Mixture modeling of transcript abundance classes in natural populations

Hsieh, Wen-Ping, Passador-Gurgel, Gisele, Stone, Eric A. and Gibson, Greg (2007) Mixture modeling of transcript abundance classes in natural populations. Genome Biology, 8 6: 1-14. doi:10.1186/gb-2007-8-6-r98


Author Hsieh, Wen-Ping
Passador-Gurgel, Gisele
Stone, Eric A.
Gibson, Greg
Title Mixture modeling of transcript abundance classes in natural populations
Journal name Genome Biology   Check publisher's open access policy
ISSN 1474-760X
Publication date 2007-06-04
Sub-type Article (original research)
DOI 10.1186/gb-2007-8-6-r98
Open Access Status DOI
Volume 8
Issue 6
Start page 1
End page 14
Total pages 14
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Formatted abstract
Background
Populations diverge in genotype and phenotype under the influence of such evolutionary processes as genetic drift, mutation accumulation, and natural selection. Because genotype maps onto phenotype by way of transcription, it is of interest to evaluate how these evolutionary factors influence the structure of variation at the level of transcription. Here, we explore the distributions of cis-acting and trans-acting factors and their relative contributions to expression of transcripts that exhibit two or more classes of abundance among individuals within populations.

Results
Expression profiling using cDNA microarrays was conducted in Drosophila melanogaster adult female heads for 58 nearly isogenic lines from a North Carolina population and 50 from a California population. Using a mixture modeling approach, transcripts were identified that exhibit more than one mode of transcript abundance across the samples. Power studies indicate that sample sizes of 50 individuals will generally be sufficient to detect divergent transcript abundance classes. The distribution of transcript abundance classes is skewed toward low frequency minor classes, which is reminiscent of the typical skew in genotype frequencies. Similar results are observed in reported data on gene expression in human lymphoblast cell lines, in which analysis of association with linked polymorphisms implies that cis-acting single nucleotide polymorphisms make only a modest contribution to bimodal distributions of transcript abundance.

Conclusion
Population surveys of gene expression may complement genetical genomics as a general approach to quantifying sources of transcriptional variation. Differential expression of transcripts among individuals is due to a complex interplay of cis-acting and trans-acting factors.
Keyword Molecular biology
Biology
Genomes
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Biological Sciences Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 10 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Thu, 05 Mar 2009, 11:34:36 EST by Ms Karen Naughton on behalf of School of Biological Sciences