolation. Here, using a synthetic amphiploid (AADDA₂A₂) previously reported, we developed a set of 289 G. arboreum chromosome segment introgression lines (ILs) in G. hirsutum by expanding the backcrossing population and through precise marker-assisted selection (MAS) although complex chromosomal structural variations existed between parents which severely hindered introgression. Our results showed the total coverage length of introgressed segments was 1,116.29 Mb, representing 78.48% of the A_t-subgenome in the G. hirsutum background, with an average segment-length of 8.69 Mb. A total of 81 co- quantitative trait loci (QTLs) for yield and fiber quality were identified by both the RSTEP-ADD-based QTL mapping and the genome-wide association study (GWAS) analysis, with 1.01-24.78% of the phenotypic variance explained. Most QTLs for boll traits showed negative additive effects, but G. arboreum still has the potential to improve boll-number traits in G. hirsutum. Most QTLs for fiber quality showed negative additive effects, implying these QTLs were domesticated in G. hirsutum compared with G. arboreum and, a small quantity of fiber quality QTLs showing positive additive effects, conversely; however, indicates that G. arboreum has the underlying genes of enhancing fiber quality of G. hirsutum. This study provides new insights into the breeding genetic potential of G. arboreum, lays the foundation for further mining favorable genes of interest, and provides guidance for inter-ploidy gene transference from relatives into cultivated crops.

Co-expression network and comparative transcriptome analysis for fiber initiation and elongation reveal genetic differences in two lines from upland cotton CCRI70 RIL population

Upland cotton is the most widely planted for natural fiber around the world, and either lint percentage (LP) or fiber length (FL) is the crucial component tremendously affecting cotton yield and fiber quality, respectively. In this study, two lines MBZ70-053 and MBZ70-236 derived from G. hirsutum CCRI70 recombinant inbred line (RIL) population presenting different phenotypes in LP and FL traits were chosen to conduct RNA sequencing on ovule and fiber samples, aiming at exploring the differences of molecular and genetic mechanisms during cotton fiber initiation and elongation stages. As a result, 249/128, 369/206, 4296/1198 and 3547/2129 up-/down- regulated differentially expressed genes (DGEs) in L2 were obtained at -3, 0, 5 and 10 days post-anthesis (DPA), respectively. Seven gene expression profiles were discriminated using Short Time-series Expression Miner (STEM) analysis; seven modules and hub genes were identified using weighted gene co-expression network analysis. The DEGs were mainly enriched into energetic metabolism and accumulating as well as auxin signaling pathway in initiation and elongation stages, respectively. Meanwhile, 29 hub genes were identified as 14-3-3ω , TBL35, GhACS, PME3, GAMMA-TIP, PUM-7, etc., where the DEGs and hub genes revealed the genetic and molecular mechanisms and differences during cotton fiber development.

A statistical framework for QTL hotspot detection

Quantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.

Divergent improvement of two cultivated allotetraploid cotton species

Interspecific genomic variation can provide a genetic basis for local adaptation and domestication. A series of studies have presented its role of interspecific haplotypes and introgressions in adaptive traits, but few studies have addressed their role in improving agronomic character. Two allotetraploid Gossypium species, Gossypium barbadense (Gb) and G. hirsutum (Gh) originating from the Americas, are cultivated independently. Here, through sequencing and the comparison of one GWAS panel in 229 Gb accessions and two GWAS panels in 491 Gh accessions, we found that most associated loci or functional haplotypes for agronomic traits were highly divergent, representing the strong divergent improvement between Gb and Gh. Using a comprehensive interspecific haplotype map, we revealed that six interspecific introgressions from Gh to Gb were significantly associated with the phenotypic performance of Gb, which could explain 5%-40% of phenotypic variation in yield and fibre qualities. In addition, three introgressions overlapped with six associated loci in Gb, indicating that these introgression regions were under further selection and stabilized during improvement. A single interspecific introgression often possessed yield-increasing potential but decreased fibre qualities, or the opposite, making it difficult to simultaneously improve yield and fibre qualities. Our study not only has proved the importance of interspecific functional haplotypes or introgressions in the divergent improvement of Gb and Gh, but also supports their potential value in further human-mediated hybridization or precision breeding.

Edge Detecting Method for Microscopic Image of Cotton Fiber Cross-Section Using RCF Deep Neural Network

Currently, analyzing the microscopic image of cotton fiber cross-section is the most accurate and effective way to measure its grade of maturity and then evaluate the quality of cotton samples. However, existing methods cannot extract the edge of the cross-section intact, which will affect the measurement accuracy of maturity grade. In this paper, a new edge detection algorithm that is based on the RCF convolutional neural network (CNN) is proposed. For the microscopic image dataset of the cotton fiber cross-section constructed in this paper, the original RCF was firstly used to extract the edge of the cotton fiber cross-section in the image. After analyzing the output images of RCF in each convolution stage, the following two conclusions are drawn: (1) the shallow layers contain a lot of important edge information of the cotton fiber cross-section; (2) because the size of the cotton fiber cross-section in the image is relatively small and the receptive field of the convolutional layer gradually increases with the deepening of the number of layers, the edge information detected by the deeper layers becomes increasingly coarse. In view of the above two points, the following improvements are proposed in this paper: (1) modify the network supervision model and loss calculation structure; (2) the dilated convolution in the deeper layers is removed; therefore, the receptive field in the deeper layers is reduced to adapt to the detection of small objects. The experimental results show that the proposed method can effectively improve the accuracy of edge extraction of cotton fiber cross-section.

Identification of hub genes through co-expression network of major QTLs of fiber length and strength traits in multiple RIL populations of cotton

The present study demonstrated a de novo correlation among fiber quality genes in multiple RIL populations including sGK9708 × 0-153, LMY22 × LY343 and Lumianyan28 × Xinluzao24. The current study was conducted to identify the major common QTLs including fiber length and strength, and to identify the co-expression networks of fiber length and strength QTLs harbored genes to target the hub genes. The RNA-seq data of sGK9708 × 0-153 population highlighted 50 and 48 candidate genes of fiber length and fiber strength QTLs. A total of 29 and 21 hub genes were identified in fiber length and strength co-expression network modules. The absolute values of correlation coefficient close to 1 resulted highly positive correlation among hub genes. Results also suggested that the gene correlation significantly influence the gene expression at different fiber development stages. These results might provide useful reference for further experiments in multiple RIL populations and suggest potential candidate genes for functional studies in cotton.

UDP-Glucose Dehydrogenases: Identification, Expression, and Function Analyses in Upland Cotton (Gossypium hirsutum)

UDP-glucose dehydrogenase (UGD; EC1.1.1.22) is a NAD⁺-dependent enzyme that catalyzes the two-fold oxidation of UDP-glucose (UDP-Glc) to produce UDP-glucuronic acid and plays an important role in plant cell wall synthesis. A total of 42 UGD genes from four Gossypium genomes including G. hirsutum, G. arboretum, G. barbadense, and G. raimondii were identified and found that the UGD gene family has conservative evolution patterns in gene structure and protein domain. The growth of fibers can be effectively promoted after adding the UDP-Glc to the medium, and the GhUGD gene expression enhanced. In addition, the transgenic Arabidopsis lines over-expressing GH_D12G1806 had longer root lengths and higher gene expression level than the wild-type plants of Columbia-0. These results indicated that UGD may play important roles in cotton fiber development and has a guiding significance for dissecting fiber development mechanism.

Multi-responses of O-methyltransferase genes to salt stress and fiber development of Gossypium species

BACKGROUND

O-methyltransferases (OMTs) are an important group of enzymes that catalyze the transfer of a methyl group from S-adenosyl-L-methionine to their acceptor substrates. OMTs are divided into several groups according to their structural features. In Gossypium species, they are involved in phenolics and flavonoid pathways. Phenolics defend the cellulose fiber from dreadful external conditions of biotic and abiotic stresses, promoting strength and growth of plant cell wall.

RESULTS

An OMT gene family, containing a total of 192 members, has been identified and characterized in three main Gossypium species, G. hirsutum, G. arboreum and G. raimondii. Cis-regulatory elements analysis suggested important roles of OMT genes in growth, development, and defense against stresses. Transcriptome data of different fiber developmental stages in Chromosome Substitution Segment Lines (CSSLs), Recombination Inbred Lines (RILs) with excellent fiber quality, and standard genetic cotton cultivar TM-1 demonstrate that up-regulation of OMT genes at different fiber developmental stages, and abiotic stress treatments have some significant correlations with fiber quality formation, and with salt stress response. Quantitative RT-PCR results revealed that GhOMT10_Dt and GhOMT70_At genes had a specific expression in response to salt stress while GhOMT49_At, GhOMT49_Dt, and GhOMT48_At in fiber elongation and secondary cell wall stages.

CONCLUSIONS

Our results indicate that O-methyltransferase genes have multi-responses to salt stress and fiber development in Gossypium species and that they may contribute to salt tolerance or fiber quality formation in Gossypium.

Quantitative Trait Locus Analysis and Identification of Candidate Genes for Micronaire in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense

Cotton is the most important fiber crop and provides indispensable natural fibers for the textile industry. Micronaire (MIC) is determined by fiber fineness and maturity and is an important component of fiber quality. Gossypium barbadense L. possesses long, strong and fine fibers, while upland cotton (Gossypium hirsutum L.) is high yielding with high MIC and widely cultivated worldwide. To identify quantitative trait loci (QTLs) and candidate genes for MIC in G. barbadense, a population of 250 backcross inbred lines (BILs), developed from an interspecific cross of upland cotton CRI36 × Egyptian cotton (G. barbadense) Hai7124, was evaluated in 9 replicated field tests. Based on a high-density genetic map with 7709 genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers, 25 MIC QTLs were identified, including 12 previously described QTLs and 13 new QTLs. Importantly, two stable MIC QTLs (qMIC-D03-2 on D03 and qMIC-D08-1 on D08) were identified. Of a total of 338 genes identified within the two QTL regions, eight candidate genes with differential expression between TM-1 and Hai7124 were identified. Our research provides valuable information for improving MIC in cotton breeding.

A high-density genetic map and multiple environmental tests reveal novel quantitative trait loci and candidate genes for fibre quality and yield in cotton

A high-density linkage map of an intraspecific RIL population was constructed using 6187 bins to identify QTLs for fibre quality- and yield-related traits in upland cotton by whole-genome resequencing. Good fibre quality and high yield are important production goals in cotton (Gossypium hirsutum L.), which is a leading natural fibre crop worldwide. However, a greater understanding of the genetic variants underlying fibre quality- and yield-related traits is still required. In this study, a large-scale population including 588 F₇ recombinant inbred lines, derived from an intraspecific cross between the upland cotton cv. Nongdamian13, which exhibits high quality, and Nongda601, which exhibits a high yield, was genotyped by using 232,946 polymorphic single-nucleotide polymorphisms obtained via a whole-genome resequencing strategy with 4.3-fold genome coverage. We constructed a high-density bin linkage map containing 6187 bin markers spanning 4478.98 cM with an average distance of 0.72 cM. We identified 58 individual quantitative trait loci (QTLs) and 25 QTL clusters harbouring 94 QTLs, and 119 previously undescribed QTLs controlling 13 fibre quality and yield traits across eight environments. Importantly, the QTL counts for fibre quality in the Dt subgenome were more than two times that in the At subgenome, and chromosome D02 harboured the greatest number of QTLs and clusters. Furthermore, we discovered 24 stable QTLs for fibre quality and 12 stable QTLs for yield traits. Four novel major stable QTLs related to fibre length, fibre strength and lint percentage, and seven previously unreported candidate genes with significantly differential expression between the two parents were identified and validated by RNA-seq. Our research provides valuable information for improving the fibre quality and yield in cotton breeding.

Disequilibrium evolution of the Fructose-1,6-bisphosphatase gene family leads to their functional biodiversity in Gossypium species

Background

Fructose-1,6-bisphosphatase (FBP) is a key enzyme in the plant sucrose synthesis pathway, in the Calvin cycle, and plays an important role in photosynthesis regulation in green plants. However, no systemic analysis of FBPs has been reported in Gossypium species.

Results

A total of 41 FBP genes from four Gossypium species were identified and analyzed. These FBP genes were sorted into two groups and seven subgroups. Results revealed that FBP family genes were under purifying selection pressure that rendered FBP family members as being conserved evolutionarily, and there was no tandem or fragmental DNA duplication in FBP family genes. Collinearity analysis revealed that a FBP gene was located in a translocated DNA fragment and the whole FBP gene family was under disequilibrium evolution that led to a faster evolutionary progress of the members in G. barbadense and in A_t subgenome than those in other Gossypium species and in the D_t subgenome, respectively, in this study. Through RNA-seq analyses and qRT-PCR verification, different FBP genes had diversified biological functions in cotton fiber development (two genes in 0 DPA and 1DPA ovules and four genes in 20–25 DPA fibers), in plant responses to Verticillium wilt onset (two genes) and to salt stress (eight genes).

Conclusion

The FBP gene family displayed a disequilibrium evolution pattern in Gossypium species, which led to diversified functions affecting not only fiber development, but also responses to Verticillium wilt and salt stress. All of these findings provide the foundation for further study of the function of FBP genes in cotton fiber development and in environmental adaptability.