Quantitative genetics in the study of virus-induced disease

Abstract

While the role of viral variants has long been known to play a key role in causing variation in disease severity, it is also clear that host genetic variation plays a critical role in determining virus-induced disease responses. However, a variety of factors, including confounding environmental variables, rare genetic variants requiring extremely large cohorts, the temporal dynamics of infections, and ethical limitation on human studies, have made the identification and dissection of variant host genes and pathways difficult within human populations. This difficulty has led to the development of a variety of experimental approaches used to identify host genetic contributions to disease responses. In this chapter, we describe the history of genetic associations within the human population, the development of experimentally tractable systems, and the insights these specific approaches provide. We conclude with a discussion of recent advances that allow for the investigation of the role of complex genetic networks that underlie host responses to infection, with the goal of drawing connections to human infections. In particular, we highlight the need for robust animal models with which to directly control and assess the role of host genetics on viral infection outcomes.

Keywords: Association; Complex trait; GWAS; Genetic mapping; Genetic reference population; Linkage; QTL; Viral disease.

Figure 4.1

Different genetic mapping approaches. (A) Family pedigree containing a trait used for linkage mapping. The trait of interest (black individuals) is mapped by comparing trait to markers (A/a and D/d markers below individuals) within this family. Note that the trait is tightly linked to the D markers. (B) Experimental pedigree to identify QTL contributing to a continuous disease trait. Founder lines show a clear difference in phenotypes (black square and white circle at top of pedigree). F1 offspring all have intermediate phenotypes (gray individuals in middle of pedigree). F2 animals show a range of phenotypes (grayscale intensity). QTL analysis seeks to explain some portion of phenotype (grayscale) differences based on markers. In this case, individuals with A markers tend to be lighter in shade than those with a markers. (C) GWAS studies examine large pools of individuals without family structure (e.g., that are only evolutionarily distantly related). Within such a population, only SNPs that are very close to causative polymorphisms (or are in fact the causative polymorphisms) will avoid recombination breakdown of unequal associations. Therefore, by examining large numbers of SNPs in this population, those tightly associated with the phenotype will be identified. In this example, the first SNP (highlighted in red box) is associated with disease (black individuals). 5/6 individuals with the disease have a T at the SNP. In contrast, only 1/23 individuals without the disease have a T at the SNP.

Figure 4.2

Experimental models for dissection of host genetic impact of viral disease. A number of different experimental approaches have been utilized to better understand the role of host genetics on viral disease. (A) Genetic knockout systems. Complete disruption of a gene product, where the contrast is between the wild-type inbred strain and the mutant strain. Both lines are isogenic except at the disrupted gene. (B) ENU mutagenesis. Random mutagenesis can produce variants that affect gene function. Again, by isolating and fixing the mutation, a direct comparison can be made to the original wild-type inbred strain, as the two lines will be isogenic except at the mutation of interest. (C) Comparisons between two inbred strains can reveal distinct disease responses (as in Boon et al., 2011, Srivastava et al., 2009, Zumbrun et al., 2012). Such results show that one or a number of unidentified genetic factors cause these differences. A variety of approaches can then identify these factors. (D) Consomic panels create novel inbred lines that contain an entire genome of one founder strain, except that each consomic line contains a single chromosome from the other founder strain. Disease measurements across such panels are useful for identifying and honing in (through the use of congenic animals) on genes of large effect or Mendelian genes affecting disease outcomes (Burgio et al., 2007). (E) By crossing animals from two founder lines together, and then breeding the F1 animals together, large pools of F2 animals can be quickly generated for QTL mapping studies. These F2 crosses result in individuals that are all genetically related, but each with a distinct (and incompletely inbred) genome. (F) In order to compare across QTL studies, and to integrate experimental replication and control into genetic mapping approaches, several recombinant inbred panels have been created (e.g., the BxD, AxB, and BxA panels in mouse and several panels in rice and arabidopsis). Each line is completely inbred, and its genome is a mosaic of the two founder lines. (G) The collaborative cross is a new recombinant inbred panel derived from eight highly genetically diverse founder strains. Thus, each CC line's genome is a mosaic of eight founder lines. At any given locus, up to eight alleles can be segregating in this population enabling both QTL mapping and more robust modeling of human genome-wide variation.