Separation of base allele and sampling term effects gives new insights in variance component QTL analysis

Abstract

Background: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix).

Association Between Twelve Polymorphisms in Five X-ray Repair Cross-complementing Genes and the Risk of Urological Neoplasms: A Systematic Review and Meta-Analysis

“…Table 1 showed the characteristics of all the eligible studies and genotype frequency distributions of twelve polymorphisms in five XRCC genes ( XRCC1 -rs915927, XRCC1 -rs25489, XRCC1 -rs25487, XRCC1 -rs1799782, XRCC1 -rs3213245, XRCC2 -rs3218536, XRCC3 -rs1799796, XRCC3 -rs861539, XRCC4 -rs6869366, XRCC4 -rs28360071, XRCC4 -rs1805377, XRCC7 -rs7003908) included in current meta-analysis (Agalliu et al, 2010, Andrew et al, 2015, Andrew et al, 2007, Andrew et al, 2006, Arizono et al, 2008, Berhane et al, 2012, Broberg et al, 2005, Chang et al, 2009, Lan et al, 2006, Lavender et al, 2010, Chang et al, 2008, Dhillon et al, 2009, Figueroa et al, 2007a, Figueroa et al, 2007b, Fontana et al, 2008, Gangwar et al, 2009, Hamano et al, 2008, Hirata et al, 2006, Hirata et al, 2007, Huang et al, 2007, Abe et al, 2011, Mittal et al, 2008, Narter et al, 2009, Nowacka-Zawisza et al, 2015, Ramaniuk et al, 2014, Ritchey et al, 2005, Rybicki et al, 2004, Sak et al, 2007, Sanyal et al, 2004, Shen et al, 2003, Stern et al, 2002, Stern et al, 2001, Van Gils et al, 2002, Wang et al, 2010, Wang et al, 2008, Wen et al, 2009, Wen et al, 2013, Wu et al, 2006, Xu et al, 2007, Zhi et al, 2012, Hao et al, 2008, Zhou et al, 2012, Zhu et al, 2014, Zhu et al, 2012, Kelsey et al, 2004, Kuasne et al, 2011, Luedeke et al, 2009, Mandal et al, 2010, Mandal et al, 2011, Matullo, 2005, Matullo et al, 2006, Matullo et al, 2001, Mittal et al, 2012a, Mittal et al, 2012b). The study selection processes were presented in Supplementary Figs.…”

Non‐iterative variance component estimation in QTL analysis

“…These matrix inversions are relatively easy to optimize in computational speed when there are few columns in ( X , Z 1 , Z 2 ). The number of fixed effects are usually small in QTL problems, and the rank of the IBD matrices is either small or can be approximated with lower rank matrices (Rönnegård and Carlborg 2007; Rönnegård et al. 2007).…”

Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions

“…To perform vGWAS in the LMM framework and to identify genome-wide vQTL, we used a HGLM approach. HGLM (Lee and Nelder, 1996) is a class of GLM and is a direct extension of the DGLM that allows joint modelling of the mean and dispersion parts and introduces random effects as a linear predictor for the mean (Rönnegård and Carlborg, 2007). The mean part of HGLM was given as follows: assuming that where Z is the incident matrix of random effects of genotypes; u is the vector of random effects with ; G is the GRM of VanRaden (2008); and is the additive genetic variance.…”