Construction of a high-density genetic map and lint percentage and cottonseed nutrient trait QTL identification in upland cotton (Gossypium hirsutum L.)

Fertile grounds: exploring male sterility in cotton and its marker development

The high cost of producing conventional hybrid cotton seeds led to more research efforts on cotton male sterility systems. There is a lack of studies on cytology, histology, morphological variation, yield, and altered restorer backgrounds to identify and develop male sterility markers in cotton hybrids. Hybrid cotton can be efficiently produced by exploiting genetic male sterility. Among the 19 Genetic Male Sterility (GMS) genes discovered, the lines with ms5ms6 genes are mostly utilised to establish successful hybrid cotton in India. Molecular markers closely associated with the MS alleles are identified to facilitate the efficient and rapid backcrossing of male-sterility genes into elite lines or cultivars by marker-assisted backcrossing. The majority of the markers which are random DNA markers (RDMs), are probably lost, when recombination occurs. In contradiction, molecular markers (functional markers, or FMs) within the genic region can be identified and employed in crops for diverse traits, if prospective characteristic genes are known. In this review, the mechanism of male sterility, its gene expression level, and the need for functional markers for the male sterility trait in cotton have been put forward.

Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.)

KEY MESSAGE

A Bayesian linkage disequilibrium-based multiple-locus mixed model identified QTLs for fibre, seed and oil traits and predicted breeding worthiness of test lines, enabling their simultaneous improvement in cotton. Improving cotton seed and oil yields has become increasingly important while continuing to breed for higher lint yield. In this study, a novel Bayesian linkage disequilibrium-based multiple-locus mixed model was developed for QTL identification and genomic prediction (GP). A multi-parent population consisting of 256 recombinant inbred lines, derived from four elite cultivars with distinct combinations of traits, was used in the analysis of QTLs for lint percentage, seed index, lint index and seed oil content and their interrelations. All four traits were moderately heritable and correlated but with no large influence of genotype × environment interactions across multiple seasons. Seven to ten major QTLs were identified for each trait with many being adjacent or overlapping for different trait pairs. A fivefold cross-validation of the model indicated prediction accuracies of 0.46-0.62. GP results based on any two-season phenotypes were strongly correlated with phenotypic means of a pooled analysis of three-season experiments (r = 0.83-0.92). When used for selection of improvement in lint, seed and oil yields, GP captured 40-100% of individuals with comparable lint yields of those selected based on the three-season phenotypic results. Thus, this quantitative genomics-enabled approach can not only decipher the genomic variation underlying lint, seed and seed oil traits and their interrelations, but can provide predictions for their simultaneous improvement. We discuss future breeding strategies in cotton that will enhance the entire value of the crop, not just its fibre.

GhL1L1 regulates the contents of unsaturated fatty acids by activating the expression of GhFAD2 genes in cotton

Edible oils with high unsaturated fatty acids, particularly oleic acid, are beneficial to human health. Cotton is one of the top five oil crops in the world, but the mechanism of high-quality oil synthesis and regulatory networks in cotton are largely unclear. Here, we identified Leafy cotyledon1-like 1 (GhL1L1), a NF-YB subfamily gene that is specifically expressed during somatic embryogenesis and seed maturation in cotton. Overexpression of GhL1L1 regulates the contents of unsaturated fatty acids in cotton, especially in the seeds, which is associated with altered expression of the cotton fatty acid biosynthesis-related genes. GhL1L1 synergistically enhanced the expression of GhFAD2-1A by binding to the G-box in its promoter, leading to an increase in the content of linoleic acid. Furthermore, this activation could be enhanced by GhNF-YC2 and GhNF-YA1 by form a transcriptional complex. Collectively, these results contribute to provide new insights into the molecular mechanism of oil biosynthesis in cotton and can facilitate genetic manipulation of cotton varieties with enhanced oil content.

Genomic and co-expression network analyses reveal candidate genes for oil accumulation based on an introgression population in Upland cotton (Gossypium hirsutum)

KEY MESSAGE

Integrated QTL mapping and WGCNA condense the potential gene regulatory network involved in oil accumulation. A glycosyl hydrolases gene (GhHSD1) for oil biosynthesis was confirmed in Arabidopsis, which will provide useful knowledge to understand the functional mechanism of oil biosynthesis in cotton. Cotton is an economical source of edible oil for the food industry. The genetic mechanism that regulates oil biosynthesis in cottonseeds is essential for the genetic enhancement of oil content (OC). To explore the functional genomics of OC, this study utilized an interspecific backcross inbred line population to dissect the quantitative trait locus (QTL) interlinked with OC. In total, nine OC QTLs were identified, four of which were novel, and each QTL explained 3.62-34.73% of the phenotypic variation of OC. The comprehensive transcript profiling of developing cottonseeds revealed 3,646 core genes differentially expressed in both inbred parents. Functional enrichment analysis determined 43 genes were annotated with oil biosynthesis processes. Implementation of weighted gene co-expression network analysis showed that 803 differential genes had a significant correlation with the OC phenotype. Further integrated analysis identified seven important genes located in OC QTLs. Of which, the GhHSD1 gene located in stable QTL qOC-Dt3-1 exhibited the highest functional linkages with the other network genes. Phylogenetic analysis showed significant evolutionary differences in the HSD1 sequences between oilseed- and starch- crops. Furthermore, the overexpression of GhHSD1 in Arabidopsis yielded almost 6.78% higher seed oil. This study not only uncovers important genetic loci for oil accumulation in cottonseed, but also provides a set of new candidate genes that potentially influence the oil biosynthesis pathway in cottonseed.

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 association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Genetic dissection of lint percentage in short-season cotton using combined QTL mapping and RNA-seq

KEY MESSAGE

In total, 17 QTLs for lint percentage in short-season cotton, including three stable QTLs, were detected. Twenty-eight differentially expressed genes located within the stable QTLs were identified, and two genes were validated by qRT-PCR. The breeding and use of short-season cotton have significant values in addressing the question of occupying farmlands with either cotton or cereals. However, the fiber yields of short-season cotton varieties are significantly lower than those of middle- and late-maturing varieties. How to effectively improve the fiber yield of short-season cotton has become a focus of cotton research. Here, a high-density genetic map was constructed using genome resequencing and an RIL population generated from the hybridization of two short-season cotton accessions, Dong3 and Dong4. The map contained 4960 bin markers across the 26 cotton chromosomes and spanned 3971.08 cM, with an average distance of 0.80 cM between adjacent markers. Based on the genetic map, quantitative trait locus (QTL) mapping for lint percentage (LP, %), an important yield component trait, was performed. In total, 17 QTLs for LP, including three stable QTLs, qLP-A02, qLP-D04, and qLP-D12, were detected. Three out of 11 non-redundant QTLs overlapped with previously reported QTLs, whereas the other eight were novel QTLs. A total of 28 differentially expressed genes associated with the three stable QTLs were identified using RNA-seq of ovules and fibers at different seed developmental stages from the parental materials. The two genes, Ghir_A02G017640 and Ghir_A02G018500, may be related to LP as determined by further qRT-PCR validation. This study provides useful information for the genetic dissection of LP and promotes the molecular breeding of short-season cotton.

Unraveling genomic regions and candidate genes for multiple disease resistance in upland cotton using meta-QTL analysis

Verticillium wilt (VW), Fusarium wilt (FW) and Root-knot nematode (RKN) are the main diseases affecting cotton production. However, many reported quantitative trait loci (QTLs) for cotton resistance have not been used for agricultural practices because of inconsistencies in the cotton genetic background. The integration of existing cotton genetic resources can facilitate the discovery of important genomic regions and candidate genes involved in disease resistance. Here, an improved and comprehensive meta-QTL analysis was conducted on 487 disease resistant QTLs from 31 studies in the last two decades. A consensus linkage map with genetic overall length of 3006.59 cM containing 8650 markers was constructed. A total of 28 Meta-QTLs (MQTLs) were discovered, among which nine MQTLs were identified as related to resistance to multiple diseases. Candidate genes were predicted based on public transcriptome data and enriched in pathways related to disease resistance. This study used a method based on the integration of Meta-QTL, known genes and transcriptomics to reveal major genomic regions and putative candidate genes for resistance to multiple diseases, providing a new basis for marker-assisted selection of high disease resistance in cotton breeding.

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races

Lint percentage is one of the most essential yield components and an important economic index for cotton planting. Improving lint percentage is an effective way to achieve high-yield in cotton breeding worldwide, especially upland cotton (Gossypium hirsutum L.). However, the genetic basis controlling lint percentage has not yet been systematically understood. Here, we performed a genome-wide association mapping for lint percentage using a natural population consisting of 189 G. hirsutum accessions (188 accessions of G. hirsutum races and one cultivar TM-1). The results showed that 274 single-nucleotide polymorphisms (SNPs) significantly associated with lint percentage were detected, and they were distributed on 24 chromosomes. Forty-five SNPs were detected at least by two models or at least in two environments, and their 5 Mb up- and downstream regions included 584 makers related to lint percentage identified in previous studies. In total, 11 out of 45 SNPs were detected at least in two environments, and their 550 Kb up- and downstream region contained 335 genes. Through RNA sequencing, gene annotation, qRT-PCR, protein-protein interaction analysis, the cis-elements of the promotor region, and related miRNA prediction, Gh_D12G0934 and Gh_A08G0526 were selected as key candidate genes for fiber initiation and elongation, respectively. These excavated SNPs and candidate genes could supplement marker and gene information for deciphering the genetic basis of lint percentage and facilitate high-yield breeding programs of G. hirsutum ultimately.

Yellow Petal locus GaYP promotes flavonol biosynthesis and yellow coloration in petals of Asiatic cotton (Gossypium arboreum)

Yellow Petal locus GaYP is located on chromosome 11 and encodes a Sg6 R2R3-MYB transcription factor, which promotes flavonol biosynthesis and yellow coloration in Asiatic cotton petals. Petal color is pivotal to ornamental value and reproduction of plants. Yellow coloration in plant petals is mainly attributed to colorants including carotenoids, aurones and some flavonols. To date, the genetic regulatory mechanism of flavonol biosynthesis in petals is still to be elucidated. Here, we employed Asiatic cottons with or without deep yellow coloration in petals to address this question. Multi-omic and biochemical analysis revealed significantly up-regulated transcription of flavonol structural genes and increased levels of flavonols, especially gossypetin and 6-hydroxykaempferol, in yellow petals of Asiatic cotton. Furthermore, the Yellow Petal gene (GaYP) was mapped on chromosome 11 by using a recombinant inbred line population. It was found that GaYP encoded a transcriptional factor belonging to Sg6 R2R3-MYB proteins. GaYP could bind to the promoter of flavonol synthase gene (GaFLS) and activate the transcription of downstream genes. Knocking out of GaYP or GaFLS homologs in upland cotton largely eliminated flavonol accumulation and pale yellow coloration in petals. Our results indicated that flavonol synthesis, up-regulated by the R2R3-MYB transcription activator GaYP, was the causative factor for yellow coloration of Asiatic cotton petals. In addition, knocking out of GaYP homologs also led to decrease in anthocyanin accumulation and petal size in upland cotton, suggesting that GaYP and its homologs might modulate developmental or physiological processes beyond flavonol biosynthesis.

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.

Genome-wide association study reveals novel quantitative trait loci and candidate genes of lint percentage in upland cotton based on the CottonSNP80K array

Thirty-four SNPs corresponding with 22 QTLs for lint percentage, including 13 novel QTLs, was detected via GWAS. Two candidate genes underlying this trait were also identified. Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop cultivated worldwide. Lint percentage (LP, %) is one of the important yield components, and increasing LP is a core goal of cotton breeding improvement. However, the genetic and molecular mechanisms underlying LP in upland cotton remain unclear. Here, we performed a genome-wide association study (GWAS) for LP based on 254 upland cotton accessions in four environments as well as the best linear unbiased predictors using the high-density CottonSNP80K array. In total, 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened, and 34 SNPs within 22 quantitative trait loci (QTLs) were significantly associated with LP. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2), and 50 hub genes were identified through GO enrichment and weighted gene co-expression network analysis. Two candidate genes (Gh_D01G0162 and Gh_D07G0463), which may participate in early fiber development to affect the number of fiber protrusions and LP, were also identified. Their genetic variation and expression were verified by linkage disequilibrium blocks, haplotypes, and quantitative real-time polymerase chain reaction, respectively. The weighted gene interaction network analysis showed that the expression of Gh_D07G0463 was significantly correlated with that of Gh_D01G0162. These identified SNPs, QTLs and candidate genes provide important insights into the genetic and molecular mechanisms underlying variations in LP and serve as a foundation for LP improvement via marker-assisted breeding.

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.

Genetics, Breeding and Genetic Engineering to Improve Cottonseed Oil and Protein: A Review

Upland cotton (Gossypium hirsutum) is the world's leading fiber crop and one of the most important oilseed crops. Genetic improvement of cotton has primarily focused on fiber yield and quality. However, there is an increased interest and demand for enhanced cottonseed traits, including protein, oil, fatty acids, and amino acids for broad food, feed and biofuel applications. As a byproduct of cotton production, cottonseed is an important source of edible oil in many countries and could also be a vital source of protein for human consumption. The focus of cotton breeding on high yield and better fiber quality has substantially reduced the natural genetic variation available for effective cottonseed quality improvement within Upland cotton. However, genetic variation in cottonseed oil and protein content exists within the genus of Gossypium and cultivated cotton. A plethora of genes and quantitative trait loci (QTLs) (associated with cottonseed oil, fatty acids, protein and amino acids) have been identified, providing important information for genetic improvement of cottonseed quality. Genetic engineering in cotton through RNA interference and insertions of additional genes of other genetic sources, in addition to the more recent development of genome editing technology has achieved considerable progress in altering the relative levels of protein, oil, fatty acid profile, and amino acids composition in cottonseed for enhanced nutritional value and expanded industrial applications. The objective of this review is to summarize and discuss the cottonseed oil biosynthetic pathway and major genes involved, genetic basis of cottonseed oil and protein content, genetic engineering, genome editing through CRISPR/Cas9, and QTLs associated with quantity and quality enhancement of cottonseed oil and protein.

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.

Genetic Identification and Transcriptome Analysis of Lintless and Fuzzless Traits in Gossypium arboreum L

Cotton fibres, as single cells arising from the seed coat, can be classified as lint and fuzz according to their final length. Gossypium arboreum is a cultivated diploid cotton species and a potential donor of the A subgenome of the more widely grown tetraploid cottons. In this study, we performed genetic studies on one lintless and seven fuzzless G. arboreum accessions. Through association and genetic linkage analyses, a recessive locus on Chr06 containing GaHD-1 was found to be the likely gene underlying the lintless trait. GaHD-1 carried a mutation at a splicing acceptor site that resulted in alternative splicing and a deletion of 247 amino acid from the protein. The regions containing GaGIR1 and GaMYB25-like were found to be associated with fuzz development in G. arboreum, with the former being the major contributor. Comparative transcriptome analyses using 0-5 days post-anthesis (dpa) ovules from lintless, fuzzless, and normal fuzzy seed G. arboreum accessions revealed gene modules and hub genes potentially important for lint and fuzz initiation and development. Three significant modules and 26 hub genes associated with lint fibre initiation were detected by weighted gene co-expression network analysis. Similar analyses identified three vital modules and 10 hub genes to be associated with fuzz development. The findings in this study contribute to understanding the complex molecular mechanism(s) regulating fibre initiation and development and indicate that G. arboreum may have fibre developmental pathways different from tetraploid cotton. It also provides candidate genes for further investigation into modifying fibre development in G. arboreum.

Flavonoid accumulation in spontaneous cotton mutant results in red coloration and enhanced disease resistance

Cotton, the leading natural fiber, is cultivated worldwide, but its production is seriously threatened by pathogens. Accordingly, the selection of resistant cultivars has become a key priority of cotton breeding programs. In this study, a spontaneous mutant with red coloration (S156) and a control cultivar (S78) were used as experimental materials for a comparative analysis. Metabolomic analysis revealed the enrichment of flavonoids in S156 leaves compared with S78 leaves, and transcriptomic analysis revealed the upregulated expression of flavonoid biosynthesis genes in S156 leaves relative to S78 leaves. In addition, the red mutant showed a significantly increase in resistance to Verticillium dahliae, a fungal pathogen that poses a major threat to cotton production. The pathogen invasion process was suppressed in the red cotton cultivar. This study reveals the mechanism underlying the red coloration of S156 cotton and indicates the great potential of red cotton in pathogen- and insect-resistant breeding of cotton.

QTL analysis and candidate gene identification for plant height in cotton based on an interspecific backcross inbred line population of Gossypium hirsutum × Gossypium barbadense

We constructed the first high-quality and high-density genetic linkage map for an interspecific BIL population in cotton by specific-locus amplified fragment sequencing for QTL mapping. A novel gene GhPIN3 for plant height was identified in cotton. Ideal plant height (PH) is important for improving lint yield and mechanized harvesting in cotton. Most published genetic studies on cotton have focused on fibre yield and quality traits rather than PH. To facilitate the understanding of the genetic basis in PH, an interspecific backcross inbred line (BIL) population of 250 lines derived from upland cotton (Gossypium hirsutum L.) CRI36 and Egyptian cotton (G. barbadense L.) Hai7124 was used to construct a high-density genetic linkage map for quantitative trait locus (QTL) mapping. The high-density genetic map harboured 7,709 genotyping-by-sequencing (GBS)-based single nucleotide polymorphism (SNP) markers that covered 3,433.24 cM with a mean marker interval of 0.67 cM. In total, ten PH QTLs were identified and each explained 4.27-14.92% of the phenotypic variation, four of which were stable as they were mapped in at least two tests or based on best linear unbiased prediction in seven field tests. Based on functional annotation of orthologues in Arabidopsis and transcriptome data for the genes within the stable QTL regions, GhPIN3 encoding for the hormone auxin efflux carrier protein was identified as a candidate gene located in the stable QTL qPH-Dt1-1 region. A qRT-PCR analysis showed that the expression level of GhPIN3 in apical tissues was significantly higher in four short-statured cotton genotypes than that in four tall-statured cotton genotypes. Virus-induced gene silencing cotton has significantly increased PH when the expression of the GhPIN3 gene was suppressed.

Genome-wide association study of the oil content in upland cotton (Gossypium hirsutum L.) and identification of GhPRXR1, a candidate gene for a stable QTLqOC-Dt5-1

Cottonseed oil is one of the most important renewable resources for edible oil and biodiesel. To detect QTLs associated with cottonseed oil content (OC) and identify candidate genes that regulate oil biosynthesis, a panel of upland cotton germplasm lines was selected among those previously used to perform GWASs in China. In the present study, 13 QTLs associated with 53 common SNPs on 13 chromosomes were identified in multiple environments based on 15,369 polymorphic SNPs using the Cotton63 KSNP array. Of these, the OC QTL qOC-Dt5-1 delineated by nine SNPs occurred in a confidence interval of 4 SSRs with previously reported OC QTLs. A combined transcriptome and qRT-PCR analysis revealed that a peroxidase gene (GhPRXR1) was predominantly expressed during the middle-late stage (20-35 days post anthesis) of ovule development. The overexpression of GhPRXR1 in yeast significantly increased the OC by 20.01-37.25 %. Suppression of GhPRXR1 gene expression in the virus-induced gene-silenced cotton reduced the OC by 18.11%. Our results contribute to identifying more OC QTLs and verifying a candidate gene that influences cottonseed oil biosynthesis.

A high density SLAF-seq SNP genetic map and QTL for seed size, oil and protein content in upland cotton

BACKGROUND

Cotton is a leading natural fiber crop. Beyond its fiber, cottonseed is a valuable source of plant protein and oil. Due to the much higher value of cotton fiber, there is less consideration of cottonseed quality despite its potential value. Though some QTL controlling cottonseed quality have been identified, few of them that warrant further study are known. Identifying stable QTL controlling seed size, oil and protein content is necessary for improvement of cottonseed quality.

RESULTS

In this study, a recombinant inbred line (RIL) population was developed from a cross between upland cotton cultivars/lines Yumian 1 and M11. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to construct a genetic map that covered 3353.15 cM with an average distance between consecutive markers of 0.48 cM. The seed index, together with kernel size, oil and protein content were further used to identify QTL. In total, 58 QTL associated with six traits were detected, including 13 stable QTL detected in all three environments and 11 in two environments.

CONCLUSION

A high resolution genetic map including 7033 SNP loci was constructed through specific locus amplified fragment sequencing technology. A total of 13 stable QTL associated with six cottonseed quality traits were detected. These stable QTL have the potential for fine mapping, identifying candidate genes, elaborating molecular mechanisms of cottonseed development, and application in cotton breeding programs.

QTL analysis for yield and fibre quality traits using three sets of introgression lines developed from three Gossypium hirsutum race stocks

Upland cotton (Gossypium hirsutum L.) race stocks may possess desirable traits for the genetic improvement of cotton. Quantitative trait locus (QTL) analysis can assist in uncovering new alleles from unadapted race stocks. In this study, three sets of chromosome segment introgression lines (ILs) were developed from three backcrosses (BC₃) between three race stocks, G. hirsutum races latifolium accs. TX-34 and TX-48 and punctatum acc. TX-114, as donor parents and Texas Marker-1 (TM-1) as the recurrent parent. Based on a total of 452 polymorphic simple sequence repeat (SSR) markers in BC₃F₂ genotyping, 149, 150 and 184 ILs were obtained from TM-1 × TX-34, TM-1 × TX-48 and TM-1 × TX-114, respectively. The average introgressed chromosomal segment length was 12.7 cM, and the total genetic distance was 3268 cM covering approximately 73.4% of the Upland cotton genome. The BC₃F₂, BC₃F_2:3 and BC₃F_2:4 progeny, which produced the ILs, were evaluated for yield and fibre quality traits. A total of 128 QTLs were detected, each of which explained 1.6-13.0% of the phenotypic variation. Thirty-five common QTLs related to eight traits were detected. Six QTL clusters were found on five chromosomes. Thirty-eight QTLs were previously unreported, and they may be footprints of cotton domestication. Domestication or artificial selection by humans successfully eliminated most unfavourable QTLs (21/38); however, some favourable QTLs (17/38) are not present in modern cultivars, demonstrating the importance of race stocks for improving cotton cultivars. The 26 elite ILs developed could be used to improve the yield and fibre quality components simultaneously. These results provide information on desirable QTLs for cotton improvement.

A high density SLAF-SNP genetic map and QTL detection for fibre quality traits in Gossypium hirsutum

Background

Upland Cotton (Gossypium hirsutum) is a very important cash crop known for its high quality natural fiber. Recent advances in sequencing technologies provide powerful tools with which to explore the cotton genome for single nucleotide polymorphism marker identification and high density genetic map construction toward more reliable quantitative trait locus mapping.

Results

In the present study, a RIL population was developed by crossing a Chinese high fiber quality cultivar (Yumian 1) and an American high fiber quality line (CA3084), with distinct genetic backgrounds. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to discover SNPs, and a genetic map containing 6254 SNPs was constructed, covering 3141.72 cM with an average distance of 0.5 cM between markers. A total of 95 QTL were detected for fiber quality traits in three environments, explaining 5.5-24.6% of the phenotypic variance. Fifty-five QTL found in multiple environments were considered stable QTL. Nine of the stable QTL were found in all three environments. We identified 14 QTL clusters on 13 chromosomes, each containing one or more stable QTL.

Conclusion

A high-density genetic map of Gossypium hirsutum developed by using specific locus amplified fragment sequencing technology provides detailed mapping of fiber quality QTL, and identification of ‘stable QTL’ found in multiple environments. A marker-rich genetic map provides a foundation for fine mapping, candidate gene identification and marker-assisted selection of favorable alleles at stable QTL in breeding programs.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5294-5) contains supplementary material, which is available to authorized users.

Genome-Wide Association Study Identifies Candidate Genes Related to Seed Oil Composition and Protein Content in Gossypium hirsutum L

Cotton (Gossypium spp.) is a leading natural fiber crop and an important source of vegetable protein and oil for humans and livestock. To investigate the genetic architecture of seed nutrients in upland cotton, a genome-wide association study (GWAS) was conducted in a panel of 196 germplasm resources under three environments using a CottonSNP80K chip of 77,774 loci. Relatively high genetic diversity (average gene diversity being 0.331) and phenotypic variation (coefficient of variation, CV, exceeding 3.9%) were detected in this panel. Correlation analysis revealed that the well-documented negative association between seed protein (PR) and oil may be to some extent attributable to the negative correlation between oleic acid (OA) and PR. Linkage disequilibrium (LD) was unevenly distributed among chromosomes and subgenomes. It ranged from 0.10-0.20 Mb (Chr19) to 5.65-5.75 Mb (Chr25) among the chromosomes and the range of Dt-subgenomes LD decay distances was smaller than At-subgenomes. This panel was divided into two subpopulations based on the information of 41,815 polymorphic single-nucleotide polymorphism (SNP) markers. The mixed linear model considering both Q-matrix and K-matrix [MLM(Q+K)] was employed to estimate the association between the SNP markers and the seed nutrients, considering the false positives caused by population structure and the kinship. A total of 47 SNP markers and 28 candidate quantitative trait loci (QTLs) regions were found to be significantly associated with seven cottonseed nutrients, including protein, total fatty acid, and five main fatty acid compositions. In addition, the candidate genes in these regions were analyzed, which included three genes, Gh_D12G1161, Gh_D12G1162, and Gh_D12G1165 that were most likely involved in the control of cottonseed protein concentration. These results improved our understanding of the genetic control of cottonseed nutrients and provided potential molecular tools to develop cultivars with high protein and improved fatty acid compositions in cotton breeding programs through marker-assisted selection.

GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.

Genetic Map Construction and Fiber Quality QTL Mapping Using the CottonSNP80K Array in Upland Cotton

Cotton fiber quality traits are controlled by multiple quantitative trait loci (QTL), and the improvement of these traits requires extensive germplasm. Herein, an Upland cotton cultivar from America, Acala Maxxa, was crossed with a local high fiber quality cultivar, Yumian 1, and 180 recombinant inbred lines (RILs) were obtained. In order to dissect the genetic basis of fiber quality differences between these parents, a genetic map containing 12116 SNP markers was constructed using the CottonSNP80K assay, which covered 3741.81 cM with an average distance of 0.31 cM between markers. Based on the genetic map and growouts in three environments, we detected a total of 104 QTL controlling fiber quality traits. Among these QTL, 25 were detected in all three environments and 35 in two environments. Meanwhile, 19 QTL clusters were also identified, and nine contained at least one stable QTL (detected in three environments for a given trait). These stable QTL or QTL clusters are priorities for fine mapping, identifying candidate genes, elaborating molecular mechanisms of fiber development, and application in cotton breeding programs by marker-assisted selection (MAS).

High-density genetic linkage map construction by F2 populations and QTL analysis of early-maturity traits in upland cotton (Gossypium hirsutum L.)

Due to China’s rapidly increasing population, the total arable land area has dramatically decreased; as a consequence, the competition for farming land allocated for grain and cotton production has become fierce. Therefore, to overcome the existing contradiction between cotton grain and fiber production and the limited farming land, development of early-maturing cultivars is necessary. In this research, a high-density linkage map of upland cotton was constructed using genotyping by sequencing (GBS) to discover single nucleotide polymorphism (SNP) markers associated with early maturity in 170 F₂ individuals derived from a cross between LU28 and ZHONG213. The high-density genetic map, which was composed of 3978 SNP markers across the 26 cotton chromosomes, spanned 2480 cM with an average genetic distance of 0.62 cM. Collinearity analysis showed that the genetic map was of high quality and accurate and agreed well with the Gossypium hirsutum reference genome. Based on this high-density linkage map, QTL analysis was performed on cotton early-maturity traits, including FT, FBP, WGP, NFFB, HNFFB and PH. A total 47 QTLs for the six traits were detected; each of these QTLs explained between 2.61% and 32.57% of the observed phenotypic variation. A major region controlling early-maturity traits in Gossypium hirsutum was identified for FT, FBP, WGP, NFFB and HNFFB on chromosome D03. QTL analyses revealed that phenotypic variation explained (PVE) ranged from 10.42% to 32.57%. Two potential candidate genes, Gh_D03G0885 and Gh_D03G0922, were predicted in a stable QTL region and had higher expression levels in the early-maturity variety ZHONG213 than in the late-maturity variety LU28. However, further evidence is required for functional validation. This study could provide useful information for the dissection of early-maturity traits and guide valuable genetic loci for molecular-assisted selection (MAS) in cotton breeding.

Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.)

Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.

Construction of a high-density genetic map and the X/Y sex-determining gene mapping in spinach based on large-scale markers developed by specific-locus amplified fragment sequencing (SLAF-seq)

Background

Cultivated spinach (Spinacia oleracea L.) is one of the most widely cultivated types of leafy vegetable in the world, and it has a high nutritional value. Spinach is also an ideal plant for investigating the mechanism of sex determination because it is a dioecious species with separate male and female plants. Some reports on the sex labeling and localization of spinach in the study of molecular markers have surfaced. However, there have only been two reports completed on the genetic map of spinach. The lack of rich and reliable molecular markers and the shortage of high-density linkage maps are important constraints in spinach research work. In this study, a high-density genetic map of spinach based on the Specific-locus Amplified Fragment Sequencing (SLAF-seq) technique was constructed; the sex-determining gene was also finely mapped.

Results

Through bio-information analysis, 50.75 Gb of data in total was obtained, including 207.58 million paired-end reads. Finally, 145,456 high-quality SLAF markers were obtained, with 27,800 polymorphic markers and 4080 SLAF markers were finally mapped onto the genetic map after linkage analysis. The map spanned 1,125.97 cM with an average distance of 0.31 cM between the adjacent marker loci. It was divided into 6 linkage groups corresponding to the number of spinach chromosomes. Besides, the combination of Bulked Segregation Analysis (BSA) with SLAF-seq technology(super-BSA) was employed to generate the linkage markers with the sex-determining gene. Combined with the high-density genetic map of spinach, the sex-determining gene X/Y was located at the position of the linkage group (LG) 4 (66.98 cM–69.72 cM and 75.48 cM–92.96 cM), which may be the ideal region for the sex-determining gene.

Conclusions

A high-density genetic map of spinach based on the SLAF-seq technique was constructed with a backcross (BC₁) population (which is the highest density genetic map of spinach reported at present). At the same time, the sex-determining gene X/Y was mapped to LG4 with super-BSA. This map will offer a suitable basis for further study of spinach, such as gene mapping, map-based cloning of Specific genes, quantitative trait locus (QTL) mapping and marker-assisted selection (MAS). It will also provide an efficient reference for studies on the mechanism of sex determination in other dioecious plants.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3659-9) contains supplementary material, which is available to authorized users.

Identification of genes related to salt stress tolerance using intron-length polymorphic markers, association mapping and virus-induced gene silencing in cotton

Intron length polymorphisms (ILPs), a type of gene-based functional marker, could themselves be related to the particular traits. Here, we developed a genome-wide cotton ILPs based on orthologs annotation from two sequenced diploid species, A-genome Gossypium arboreum and D-genome G. raimondii. We identified 10,180 putative ILP markers from 5,021 orthologous genes. Among these, 535 ILP markers from 9 gene families related to stress were selected for experimental verification. Polymorphic rates were 72.71% between G. arboreum and G. raimondii and 36.45% between G. hirsutum acc. TM-1 and G. barbadense cv. Hai7124. Furthermore, 14 polymorphic ILP markers were detected in 264 G. hirsutum accessions. Coupled with previous simple sequence repeats (SSRs) evaluations and salt tolerance assays from the same individuals, we found a total of 25 marker-trait associations involved in nine ILPs. The nine genes, temporally named as C1 to C9, showed the various expressions in different organs and tissues, and five genes (C3, C4, C5, C7 and C9) were significantly upregulated after salt treatment. We verified that the five genes play important roles in salt tolerance. Particularly, silencing of C4 (encodes WRKY DNA-binding protein) and C9 (encodes Mitogen-activated protein kinase) can significantly enhance cotton susceptibility to salt stress.

Genetic Analysis and QTL Detection on Fiber Traits Using Two Recombinant Inbred Lines and Their Backcross Populations in Upland Cotton

Cotton fiber, a raw natural fiber material, is widely used in the textile industry. Understanding the genetic mechanism of fiber traits is helpful for fiber quality improvement. In the present study, the genetic basis of fiber quality traits was explored using two recombinant inbred lines (RILs) and corresponding backcross (BC) populations under multiple environments in Upland cotton based on marker analysis. In backcross populations, no significant correlation was observed between marker heterozygosity and fiber quality performance and it suggested that heterozygosity was not always necessarily advantageous for the high fiber quality. In two hybrids, 111 quantitative trait loci (QTL) for fiber quality were detected using composite interval mapping, in which 62 new stable QTL were simultaneously identified in more than one environment or population. QTL detected at the single-locus level mainly showed additive effect. In addition, a total of 286 digenic interactions (E-QTL) and their environmental interactions [QTL × environment interactions (QEs)] were detected for fiber quality traits by inclusive composite interval mapping. QE effects should be considered in molecular marker-assisted selection breeding. On average, the E-QTL explained a larger proportion of the phenotypic variation than the main-effect QTL did. It is concluded that the additive effect of single-locus and epistasis with few detectable main effects play an important role in controlling fiber quality traits in Upland cotton.

Genome-Wide SNP Linkage Mapping and QTL Analysis for Fiber Quality and Yield Traits in the Upland Cotton Recombinant Inbred Lines Population

It is of significance to discover genes related to fiber quality and yield traits and tightly linked markers for marker-assisted selection (MAS) in cotton breeding. In this study, 188 F8 recombinant inbred lines (RILs), derived from a intraspecific cross between HS46 and MARCABUCAG8US-1-88 were genotyped by the cotton 63K single nucleotide polymorphism (SNP) assay. Field trials were conducted in Sanya, Hainan Province, during the 2014-2015 cropping seasons under standard conditions. Results revealed significant differences (P < 0.05) among RILs, environments and replications for fiber quality and yield traits. Broad-sense heritabilities of all traits including fiber length, fiber uniformity, micronaire, fiber elongation, fiber strength, boll weight, and lint percentage ranged from 0.26 to 0.66. A 1784.28 cM (centimorgans) linkage map, harboring 2618 polymorphic SNP markers, was constructed, which had 0.68 cM per marker density. Seventy-one quantitative trait locus (QTLs) for fiber quality and yield traits were detected on 21 chromosomes, explaining 4.70∼32.28% phenotypic variance, in which 16 were identified as stable QTLs across two environments. Meanwhile, 12 certain regions were investigated to be involved in the control of one (hotspot) or more (cluster) traits, mainly focused on Chr05, Chr09, Chr10, Chr14, Chr19, and Chr20. Nineteen pairs of epistatic QTLs (e-QTLs) were identified, of which two pairs involved in two additive QTLs. These additive QTLs, e-QTLs, and QTL clusters were tightly linked to SNP markers, which may serve as target regions for map-based cloning, gene discovery, and MAS in cotton breeding.

Mapping of fiber quality QTLs reveals useful variation and footprints of cotton domestication using introgression lines

Fiber quality improvement is a driving force for further cotton domestication and breeding. Here, QTLs for fiber quality were mapped in 115 introgression lines (ILs) first developed from two intraspecific populations of cultivated and feral cotton landraces. A total of 60 QTLs were found, which explained 2.03–16.85% of the phenotypic variance found in fiber quality traits. A total of 36 markers were associated with five fiber traits, 33 of which were found to be associated with QTLs in multiple environments. In addition, nine pairs of common QTLs were identified; namely, one pair of QTLs for fiber elongation, three pairs for fiber length, three pairs for fiber strength and two pairs for micronaire (qMICs). All common QTLs had additive effects in the same direction in both IL populations. We also found five QTL clusters, allowing cotton breeders to focus their efforts on regions of QTLs with the highest percentages of phenotypic variance. Our results also reveal footprints of domestication; for example, fourteen QTLs with positive effects were found to have remained in modern cultivars during domestication, and two negative qMICs that had never been reported before were found, suggesting that the qMICs regions may be eliminated during artificial selection.

Fine mapping and RNA-Seq unravels candidate genes for a major QTL controlling multiple fiber quality traits at the T1 region in upland cotton

BACKGROUND

Improving fiber quality is a major challenge in cotton breeding, since the molecular basis of fiber quality traits is poorly understood. Fine mapping and candidate gene prediction of quantitative trait loci (QTL) controlling cotton fiber quality traits can help to elucidate the molecular basis of fiber quality. In our previous studies, one major QTL controlling multiple fiber quality traits was identified near the T1 locus on chromosome 6 in Upland cotton.

RESULTS

To finely map this major QTL, the F2 population with 6975 individuals was established from a cross between Yumian 1 and a recombinant inbred line (RIL118) selected from a recombinant inbred line population (T586 × Yumian 1). The QTL was mapped to a 0.28-cM interval between markers HAU2119 and SWU2302. The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively. The QTL region corresponded to a 2.7-Mb interval on chromosome 10 in the G. raimondii genome sequence and a 5.3-Mb interval on chromosome A06 in G. hirsutum. The fiber of Yumian 1 was much longer than that of RIL118 from 3 DPA to 7 DPA. RNA-Seq of ovules at 0 DPA and fibers at 5 DPA from Yumian 1 and RIL118 showed four genes in the QTL region of the G. raimondii genome to be extremely differentially expressed. RT-PCR analysis showed three genes in the QTL region of the G. hirsutum genome to behave similarly.

CONCLUSIONS

This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis. Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population

BACKGROUND

The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles.

RESULTS

The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton.

CONCLUSION

Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.

Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population

BACKGROUND

The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles.

RESULTS

The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0.92), fiber micronaire (0.85), and fiber uniformity (0.80), but low for fiber elongation (0.27). Meta-clusters on c4, c7, c14 and c25 were identified as stable QTL clusters and were considered more valuable in MAS for the improvement of fiber quality of upland cotton.

CONCLUSION

Multiple environmental evaluations of an intraspecific RIL population were conducted to identify stable QTLs. Meta-QTL analyses identified a common chromosomal region that plays an important role in fiber development. Therefore, QTLs identified in the present study are an ideal candidate for MAS in cotton breeding programs to improve fiber quality.

Detection of Favorable QTL Alleles and Candidate Genes for Lint Percentage by GWAS in Chinese Upland Cotton

Improving cotton yield is a major breeding goal for Chinese upland cotton. Lint percentage is an important yield component and a critical economic index for cotton cultivars, and raising the lint percentage has a close relationship to improving cotton lint yield. To investigate the genetic architecture of lint percentage, a diversity panel consisting of 355 upland cotton accessions was grown, and the lint percentage was measured in four different environments. Genotyping was performed with specific-locus amplified fragment sequencing (SLAF-seq). Twelve single-nucleotide polymorphisms (SNPs) associated with lint percentage were detected via a genome-wide association study (GWAS), in which five SNP loci distributed on chromosomes A_t3 (A02) and A_t4 (A08) and contained two major-effect QTLs, which were detected in the best linear unbiased predictions (BLUPs) and in more than three environments simultaneously. Furthermore, favorable haplotypes (FHs) of two major-effect QTLs and 47 putative candidate genes in the two linkage disequilibrium (LD) blocks of these associated loci were identified. The expression levels of these putative candidate genes were estimated using RNA-seq data from ten upland cotton tissues. We found that Gh_A02G1268 was very highly expressed during the early fiber development stage, whereas the gene was poorly expressed in the seed. These results implied that Gh_A02G1268 may determine the lint percentage by regulating seed and fiber development. The favorable QTL alleles and candidate genes for lint percentage identified in this study will have high potential for improving lint yield in future Chinese cotton breeding programs.