Context-dependent genetic architecture of Drosophila life span

Abstract

Understanding the genetic basis of variation in life span is a major challenge that is difficult to address in human populations. Evolutionary theory predicts that alleles affecting natural variation in life span will have properties that enable them to persist in populations at intermediate frequencies, such as late-life-specific deleterious effects, antagonistic pleiotropic effects on early and late-age fitness components, and/or sex-and environment-specific or antagonistic effects. Here, we quantified variation in life span in males and females reared in 3 thermal environments for the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and an advanced intercross outbred population derived from a subset of DGRP lines. Quantitative genetic analyses of life span and the micro-environmental variance of life span in the DGRP revealed significant genetic variance for both traits within each sex and environment, as well as significant genotype-by-sex interaction (GSI) and genotype-by-environment interaction (GEI). Genome-wide association (GWA) mapping in both populations implicates over 2,000 candidate genes with sex-and environment-specific or antagonistic pleiotropic allelic effects. Over 1,000 of these genes are associated with variation in life span in other D. melanogaster populations. We functionally assessed the effects of 15 candidate genes using RNA interference (RNAi): all affected life span and/or micro-environmental variance of life span in at least one sex and environment and exhibited sex-and environment-specific effects. Our results implicate novel candidate genes affecting life span and suggest that variation for life span may be maintained by variable allelic effects in heterogeneous environments.

Genetic Basis of Increased Lifespan and Postponed Senescence inDrosophila melanogaster

“…Natural D. melanogaster populations harbor considerable segregating genetic variation for lifespan, as evidenced by the large number of QTL affecting lifespan (Nuzhdin et al 1997;Leips and Mackay 2000;Pasyukova et al 2000;Vieira et al 2000;Leips and Mackay 2002;Forbes et al 2004;Wilson et al 2006;Durham et al 2014;Ivanov et al 2015;Huang et al 2020) and rapid evolution of long-lived strains by selecting for increased age of reproduction from several different geographical populations (Rose 1984;Luckinbill et al 1984;Sgrò and Partridge 1999). Previously, we assessed the genetic divergence between five long-lived O lines selected for postponed senescence and five B control lines with normal lifespan (Rose 1984;Carnes et al 2015), and identified 1,925 nominally significant (P , 10 23 ) genes based on analyses of individual variants.…”

“…Thus, increasing lifespan does not necessarily occur at the cost of reduced reproductive capacity (although other, unmeasured, fitness components may be affected). piwi and sgg are highly pleiotropic genes known to affect oogenesis; in addition, both genes have been independently associated with naturally occurring genetic variation in lifespan (Huang et al 2020) and response to selection for delayed reproductive senescence (Luckinbill et al 1984;Fabian et al 2018).…”

“…This suggests there may be naturally occurring variation in levels of expression of these genes in these tissues, and selection resulted in their increased expression in ovaries and accessory glands in the O lines. Regardless of whether this testable hypothesis is true, variation in nine of these genes (blw, CG14969, CG4452, CG7970, CycE, Fdx1, Hsp22, l(1)G0004, ND-ACP) has been independently associated with variation in lifespan (Garcia et al 2017;Huang et al 2020) and response to selection for delayed reproductive senescence (Remolina et al 2012) in other populations.…”

“…Quantitative trait loci (QTL) affecting lifespan have been mapped in D. melanogaster (Nuzhdin et al 1997;Leips and Mackay 2000;Pasyukova et al 2000;Vieira et al 2000;Leips and Mackay 2002;Forbes et al 2004;Wilson, Morgan, and Mackay 2006;Durham et al 2014;Ivanov et al 2015;Fabian et al 2018;Huang et al 2020), C. elegans Shook 1996;Ayyadevara et al 2001;Shmookler Reis et al 2006), mice (Jackson et al 2002;Doria et al 2004;Lang et al 2010), and humans (Beekman et al 2013;Deelen et al 2013;Deelen et al 2014). However, only a few genes implicated by QTL mapping have been shown to be capable of affecting both lifespan and reproductive senescence using an independent assay (Durham et al 2014).…”

No support for the genetic hypothesis of the Black-white achievement gap using polygenic scores and tests for divergent selection

“…As discussed above these analyses about additivity of genetic effects and their similar behavior between populations. These assumptions are known to be false, for example in a complex trait like life span in Drosophila melanogaster showed extensive context-dependent allelic effects across several environments and between sexes 85 . Similarly, there is evidence of context dependence of polygenic scores in humans of the same ancestry group, especially for traits like educational attainment 43 .…”