Academic journal article Genetics

Properties and Power of the Drosophila Synthetic Population Resource for the Routine Dissection of Complex Traits

Academic journal article Genetics

Properties and Power of the Drosophila Synthetic Population Resource for the Routine Dissection of Complex Traits

Article excerpt

ABSTRACT The Drosophila Synthetic Population Resource (DSPR) is a newly developed multifounder advanced intercross panel consisting of >1600 recombinant inbred lines (RILs) designed for the genetic dissection of complex traits. Here, we describe the inference of the underlying mosaic founder structure for the full set of RILs from a dense set of semicodominant restriction-site- associated DNA (RAD) markers and use simulations to explore how variation in marker density and sequencing coverage affects inference. For a given sequencing effort, marker density is more important than sequence coverage per marker in terms of the amount of genetic information we can infer. We also assessed the power of the DSPR by assigning genotypes at a hidden QTL to each RIL on the basis of the inferred founder state and simulating phenotypes for different experimental designs, different genetic architectures, different sample sizes, and QTL of varying effect sizes. We found the DSPR has both high power (e.g., 84% power to detect a 5% QTL) and high mapping resolution (e.g., ~1.5 cM for a 5% QTL).

(ProQuest: ... denotes formulae omitted.)

THE ultimate goal of modern genetics is to determine how molecular genetic variation is translated into organismal phenotypes. The vast majority of continuously varying phenotypes are influenced by many genetic variants that often interact with one another and with environmental factors (Falconer and Mackay 1996; Roff1997; Lynch and Walsh 1998). This underlying complexity has made identifying causative genetic variants for most traits a steep challenge for which the scientific community has only had limited, albeit increasing, success (Mackay 2001; Chanock et al. 2007; Wellcome Trust Case Control Consortium 2007; Mccarthy et al. 2008; Stranger et al. 2011). As a result, there is a large discrepancy between the known heritability of most traits and the fraction of that heritability that can be explained by known causative genetic variants (Manolio et al. 2009; Stranger et al. 2011). This discrepancy has spurred the development of new mapping panels designed to address the shortcomings of existing genome-wide association studies and QTL mapping panels derived from only two parents.

The Drosophila Synthetic Population Resource (DSPR) is one such panel (King et al. 2012) similar in concept to other available linkage-based resources: the mouse Collaborative Cross (Churchill et al. 2004; Aylor et al. 2011; Philip et al. 2011), the Arabidopsis multiparent recombinant inbred line population (AMPRIL) (Huang et al. 2011), the Arabidopsis multiparent advanced generation intercross lines (MAGIC) (Kover et al. 2009), and the maize nested associated mapping population (NAM) (Yu et al. 2008; Buckler et al. 2009; Mcmullen et al. 2009; Li et al. 2011). The DSPR is a linkage- based panel that uses a synthetic population approach (Macdonald and Long 2007). To create the DSPR, two separate synthetic populations were created each from a 50- generation intercross of 8 inbred founder lines with one founder line shared between the two populations. From these two synthetic populations, .1600 recombinant inbred lines (RILs) were created via 25 generations of full-sib inbreeding. The large number of generations of recombination experienced by the DSPR produces a panel with genomic segments averaging 3 cM in size and, as a result, has the potential for much higher mapping resolution than previously available Drosophila mapping panels (King et al. 2012). In addition, a major strength of the synthetic population approach is the expectation of high power to detect genetic variants irrespective of their population frequency, provided such variants are sampled in the founder chromosomes (Macdonald and Long 2007).

Different types of mapping designs have different advantages depending on the nature of the genetic variation underlying a phenotype. Rare alleles are statistically very difficult to detect via genome-wide association in randomly ascertained panels that sample the natural genetic variation (Bansal et al. …

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