Affordable Access

Access to the full text

A fast-linear mixed model for genome-wide haplotype association analysis: application to agronomic traits in maize

Authors
  • Chen, Heli1
  • Hao, Zhiyu2
  • Zhao, Yunfeng1
  • Yang, Runqing1, 2
  • 1 Chinese Academy of Fishery Sciences, Beijing, 100141, People’s Republic of China , Beijing (China)
  • 2 Northeast Agricultural University, Harbin, 150030, China , Harbin (China)
Type
Published Article
Journal
BMC Genomics
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Feb 11, 2020
Volume
21
Issue
1
Identifiers
DOI: 10.1186/s12864-020-6552-x
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundHaplotypes combine the effects of several single nucleotide polymorphisms (SNPs) with high linkage disequilibrium, which benefit the genome-wide association analysis (GWAS). In the haplotype association analysis, both haplotype alleles and blocks are tested. Haplotype alleles can be inferred with the same statistics as SNPs in the linear mixed model, while blocks require the formulation of unified statistics to fit different genetic units, such as SNPs, haplotypes, and copy number variations.ResultsBased on the FaST-LMM, the fastLmPure function in the R/RcppArmadillo package has been introduced to speed up genome-wide regression scans by a re-weighted least square estimation. When large or highly significant blocks are tested based on EMMAX, the genome-wide haplotype association analysis takes only one to two rounds of genome-wide regression scans. With a genomic dataset of 541,595 SNPs from 513 maize inbred lines, 90,770 haplotype blocks were constructed across the whole genome, and three types of markers (SNPs, haplotype alleles, and haplotype blocks) were genome-widely associated with 17 agronomic traits in maize using the software developed here.ConclusionsTwo SNPs were identified for LNAE, four haplotype alleles for TMAL, LNAE, CD, and DTH, and only three blocks reached the significant level for TMAL, CD, and KNPR. Compared to the R/lm function, the computational time was reduced by ~ 10–15 times.

Report this publication

Statistics

Seen <100 times