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Properties of different selection signature statistics and a new strategy for combining them

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss th...

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Autores principales: Ma, Y, Ding, X, Qanbari, S, Weigend, S, Zhang, Q, Simianer, H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4611237/
https://www.ncbi.nlm.nih.gov/pubmed/25990878
http://dx.doi.org/10.1038/hdy.2015.42
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author Ma, Y
Ding, X
Qanbari, S
Weigend, S
Zhang, Q
Simianer, H
author_facet Ma, Y
Ding, X
Qanbari, S
Weigend, S
Zhang, Q
Simianer, H
author_sort Ma, Y
collection PubMed
description Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.
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spelling pubmed-46112372015-11-02 Properties of different selection signature statistics and a new strategy for combining them Ma, Y Ding, X Qanbari, S Weigend, S Zhang, Q Simianer, H Heredity (Edinb) Original Article Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait. Nature Publishing Group 2015-11 2015-05-20 /pmc/articles/PMC4611237/ /pubmed/25990878 http://dx.doi.org/10.1038/hdy.2015.42 Text en Copyright © 2015 The Genetics Society Macmillan Publishers Limited http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Original Article
Ma, Y
Ding, X
Qanbari, S
Weigend, S
Zhang, Q
Simianer, H
Properties of different selection signature statistics and a new strategy for combining them
title Properties of different selection signature statistics and a new strategy for combining them
title_full Properties of different selection signature statistics and a new strategy for combining them
title_fullStr Properties of different selection signature statistics and a new strategy for combining them
title_full_unstemmed Properties of different selection signature statistics and a new strategy for combining them
title_short Properties of different selection signature statistics and a new strategy for combining them
title_sort properties of different selection signature statistics and a new strategy for combining them
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4611237/
https://www.ncbi.nlm.nih.gov/pubmed/25990878
http://dx.doi.org/10.1038/hdy.2015.42
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