title: Detecting highly differentiated copy-number variants from pooled population sequencing.
abstract: Copy-number variants (CNVs) represent a functionally and evolutionarily important class of variation. Here we take advantage of the use of pooled sequencing to detect CNVs with large differences in allele frequency between population samples. We present a method for detecting CNVs in pooled population samples using a combination of paired-end sequences and read-depth. Highly differentiated CNVs show large differences in the number of paired-end reads supporting individual alleles and large differences in readdepth between population samples. We complement this approach with one that uses a hidden Markov model to find larger regions differing in read-depth between samples. Using novel pooled sequence data from two populations of Drosophila melanogaster along a latitudinal cline, we demonstrate the utility of our method for identifying CNVs involved in local adaptation.
authors: Department of Biology and School of Informatics and Computing, Indiana University, 1001 E Third St., Bloomington, IN 47405, USA. dschride@indiana.edu
authors: Daniel R
authors: DR
authors: Schrider
authors: David J
authors: DJ
authors: Begun
authors: Matthew W
authors: MW
authors: Hahn
mesh_terms: D000064:Acclimatization / Q000235:genetics; D000818:Animals; D019295:Computational Biology; D056915:DNA Copy Number Variations; D004331:Drosophila melanogaster / Q000235:genetics* / Q000502:physiology; D005787:Gene Frequency; D005828:Genetics, Population / Q000706:statistics & numerical data; D008390:Markov Chains; D012641:Selection, Genetic