Genomic analysis of the relationship between gene expression variation and DNA polymorphism in Drosophila simulans

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.     

Development of a genotype‐by‐sequencing immunogenetic assay as exemplified by screening for variation in red fox with and without endemic rabies exposure

Pathogens are recognized as major drivers of local adaptation in wildlife systems. By determining which gene variants are favored in local interactions among populations with and without disease, spatially explicit adaptive responses to pathogens can be elucidated. Much of our current understanding of host responses to disease comes from a small number of genes associated with an immune response. High‐throughput sequencing (HTS) technologies, such as genotype‐by‐sequencing (GBS), facilitate expanded explorations of genomic variation among populations. Hybridization‐based GBS techniques can be leveraged in systems not well characterized for specific variants associated with disease outcome to “capture” specific genes and regulatory regions known to influence expression and disease outcome. We developed a multiplexed, sequence capture assay for red foxes to simultaneously assess ~300‐kbp of genomic sequence from 116 adaptive, intrinsic, and innate immunity genes of predicted adaptive significance and their putative upstream regulatory regions along with 23 neutral microsatellite regions to control for demographic effects. The assay was applied to 45 fox DNA samples from Alaska, where three arctic rabies strains are geographically restricted and endemic to coastal tundra regions, yet absent from the boreal interior. The assay provided 61.5% on‐target enrichment with relatively even sequence coverage across all targeted loci and samples (mean = 50×), which allowed us to elucidate genetic variation across introns, exons, and potential regulatory regions (4,819 SNPs). Challenges remained in accurately describing microsatellite variation using this technique; however, longer‐read HTS technologies should overcome these issues. We used these data to conduct preliminary analyses and detected genetic structure in a subset of red fox immune‐related genes between regions with and without endemic arctic rabies. This assay provides a template to assess immunogenetic variation in wildlife disease systems.     

Gene CATCHR--gene cloning and tagging for Caenorhabditis elegans using yeast homologous recombination: a novel approach for the analysis of gene expression

Expression patterns of gene products provide important insights into gene function. Reporter constructs are frequently used to analyze gene expression in Caenorhabditis elegans, but the sequence context of a given gene is inevitably altered in such constructs. As a result, these transgenes may lack regulatory elements required for proper gene expression. We developed Gene Catchr, a novel method of generating reporter constructs that exploits yeast homologous recombination (YHR) to subclone and tag worm genes while preserving their local sequence context. YHR facilitates the cloning of large genomic regions, allowing the isolation of regulatory sequences in promoters, introns, untranslated regions and flanking DNA. The endogenous regulatory context of a given gene is thus preserved, producing expression patterns that are as accurate as possible. Gene Catchr is flexible: any tag can be inserted at any position without introducing extra sequence. Each step is simple and can be adapted to process multiple genes in parallel. We show that expression patterns derived from Gene Catchr transgenes are consistent with previous reports and also describe novel expression data. Mutant rescue assays demonstrate that Gene Catchr-generated transgenes are functional. Our results validate the use of Gene Catchr as a valuable tool to study spatiotemporal gene expression.     

Nucleotide variation in the tinman and bagpipe homeobox genes of Drosophila melanogaster

The tinman (tin) and bagpipe (bap) genes are members of the NK homeobox gene family of Drosophila, so that tin occupies a higher position than bap in the regulatory hierarchy. Little is known about the level and pattern of genetic polymorphism in homeobox genes. We have analyzed nucleotide polymorphism in 27 strains of Drosophila melanogaster and one each of D. simulans and D. sechellia, within two closely linked regions encompassing a partial sequence of tin and the complete sequence of bap. The two genes exhibit different levels and patterns of nucleotide diversity. Two sets of sharply divergent sequence types are detected for tin. The haplotype structure of bap is more complex: about half of the sequences are identical (or virtually so), while the rest are fairly heterogeneous. The level of silent nucleotide variability is 0.0063 for tin but significantly higher, 0.0141, for bap, a level of polymorphism comparable to the most polymorphic structural genes of D. melanogaster. Recombination rate and gene conversion are also higher for bap than for tin. There is strong linkage disequilibrium, with the highest values in the introns of both genes and exon II of bap. The patterns of polymorphism in tin and bap are not compatible with an equilibrium model of selective neutrality. We suggest that negative selection and demographic history are the major factors shaping the pattern of nucleotide polymorphism in the tin and bap genes; moreover, there are clear indications of positive selection in the bap gene.     

Analysis of the QTL for sleep homeostasis in mice: Homer1a is a likely candidate.

Electroencephalographic oscillations in the frequency range of 0.5-4 Hz, characteristic of slow-wave sleep (SWS), are often referred to as the delta oscillation or delta power. Delta power reflects sleep intensity and correlates with the homeostatic response to sleep loss. A published survey of inbred strains of mice demonstrated that the time course of accumulation of delta power varied among inbred strains, and the segregation of the rebound of delta power in BxD recombinant inbred strains identified a genomic region on chromosome 13 referred to as the delta power in SWS (or Dps1). The quantitative trait locus (QTL) contains genes that modify the accumulation of delta power after sleep deprivation. Here, we narrow the QTL using interval-specific haplotype analysis and present a comprehensive annotation of the remaining genes in the Dps1 region with sequence comparisons to identify polymorphisms within the coding and regulatory regions. We established the expression pattern of selected genes located in the Dps1 interval in sleep and wakefulness in B6 and D2 parental strains. Taken together, these steps reduced the number of potential candidate genes that may underlie the accumulation of delta power after sleep deprivation and explain the Dps1 QTL. The strongest candidate gene is Homer1a, which is supported by expression differences between sleep and wakefulness and the SNP polymorphism in the upstream regulatory regions.     

The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity

Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene’s proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene’s regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen’s Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance, ncCADD and ncGWAVA, and find both scores are significantly predictive of human dosage sensitive genes and appear to carry information beyond conservation, as assessed by ncGERP. These results highlight that the intolerance of noncoding sequence stretches in the human genome can provide a critical complementary tool to other genome annotation approaches to help identify the parts of the human genome increasingly likely to harbor mutations that influence risk of disease.     

Effects of cis and trans regulatory variations on the expression divergence of heat shock response genes between yeast strains

Phenotypic variation among individuals in a population can be due to DNA sequence variation in protein coding regions or in regulatory elements. Recently, many studies have indicated that mutations in regulatory elements may be the major cause of phenotypic evolution. However, the mechanisms for evolutionary changes in gene expression are still not well understood. Here, we studied the relative roles of cis and trans regulatory changes in Saccharomyces cerevisiae cells to cope with heat stress. It has been found that the expression level of ~ 300 genes was induced at least two fold and that of ~ 500 genes was repressed at least two fold in response to heat shock. From the former set of genes, we randomly selected 65 genes that showed polymorphism(s) between the BY and RM strains for pyrosequencing analysis to explore the relative contributions of cis and trans regulatory variations to the expression divergence between BY and RM. Our data indicated that the expression divergence between BY and RM was mainly due to trans regulatory variations under either the normal condition or the heat stress condition. However, the relative contribution of trans regulatory variation was decreased from 76.9% to 61.5% after the heat shock stress. These results indicated that the cis regulatory variation may play an important role in the adaption to heat stress. In our data, 43.1% (28 genes) of the 65 genes showed the same trend of cis or trans variation effect after the heat shock stress, 35.4% (23 genes) showed an increased cis variation effect and 21.5% (14 genes) showed an increased trans variation effect after the heat shock stress. Thus, our data give insights into the relative roles of cis and trans variations in response to heat shock in yeast.