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

Abstract

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.

Parallel and Intertwining Threads of Domestication in Allopolyploid Cotton

“…[11][12][13][14] Whole-genome resequencing has been used to decipher the underpinnings of the domestication syndrome in many crops, including rice, [15][16][17] maize, [18] soybean, [19] and others. Recent advances in cotton genome sequencing [20][21][22][23][24][25][26][27][28][29][30][31][32][33] have been used to assess the domestication history of G. hirsutum and G. barbadense; however, these studies included limited representation of the wild/landrace gene pool from the ancestral geographic centers of origin and/or low coverage sequencing. Accordingly, the present study was designed expressly to assess the effects of domestication and improvement of G. hirsutum and G. barbadense on the origin and composition of their modern gene pools.…”

“…[ 11–14 ] Whole‐genome resequencing has been used to decipher the underpinnings of the domestication syndrome in many crops, including rice, [ 15–17 ] maize, [ 18 ] soybean, [ 19 ] and others. Recent advances in cotton genome sequencing [ 20–33 ] have been used to assess the domestication history of G . hirsutum and G .…”

GhCO and GhCRY1 accelerate floral meristem initiation in response to increased blue light to shorten cotton breeding

“…4B). Interestingly, four of the flower-related genes identified by genome-wide association analysis of 355 group cultivars (Li et al, 2021) were differentially expressed between early- and late-maturity cultivars during cotton SAM development, and the expression level peak occurred at 2 or 2.5 TLS (Fig. 4C).…”

“…The early or late differentiation of FMs, which is determined by the fate of SAM, is directly related to the maturity period and architecture of a cultivar (Niwa et al, 2013), which is very important for practising double-cropping systems, namely, rapeseed/wheat-cotton production systems. One of the biggest challenges in cotton breeding is the long growth cycle (Li et al, 2021). Therefore, studying the fate determination mechanism of SAMs is very important to optimize the timing of cotton fruit branching and shorten the cotton growth stage to meet the large and increasing clothing demands of an ever-growing world population.…”

Genetic Diversity, QTL Mapping, and Marker-Assisted Selection Technology in Cotton (Gossypium spp.)

“…Cotton is mainly grown in the regions which are affected by abiotic stresses, such as drought and salt ( Abdelraheem et al, 2019 ). There is an urgent need to study of genetic bases of abiotic stress resistance and to improve drought resistance of cotton ( Li et al, 2020c ). Recently, Abdelraheem et al (2019 , 2021) have identified drought and salinity stress resistance-related QTLs using SNP markers on an inter-cross mapping population ( Abdelraheem et al, 2019 , 2021 ).…”