Determining causality and consequence of expression quantitative trait loci

Expression quantitative trait loci (eQTLs) are currently the most abundant and systematically-surveyed class of functional consequence for genetic variation. Recent genetic studies of gene expression have identified thousands of eQTLs in diverse tissue types for the majority of human genes. Application of this large eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases. However, only now has both the availability of individuals with full genomes and corresponding advances in functional genomics provided the opportunity to dissect eQTLs to identify causal regulatory variants. Resolving the properties of such causal regulatory variants is improving understanding of the molecular mechanisms that influence traits and guiding the development of new genome-scale approaches to variant interpretation. In this review, we provide an overview of current computational and experimental methods for identifying causal regulatory variants and predicting their phenotypic consequences.     

Gene expression in skin and lymphoblastoid cells: Refined statistical method reveals extensive overlap in cis-eQTL signals

Psoriasis, an immune-mediated, inflammatory disease of the skin and joints, provides an ideal system for expression quantitative trait locus (eQTL) analysis, because it has a strong genetic basis and disease-relevant tissue (skin) is readily accessible. To better understand the role of genetic variants regulating cutaneous gene expression, we identified 841 cis-acting eQTLs using RNA extracted from skin biopsies of 53 psoriatic individuals and 57 healthy controls. We found substantial overlap between cis-eQTLs of normal control, uninvolved psoriatic, and lesional psoriatic skin. Consistent with recent studies and with the idea that control of gene expression can mediate relationships between genetic variants and disease risk, we found that eQTL SNPs are more likely to be associated with psoriasis than are randomly selected SNPs. To explore the tissue specificity of these eQTLs and hence to quantify the benefits of studying eQTLs in different tissues, we developed a refined statistical method for estimating eQTL overlap and used it to compare skin eQTLs to a published panel of lymphoblastoid cell line (LCL) eQTLs. Our method accounts for the fact that most eQTL studies are likely to miss some true eQTLs as a result of power limitations and shows that ～70% of cis-eQTLs in LCLs are shared with skin, as compared with the naive estimate of < 50% sharing. Our results provide a useful method for estimating the overlap between various eQTL studies and provide a catalog of cis-eQTLs in skin that can facilitate efforts to understand the functional impact of identified susceptibility variants on psoriasis and other skin traits.     

Genetics of gene expression characterizes response to selective breeding for alcohol preference

Numerous selective breeding experiments have been performed with rodents, in an attempt to understand the genetic basis for innate differences in preference for alcohol consumption. Quantitative trait locus (QTL) analysis has been used to determine regions of the genome that are associated with the behavioral difference in alcohol preference/consumption. Recent work suggests that differences in gene expression represent a major genetic basis for complex traits. Therefore, the QTLs are likely to harbor regulatory regions (eQTLs) for the differentially expressed genes that are associated with the trait. In this study, we examined brain gene expression differences over generations of selection of the third replicate lines of high and low alcohol‐preferring (HAP3 and LAP3) mice, and determined regions of the genome that control the expression of these differentially expressed genes (_deeQTLs). We also determined eQTL regions (_rveQTLs) for genes that showed a decrease in variance of expression levels over the course of selection. We postulated that _deeQTLs that overlap with _rveQTLs, and also with phenotypic QTLs, represent genomic regions that are affected by the process of selection. These overlapping regions controlled the expression of candidate genes (that displayed differential expression and reduced variance of expression) for the predisposition to differences in alcohol consumption by the HAP3/LAP3 mice.     

Genetical genomics in livestock: potentials and pitfalls

Genetical genomics combines gene mapping and gene expression approaches to identify loci controlling gene expression (eQTLs) that may underlie functional trait variation. The combination of genomic tools has great potential to facilitate dissection of complex traits, but studies need careful design and interpretation. Here we explore both the potential and the pitfalls of this approach with illustrations from actual studies. There are now an appreciable number of studies in model species and even humans demonstrating the feasibility of genetical genomics. However, most studies are too limited in size and design to unlock the full potential of the approach. Limited statistical power of studies exacerbates the problem of detection of false-positive eQTL and some reported results should be interpreted with caution. As one approach to more successful implementation of genetical genomics, we propose to combine expression studies with fine mapping of functional trait loci. This synergistic approach facilitates the implementation of genetical genomics for species without inbred resources but is equally applicable to model species. These properties make it particularly suitable for livestock populations where many QTL are already in the public domain and potentially very large pedigreed populations can be accessed.     

Expression quantitative trait loci: present and future

The last few years have seen the development of large efforts for the analysis of genome function, especially in the context of genome variation. One of the most prominent directions has been the extensive set of studies on expression quantitative trait loci (eQTLs), namely, the discovery of genetic variants that explain variation in gene expression levels. Such studies have offered promise not just for the characterization of functional sequence variation but also for the understanding of basic processes of gene regulation and interpretation of genome-wide association studies. In this review, we discuss some of the key directions of eQTL research and its implications.     

Transient expression assays in grapevine: a step towards genetic improvement

In the past few years, the usefulness of transient expression assays has continuously increased for the characterization of unknown gene function and metabolic pathways. In grapevine (Vitis vinifera L.), one of the most economically important fruit crops in the world, recent systematic sequencing projects produced many gene data sets that require detailed analysis. Due to their rapid nature, transient expression assays are well suited for large‐scale genetic studies. Although genes and metabolic pathways of any species can be analysed by transient expression in model plants, a need for homologous systems has emerged to avoid the misinterpretation of results due to a foreign genetic background. Over the last 10 years, various protocols have thus been developed to apply this powerful technology to grapevine. Using cell suspension cultures, somatic embryos, leaves or whole plantlets, transient expression assays enabled the study of the function, regulation and subcellular localization of genes involved in specific metabolic pathways such as the biosynthesis of phenylpropanoids. Disease resistance genes that could be used for marker‐assisted selection in conventional breeding or for stable transformation of elite cultivars have also been characterized. Additionally, transient expression assays have proved useful for shaping new tools for grapevine genetic improvement: synthetic promoters, silencing constructs, minimal linear cassettes or viral vectors. This review provides an update on the different tools (DNA constructs, reporter genes, vectors) and methods (Agrobacterium‐mediated and direct gene transfer methods) available for transient gene expression in grapevine. The most representative results published thus far are then described.     

Revealing the architecture of gene regulation: the promise of eQTL studies

Expression quantitative trait loci (eQTL) mapping studies have become a widely used tool for identifying genetic variants that affect gene regulation. In these studies, expression levels are viewed as quantitative traits, and gene expression phenotypes are mapped to particular genomic loci by combining studies of variation in gene expression patterns with genome-wide genotyping. Results from recent eQTL mapping studies have revealed substantial heritable variation in gene expression within and between populations. In many cases, genetic factors that influence gene expression levels can be mapped to proximal (putatively cis) eQTLs and, less often, to distal (putatively trans) eQTLs. Beyond providing great insight into the biology of gene regulation, a combination of eQTL studies with results from traditional linkage or association studies of human disease may help predict a specific regulatory role for polymorphic sites previously associated with disease.     

Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State

Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombinant inbred mouse strains. This analysis allowed us to analyze eQTL robustness/sensitivity across different cellular differentiation states. Although we identified a large number (365) of “static” eQTLs that were consistently active in all four cell types, we found a much larger number (1,283) of “dynamic” eQTLs showing cell-type–dependence. Of these, 140, 45, 531, and 295 were preferentially active in stem, progenitor, erythroid, and myeloid cells, respectively. A detailed investigation of those dynamic eQTLs showed that in many cases the eQTL specificity was associated with expression changes in the target gene. We found no evidence for target genes that were regulated by distinct eQTLs in different cell types, suggesting that large-scale changes within functional regulatory networks are uncommon. Our results demonstrate that heritable differences in gene expression are highly sensitive to the developmental stage of the cell population under study. Therefore, future genetical genomics studies should aim at studying multiple well-defined and highly purified cell types in order to construct as comprehensive a picture of the changing functional regulatory relationships as possible.     

Phenotypic plasticity in gene expression contributes to divergence of locally adapted populations of Fundulus heteroclitus

We examine the interaction between phenotypic plasticity and evolutionary adaptation using muscle gene expression levels among populations of the fish Fundulus heteroclitus acclimated to three temperatures. Our analysis reveals shared patterns of phenotypic plasticity due to thermal acclimation as well as non‐neutral patterns of variation among populations adapted to different thermal environments. For the majority of significant differences in gene expression levels, phenotypic plasticity and adaptation operate on different suites of genes. The subset of genes that demonstrate both adaptive differences and phenotypic plasticity, however, exhibit countergradient variation of expression. Thus, expression differences among populations counteract environmental effects, reducing the phenotypic differentiation between populations. Finally, gene‐by‐environment interactions among genes with non‐neutral patterns of expression suggest that the penetrance of adaptive variation depends on the environmental conditions experienced by the individual.     

生态基因组学研究进展

生态基因组学是一个整合生态学、分子遗传学和进化基因组学的新兴交叉学科。生态基因组学将基因组学的研究手段和方法引入生态学领域,通过将群体基因组学、转录组学、蛋白质组学等手段与方法将个体、种群及群落、生态系统不同层次的生态学相互作用整合起来,确定在生态学响应及相互作用中具有重要意义的关键的基因和遗传途径,阐明这些基因及遗传途径变异的程度及其生态和进化后果的特征,从基因水平探索有机体响应天然环境(包括生物与非生物的环境因子)的遗传学机制。生态基因组学的研究对象可以分为模式生物与非模式生物两大类。拟南芥、酿酒酵母等模式生物在生态基因组学领域发挥了重要作用。随着越来越多基因组学技术的开发与完善,越来越多的非模式生物生态基因组学的研究将为生态学的发展提供重要的理论与实践依据。生态基因组学最核心的方法包括寻找序列变异、研究基因差异表达和分析基因功能等方法。生态基因组学已广泛渗透到生态学的相关领域中,将会在生物对环境的响应、物种间的相互作用、进化生态学、全球变化生态学、入侵生态学、群落生态学等研究领域发挥更大的作用。     

Genomic approaches to analyzing natural variation in Arabidopsis thaliana

The genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Abundant polymorphic markers aid quantitative trait locus (QTL) mapping, the fully sequenced genome provides rapid identification of candidate loci, and extensive knockout collections allow those candidate loci to be tested. Combining QTL mapping of classic phenotypic traits with biochemical or expression analysis is providing mechanistic insight into the traits of interest. Conversely, natural variation studies are now being done on genomic traits such as methylation or chiasma frequency.