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Integration of genomic and epigenomic features to predict meiotic recombination hotspots in human and mouse

Authors:

Chee Keong Kwoh,

Teresa M. Przytycka,

Jie ZhengAuthors Info & Claims

BCB '12: Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine

Pages 297 - 304

https://doi.org/10.1145/2382936.2382974

Published: 07 October 2012 Publication History

Abstract

The regulatory mechanism of meiotic recombination hotspots is a fundamental problem in biology, with broad impacts on areas ranging from disease study to evolution. Recently, many genomic and epigenomic features have been associated with recombination hotspots, but none of them can explain hotspots consistently. It is highly desirable to integrate the different features into a predictive model, and study the relation of the features with hotspots and themselves with a systems approach. Moreover, due to rapid and dynamic evolution of recombination hotspots, regulatory mechanisms of hotspots that are evolutionarily conserved among species remain unclear.

We propose a machine learning approach that encode genomic and epigenomic features into a support vector machine (SVM). Trained on known hotspots and coldspots in human and mouse genomes, the model is able to predict hotspots based on the features with good performance in both species. Moreover, the model reports a ranking of feature importance, uncovering the interactions of the features with hotspots and themselves. Applying the method to large-scale data, we identified evolutionarily conserved patterns of trans-regulators and feature importance between human and mouse hotspots. This is the first attempt to build a predictive model to identify evolutionarily conserved mechanisms for recombination hotspots by integrating both genomic and epigenomic features.

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Cited By

Liu GXing YCai L(2015)Using weighted features to predict recombination hotspots in Saccharomyces cerevisiaeJournal of Theoretical Biology10.1016/j.jtbi.2015.06.030382(15-22)Online publication date: Oct-2015
https://doi.org/10.1016/j.jtbi.2015.06.030
Yang PWu MGuo JKwoh CPrzytycka TZheng J(2014)LDsplit: screening for cis-regulatory motifs stimulating meiotic recombination hotspots by analysis of DNA sequence polymorphismsBMC Bioinformatics10.1186/1471-2105-15-4815:1Online publication date: 17-Feb-2014
https://doi.org/10.1186/1471-2105-15-48

Index Terms

Integration of genomic and epigenomic features to predict meiotic recombination hotspots in human and mouse
1. Applied computing
  1. Life and medical sciences
2. Information systems
  1. Information systems applications

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Published In

cover image ACM Conferences

BCB '12: Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine

October 2012

725 pages

ISBN:9781450316705

DOI:10.1145/2382936

General Chair:
Sanjay Ranka
University of Florida
,
Program Chairs:
Tamer Kahveci
University of Florida
,
Mona Singh
Princeton University

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 07 October 2012

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BCB' 12: ACM International Conference on Bioinformatics, Computational Biology and Biomedicine

October 7 - 10, 2012

Florida, Orlando

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BCB '12 Paper Acceptance Rate 33 of 159 submissions, 21%;

Overall Acceptance Rate 254 of 885 submissions, 29%

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Cited By

Liu GXing YCai L(2015)Using weighted features to predict recombination hotspots in Saccharomyces cerevisiaeJournal of Theoretical Biology10.1016/j.jtbi.2015.06.030382(15-22)Online publication date: Oct-2015
https://doi.org/10.1016/j.jtbi.2015.06.030
Yang PWu MGuo JKwoh CPrzytycka TZheng J(2014)LDsplit: screening for cis-regulatory motifs stimulating meiotic recombination hotspots by analysis of DNA sequence polymorphismsBMC Bioinformatics10.1186/1471-2105-15-4815:1Online publication date: 17-Feb-2014
https://doi.org/10.1186/1471-2105-15-48

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