Genomic and GWAS analyses demonstrate phylogenomic relationships of Gossypium barbadense in China and selection for fibre length, lint percentage and Fusarium wilt resistance

Plant Biotechnol J. 2022 Apr;20(4):691-710. doi: 10.1111/pbi.13747. Epub 2021 Dec 11.

Abstract

Sea Island cotton (Gossypium barbadense) is the source of the world's finest fibre quality cotton, yet relatively little is understood about genetic variations among diverse germplasms, genes underlying important traits and the effects of pedigree selection. Here, we resequenced 336 G. barbadense accessions and identified 16 million SNPs. Phylogenetic and population structure analyses revealed two major gene pools and a third admixed subgroup derived from geographical dissemination and interbreeding. We conducted a genome-wide association study (GWAS) of 15 traits including fibre quality, yield, disease resistance, maturity and plant architecture. The highest number of associated loci was for fibre quality, followed by disease resistance and yield. Using gene expression analyses and VIGS transgenic experiments, we confirmed the roles of five candidate genes regulating four key traits, that is disease resistance, fibre length, fibre strength and lint percentage. Geographical and temporal considerations demonstrated selection for the superior fibre quality (fibre length and fibre strength), and high lint percentage in improving G. barbadense in China. Pedigree selection breeding increased Fusarium wilt disease resistance and separately improved fibre quality and yield. Our work provides a foundation for understanding genomic variation and selective breeding of Sea Island cotton.

Keywords: Gossypium barbadense; Fusarium wilt disease resistance; GWAS; fibre quality; yield.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chromosome Mapping
  • Cotton Fiber
  • Disease Resistance / genetics
  • Fusarium*
  • Genome, Plant / genetics
  • Genome-Wide Association Study
  • Gossypium* / genetics
  • Phenotype
  • Phylogeny
  • Plant Breeding
  • Quantitative Trait Loci