Natural variation in genome architecture among 205 <i>Drosophila melanogaster</i> Genetic Reference Panel lines

Wen Huang(North Carolina State University), Andreas Massouras(SIB Swiss Institute of Bioinformatics), Yutaka Inoue(Osaka University of Arts), Jason A. Peiffer(North Carolina State University), Miquel Ràmia(Universitat Autònoma de Barcelona), Aaron M. Tarone(Texas A&M University), Lavanya Turlapati(North Carolina State University), Thomas Zichner(European Molecular Biology Laboratory), Dianhui Zhu(Baylor College of Medicine), Richard F. Lyman(North Carolina State University), Michael M. Magwire(North Carolina State University), Kerstin P. Blankenburg(Baylor College of Medicine), Mary Anna Carbone(North Carolina State University), Kyle Chang(Baylor College of Medicine), Lisa L. Ellis(Texas A&M University), Sonia Rodríguez Fernández(Baylor College of Medicine), Yi Han(Baylor College of Medicine), Gareth Highnam(Virginia Tech), Carl E. Hjelmen(Texas A&M University), John Jack(North Carolina State University), Mehwish Javaid(Baylor College of Medicine), Joy C. Jayaseelan(Baylor College of Medicine), Divya Kalra(Baylor College of Medicine), Sandy Lee(Baylor College of Medicine), Lora Lewis(Baylor College of Medicine), Mala Munidasa(Baylor College of Medicine), Fiona Ongeri(Baylor College of Medicine), Shohba Patel(Baylor College of Medicine), Lora Perales(Baylor College of Medicine), Agapito Perez(Baylor College of Medicine), Lingling Pu(Baylor College of Medicine), Stephanie M. Rollmann(North Carolina State University), R. Montgomery Ruth(Baylor College of Medicine), Nehad Saada(Baylor College of Medicine), Crystal B. Warner(Baylor College of Medicine), Aneisa Williams(Baylor College of Medicine), Yuanqing Wu(Baylor College of Medicine), Akihiko Yamamoto(North Carolina State University), Yiqing Zhang(Baylor College of Medicine), Yiming Zhu(Baylor College of Medicine), Robert R. H. Anholt(North Carolina State University), Jan O. Korbel(European Molecular Biology Laboratory), David Mittelman(Virginia Tech), Donna M. Muzny(Baylor College of Medicine), Richard A. Gibbs(Baylor College of Medicine), Antonio Barbadilla(Universitat Autònoma de Barcelona), J. Spencer Johnston(Texas A&M University), Eric A. Stone(North Carolina State University), Stephen Richards(Baylor College of Medicine), Bart Deplancke(SIB Swiss Institute of Bioinformatics), Trudy F. C. Mackay(North Carolina State University)
Genome Research
April 8, 2014
Cited by 711Open Access
Full Text

Abstract

The Drosophila melanogaster Genetic Reference Panel (DGRP) is a community resource of 205 sequenced inbred lines, derived to improve our understanding of the effects of naturally occurring genetic variation on molecular and organismal phenotypes. We used an integrated genotyping strategy to identify 4,853,802 single nucleotide polymorphisms (SNPs) and 1,296,080 non-SNP variants. Our molecular population genomic analyses show higher deletion than insertion mutation rates and stronger purifying selection on deletions. Weaker selection on insertions than deletions is consistent with our observed distribution of genome size determined by flow cytometry, which is skewed toward larger genomes. Insertion/deletion and single nucleotide polymorphisms are positively correlated with each other and with local recombination, suggesting that their nonrandom distributions are due to hitchhiking and background selection. Our cytogenetic analysis identified 16 polymorphic inversions in the DGRP. Common inverted and standard karyotypes are genetically divergent and account for most of the variation in relatedness among the DGRP lines. Intriguingly, variation in genome size and many quantitative traits are significantly associated with inversions. Approximately 50% of the DGRP lines are infected with Wolbachia, and four lines have germline insertions of Wolbachia sequences, but effects of Wolbachia infection on quantitative traits are rarely significant. The DGRP complements ongoing efforts to functionally annotate the Drosophila genome. Indeed, 15% of all D. melanogaster genes segregate for potentially damaged proteins in the DGRP, and genome-wide analyses of quantitative traits identify novel candidate genes. The DGRP lines, sequence data, genotypes, quality scores, phenotypes, and analysis and visualization tools are publicly available.


Related Papers

No related papers found

Powered by citation graph analysis