Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis.

ABSTRACT:

Background

Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees.

Results

We identify 55 novel quantitative trait loci (QTLs) that are associated with phenotypic variation. The largest number of QTLs is as

SUBMITTER: Chen ZQ 

PROVIDER: S-EPMC8201819 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature