期刊
EVOLUTION
卷 66, 期 11, 页码 3390-3403出版社
WILEY
DOI: 10.1111/j.1558-5646.2012.01710.x
关键词
Fecundity; pleiotropy; quantitative genetics; selection-experimental; senescence; trade-offs
资金
- National Science Foundation [DEB 0848337, DEB 0848869, MRI 0923513]
- National Institutes of Health [AG022824, HG002790]
- Direct For Biological Sciences
- Division Of Environmental Biology [0848869] Funding Source: National Science Foundation
- Direct For Biological Sciences
- Div Of Biological Infrastructure [0923513] Funding Source: National Science Foundation
- Division Of Environmental Biology
- Direct For Biological Sciences [0848337] Funding Source: National Science Foundation
Natural diversity in aging and other life-history patterns is a hallmark of organismal variation. Related species, populations, and individuals within populations show genetically based variation in life span and other aspects of age-related performance. Population differences are especially informative because these differences can be large relative to within-population variation and because they occur in organisms with otherwise similar genomes. We used experimental evolution to produce populations divergent for life span and late-age fertility and then used deep genome sequencing to detect sequence variants with nucleotide-level resolution. Several genes and genome regions showed strong signatures of selection, and the same regions were implicated in independent comparisons, suggesting that the same alleles were selected in replicate lines. Genes related to oogenesis, immunity, and protein degradation were implicated as important modifiers of late-life performance. Expression profiling and functional annotation narrowed the list of strong candidate genes to 38, most of which are novel candidates for regulating aging. Life span and early age fecundity were negatively correlated among populations; therefore, the alleles we identified also are candidate regulators of a major life-history trade-off. More generally, we argue that hitchhiking mapping can be a powerful tool for uncovering the molecular bases of quantitative genetic variation.
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