Open AccessGenomewide Markers for Controlling Background Variation in Association Mapping
Author(s) -
Bernardo Rex
Publication year - 2013
Publication title -
the plant genome
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 41
ISSN - 1940-3372
DOI - 10.3835/plantgenome2012.11.0028
Subject(s) - quantitative trait locus , biology , population , association mapping , false positive paradox , genetics , linkage (software) , genetic association , trait , linkage disequilibrium , computational biology , family based qtl mapping , gene mapping , evolutionary biology , statistics , allele , single nucleotide polymorphism , mathematics , genotype , haplotype , computer science , chromosome , gene , demography , sociology , programming language
Current procedures for association mapping in plants account for population structure (Q) and kinship (K). Here I propose an association mapping procedure that uses genomewide markers (G) to account for quantitative trait loci (QTL) on background chromosomes. My objective was to determine if the G and QG models are superior to the K and QK models. I simulated mapping population sizes of N = 384, 768, and 1536 inbreds that belonged to three known subpopulations. The G and QG models showed the best adherence to the significance level ( P ) specified by the investigator for declaring QTL. Across different genetic models (15 or 30 QTL), population sizes, and P levels, the Q model suffered from a high number of false positives ( N FP ). With the K and QK models, a relaxed P level led to a reasonable number of true QTL detected ( N TQ ) with N = 384 or 768 but it led to high N FP with N = 1536. Compared with the K and QK models, the G and QG models had a better balance between high N TQ and low N FP . The results strongly indicated that the G and QG models are superior to the K and QK models.