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  Tracking signatures of response over 20 generations of selection for long leg length in mice

Hiramatsu, L., Belohlavy, S., Kučka, M., Barton, N., Rolian, C., & Chan, Y. (2018). Tracking signatures of response over 20 generations of selection for long leg length in mice. In Population, Evolutionary, and Quantitative Genetics Conference (PEQG 2018) (pp. 129-130).

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-4C43-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-4C49-D
Genre: Meeting Abstract

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https://genetics-gsa.org/peqg/wp-content/uploads/sites/19/2021/11/2018PEQGFullAbstracts.pdf (Abstract)
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 Creators:
Hiramatsu, L1, Author           
Belohlavy, S, Author
Kučka, M1, Author                 
Barton, NH, Author
Rolian, C, Author
Chan, YF1, Author                 
Affiliations:
1Chan Group, Friedrich Miescher Laboratory, Max Planck Society, ou_3008688              

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 Abstract: Selection experiments offer a powerful approach to study how genomes evolve in response to selection pressures. Especially useful are pedigreed selection experiments, which offer time-series reconstruction of genomic change. We used mice from the Longshanks selection experiment for longer relative tibia length in mice. Two replicate lines were selectively bred over 20 generations using up to 16 breeding pairs per line per generation, resulting in a 13-15% increase in tibiae length (see abstract by Y.F. Chan). We tracked haplotype segregation through each generation by pedigree- assisted imputation. We contrasted locus-by-locus allele trajectories with theoretical predictions of selection response (see abstract by N. Barton). We also traced variation of local recombination rate and events through tracking the breakdown of haplotypes. We show here that despite small population size of only Ne = 46, selection response remains rapid and robus within the first 20 generations. The Longshanks experiment provides a comprehensively detailed system to study how the mammalian genome responds to selection and allowed the testing of theoretic models of varying genetic architectures.

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 Dates: 2018-05
 Publication Status: Published online
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Title: 2018 Population, Evolutionary, and Quantitative Genetics Conference (PEQG 2018)
Place of Event: Madison, WI, USA
Start-/End Date: 2018-05-13 - 2018-05-16

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Title: Population, Evolutionary, and Quantitative Genetics Conference (PEQG 2018)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 341T Start / End Page: 129 - 130 Identifier: -