Allotetraploid cotton species (Gossypium hirsutum and Gossypium barbadense) have long been cultivated worldwide for natural renewable textile fibers. The draft genome sequences of both species are available but they are highly fragmented and incomplete1-4. Here we report reference-grade genome assemblies and annotations for G. hirsutum accession Texas Marker-1 (TM-1) and G. barbadense accession 3-79 by integrating single-molecule real-time sequencing, BioNano optical mapping and high-throughput chromosome conformation capture techniques. Compared with previous assembled draft genomes1,3, these genome sequences show considerable improvements in contiguity and completeness for regions with high content of repeats such as centromeres. Comparative genomics analyses identify extensive structural variations that probably occurred after polyploidization, highlighted by large paracentric/pericentric inversions in 14 chromosomes. We constructed an introgression line population to introduce favorable chromosome segments from G. barbadense to G. hirsutum, allowing us to identify 13 quantitative trait loci associated with superior fiber quality. These resources will accelerate evolutionary and functional genomic studies in cotton and inform future breeding programs for fiber improvement.

Background: The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to fiber quality, disease and pest resistance, branch number, seed quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on fiber traits, a number of papers on QTL mapping of fiber quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed. Results: In this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for fiber quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots. Conclusions: Putative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.

Summary: 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.

Background: Cotton, with a large genome, is an important crop throughout the world. A high-density genetic linkage map is the prerequisite for cotton genetics and breeding. A genetic map based on simple polymerase chain reaction markers will be efficient for marker-assisted breeding in cotton, and markers from transcribed sequences have more chance to target genes related to traits. To construct a genome-wide, functional marker-based genetic linkage map in cotton, we isolated and mapped expressed sequence tag-simple sequence repeats (EST-SSRs) from cotton ESTs derived from the A₁, D₅, (AD)₁, and (AD)₂ genome. Results: A total of 3177 new EST-SSRs developed in our laboratory and other newly released SSRs were used to enrich our interspecific BC₁ genetic linkage map. A total of 547 loci and 911 loci were obtained from our EST-SSRs and the newly released SSRs, respectively. The 1458 loci together with our previously published data were used to construct an updated genetic linkage map. The final map included 2316 loci on the 26 cotton chromosomes, 4418.9 cM in total length and 1.91 cM in average distance between adjacent markers. To our knowledge, this map is one of the three most dense linkage maps in cotton. Twenty-one segregation distortion regions (SDRs) were found in this map; three segregation distorted chromosomes, Chr02, Chr16, and Chr18, were identified with 99.9% of distorted markers segregating toward the heterozygous allele. Functional analysis of SSR sequences showed that 1633 loci of this map (70.6%) were transcribed loci and 1332 loci (57.5%) were translated loci. Conclusions: This map lays groundwork for further genetic analyses of important quantitative traits, marker-assisted selection, and genome organization architecture in cotton as well as for comparative genomics between cotton and other species. The segregation distorted chromosomes can be a guide to identify segregation distortion loci in cotton. The annotation of SSR sequences identified frequent and rare gene ontology items on each chromosome, which is helpful to discover functions of cotton chromosomes.

Since upland cotton was introduced into China during the 1920s–1950s, hundreds of inbreed cultivars have been developed. To explore the molecular diversity, population structure and elite alleles, 503 inbred cultivars developed in China and some foreign cultivars from the United States and the Soviet Union were collected and analyzed by 494 genome-wide SSRs (Simple Sequence Repeats). Four hundred and ninety-four pairs of SSRs with high polymorphism and uniform distribution on 26 chromosomes were used to scan polymorphisms in 503 nation-wide upland cottons. The programming language R was used to make boxplots for the phenotypic traits in different environments. Molecular marker data and 6 fiber quality traits were analyzed by the method of MLM (mixed linear model) (P + G + Q + K) in the TASSEL software package on the basis of the population structure and linkage disequilibrium analysis. The loci of elite allelic variation and typical materials carrying elite alleles were identified based on phenotypic effect values. A total of 179 markers were polymorphic and generated 426 allele loci; the population based on molecular diversity was classified into seven subpopulations corresponding to pedigree origin, ecological and geographical distribution. The attenuation distance of linkage disequilibrium dropped significantly up to 0–5 cM. Association mapping for fiber quality showed that 216 marker loci were associated with fiber quality traits (P < 0.05) explaining 0.58 % ~ 5.12 % of the phenotypic variation, with an average of 2.70 %. Thirteen marker loci were coincident with other studies, and three were detected for the same trait. Seven quantitative trait loci were related to known genes in fiber development. Based on phenotypic effects, 48 typical materials that contained the elite allele loci related to fiber quality traits were identified and are widely used in practical breeding. The molecular diversity and population structure of 503 nation-wide upland cottons in China were evaluated by 494 genome-wide SSRs, and association mapping for fiber quality revealed known and novel elite alleles. The molecular diversity provides a guide for parental mating in cotton breeding, and the association mapping results will aid in the fine-mapping genes related to fiber quality traits and facilitate further studies on candidate genes.