A genome-wide association study of early-maturation traits in upland cotton based on the CottonSNP8oK array

Genome-wide association studies(GWASs)efficiently identify genetic loci controlling traits at a relatively high resolution.In this study,variations in major early-maturation traits,including seedling period(SP),bud period(BP),flower and boll period(FBP),and growth period(GP),of 169 upland cotton accessions were investigated,and a GWAS of early maturation was performed based on a CottonSNP80K array.A total of49,650 high-quality single-nucleotide polymorphisms(SNPs)were screened,and 29 significant SNPs located on chromosomes A6,A7,A8,D1,D2,and D9,were repeatedly identified as associated with early-maturation traits,in at least two environments or two algorithms.Of these 29 significant SNPs,1,12,11,and 5 were related to SP,BP,FBP,and GP,respectively.Six peak SNPs,TM47967,TM13732,TM20937,TM28428,TM50283,and TM72552,exhibited phenotypic contributions of approximately 10%,which could allow them to be used for marker-assisted selection.One of these,TM72552,as well as four other SNPs,TM72554,TM72555,TM72558,and TM72559,corresponded to the quantitative trait loci previously reported.In total,274 candidate genes were identified from the genome sequences of upland cotton and were categorized based on their functional annotations.Finally,our studies identified Gh_D01G0340 and Gh_D01G0341 as potential candidate genes for improving cotton early maturity.     

Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome‐wide association study using high‐density SNPs

Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.     

A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton

Key message

A total of 62 SNPs associated with yield-related traits were identified by a GWAS. Based on significant SNPs, two candidate genes pleiotropically increase lint yield.

Abstract

Improved fibre yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. To better decipher the molecular mechanism underlying these traits, we conducted a genome-wide association study to determine candidate loci associated with six yield-related traits in a population of 719 upland cotton germplasm accessions; to accomplish this, we used 10,511 single-nucleotide polymorphisms (SNPs) genotyped by an Illumina CottonSNP63K array. Six traits, including the boll number, boll weight, lint percentage, fruit branch number, seed index and lint index, were assessed in multiple environments; large variation in all phenotypes was detected across accessions. We identified 62 SNP loci that were significantly associated with different traits on chromosomes A07, D03, D05, D09, D10 and D12. A total of 689 candidate genes were screened, and 27 of them contained at least one significant SNP. Furthermore, two genes (Gh_D03G1064 and Gh_D12G2354) that pleiotropically increase lint yield were identified. These identified SNPs and candidate genes provide important insights into the genetic control underlying high yields in G. hirsutum, ultimately facilitating breeding programmes of high-yielding cotton.

     

Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton

Key message

Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton.

Abstract

A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.

     

Identification of candidate genes for key fibre‐related QTLs and derivation of favourable alleles in Gossypium hirsutum recombinant inbred lines with G. barbadense introgressions

Fine mapping QTLs and identifying candidate genes for cotton fibre‐quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high‐density genetic map by specific‐locus amplified fragment sequencing (SLAF‐seq) to identify QTLs associated with fibre‐quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high‐yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre‐quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF‐based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co‐located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre‐related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre‐length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint‐percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre‐related traits and would be helpful for cloning fibre‐development‐related genes as well as for marker‐assisted genetic improvement in cotton.     

Genomic analyses reveal the genetic basis of early maturity and identification of loci and candidate genes in upland cotton (Gossypium hirsutum L.)

Although upland cotton (Gossypium hirsutism L.) originated in the tropics, this early maturity cotton can be planted as far north as 46°N in China due to the accumulation of numerous phenotypic and physiological adaptations during domestication. However, how the genome of early maturity cotton has been altered by strong human selection remains largely unknown. Herein, we report a cotton genome variation map generated by the resequencing of 436 cotton accessions. Whole‐genome scans for sweep regions identified 357 putative selection sweeps covering 4.94% (112 Mb) of the upland cotton genome, including 5184 genes. These genes were functionally related to flowering time control, hormone catabolism, ageing and defence response adaptations to environmental changes. A genome‐wide association study (GWAS) for seven early maturity traits identified 307 significant loci, 22.48% (69) of which overlapped with putative selection sweeps that occurred during the artificial selection of early maturity cotton. Several previously undescribed candidate genes associated with early maturity were identified by GWAS. This study provides insights into the genetic basis of early maturity in upland cotton as well as breeding resources for cotton improvement.     

Population genomics reveals a fine‐scale recombination landscape for genetic improvement of cotton

Recombination breaks up ancestral linkage disequilibrium, creates combinations of alleles, affects the efficiency of natural selection, and plays a major role in crop domestication and improvement. However, there is little knowledge regarding the variation in the population‐scaled recombination rate in cotton. We constructed recombination maps and characterized the difference in the genomic landscape of the population‐scaled recombination rate between Gossypium hirsutum and G. arboreum and sub‐genomes based on the 381 sequenced G. hirsutum and 215 G. arboreum accessions. Comparative genomics identified large structural variations and syntenic genes in the recombination regions, suggesting that recombination was related to structural variation and occurred preferentially in the distal chromosomal regions. Correlation analysis indicated that recombination was only slightly affected by geographical distribution and breeding period. A genome‐wide association study (GWAS) was performed with 15 agronomic traits using 267 cotton accessions and identified 163 quantitative trait loci (QTL) and an important candidate gene (Ghir_COL2) for early maturity traits. Comparative analysis of recombination and a GWAS revealed that the QTL of fibre quality traits tended to be more common in high‐recombination regions than were those of yield and early maturity traits. These results provide insights into the population‐scaled recombination landscape, suggesting that recombination contributed to the domestication and improvement of cotton, which provides a useful reference for studying recombination in other species.     

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

Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty‐seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA‐Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu‐chr13‐2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.     

Evidence for the genetic basis and epistatic interactions underlying ocean‐ and river‐maturing ecotypes of Pacific Lamprey (Entosphenus tridentatus) returning to the Klamath River,California

Surveys of genomic variation have improved our understanding of the relationship between fitness‐related phenotypes and their underlying genetic basis. In some cases, single large‐effect genes have been found to underlie important traits; however, complex traits are expected to be under polygenic control and elucidation of multiple gene interactions may be required to fully understand the genetic basis of the trait. In this study, we investigated the genetic basis of the ocean‐ and river‐maturing ecotypes in anadromous Pacific lamprey (Entosphenus tridentatus). In Pacific lamprey, the ocean‐maturing ecotype is distinguished by advanced maturity of females (e.g., large egg mass) at the onset of freshwater migration relative to immature females of the river‐maturing ecotype. We examined a total of 219 adult Pacific lamprey that were collected at‐entry to the Klamath River over a 12‐month period. Each individual was genotyped at 308 SNPs representing known neutral and adaptive loci and measured at morphological traits, including egg mass as an indicator of ocean‐ and river‐maturing ecotype for females. The two ecotypes did not exhibit genetic structure at 148 neutral loci, indicating that ecotypic diversity exists within a single population. In contrast, we identified the genetic basis of maturation ecotypes in Pacific lamprey as polygenic, involving two unlinked gene regions that have a complex epistatic relationship. Importantly, these gene regions appear to show stronger effects when considered in gene interaction models than if just considered additive, illustrating the importance of considering epistatic effects and gene networks when researching the genetic basis of complex traits in Pacific lamprey and other species.     

Genomic divergence in cotton germplasm related to maturity and heterosis

Commercial varieties of upland cotton(Gossypium hirsutum) have undergone extensive breeding for agronomic traits, such as fiber quality, disease resistance,and yield. Cotton breeding programs have widely used Chinese upland cotton source germplasm(CUCSG) with excellent agronomic traits. A better understanding of the genetic diversity and genomic characteristics of these accessions could accelerate the identification of desirable alleles. Here, we analyzed 10,522 high-quality singlenucleotide polymorphisms(SNP) with the CottonSNP63 K microarray in 137 cotton accessions(including 12 hybrids of upland cotton). These data were used to investigate the genetic diversity, population structure,and genomic characteristics of each population and the contribution of these loci to heterosis. Three subgroups were identified, in agreement with their knownpedigrees, geographical distributions, and times since introduction. For each group, we identified lineagespecific genomic divergence regions, which potentially harbor key alleles that determine the characteristics of each group, such as early maturity-related loci. Investigation of the distribution of heterozygous loci, among 12 commercial cotton hybrids, revealed a potential role for these regions in heterosis. Our study provides insight into the population structure of upland cotton germplasm. Furthermore, the overlap between lineagespecific regions and heterozygous loci, in the high-yield hybrids, suggests a role for these regions in cotton heterosis.     

QTL mapping of yield and fiber traits based on a four-way cross population in <Emphasis Type="Italic">Gossypium hirsutum</Emphasis> L.

Four-way cross (4WC) involving four different inbred lines frequently appears in the cotton breeding programs. However, linkage analysis and quantitative trait loci (QTL) mapping with molecular markers in cotton has largely been applied to populations derived from a cross between two inbred lines, and few results of QTL dissection were conducted in a 4WC population. In this study, an attempt was made to construct a linkage map and identify QTL for yield and fiber quality traits in 4WC derived from four different inbred lines in Gossypium hirsutum L. A linkage map was constructed with 285 SSR loci and one morphological locus, covering 2113.3 cM, approximately 42% of the total recombination length of the cotton genome. A total of 31 QTL with 5.1–25.8% of the total phenotypic variance explained were detected. Twenty-four common QTL across environments showed high stability, and six QTL were environment-specific. Several genomic segments affecting multiple traits were identified. The advantage of QTL mapping using a 4WC were discussed. This study presents the first example of QTL mapping using a 4WC population in upland cotton. The results presented here will enhance the understanding of the genetic basis of yield and fiber quality traits and enable further marker-assisted selection in cultivar populations in upland cotton.     

Insights into the genetic history of Green‐legged Partridgelike fowl: mtDNA and genome‐wide SNP analysis

The Green‐legged Partridgelike (GP) fowl, an old native Polish breed, is characterised by reseda green‐coloured shanks rather than yellow, white, slate or black commonly observed across most domestic breeds of chicken. Here, we investigate the origin, genetic relationships and structure of the GP fowl using mtDNA D‐loop sequencing and genome‐wide SNP analysis. Genome‐wide association analysis between breeds enables us to verify the genetic control of the reseda green shank phenotype, a defining trait for the breed. Two mtDNA D‐loop haplogroups and three autosomal genetic backgrounds are revealed. Significant associations of SNPs on chromosomes GGA24 and GGAZ indicate that the reseda green leg phenotype is associated with recessive alleles linked to the W and Id loci. Our results provide new insights into the genetic history of European chicken, indicating an admixd origin of East European traditional breeds of chicken on the continent, as supported by the presence of the reseda green phenotype and the knowledge that the GP fowl as a breed was developed before the advent of commercial stocks.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small‐effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine‐spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL‐mapping approaches based on a de‐biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL‐mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single‐locus analyses of an F₂ interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1–6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small‐effect loci. Apart from suggesting moderately heritable (h² ≈ 0.15–0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL‐mapping approach developed here has distinctive advantages over the traditional QTL‐mapping methods in analyses of dense marker panels.     

Time‐specific and pleiotropic quantitative trait loci coordinately modulate stem growth in Populus

In perennial woody plants, the coordinated increase of stem height and diameter during juvenile growth improves competitiveness (i.e. access to light); however, the factors underlying variation in stem growth remain unknown in trees. Here, we used linkage‐linkage disequilibrium (linkage‐LD) mapping to decipher the genetic architecture underlying three growth traits during juvenile stem growth. We used two Populus populations: a linkage mapping population comprising a full‐sib family of 1,200 progeny and an association mapping panel comprising 435 unrelated individuals from nearly the entire natural range of Populus tomentosa. We mapped 311 quantitative trait loci (QTL) for three growth traits at 12 timepoints to 42 regions in 17 linkage groups. Of these, 28 regions encompassing 233 QTL were annotated as 27 segmental homology regions (SHRs). Using SNPs identified by whole‐genome re‐sequencing of the 435‐member association mapping panel, we identified significant SNPs (P ≤ 9.4 × 10^?7) within 27 SHRs that affect stem growth at nine timepoints with diverse additive and dominance patterns, and these SNPs exhibited complex allelic epistasis over the juvenile growth period. Nineteen genes linked to potential causative alleles that have time‐specific or pleiotropic effects, and mostly overlapped with significant signatures of selection within SHRs between climatic regions represented by the association mapping panel. Five genes with potential time‐specific effects showed species‐specific temporal expression profiles during the juvenile stages of stem growth in five representative Populus species. Our observations revealed the importance of considering temporal genetic basis of complex traits, which will facilitate the molecular design of tree ideotypes.     

陆地棉主要产量相关性状的SSR标记关联分析

高产优质育种是我国棉花育种的主要目标。寻找与目标性状关联的分子标记,可克服常规育种的盲目性,提高分子标记辅助选择育种的准确性。本研究对118份陆地棉种质资源的衣分、单铃重、单株铃数及子指等4个产量相关性状进行2年2点的表型鉴定,并利用覆盖全基因组的、有多态性的214对SSR标记进行标记与性状的关联分析。结果表明:118份材料的4个产量相关性状表型变异丰富,平均变异系数的变幅在6.1%~19.1%之间,且在各环境中表现较为稳定;基因型分析表明,214对标记共检测到460个等位变异,基因多样性指数平均为0.5151,PIC值平均为0.4587,表明该批标记具有较多的等位变异数和较高的基因多样性;群体结构分析表明该批材料可分为4个亚群,且各类群中材料与地理来源无对应关系;关联分析结果显示,在显著条件下(-log10P1.3,P0.05),共有39个标记位点能够在2个及2个以上的环境中同时检测到,其中有4个标记位点同时与2个以上性状相关联,进一步比较发现,有7个位点与前人研究结果一致,其余32个位点为新发现的位点。研究结果可为陆地棉产量性状遗传改良的分子标记辅助选择提供理论依据。     

Detection of favorable alleles for yield and yield components by association mapping in upland cotton

Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(??lgP?>?1.30, P?<?0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.     

Screening of abiotic stress‐responsive cotton genes using a cotton full‐length cDNA overexpressing Arabidopsis library

Cotton (Gossypium hirsutum L.) is a major crop and the main source of natural fiber worldwide. Because various abiotic and biotic stresses strongly influence cotton fiber yield and quality, improved stress resistance of this crop plant is urgently needed. In this study, we used Gateway technology to construct a normalized full‐length cDNA overexpressing (FOX) library from upland cotton cultivar ZM12 under various stress conditions. The library was transformed into Arabidopsis to produce a cotton‐FOX‐Arabidopsis library. Screening of this library yielded 6,830 transgenic Arabidopsis lines, of which 757 were selected for sequencing to ultimately obtain 659 cotton ESTs. GO and KEGG analyses mapped most of the cotton ESTs to plant biological process, cellular component, and molecular function categories. Next, 156 potential stress‐responsive cotton genes were identified from the cotton‐FOX‐Arabidopsis library under drought, salt, ABA, and other stress conditions. Four stress‐related genes identified from the library, designated as GhCAS, GhAPX, GhSDH, and GhPOD, were cloned from cotton complementary DNA, and their expression patterns under stress were analyzed. Phenotypic experiments indicated that overexpression of these cotton genes in Arabidopsis affected the response to abiotic stress. The method developed in this study lays a foundation for high‐throughput cloning and rapid identification of cotton functional genes.