共查询到20条相似文献,搜索用时 15 毫秒
1.
Yong Zeng Gang Wang Ence Yang Guoli Ji Candice L. Brinkmeyer-Langford James J. Cai 《PLoS genetics》2015,11(1)
Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions. 相似文献
2.
Genomic analysis of the relationship between gene expression variation and DNA polymorphism in Drosophila simulans
下载免费PDF全文
![点击此处可从《Genome biology》网站下载免费的PDF全文](/ch/ext_images/free.gif)
Background
Understanding how DNA sequence polymorphism relates to variation in gene expression is essential to connecting genotypic differences with phenotypic differences among individuals. Addressing this question requires linking population genomic data with gene expression variation.Results
Using whole genome expression data and recent light shotgun genome sequencing of six Drosophila simulans genotypes, we assessed the relationship between expression variation in males and females and nucleotide polymorphism across thousands of loci. By examining sequence polymorphism in gene features, such as untranslated regions and introns, we find that genes showing greater variation in gene expression between genotypes also have higher levels of sequence polymorphism in many gene features. Accordingly, X-linked genes, which have lower sequence polymorphism levels than autosomal genes, also show less expression variation than autosomal genes. We also find that sex-specifically expressed genes show higher local levels of polymorphism and divergence than both sex-biased and unbiased genes, and that they appear to have simpler regulatory regions.Conclusion
The gene-feature-based analyses and the X-to-autosome comparisons suggest that sequence polymorphism in cis-acting elements is an important determinant of expression variation. However, this relationship varies among the different categories of sex-biased expression, and trans factors might contribute more to male-specific gene expression than cis effects. Our analysis of sex-specific gene expression also shows that female-specific genes have been overlooked in analyses that only point to male-biased genes as having unusual patterns of evolution and that studies of sexually dimorphic traits need to recognize that the relationship between genetic and expression variation at these traits is different from the genome as a whole. 相似文献3.
4.
Heritable variation in regulatory or coding regions is the raw material for evolutionary processes. The advent of microarrays has recently promoted examination of the extent of variation in gene expression within and among taxa and examination of the evolutionary processes affecting variation. This review examines these issues. We find: (i) microarray-based measures of gene expression are precise given appropriate experimental design; (ii) there is large inter-individual variation, which is composed of a minor nongenetic component and a large heritable component; (iii) variation among populations and species appears to be affected primarily by neutral drift and stabilizing selection, and to a lesser degree by directional selection; and (iv) neutral evolutionary divergence in gene expression becomes nonlinear with greater divergence times due to functional constraint. Evolutionary analyses of gene expression reviewed here provide unique insights into partitioning of regulatory variation in nature. However, common limitations of these studies include the tendency to assume a linear relationship between expression divergence and species divergence, and failure to test explicit hypotheses that involve the ecological context of evolutionary divergence. 相似文献
5.
Wentzell AM Rowe HC Hansen BG Ticconi C Halkier BA Kliebenstein DJ 《PLoS genetics》2007,3(9):1687-1701
6.
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
Yevhen Vainshtein Mayka Sanchez Alvis Brazma Matthias W Hentze Thomas Dandekar Martina U Muckenthaler 《BMC bioinformatics》2010,11(1):112
Background
Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. 相似文献7.
Susana Campino Julian Forton Srilakshmi Raj Bert Mohr Sarah Auburn Andrew Fry Valentina D. Mangano Claire Vandiedonck Anna Richardson Kirk Rockett Taane G. Clark Dominic P. Kwiatkowski 《PloS one》2008,3(12)
Background
Localising regulatory variants that control gene expression is a challenge for genome research. Several studies have recently identified non-coding polymorphisms associated with inter-individual differences in gene expression. These approaches rely on the identification of signals of association against a background of variation due to other genetic and environmental factors. A complementary approach is to use an Allele-Specific Expression (ASE) assay, which is more robust to the effects of environmental variation and trans-acting genetic factors.Methodology/Principal Findings
Here we apply an ASE method which utilises heterozygosity within an individual to compare expression of the two alleles of a gene in a single cell. We used individuals from three HapMap population groups and analysed the allelic expression of genes with cis-regulatory regions previously identified using total gene expression studies. We were able to replicate the results in five of the six genes tested, and refined the cis- associated regions to a small number of variants. We also showed that by using multi-populations it is possible to refine the associated cis-effect DNA regions.Conclusions/Significance
We discuss the efficacy and drawbacks of both total gene expression and ASE approaches in the discovery of cis-acting variants. We show that the ASE approach has significant advantages as it is a cleaner representation of cis-acting effects. We also discuss the implication of using different populations to map cis-acting regions and the importance of finding regulatory variants which contribute to human phenotypic variation. 相似文献8.
9.
MOTIVATION: Comparisons of gene expression levels within and between species have become a central tool in the study of the genetic basis for phenotypic variation, as well as in the study of the evolution of gene regulation. DNA microarrays are a key technology that enables these studies. Currently, however, microarrays are only available for a small number of species. Thus, in order to study gene expression levels in species for which microarrays are not available, researchers face three sets of choices: (i) use a microarray designed for another species, but only compare gene expression levels within species, (ii) construct a new microarray for every species whose gene expression profiles will be compared or (iii) build a multi-species microarray with probes from each species of interest. Here, we use data collected using a multi-primate cDNA array to evaluate the reliability of each approach. RESULTS: We find that, for inter-species comparisons, estimates of expression differences based on multi-species microarrays are more accurate than those based on multiple species-specific arrays. We also demonstrate that within-species expression differences can be estimated using a microarray for a closely related species, without discernible loss of information. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. 相似文献
10.
11.
Hugh J. French Rosalind Attenborough Kristine Hardy M. Frances Shannon Rohan B. H. Williams 《Mammalian genome》2009,20(9-10):604-611
Our knowledge of regulatory mechanisms of gene expression and other chromosomal processes related to DNA methylation and chromatin state is continuing to grow at a rapid pace. Understanding how these epigenomic phenomena vary between individuals will have an impact on understanding their broader role in determining variation in gene expression and biochemical, physiological, and behavioural phenotypes. In this review we survey recent progress in this area, focusing on data available from humans. We highlight the role of obligatory (sequence-dependent) epigenomic variation as an important mechanism for generating interindividual variation that could impact our understanding of the mechanistic basis of complex trait architecture. 相似文献
12.
13.
14.
15.
16.
17.
Previous studies have shown that development can be robust to variation in parameters such as the timing or level of gene expression. This leads to the prediction that natural populations should be able to host developmental variation that has little phenotypic effect. Cryptic variation is of particular interest because it can result in selectable phenotypes when "released" by environmental or genetic factors. Currently, however, we have little idea of how variation is distributed between genes or over time in pattern formation processes. Here we survey expression of Notch (N), Spalt (Sal), and Engrailed (En) during butterfly eyespot determination to better understand how pattern formation may vary within a population. We observed substantial heterochronic variance in the progress of spatial expression patterns for all three proteins, suggesting some degree of developmental buffering in eyespot development. Peak variance for different proteins was found at both early and late stages of development, contrasting with previous models suggesting that the distribution of variance should be more temporally focused during pattern formation. We speculate that our observations are representative of a standing reservoir of cryptic variation that may contribute to phenotypic evolution under certain circumstances. Our results also provide a strong cautionary message that gene expression studies with limited sample sizes can be positively misleading in terms of inferring expression pattern time series, as well as for making cross-species phylogenetic comparisons. 相似文献
18.
19.
The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements 总被引:2,自引:0,他引:2
MAQC Consortium Shi L Reid LH Jones WD Shippy R Warrington JA Baker SC Collins PJ de Longueville F Kawasaki ES Lee KY Luo Y Sun YA Willey JC Setterquist RA Fischer GM Tong W Dragan YP Dix DJ Frueh FW Goodsaid FM Herman D Jensen RV Johnson CD Lobenhofer EK Puri RK Schrf U Thierry-Mieg J Wang C Wilson M Wolber PK Zhang L Amur S Bao W Barbacioru CC Lucas AB Bertholet V Boysen C Bromley B Brown D Brunner A Canales R Cao XM Cebula TA Chen JJ Cheng J Chu TM Chudin E Corson J Corton JC Croner LJ 《Nature biotechnology》2006,24(9):1151-1161
Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. 相似文献
20.