Thumbnail Image
Item

Population Genomic Inferences from Sparse High-Throughput Sequencing of Two Populations of Drosophila melanogaster

Sackton, Timothy B
; 
Kulathinal, Rob J
; 
Bergman, Casey M
; 
Quinlan, Aaron R
; 
Dopman, Erik B
; 
Carneiro, Mauricio
; 
Marth, Gabor T
; 
Hartl, Daniel L
; 
Clark, Andrew G
Citations
Altmetric:
Genre
Journal Article
Date
2009-01-01
Advisor
Committee member
Group
Department
Subject
Drosophila
 copy number polymorphism
 next-gen sequencing
 nucleotide diversity
 population genomics
 transposable elements
Permanent link to this record
http://hdl.handle.net/20.500.12613/5593
Collections
Faculty/Researcher Works
Show all metadata
Files
Thumbnail Image
Population genomic inferences from sparse high-throughput sequencing of two populations of Drosophila melanogaster.pdf
Adobe PDF, 762.11 KB
Research Projects
Organizational Units
Journal Issue
DOI
10.1093/gbe/evp048
Abstract
Short-read sequencing techniques provide the opportunity to capture genome-wide sequence data in a single experiment. A current challenge is to identify questions that shallow-depth genomic data can address successfully and to develop corresponding analytical methods that are statistically sound. Here, we apply the Roche/454 platform to survey natural variation in strains of Drosophila melanogaster from an African (n = 3) and a North American (n = 6) population. Reads were aligned to the reference D. melanogaster genomic assembly, single nucleotide polymorphisms were identified, and nucleotide variation was quantified genome wide. Simulations and empirical results suggest that nucleotide diversity can be accurately estimated from sparse data with as little as 0.2x coverage per line. The unbiased genomic sampling provided by random short-read sequencing also allows insight into distributions of transposable elements and copy number polymorphisms found within populations and demonstrates that short-read sequencing methods provide an efficient means to quantify variation in genome organization and content. Continued development of methods for statistical inference of shallow-depth genome-wide sequencing data will allow such sparse, partial data sets to become the norm in the emerging field of population genomics.
Description
Citation
Citation to related work
Oxford University Press (OUP)
Has part
Genome Biology and Evolution
ADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
Embedded videos