Genomic Variation and Its Impact on Gene Expression in Drosophila melanogaster

Understanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals.     

The Impact of Gene Expression Variation on the Robustness and Evolvability of a Developmental Gene Regulatory Network

Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear), allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.     

Behavior and Genetic Variation in Natural Populations

An analysis of allelic variation at genetic loci controllingseveral esterases and hemoglobin, as demonstrated by electrophoresis,indicates that wild populations of the house mouse (Mus musculus)are characterized by fine-scale genetic subdivision, which,through the territorial behavior of family groups (tribes),is achieved even in the absence of physical or ecological barriersto migration. Heterogeneity in allele frequencies among samples from farmsin the same region and from barns on the same farm was demonstrated.Spatial variation in allele frequencies within single barns,involving a clustering of like genotypes, was shown by grid-trapping,thus providing direct evidence of tribal subdivision in continuouslydistributed populations. For two loci, Es-3 and Hbb, an excess of heterozygotes appearedin samples from small populations, while a deficit characterizedsamples from large populations. The evolutionary significance of subdivision and consequentdrift in house mouse populations cannot properly be evaluatedat this time. Although stochastic processes may play the dominantrole in determining, at a given locus, the genotypes of individualsand frequencies of alleles in small populations, geographicpatterns of variation, as studied in Texas, are characterizedby uniformity of allelic frequency in major physiographic orclimatic regions, as would be expected if selection is determiningthe frequencies.     

脊椎动物心肌基因表达的分子调控

鉴定在心脏发育过程中指导心脏形成的分子途径,将对心脏是如何形成和这些途径的打断如何导致先天性以及后天性心脏病的发生提供一个基本的认识,尽管脊椎动物骨骼肌和心肌看起来很相似,然而,它们的细胞谱系的特化和模式化是由不同的基因推动的,已知有几个转录因子家族在心肌发育和模式建成中发挥重要作用,包括MADS同源盒蛋白MEF2和SRF,螺旋-环-螺旋HAND因子,锌指GATA-4/5/6因子和NK-2同源异型因子,这些转录因子能激活心脏目标基因,从而调控心肌基因的表达.     

Identifying the Genetic Variation of Gene Expression Using Gene Sets: Application of Novel Gene Set eQTL Approach to PharmGKB and KEGG

Genetic variation underlying the regulation of mRNA gene expression in humans may provide key insights into the molecular mechanisms of human traits and complex diseases. Current statistical methods to map genetic variation associated with mRNA gene expression have typically applied standard linkage and/or association methods; however, when genome-wide SNP and mRNA expression data are available performing all pair wise comparisons is computationally burdensome and may not provide optimal power to detect associations. Consideration of different approaches to account for the high dimensionality and multiple testing issues may provide increased efficiency and statistical power. Here we present a novel approach to model and test the association between genetic variation and mRNA gene expression levels in the context of gene sets (GSs) and pathways, referred to as gene set - expression quantitative trait loci analysis (GS-eQTL). The method uses GSs to initially group SNPs and mRNA expression, followed by the application of principal components analysis (PCA) to collapse the variation and reduce the dimensionality within the GSs. We applied GS-eQTL to assess the association between SNP and mRNA expression level data collected from a cell-based model system using PharmGKB and KEGG defined GSs. We observed a large number of significant GS-eQTL associations, in which the most significant associations arose between genetic variation and mRNA expression from the same GS. However, a number of associations involving genetic variation and mRNA expression from different GSs were also identified. Our proposed GS-eQTL method effectively addresses the multiple testing limitations in eQTL studies and provides biological context for SNP-expression associations.     

Genetic Variation in Natural Populations of Stipa tenacissima from Algeria

Intermicrosatellite PCR [inter-simple sequence repeat (ISSR)-PCR] markers and cytogenetics criteria were used to assess the level of genetic diversity and genetic structure in 17 populations of Stipa tenacissima (Gramineae) from Algeria. All populations sampled in the steppe area were diploids (2n = 2x = 24), and those sampled in the dry area were hexaploids (2n = 6x = 72). The dendrogram based on ISSR-PCR showed homogeneity within populations and large variability among populations. All individuals of the same population were gathered and formed groups clearly separated in all populations. These groups were separated into two clusters related to biotope, one from the steppe area and the other from the dry area. AMOVA indicated low genetic diversity among populations (30% of variation) and high within populations (70%). This variation pattern would constitute an adaptive strategy to grow in various ecological conditions.     

山猪群体钙调蛋白酶抑制蛋白基因遗传变异研究

目的：研究猪钙调蛋白酶抑制蛋白（CAST）基因在山猪群体的遗传变异情况,为山猪肉质研究奠定基础。方法：应用PCR-SSCP技术和测序方法检测山猪及其杂种猪CAST基因的遗传多态性,并与其他品种猪相应序列进行比较。结果：用pCT1引物在山猪及其杂种群体中检测到2个多态位点（A,B）,用pCT2引物检测到3个多态位点（C,D,E）;序列分析表明,C和E位点共同拥有6处变异。结论：通过与其他猪品种比较,发现山猪的CASTMsp基因型分布与梅山猪的基因型分布完全一样,而与国外品种猪的基因型分布差异明显。     

Tissue-Specific Effects of Genetic and Epigenetic Variation on Gene Regulation and Splicing

Understanding how genetic variation affects distinct cellular phenotypes, such as gene expression levels, alternative splicing and DNA methylation levels, is essential for better understanding of complex diseases and traits. Furthermore, how inter-individual variation of DNA methylation is associated to gene expression is just starting to be studied. In this study, we use the GenCord cohort of 204 newborn Europeans’ lymphoblastoid cell lines, T-cells and fibroblasts derived from umbilical cords. The samples were previously genotyped for 2.5 million SNPs, mRNA-sequenced, and assayed for methylation levels in 482,421 CpG sites. We observe that methylation sites associated to expression levels are enriched in enhancers, gene bodies and CpG island shores. We show that while the correlation between DNA methylation and gene expression can be positive or negative, it is very consistent across cell-types. However, this epigenetic association to gene expression appears more tissue-specific than the genetic effects on gene expression or DNA methylation (observed in both sharing estimations based on P-values and effect size correlations between cell-types). This predominance of genetic effects can also be reflected by the observation that allele specific expression differences between individuals dominate over tissue-specific effects. Additionally, we discover genetic effects on alternative splicing and interestingly, a large amount of DNA methylation correlating to alternative splicing, both in a tissue-specific manner. The locations of the SNPs and methylation sites involved in these associations highlight the participation of promoter proximal and distant regulatory regions on alternative splicing. Overall, our results provide high-resolution analyses showing how genome sequence variation has a broad effect on cellular phenotypes across cell-types, whereas epigenetic factors provide a secondary layer of variation that is more tissue-specific. Furthermore, the details of how this tissue-specificity may vary across inter-relations of molecular traits, and where these are occurring, can yield further insights into gene regulation and cellular biology as a whole.