Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods.

ABSTRACT: Genomic selection or genomic prediction (GP) has increasingly become an important molecular breeding technology for crop improvement. GP aims to utilise genome-wide marker data to predict genomic breeding value for traits of economic importance. Though GP studies have been widely conducted in various crop species such as wheat and maize, its application in cotton, an essential renewable textile fibre crop, is still significantly underdeveloped. We aim to develop a new GP-based breeding system that can improve the efficiency of our cotton breeding program. This article presents a GP study on cotton fibre quality and yield traits using 1385 breeding lines from the Commonwealth Scientific and Industrial Research Organisation (CSIRO, Australia) cotton breeding program which were genotyped usin

SUBMITTER: Li Z 

PROVIDER: S-EPMC9338257 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature