Fine-mapping QTLs in advanced intercross lines and other outbred populations

Abstract

Quantitative genetic studies in model organisms, particularly in mice, have been extremely successful in identifying chromosomal regions that are associated with a wide variety of behavioral and other traits. However, it is now widely understood that identification of the underlying genes will be far more challenging. In the last few years, a variety of populations have been utilized in an effort to more finely map these chromosomal regions with the goal of identifying specific genes. The common property of these newer populations is that linkage disequilibrium spans relatively short distances, which permits fine-scale mapping resolution. This review focuses on advanced intercross lines (AILs) which are the simplest such population. As originally proposed in 1995 by Darvasi and Soller, an AIL is the product of intercrossing two inbred strains beyond the F2 generation. Unlike recombinant inbred strains, AILs are maintained as outbred populations; brother-sister matings are specifically avoided. Each generation of intercrossing beyond the F2 further degrades linkage disequilibrium between adjacent makers, which allows for fine scale mapping of quantitative trait loci (QTLs). Advances in genotyping technology and techniques for the statistical analysis of AILs have permitted rapid advances in the application of AILs. We review some of the analytical issues and available software, including QTLRel, EMMA, EMMAX, GEMMA, TASSEL, GRAMMAR, WOMBAT, Mendel and others.

Genome wide association analysis in a mouse advanced intercross line

“…In the 240 present study, we used 1,063 male and female mice from LG x SM G50-56 to identify 126 loci for a 241 variety of traits selected for their relevance to human psychiatric and metabolic diseases (Lawson and 242 Cheverud 2010;Swerdlow et al 2016;de Wit and Phillips 2012) (Fig.3; Supplemental Table S1; 243 Supplemental Fig.S2). Whereas our previous work established AILs as an effective tool for fine-244 mapping loci identified in F2 crosses (Gonzales and Palmer 2014;Carroll et al 2017;Parker et al 2014;245 Cheng et al 2010;Samocha et al 2010;Lionikas et al 2010), this study 246 demonstrates that AILs are also a powerful fine mapping population in their own right. We show that 247 several QTGs we identified are corroborated by extant human and mouse genetic data.…”

“…To 251 address this limitation, we and others have used AILs (Gonzales and Palmer 2014). Because both inbred 252 strains contribute equally to an AIL, there are numerous common variants (Fig.…”

“…disequilibrium (LD) decay, which is critical to mapping resolution, has improved since LG x SM G34 72 ( Fig.1C; Cheng et al 2010). 73 LOCO-LMM effectively reduces the type II error rate 74 Linear mixed models (LMMs) are commonly used to perform GWAS in AILs and other populations that 75 include close relatives (Gonzales and Palmer 2014). SNP data are used to obtain a genetic relationship 76 matrix (GRM); however, 77 this can lead to an 78 inflation of the type II error 79 rate due to proximal 80 contamination (Cheng et 81 al.…”

Genetics of aging bone

“…For a thorough discussion of the genetic mapping advantages of these populations, the reader is referred to the two reviews referenced (87, 88). The disadvantage of these mice is that in theory each allelic combination is only seen once per study, so invasive or terminal phenotyping protocols cannot be repeatedly measured per genome with aging.…”

Transgenerational cardiology: One way to a baby's heart is through the mother

“…With each generation, t , the resolution of mapping increases by a factor of t /2 over short genomic distances in an advanced intercross relative to the F2 (Darvasi and Soller, 1995). An advanced intercross takes considerable effort to produce but offers many advantages for the analysis of complex genetic traits (Gonzales and Palmer, 2014). …”