Inherited variation in gene expression

Novel insights into the pleiotropic health effects of growth differentiation factor 11 gained from genome-wide association studies in population biobanks

BACKGROUND

Growth differentiation factor 11 (GDF11) is a member of the transforming growth factor-β (TGF-β) superfamily that has gained considerable attention over the last decade for its observed ability to reverse age-related deterioration of multiple tissues, including the heart. Yet as many researchers have struggled to confirm the cardioprotective and anti-aging effects of GDF11, the topic has grown increasingly controversial, and the field has reached an impasse. We postulated that a clearer understanding of GDF11 could be gained by investigating its health effects at the population level.

METHODS AND RESULTS

We employed a comprehensive strategy to interrogate results from genome-wide association studies in population Biobanks. Interestingly, phenome-wide association studies (PheWAS) of GDF11 tissue-specific cis-eQTLs revealed associations with asthma, immune function, lung function, and thyroid phenotypes. Furthermore, PheWAS of GDF11 genetic variants confirmed these results, revealing similar associations with asthma, immune function, lung function, and thyroid health. To complement these findings, we mined results from transcriptome-wide association studies, which uncovered associations between predicted tissue-specific GDF11 expression and the same health effects identified from PheWAS analyses.

CONCLUSIONS

In this study, we report novel relationships between GDF11 and disease, namely asthma and hypothyroidism, in contrast to its formerly assumed role as a rejuvenating factor in basic aging and cardiovascular health. We propose that these associations are mediated through the involvement of GDF11 in inflammatory signaling pathways. Taken together, these findings provide new insights into the health effects of GDF11 at the population level and warrant future studies investigating the role of GDF11 in these specific health conditions.

Synergy of gut microbiota and host genome in driving heterosis expression of chickens

Heterosis has been widely utilized in agricultural production. Despite over a century of extensive research, the underlying mechanisms of heterosis remain elusive. Most hypotheses and research have focused on the genetic basis of heterosis. However, the potential role of gut microbiota in heterosis has been largely ignored. Here, we carefully design a crossbreeding experiment with two distinct broiler breeds and conduct 16S rRNA amplicon and transcriptome sequencing to investigate the synergistic role of gut microbiota and host genes in driving heterosis. We find that the breast muscle weight of the hybrids exhibits a high heterosis, 6.28% higher than mid-parent value. A notable difference is observed in the composition and potential function of cecal microbiota between hybrids and their parents. Over 90% of the differentially colonized microbiota and differentially expressed genes exhibit nonadditive patterns. Integrative analyses uncover associations between nonadditive genes and nonadditive microbiota, including a connection between the expression of cellular signaling pathway and metabolism-related genes and the abundance of Odoribacter, Oscillibacter, and Alistipes in hybrids. Moreover, higher abundances of these microbiota are related to better meat yield. In summary, these findings highlight the importance of gut microbiota in heterosis, serving as crucial factors that modulate heterosis expression in chickens.

Effects of Nobiletin supplementation on the freezing diluent on porcine sperm cryo-survival and subsequent in vitro embryo development

Nobiletin (NOB) is a bioflavonoid compound isolated from citrus fruit peels. The present study aimed to elucidate whether NOB facilitates the porcine sperm cryosurvival and embryo development after in vitro fertilization (IVF). To this end, spermatozoa were diluted and cryopreserved in a freezing extender supplemented with 0 (control), 50, 100, 150, and 200 μM Nobiletin. The kinematic patterns of frozen-thawed (FT) sperm were assessed after 30 and 90 min incubation using a Sperm Class Analyzer (SCA). Viability, acrosome integrity, and mitochondrial membrane potential (MMP) were measured by fluorescence microscopy 30 min after thawing using SYBR-14/PI, PSA/FITC, and R123/PI, respectively. Lipid peroxidation was determined using MDA assay after incubation for 90 min. The addition of 100 μM and 150 μM NOB to the extender significantly improved sperm progressive motility, and acrosome integrity compared to the control group (P < 0.05). The proportion of viable spermatozoa was significantly higher in the 150 μM NOB group. MDA levels were less in 50 μM and 150 μM NOB treated groups compared to the control. In addition, IVF with FT sperm was used to assess the embryo developmental competence. Treatment with 150 μM NOB before cryopreservation increased the cleavage and blastocyst formation rates compared to the control group. Furthermore, the relative expression of POU5F1 and AMPK, genes related to pluripotency and cell differentiation were significantly upregulated in embryos resulting from NOB-treated sperm compared to the control group. These results suggest that Nobiletin is a functionally novel phytochemical to mitigate oxidative stress during the freezing-thawing of porcine spermatozoa as reflected by improved FT sperm quality and IVF outcome.

Natural variation in codon bias and mRNA folding strength interact synergistically to modify protein expression in Saccharomyces cerevisiae

Codon bias and mRNA folding strength (mF) are hypothesized molecular mechanisms by which polymorphisms in genes modify protein expression. Natural patterns of codon bias and mF across genes as well as effects of altering codon bias and mF suggest that the influence of these 2 mechanisms may vary depending on the specific location of polymorphisms within a transcript. Despite the central role codon bias and mF may play in natural trait variation within populations, systematic studies of how polymorphic codon bias and mF relate to protein expression variation are lacking. To address this need, we analyzed genomic, transcriptomic, and proteomic data for 22 Saccharomyces cerevisiae isolates, estimated protein accumulation for each allele of 1,620 genes as the log of protein molecules per RNA molecule (logPPR), and built linear mixed-effects models associating allelic variation in codon bias and mF with allelic variation in logPPR. We found that codon bias and mF interact synergistically in a positive association with logPPR, and this interaction explains almost all the effects of codon bias and mF. We examined how the locations of polymorphisms within transcripts influence their effects and found that codon bias primarily acts through polymorphisms in domain-encoding and 3' coding sequences, while mF acts most significantly through coding sequences with weaker effects from untranslated regions. Our results present the most comprehensive characterization to date of how polymorphisms in transcripts influence protein expression.

Ecological Speciation Promoted by Divergent Regulation of Functional Genes Within African Cichlid Fishes

Rapid ecological speciation along depth gradients has taken place repeatedly in freshwater fishes, yet molecular mechanisms facilitating such diversification are typically unclear. In Lake Masoko, an African crater lake, the cichlid Astatotilapia calliptera has diverged into shallow-littoral and deep-benthic ecomorphs with strikingly different jaw structures within the last 1,000 years. Using genome-wide transcriptome data, we explore two major regulatory transcriptional mechanisms, expression and splicing-QTL variants, and examine their contributions to differential gene expression underpinning functional phenotypes. We identified 7,550 genes with significant differential expression between ecomorphs, of which 5.4% were regulated by cis-regulatory expression QTLs, and 9.2% were regulated by cis-regulatory splicing QTLs. We also found strong signals of divergent selection on differentially expressed genes associated with craniofacial development. These results suggest that large-scale transcriptome modification plays an important role during early-stage speciation. We conclude that regulatory variants are important targets of selection driving ecologically relevant divergence in gene expression during adaptive diversification.

Genomic Basis of Transcriptome Dynamics in Rice under Field Conditions

How genetic variations affect gene expression dynamics of field-grown plants remains unclear. Expression quantitative trait loci (eQTL) analysis is frequently used to find genomic regions underlying gene expression polymorphisms. This approach requires transcriptome data for the complete set of the QTL mapping population under the given conditions. Therefore, only a limited range of environmental conditions is covered by a conventional eQTL analysis. We sampled sparse time series of field-grown rice from chromosome segment substitution lines (CSSLs) and conducted RNA sequencing (RNA-Seq). Then, by using statistical analysis integrating meteorological data and the RNA-Seq data, we identified 1,675 eQTLs leading to polymorphisms in expression dynamics under field conditions. A genomic region on chromosome 11 influences the expression of several defense-related genes in a time-of-day- and scaled-age-dependent manner. This includes the eQTLs that possibly influence the time-of-day- and scaled-age-dependent differences in the innate immunity between Koshihikari and Takanari. Based on the eQTL and meteorological data, we successfully predicted gene expression under environments different from training environments and in rice cultivars with more complex genotypes than the CSSLs. Our novel approach of eQTL identification facilitated the understanding of the genetic architecture of expression dynamics under field conditions, which is difficult to assess by conventional eQTL studies. The prediction of expression based on eQTLs and environmental information could contribute to the understanding of plant traits under diverse field conditions.

Tissue context determines the penetrance of regulatory DNA variation

Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.

Identification of Gingivitis-Related Genes Across Human Tissues Based on the Summary Mendelian Randomization

Periodontal diseases are among the most frequent inflammatory diseases affecting children and adolescents, which affect the supporting structures of the teeth and lead to tooth loss and contribute to systemic inflammation. Gingivitis is the most common periodontal infection. Gingivitis, which is mainly caused by a substance produced by microbial plaque, systemic disorders, and genetic abnormalities in the host. Identifying gingivitis-related genes across human tissues is not only significant for understanding disease mechanisms but also disease development and clinical diagnosis. The Genome-wide association study (GWAS) a commonly used method to mine disease-related genetic variants. However, due to some factors such as linkage disequilibrium, it is difficult for GWAS to identify genes directly related to the disease. Hence, we constructed a data integration method that uses the Summary Mendelian randomization (SMR) to combine the GWAS with expression quantitative trait locus (eQTL) data to identify gingivitis-related genes. Five eQTL studies from different human tissues and one GWAS studies were referenced in this paper. This study identified several candidates SNPs and genes relate to gingivitis in tissue-specific or cross-tissue. Further, we also analyzed and explained the functions of these genes. The R program for the SMR method has been uploaded to GitHub(https://github.com/hxdde/SMR).

Genetic basis of negative heterosis for growth traits in chickens revealed by genome-wide gene expression pattern analysis

Background

Heterosis is an important biological phenomenon that has been extensively utilized in agricultural breeding. However, negative heterosis is also pervasively observed in nature, which can cause unfavorable impacts on production performance. Compared with systematic studies of positive heterosis, the phenomenon of negative heterosis has been largely ignored in genetic studies and breeding programs, and the genetic mechanism of this phenomenon has not been thoroughly elucidated to date. Here, we used chickens, the most common agricultural animals worldwide, to determine the genetic and molecular mechanisms of negative heterosis.

Results

We performed reciprocal crossing experiments with two distinct chicken lines and found that the body weight presented widely negative heterosis in the early growth of chickens. Negative heterosis of carcass traits was more common than positive heterosis, especially breast muscle mass, which was over − 40% in reciprocal progenies. Genome-wide gene expression pattern analyses of breast muscle tissues revealed that nonadditivity, including dominance and overdominace, was the major gene inheritance pattern. Nonadditive genes, including a substantial number of genes encoding ATPase and NADH dehydrogenase, accounted for more than 68% of differentially expressed genes in reciprocal crosses (4257 of 5587 and 3617 of 5243, respectively). Moreover, nonadditive genes were significantly associated with the biological process of oxidative phosphorylation, which is the major metabolic pathway for energy release and animal growth and development. The detection of ATP content and ATPase activity for purebred and crossbred progenies further confirmed that chickens with lower muscle yield had lower ATP concentrations but higher hydrolysis activity, which supported the important role of oxidative phosphorylation in negative heterosis for growth traits in chickens.

Conclusions

These findings revealed that nonadditive genes and their related oxidative phosphorylation were the major genetic and molecular factors in the negative heterosis of growth in chickens, which would be beneficial to future breeding strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-021-00574-2.

Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits

BACKGROUND

Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits.

RESULTS

Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3).

CONCLUSIONS

The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.

Abiotic and past climatic conditions drive protein abundance variation among natural populations of the caddisfly Crunoecia irrorata

Deducing impacts of environmental change on species and the populations they form in nature is an important goal in contemporary ecology. Achieving this goal is hampered by our limited understanding of the influence of naturally occurring environmental variation on the molecular systems of ecologically relevant species, as the pathways underlying fitness-affecting plastic responses have primarily been studied in model organisms and under controlled laboratory conditions. Here, to test the hypothesis that proteome variation systematically relates to variation in abiotic conditions, we establish such relationships by profiling the proteomes of 24 natural populations of the spring-dwelling caddisfly Crunoecia irrorata. We identified protein networks whose abundances correlated with environmental (abiotic) gradients such as in situ pH, oxygen- and nitrate concentrations but also climatic data such as past thermal minima and temperature seasonality. Our analyses suggest that variations in abiotic conditions induce discrete proteome responses such as the differential abundance of proteins associated with cytoskeletal function, heat-shock proteins and proteins related to post-translational modification. Identifying these drivers of proteome divergence characterizes molecular "noise", and positions it as a background against which molecular signatures of species' adaptive responses to stressful conditions can be identified.

Additive and mostly adaptive plastic responses of gene expression to multiple stress in Tribolium castaneum

Gene expression is known to be highly responsive to the environment and important for adjustment of metabolism but there is also growing evidence that differences in gene regulation contribute to species divergence and differences among locally adapted populations. However, most studies so far investigated populations when divergence had already occurred. Selection acting on expression levels at the onset of adaptation to an environmental change has not been characterized. Understanding the mechanisms is further complicated by the fact that environmental change is often multivariate, meaning that organisms are exposed to multiple stressors simultaneously with potentially interactive effects. Here we use a novel approach by combining fitness and whole-transcriptome data in a large-scale experiment to investigate responses to drought, heat and their combination in Tribolium castaneum. We found that fitness was reduced by both stressors and their combined effect was almost additive. Expression data showed that stressor responses were acting independently and did not interfere physiologically. Since we measured expression and fitness within the same individuals, we were able to estimate selection on gene expression levels. We found that variation in fitness can be attributed to gene expression variation and that selection pressures were environment dependent and opposite between control and stress conditions. We could further show that plastic responses of expression were largely adaptive, i.e. in the direction that should increase fitness.

Cis-regulatory elements explain most of the mRNA stability variation across genes in yeast

The stability of mRNA is one of the major determinants of gene expression. Although a wealth of sequence elements regulating mRNA stability has been described, their quantitative contributions to half-life are unknown. Here, we built a quantitative model for Saccharomyces cerevisiae based on functional mRNA sequence features that explains 59% of the half-life variation between genes and predicts half-life at a median relative error of 30%. The model revealed a new destabilizing 3' UTR motif, ATATTC, which we functionally validated. Codon usage proves to be the major determinant of mRNA stability. Nonetheless, single-nucleotide variations have the largest effect when occurring on 3' UTR motifs or upstream AUGs. Analyzing mRNA half-life data of 34 knockout strains showed that the effect of codon usage not only requires functional decapping and deadenylation, but also the 5'-to-3' exonuclease Xrn1, the nonsense-mediated decay genes, but not no-go decay. Altogether, this study quantitatively delineates the contributions of mRNA sequence features on stability in yeast, reveals their functional dependencies on degradation pathways, and allows accurate prediction of half-life from mRNA sequence.

Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression

Regulatory variation influencing gene expression is a key contributor to phenotypic diversity, both within and between species. Unfortunately, RNA degrades too rapidly to be recovered from fossil remains, limiting functional genomic insights about our extinct hominin relatives. Many Neanderthal sequences survive in modern humans due to ancient hybridization, providing an opportunity to assess their contributions to transcriptional variation and to test hypotheses about regulatory evolution. We developed a flexible Bayesian statistical approach to quantify allele-specific expression (ASE) in complex RNA-seq datasets. We identified widespread expression differences between Neanderthal and modern human alleles, indicating pervasive cis-regulatory impacts of introgression. Brain regions and testes exhibited significant downregulation of Neanderthal alleles relative to other tissues, consistent with natural selection influencing the tissue-specific regulatory landscape. Our study demonstrates that Neanderthal-inherited sequences are not silent remnants of ancient interbreeding but have measurable impacts on gene expression that contribute to variation in modern human phenotypes.

Different contributions of local- and distant-regulatory changes to transcriptome divergence between stickleback ecotypes

Differential gene expression can play an important role in phenotypic evolution and divergent adaptation. Although differential gene expression can be caused by both local- and distant-regulatory changes, we know little about their relative contribution to transcriptome evolution in natural populations. Here, we conducted expression quantitative trait loci (eQTL) analysis to investigate the genetic architecture underlying transcriptome divergence between marine and stream ecotypes of threespine sticklebacks (Gasterosteus aculeatus). We identified both local and distant eQTLs, some of which constitute hotspots, regions with a disproportionate number of significant eQTLs relative to the genomic background. The majority of local eQTLs including those in the hotspots caused expression changes consistent with the direction of transcriptomic divergence between ecotypes. Genome scan analysis showed that many local eQTLs overlapped with genomic regions of high differentiation. In contrast, nearly half of the distant eQTLs including those in the hotspots caused opposite expression changes, and few overlapped with regions of high differentiation, indicating that distant eQTLs may act as a constraint of transcriptome evolution. Finally, a comparison between two salinity conditions revealed that nearly half of eQTL hotspots were environment specific, suggesting that analysis of genetic architecture in multiple conditions is essential for predicting response to selection.

Iron refractory iron deficiency anemia: a heterogeneous disease that is not always iron refractory

TMPRSS6 variants that affect protein function result in impaired matriptase‐2 function and consequently uninhibited hepcidin production, leading to iron refractory iron deficiency anemia (IRIDA). This disease is characterized by microcytic, hypochromic anemia and serum hepcidin values that are inappropriately high for body iron levels. Much is still unknown about its pathophysiology, genotype–phenotype correlation, and optimal clinical management. We describe 14 different TMPRSS6 variants, of which 9 are novel, in 21 phenotypically affected IRIDA patients from 20 families living in the Netherlands; 16 out of 21 patients were female. In 7 out of 21 cases DNA sequencing and multiplex ligation dependent probe amplification demonstrated only heterozygous TMPRSS6 variants. The age at presentation, disease severity, and response to iron supplementation were highly variable, even for patients and relatives with similar TMPRSS6 genotypes. Mono‐allelic IRIDA patients had a milder phenotype with respect to hemoglobin and MCV and presented significantly later in life with anemia than bi‐allelic patients. Transferrin saturation (TSAT)/hepcidin ratios were lower in IRIDA probands than in healthy relatives. Most patients required parenteral iron. Genotype alone was not predictive for the response to oral iron. We conclude that IRIDA is a genotypically and phenotypically heterogeneous disease. The high proportion of female patients and the discrepancy between phenotypes of probands and relatives with the same genotype, suggest a complex interplay between genetic and acquired factors in the pathogenesis of IRIDA. In the absence of inflammation, the TSAT/hepcidin ratio is a promising diagnostic tool, even after iron supplementation has been given. Am. J. Hematol. 91:E482–E490, 2016. © 2016 Wiley Periodicals, Inc.

Dissection of expression-quantitative trait locus and allele specificity using a haploid/diploid plant system - insights into compensatory evolution of transcriptional regulation within populations

Regulation of gene expression plays a central role in translating genotypic variation into phenotypic variation. Dissection of the genetic basis of expression variation is key to understanding how expression regulation evolves. Such analyses remain challenging in contexts where organisms are outbreeding, highly heterozygous and long-lived such as in the case of conifer trees. We developed an RNA sequencing (RNA-seq)-based approach for both expression-quantitative trait locus (eQTL) mapping and the detection of cis-acting (allele-specific) vs trans-acting (non-allele-specific) eQTLs. This method can be potentially applied to many conifers. We used haploid and diploid meiotic seed tissues of a single self-fertilized white spruce (Picea glauca) individual to dissect eQTLs according to linkage and allele specificity. The genetic architecture of local eQTLs linked to the expressed genes was particularly complex, consisting of cis-acting, trans-acting and, surprisingly, compensatory cis-trans effects. These compensatory effects influence expression in opposite directions and are neutral when combined in homozygotes. Nearly half of local eQTLs were under compensation, indicating that close linkage between compensatory cis-trans factors is common in spruce. Compensated genes were overrepresented in developmental and cell organization functions. Our haploid-diploid eQTL analysis in spruce revealed that compensatory cis-trans eQTLs segregate within populations and evolve in close genetic linkage.

Insights into islet development and biology through characterization of a human iPSC-derived endocrine pancreas model

Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at 6 stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from 2 donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs = 14.2, p-value = 4.9 × 10(-5)) and the pancreatic agenesis gene GATA6 (log2 FC = 12.1, p-value = 8.6 × 10(-5)), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC = 5.5, p-value = 2.0 × 10(-12)), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio = 4.2, p-value = 1.9 × 10(-3)): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

The adaptive potential of subtropical rainbowfish in the face of climate change: heritability and heritable plasticity for the expression of candidate genes

Whilst adaptation and phenotypic plasticity might buffer species against habitat degradation associated with global climate change, few studies making such claims also possess the necessary and sufficient data to support them. Doing so requires demonstration of heritable variation in traits affecting fitness under new environmental conditions. We address this issue using an emerging aquatic system to study adaptation to climate change, the crimson-spotted rainbowfish (Melanotaenia duboulayi), a freshwater species from a region of eastern Australia projected to be affected by marked temperature increases. Captive born M. duboulayi of known pedigree were used to assess the long-term effects of contemporary and 2070-projected summer temperatures on the expression of genes previously identified in a climate change transcriptomics (RNA-Seq) experiment. Nearly all genes responded to increasing temperature. Significant additive genetic variance explained a moderate proportion of transcriptional variation for all genes. Most genes also showed broad-sense genetic variation in transcriptional plasticity. Additionally, molecular pathways of candidate genes co-occur with genes inferred to be under climate-mediated selection in wild M. duboulayi populations. Together, these results indicate the presence of existing variation in important physiological traits, and the potential for adaptive responses to a changing thermal environment.

Comprehensive Analysis of the SUL1 Promoter of Saccharomyces cerevisiae

In the yeast Saccharomyces cerevisiae, beneficial mutations selected during sulfate-limited growth are typically amplifications of the SUL1 gene, which encodes the high-affinity sulfate transporter, resulting in fitness increases of >35% . Cis-regulatory mutations have not been observed at this locus; however, it is not clear whether this absence is due to a low mutation rate such that these mutations do not arise, or they arise but have limited fitness effects relative to those of amplification. To address this question directly, we assayed the fitness effects of nearly all possible point mutations in a 493-base segment of the gene's promoter through mutagenesis and selection. While most mutations were either neutral or detrimental during sulfate-limited growth, eight mutations increased fitness >5% and as much as 9.4%. Combinations of these beneficial mutations increased fitness only up to 11%. Thus, in the case of SUL1, promoter mutations could not induce a fitness increase similar to that of gene amplification. Using these data, we identified functionally important regions of the SUL1 promoter and analyzed three sites that correspond to potential binding sites for the transcription factors Met32 and Cbf1 Mutations that create new Met32- or Cbf1-binding sites also increased fitness. Some mutations in the untranslated region of the SUL1 transcript decreased fitness, likely due to the formation of inhibitory upstream open reading frames. Our methodology-saturation mutagenesis, chemostat selection, and DNA sequencing to track variants-should be a broadly applicable approach.

Omic personality: implications of stable transcript and methylation profiles for personalized medicine

Background

Personalized medicine is predicated on the notion that individual biochemical and genomic profiles are relatively constant in times of good health and to some extent predictive of disease or therapeutic response. We report a pilot study quantifying gene expression and methylation profile consistency over time, addressing the reasons for individual uniqueness, and its relation to N = 1 phenotypes.

Methods

Whole blood samples from four African American women, four Caucasian women, and four Caucasian men drawn from the Atlanta Center for Health Discovery and Well Being study at three successive 6-month intervals were profiled by RNA-Seq, miRNA-Seq, and Illumina Methylation 450 K arrays. Standard regression approaches were used to evaluate the proportion of variance for each type of omic measure among individuals, and to quantify correlations among measures and with clinical attributes related to wellness.

Results

Longitudinal omic profiles were in general highly consistent over time, with an average of 67 % variance in transcript abundance, 42 % in CpG methylation level (but 88 % for the most differentiated CpG per gene), and 50 % in miRNA abundance among individuals, which are all comparable to 74 % variance among individuals for 74 clinical traits. One third of the variance could be attributed to differential blood cell type abundance, which was also fairly stable over time, and a lesser amount to expression quantitative trait loci (eQTL) effects. Seven conserved axes of covariance that capture diverse aspects of immune function explained over half of the variance. These axes also explained a considerable proportion of individually extreme transcript abundance, namely approximately 100 genes that were significantly up-regulated or down-regulated in each person and were in some cases enriched for relevant gene activities that plausibly associate with clinical attributes. A similar fraction of genes had individually divergent methylation levels, but these did not overlap with the transcripts, and fewer than 20 % of genes had significantly correlated methylation and gene expression.

Conclusions

People express an “omic personality” consisting of peripheral blood transcriptional and epigenetic profiles that are constant over the course of a year and reflect various types of immune activity. Baseline genomic profiles can provide a window into the molecular basis of traits that might be useful for explaining medical conditions or guiding personalized health decisions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0209-4) contains supplementary material, which is available to authorized users.

Regulatory evolution and voltage-gated ion channel expression in squid axon: selection-mutation balance and fitness cliffs

It has been suggested that optimization of either axonal conduction velocity or the energy efficiency of action potential conduction predominates in the selection of voltage-gated sodium conductance levels in the squid axon. A population genetics model of channel gene regulatory function was used to examine the role of these and other evolutionary forces on the selection of both sodium and potassium channel expression levels. In this model, the accumulating effects of mutations result in degradation of gene regulatory function, causing channel gene expression to fall to near-zero in the absence of positive selection. In the presence of positive selection, channel expression levels fall to the lowest values consistent with the selection criteria, thereby establishing a selection-mutation balance. Within the parameter space of sodium and potassium conductance values, the physiological performance of the squid axon model showed marked discontinuities associated with conduction failure and excitability. These discontinuities in physiological function may produce fitness cliffs. A fitness cliff associated with conduction failure, combined with the effects of phenotypic noise, can account for the selection of sodium conductance levels, without considering either conduction velocity or metabolic cost. A fitness cliff associated with a transition in axonal excitability, combined with phenotypic noise, can explain the selection of potassium channel expression levels. The results suggest that voltage-gated ion channel expression will fall to low levels, consistent with key functional constraints, even in the absence of positive selection for energy efficiency. Channel expression levels and individual variation in channel expression within the population can be explained by regulatory evolution in combination with genetic variation in regulatory function and phenotypic noise, without resorting to more complex mechanisms, such as activity-dependent homeostasis. Only a relatively small region of the large, nominally isofunctional parameter space for channel expression will normally be occupied, because of the effects of mutation.

TBX6 null variants and a common hypomorphic allele in congenital scoliosis

BACKGROUND

Congenital scoliosis is a common type of vertebral malformation. Genetic susceptibility has been implicated in congenital scoliosis.

METHODS

We evaluated 161 Han Chinese persons with sporadic congenital scoliosis, 166 Han Chinese controls, and 2 pedigrees, family members of which had a 16p11.2 deletion, using comparative genomic hybridization, quantitative polymerase-chain-reaction analysis, and DNA sequencing. We carried out tests of replication using an additional series of 76 Han Chinese persons with congenital scoliosis and a multicenter series of 42 persons with 16p11.2 deletions.

RESULTS

We identified a total of 17 heterozygous TBX6 null mutations in the 161 persons with sporadic congenital scoliosis (11%); we did not observe any null mutations in TBX6 in 166 controls (P<3.8×10(-6)). These null alleles include copy-number variants (12 instances of a 16p11.2 deletion affecting TBX6) and single-nucleotide variants (1 nonsense and 4 frame-shift mutations). However, the discordant intrafamilial phenotypes of 16p11.2 deletion carriers suggest that heterozygous TBX6 null mutation is insufficient to cause congenital scoliosis. We went on to identify a common TBX6 haplotype as the second risk allele in all 17 carriers of TBX6 null mutations (P<1.1×10(-6)). Replication studies involving additional persons with congenital scoliosis who carried a deletion affecting TBX6 confirmed this compound inheritance model. In vitro functional assays suggested that the risk haplotype is a hypomorphic allele. Hemivertebrae are characteristic of TBX6-associated congenital scoliosis.

CONCLUSIONS

Compound inheritance of a rare null mutation and a hypomorphic allele of TBX6 accounted for up to 11% of congenital scoliosis cases in the series that we analyzed. (Funded by the National Basic Research Program of China and others.).

Heritable variation of mRNA decay rates in yeast

Gene expression levels are determined by the balance between rates of mRNA transcription and decay, and genetic variation in either of these processes can result in heritable differences in transcript abundance. Although the genetics of gene expression has been a subject of intense interest, the contribution of heritable variation in mRNA decay rates to gene expression variation has received far less attention. To this end, we developed a novel statistical framework and measured allele-specific differences in mRNA decay rates in a diploid yeast hybrid created by mating two genetically diverse parental strains. We estimate that 31% of genes exhibit allelic differences in mRNA decay rates, of which 350 can be identified at a false discovery rate of 10%. Genes with significant allele-specific differences in mRNA decay rates have higher levels of polymorphism compared to other genes, with all gene regions contributing to allelic differences in mRNA decay rates. Strikingly, we find widespread evidence for compensatory evolution, such that variants influencing transcriptional initiation and decay have opposite effects, suggesting that steady-state gene expression levels are subject to pervasive stabilizing selection. Our results demonstrate that heritable differences in mRNA decay rates are widespread and are an important target for natural selection to maintain or fine-tune steady-state gene expression levels.

Evolution and genetic architecture of chromatin accessibility and function in yeast

Chromatin accessibility is an important functional genomics phenotype that influences transcription factor binding and gene expression. Genome-scale technologies allow chromatin accessibility to be mapped with high-resolution, facilitating detailed analyses into the genetic architecture and evolution of chromatin structure within and between species. We performed Formaldehyde-Assisted Isolation of Regulatory Elements sequencing (FAIRE-Seq) to map chromatin accessibility in two parental haploid yeast species, Saccharomyces cerevisiae and Saccharomyces paradoxus and their diploid hybrid. We show that although broad-scale characteristics of the chromatin landscape are well conserved between these species, accessibility is significantly different for 947 regions upstream of genes that are enriched for GO terms such as intracellular transport and protein localization exhibit. We also develop new statistical methods to investigate the genetic architecture of variation in chromatin accessibility between species, and find that cis effects are more common and of greater magnitude than trans effects. Interestingly, we find that cis and trans effects at individual genes are often negatively correlated, suggesting widespread compensatory evolution to stabilize levels of chromatin accessibility. Finally, we demonstrate that the relationship between chromatin accessibility and gene expression levels is complex, and a significant proportion of differences in chromatin accessibility might be functionally benign.

Genetic background drives transcriptional variation in human induced pluripotent stem cells

Human iPS cells have been generated using a diverse range of tissues from a variety of donors using different reprogramming vectors. However, these cell lines are heterogeneous, which presents a limitation for their use in disease modeling and personalized medicine. To explore the basis of this heterogeneity we generated 25 iPS cell lines under normalised conditions from the same set of somatic tissues across a number of donors. RNA-seq data sets from each cell line were compared to identify the majority contributors to transcriptional heterogeneity. We found that genetic differences between individual donors were the major cause of transcriptional variation between lines. In contrast, residual signatures from the somatic cell of origin, so called epigenetic memory, contributed relatively little to transcriptional variation. Thus, underlying genetic background variation is responsible for most heterogeneity between human iPS cell lines. We conclude that epigenetic effects in hIPSCs are minimal, and that hIPSCs are a stable, robust and powerful platform for large-scale studies of the function of genetic differences between individuals. Our data also suggest that future studies using hIPSCs as a model system should focus most effort on collection of large numbers of donors, rather than generating large numbers of lines from the same donor.

Human induced pluripotent stem (hiPS) cells are a potentially powerful model system for studying human disease and development, and a resource for personalized medicine. However, it has been reported that hiPS cells exhibit substantial heterogeneity which could limit their use as model systems. Clearly, knowledge of the source of heterogeneity is key for deeper understanding of the use of human iPS cells for basic and therapeutic applications. One source of this heterogeneity has been presumed to be “memory” of the adult somatic cell from which the hIPS cells were derived, but the evidence to support this view is scant. We have generated a set of human iPS cells from a set of somatic cell types from different donors. Our study shows that cell lines from different somatic sources but from the same donor (i.e. with the same genome) are more similar than cell lines isolated from the same tissue type but from different donors. Once genetic changes are accounted for, all aspects of gene expression, including mRNA levels, splicing and imprinting are highly similar between iPS cells derived from different human tissues. Thus, most of the previously described transcriptional variation between cell lines is likely to be genetic in origin.

The nature and extent of mutational pleiotropy in gene expression of male Drosophila serrata

The nature and extent of mutational pleiotropy remain largely unknown, despite the central role that pleiotropy plays in many areas of biology, including human disease, agricultural production, and evolution. Here, we investigate the variation in 11,604 gene expression traits among 41 mutation accumulation (MA) lines of Drosophila serrata. We first confirmed that these expression phenotypes were heritable, detecting genetic variation in 96% of them in an outbred, natural population of D. serrata. Among the MA lines, 3385 (29%) of expression traits were variable, with a mean mutational heritability of 0.0005. In most traits, variation was generated by mutations of relatively small phenotypic effect; putative mutations with effects of greater than one phenotypic standard deviation were observed for only 8% of traits. With most (71%) traits unaffected by any mutation, our data provide no support for universal pleiotropy. We further characterized mutational pleiotropy in the 3385 variable traits, using sets of 5, randomly assigned, traits. Covariance among traits chosen at random with respect to their biological function is expected only if pleiotropy is extensive. Taking an analytical approach in which the variance unique to each trait in the random 5-trait sets was partitioned from variance shared among traits, we detected significant (at 5% false discovery rate) mutational covariance in 21% of sets. This frequency of statistically supported covariance implied that at least some mutations must pleiotropically affect a substantial number of traits (>70; 0.6% of all measured traits).

Genetic architecture of quantitative traits and complex diseases

More than 150 years after Mendel discovered the laws of heredity, the genetic architecture of phenotypic variation remains elusive. Here, we discuss recent progress in deciphering how genotypes map onto phenotypes, sources of genetic complexity, and how model organisms are illuminating general principles about the relationship between genetic and phenotypic variation. Moreover, we highlight insights gleaned from large-scale sequencing studies in humans, and how this knowledge informs outstanding questions about the genetic architecture of quantitative traits and complex diseases. Finally, we articulate how the confluence of technologies enabling whole-genome sequencing, comprehensive phenotyping, and high-throughput functional assays of polymorphisms will facilitate a more principled and mechanistic understanding of the genetic architecture of phenotypic variation.

Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case–control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10^–5). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways.

Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease

Some individuals with a particular disease-causing mutation or genotype fail to express most if not all features of the disease in question, a phenomenon that is known as 'reduced (or incomplete) penetrance'. Reduced penetrance is not uncommon; indeed, there are many known examples of 'disease-causing mutations' that fail to cause disease in at least a proportion of the individuals who carry them. Reduced penetrance may therefore explain not only why genetic diseases are occasionally transmitted through unaffected parents, but also why healthy individuals can harbour quite large numbers of potentially disadvantageous variants in their genomes without suffering any obvious ill effects. Reduced penetrance can be a function of the specific mutation(s) involved or of allele dosage. It may also result from differential allelic expression, copy number variation or the modulating influence of additional genetic variants in cis or in trans. The penetrance of some pathogenic genotypes is known to be age- and/or sex-dependent. Variable penetrance may also reflect the action of unlinked modifier genes, epigenetic changes or environmental factors. At least in some cases, complete penetrance appears to require the presence of one or more genetic variants at other loci. In this review, we summarize the evidence for reduced penetrance being a widespread phenomenon in human genetics and explore some of the molecular mechanisms that may help to explain this enigmatic characteristic of human inherited disease.

Exploiting gene expression variation to capture gene-environment interactions for disease

Gene-environment interactions have long been recognized as a fundamental concept in evolutionary, quantitative, and medical genetics. In the genomics era, study of how environment and genome interact to shape gene expression variation is relevant to understanding the genetic architecture of complex phenotypes. While genetic analysis of gene expression variation focused on main effects, little is known about the extent of interaction effects implicating regulatory variants and their consequences on transcriptional variation. Here we survey the current state of the concept of transcriptional gene-environment interactions and discuss its utility for mapping disease phenotypes in light of the insights gained from genome-wide association studies of gene expression.

Global properties and functional complexity of human gene regulatory variation

Identification and functional interpretation of gene regulatory variants is a major focus of modern genomics. The application of genetic mapping to molecular and cellular traits has enabled the detection of regulatory variation on genome-wide scales and revealed an enormous diversity of regulatory architecture in humans and other species. In this review I summarise the insights gained and questions raised by a decade of genetic mapping of gene expression variation. I discuss recent extensions of this approach using alternative molecular phenotypes that have revealed some of the biological mechanisms that drive gene expression variation between individuals. Finally, I highlight outstanding problems and future directions for development.

Population genomics and transcriptional consequences of regulatory motif variation in globally diverse Saccharomyces cerevisiae strains

Noncoding genetic variation is known to significantly influence gene expression levels in a growing number of specific cases; however, the patterns of genome-wide noncoding variation present within populations, the evolutionary forces acting on noncoding variants, and the relative effects of regulatory polymorphisms on transcript abundance are not well characterized. Here, we address these questions by analyzing patterns of regulatory variation in motifs for 177 DNA binding proteins in 37 strains of Saccharomyces cerevisiae. Between S. cerevisiae strains, we found considerable polymorphism in regulatory motifs across strains (mean π = 0.005) as well as diversity in regulatory motifs (mean 0.91 motifs differences per regulatory region). Population genetics analyses reveal that motifs are under purifying selection, and there is considerable heterogeneity in the magnitude of selection across different motifs. Finally, we obtained RNA-Seq data in 22 strains and identified 49 polymorphic DNA sequence motifs in 30 distinct genes that are significantly associated with transcriptional differences between strains. In 22 of these genes, there was a single polymorphic motif associated with expression in the upstream region. Our results provide comprehensive insights into the evolutionary trajectory of regulatory variation in yeast and the characteristics of a compendium of regulatory alleles.

Blood-informative transcripts define nine common axes of peripheral blood gene expression

We describe a novel approach to capturing the covariance structure of peripheral blood gene expression that relies on the identification of highly conserved Axes of variation. Starting with a comparison of microarray transcriptome profiles for a new dataset of 189 healthy adult participants in the Emory-Georgia Tech Center for Health Discovery and Well-Being (CHDWB) cohort, with a previously published study of 208 adult Moroccans, we identify nine Axes each with between 99 and 1,028 strongly co-regulated transcripts in common. Each axis is enriched for gene ontology categories related to sub-classes of blood and immune function, including T-cell and B-cell physiology and innate, adaptive, and anti-viral responses. Conservation of the Axes is demonstrated in each of five additional population-based gene expression profiling studies, one of which is robustly associated with Body Mass Index in the CHDWB as well as Finnish and Australian cohorts. Furthermore, ten tightly co-regulated genes can be used to define each Axis as "Blood Informative Transcripts" (BITs), generating scores that define an individual with respect to the represented immune activity and blood physiology. We show that environmental factors, including lifestyle differences in Morocco and infection leading to active or latent tuberculosis, significantly impact specific axes, but that there is also significant heritability for the Axis scores. In the context of personalized medicine, reanalysis of the longitudinal profile of one individual during and after infection with two respiratory viruses demonstrates that specific axes also characterize clinical incidents. This mode of analysis suggests the view that, rather than unique subsets of genes marking each class of disease, differential expression reflects movement along the major normal Axes in response to environmental and genetic stimuli.

Personal and population genomics of human regulatory variation

The characteristics and evolutionary forces acting on regulatory variation in humans remains elusive because of the difficulty in defining functionally important noncoding DNA. Here, we combine genome-scale maps of regulatory DNA marked by DNase I hypersensitive sites (DHSs) from 138 cell and tissue types with whole-genome sequences of 53 geographically diverse individuals in order to better delimit the patterns of regulatory variation in humans. We estimate that individuals likely harbor many more functionally important variants in regulatory DNA compared with protein-coding regions, although they are likely to have, on average, smaller effect sizes. Moreover, we demonstrate that there is significant heterogeneity in the level of functional constraint in regulatory DNA among different cell types. We also find marked variability in functional constraint among transcription factor motifs in regulatory DNA, with sequence motifs for major developmental regulators, such as HOX proteins, exhibiting levels of constraint comparable to protein-coding regions. Finally, we perform a genome-wide scan of recent positive selection and identify hundreds of novel substrates of adaptive regulatory evolution that are enriched for biologically interesting pathways such as melanogenesis and adipocytokine signaling. These data and results provide new insights into patterns of regulatory variation in individuals and populations and demonstrate that a large proportion of functionally important variation lies beyond the exome.

Using blood informative transcripts in geographical genomics: impact of lifestyle on gene expression in fijians

In previous geographical genomics studies of the impact of lifestyle on gene expression inferred from microarray analysis of peripheral blood samples, we described the complex influences of culture, ethnicity, and gender in Morocco, and of pregnancy in Brisbane. Here we describe the use of nanofluidic Fluidigm quantitative RT-PCR arrays targeted at a set of 96 transcripts that are broadly informative of the major axes of immune gene expression, to explore the population structure of transcription in Fiji. As in Morocco, major differences are seen between the peripheral blood transcriptomes of rural villagers and residents of the capital city, Suva. The effect is much greater in Indian villages than in Melanesian highlanders and appears to be similar with respect to the nature of at least two axes of variation. Gender differences are much smaller than ethnicity or lifestyle effects. Body mass index is shown to associate with one of the axes as it does in Atlanta and Brisbane, establishing a link between the epidemiological transition of human metabolic disease, and gene expression profiles.

Coevolution within and between regulatory loci can preserve promoter function despite evolutionary rate acceleration

Phenotypes that appear to be conserved could be maintained not only by strong purifying selection on the underlying genetic systems, but also by stabilizing selection acting via compensatory mutations with balanced effects. Such coevolution has been invoked to explain experimental results, but has rarely been the focus of study. Conserved expression driven by the unc-47 promoters of Caenorhabditis elegans and C. briggsae persists despite divergence within a cis-regulatory element and between this element and the trans-regulatory environment. Compensatory changes in cis and trans are revealed when these promoters are used to drive expression in the other species. Functional changes in the C. briggsae promoter, which has experienced accelerated sequence evolution, did not lead to alteration of gene expression in its endogenous environment. Coevolution among promoter elements suggests that complex epistatic interactions within cis-regulatory elements may facilitate their divergence. Our results offer a detailed picture of regulatory evolution in which subtle, lineage-specific, and compensatory modifications of interacting cis and trans regulators together maintain conserved gene expression patterns.

Some phenotypes, including gene expression patterns, are conserved between distantly related species. However, the molecular bases of those phenotypes are not necessarily conserved. Instead, regulatory DNA sequences and the proteins with which they interact can change over time with balanced effects, preserving expression patterns and concealing regulatory divergence. Coevolution between interacting molecules makes gene regulation highly species-specific, and it can be detected when the cis-regulatory DNA of one species is used to drive expression in another species. In this way, we identified regions of the C. elegans and C. briggsae unc-47 promoters that have coevolved with the lineage-specific trans-regulatory environments of these organisms. The C. briggsae promoter experienced accelerated sequence change relative to related species. All of this evolution occurred without changing the expression pattern driven by the promoter in its endogenous environment.

DNA breathing dynamics distinguish binding from nonbinding consensus sites for transcription factor YY1 in cells

The genome-wide mapping of the major gene expression regulators, the transcription factors (TFs) and their DNA binding sites, is of great importance for describing cellular behavior and phenotypic diversity. Presently, the methods for prediction of genomic TF binding produce a large number of false positives, most likely due to insufficient description of the physiochemical mechanisms of protein–DNA binding. Growing evidence suggests that, in the cell, the double-stranded DNA (dsDNA) is subject to local transient strands separations (breathing) that contribute to genomic functions. By using site-specific chromatin immunopecipitations, gel shifts, BIOBASE data, and our model that accurately describes the melting behavior and breathing dynamics of dsDNA we report a specific DNA breathing profile found at YY1 binding sites in cells. We find that the genomic flanking sequence variations and SNPs, may exert long-range effects on DNA dynamics and predetermine YY1 binding. The ubiquitous TF YY1 has a fundamental role in essential biological processes by activating, initiating or repressing transcription depending upon the sequence context it binds. We anticipate that consensus binding sequences together with the related DNA dynamics profile may significantly improve the accuracy of genomic TF binding sites and TF binding-related functional SNPs.

Liver expression quantitative trait loci: a foundation for pharmacogenomic research

Expression quantitative trait loci (eQTL) analysis can provide insights into the genetic regulation of gene expression at a genomic level and this information is proving extremely useful in many different areas of research. As a consequence of the role of the liver in drug metabolism and disposition, the study of eQTLs in primary human liver tissue could provide a foundation for pharmacogenomics. Thus far, four genome-wide eQTL studies have been performed using human livers. Many liver eQTLs have been found to be reproducible and a proportion of these may be specific to the liver. Already these data have been used to interpret and inform clinic genome-wide association studies, providing potential mechanistic evidence for clinical associations and identifying genes which may impact clinical phenotypes. However, the utility of liver eQTL data has not yet been fully explored or realized in pharmacogenomics. As further liver eQTL research is undertaken, the genetic regulation of gene expression will become much better characterized and this knowledge will create a rational basis for the prospective pharmacogenomic study of many drugs.

Genes controlling vaccine responses and disease resistance to respiratory viral pathogens in cattle

Farm animals remain at risk of endemic, exotic and newly emerging viruses. Vaccination is often promoted as the best possible solution, and yet for many pathogens, either there are no appropriate vaccines or those that are available are far from ideal. A complementary approach to disease control may be to identify genes and chromosomal regions that underlie genetic variation in disease resistance and response to vaccination. However, identification of the causal polymorphisms is not straightforward as it generally requires large numbers of animals with linked phenotypes and genotypes. Investigation of genes underlying complex traits such as resistance or response to viral pathogens requires several genetic approaches including candidate genes deduced from knowledge about the cellular pathways leading to protection or pathology, or unbiased whole genome scans using markers spread across the genome. Evidence for host genetic variation exists for a number of viral diseases in cattle including bovine respiratory disease and anecdotally, foot and mouth disease virus (FMDV). We immunised and vaccinated a cattle cross herd with a 40-mer peptide derived from FMDV and a vaccine against bovine respiratory syncytial virus (BRSV). Genetic variation has been quantified. A candidate gene approach has grouped high and low antibody and T cell responders by common motifs in the peptide binding pockets of the bovine major histocompatibility complex (BoLA) DRB3 gene. This suggests that vaccines with a minimal number of epitopes that are recognised by most cattle could be designed. Whole genome scans using microsatellite and single nucleotide polymorphism (SNP) markers has revealed many novel quantitative trait loci (QTL) and SNP markers controlling both humoral and cell-mediated immunity, some of which are in genes of known immunological relevance including the toll-like receptors (TLRs). The sequencing, assembly and annotation of livestock genomes and is continuing apace. In addition, provision of high-density SNP chips should make it possible to link phenotypes with genotypes in field populations without the need for structured populations or pedigree information. This will hopefully enable fine mapping of QTL and ultimate identification of the causal gene(s). The research could lead to selection of animals that are more resistant to disease and new ways to improve vaccine efficacy.

On the prospects of whole-genome association mapping in Saccharomyces cerevisiae

Advances in sequencing technology have enabled whole-genome sequences to be obtained from multiple individuals within species, particularly in model organisms with compact genomes. For example, 36 genome sequences of Saccharomyces cerevisiae are now publicly available, and SNP data are available for even larger collections of strains. One potential use of these resources is mapping the genetic basis of phenotypic variation through genome-wide association (GWA) studies, with the benefit that associated variants can be studied experimentally with greater ease than in outbred populations such as humans. Here, we evaluate the prospects of GWA studies in S. cerevisiae strains through extensive simulations and a GWA study of mitochondrial copy number. We demonstrate that the complex and heterogeneous patterns of population structure present in yeast populations can lead to a high type I error rate in GWA studies of quantitative traits, and that methods typically used to control for population stratification do not provide adequate control of the type I error rate. Moreover, we show that while GWA studies of quantitative traits in S. cerevisiae may be difficult depending on the particular set of strains studied, association studies to map cis-acting quantitative trait loci (QTL) and Mendelian phenotypes are more feasible. We also discuss sampling strategies that could enable GWA studies in yeast and illustrate the utility of this approach in Saccharomyces paradoxus. Thus, our results provide important practical insights into the design and interpretation of GWA studies in yeast, and other model organisms that possess complex patterns of population structure.

Genome-wide transcription analysis of clinal genetic variation in Drosophila

Clinal variation in quantitative traits is widespread, but its genetic basis awaits identification. Drosophila melanogaster shows adaptive, clinal variation in traits such as body size along latitudinal gradients on multiple continents. To investigate genome wide transcription differentiation between North and South that might contribute to the clinal phenotypic variation, we compared RNA expression patterns during development of D. melanogaster from tropical northern and temperate southern populations using whole genome tiling arrays. We found that genes that were differentially expressed between the cline ends were generally associated with metabolism and growth, and experimental alteration of expression of a sample of them generally resulted in altered body size in the predicted direction, sometimes significantly so. We further identified the serpent (srp) transcription factor binding sites to be enriched near genes up-regulated in expression in the south. Analysis of clinal populations revealed a significant cline in the expression level of srp. Experimental over-expression of srp increased body size, as predicted from its clinal expression pattern, suggesting that it may be involved in regulating adaptive clinal variation in Drosophila. This study identified a handful of genes that contributed to clinal phenotypic variation through altered gene expression level, yet misexpression of individual gene led to modest body size change.

TGFBR1 intralocus epistatic interaction as a risk factor for colorectal cancer

In colorectal cancer (CRC), an inherited susceptibility risk affects about 35% of patients, whereas high-penetrance germline mutations account for <6% of cases. A considerable proportion of sporadic tumors could be explained by the coinheritance of multiple low-penetrance variants, some of which are common. We assessed the susceptibility to CRC conferred by genetic variants at the TGFBR1 locus. We analyzed 14 polymorphisms and the allele-specific expression (ASE) of TGFBR1 in 1025 individuals from the Spanish population. A case-control study was undertaken with 504 controls and 521 patients with sporadic CRC. Fourteen polymorphisms located at the TGFBR1 locus were genotyped with the iPLEX Gold (MassARRAY-Sequenom) technology. Descriptive analyses of the polymorphisms and haplotypes and association studies were performed with the SNPator workpackage. No relevant associations were detected between individual polymorphisms or haplotypes and the risk of CRC. The TGFBR1*9A/6A polymorphism was used for the ASE analysis. Heterozygous individuals were analyzed for ASE by fragment analysis using cDNA from normal tissue. The relative level of allelic expression was extrapolated from a standard curve. The cutoff value was calculated with Youden's index. ASE was found in 25.4% of patients and 16.4% of controls. Considering both bimodal and continuous types of distribution, no significant differences between the ASE values of patients and controls were identified. Interestingly, a combined analysis of the polymorphisms and ASE for the association with CRC occurrence revealed that ASE-positive individuals carrying one of the most common haplotypes (H2: 20.7%) showed remarkable susceptibility to CRC (RR: 5.25; 95% CI: 2.547–5.250; p<0.001) with a synergy factor of 3.7. In our study, 54.1% of sporadic CRC cases were attributable to the coinheritance of the H2 haplotype and TGFBR1 ASE. These results support the hypothesis that the allelic architecture of cancer genes, rather than individual polymorphisms, more accurately defines the CRC risk.

A novel type of congenital hypochromic anemia associated with a nonsense mutation in the STEAP3/TSAP6 gene

STEAP3/TSAP6 encodes a ferrireductase that is involved in the acquisition of iron by developing erythroblasts and steap3/tsap6 null-mice display severe microcytic anemia. We report a family in which 3 siblings born to healthy parents display transfusion-dependent hypochromic anemia. A nonsense STEAP3/TSAP6 was identified in the siblings at the heterozygous state. This mutation was inherited from their father while no mutation was found in their mother. A large variability of expression was found between normal alleles in a control population, confirming a previous report that STEAP3/TSAPS6 is an expressed quantitative trait locus (e-QTL). Determination of the relative allele expression showed that the “normal” allele was expressed at a significantly higher level in the father than in the affected siblings relative to the shared mutated allele. The blood level of STEAP3/TSAP6 mRNA was severely reduced in the siblings, while both parents were in the lower range of normal controls. The STEAP3/TSAP6 protein was also reduced in lymphocytic cell lines from the patients. Collectively, our data support the hypothesis that STEAP3/TSAP6 deficiency leads to severe anemia in the affected siblings and results from the combination of a mutated allele inherited from their father and a weakly expressed allele inherited from their mother.

A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data

Variation in gene expression is thought to make a significant contribution to phenotypic diversity among individuals within populations. Although high-throughput cDNA sequencing offers a unique opportunity to delineate the genome-wide architecture of regulatory variation, new statistical methods need to be developed to capitalize on the wealth of information contained in RNA-seq data sets. To this end, we developed a powerful and flexible hierarchical Bayesian model that combines information across loci to allow both global and locus-specific inferences about allele-specific expression (ASE). We applied our methodology to a large RNA-seq data set obtained in a diploid hybrid of two diverse Saccharomyces cerevisiae strains, as well as to RNA-seq data from an individual human genome. Our statistical framework accurately quantifies levels of ASE with specified false-discovery rates, achieving high reproducibility between independent sequencing platforms. We pinpoint loci that show unusual and biologically interesting patterns of ASE, including allele-specific alternative splicing and transcription termination sites. Our methodology provides a rigorous, quantitative, and high-resolution tool for profiling ASE across whole genomes.

Insights from GWAS into the quantitative genetics of transcription in humans

Human gene expression profiles have emerged as an effective model system for the dissection of quantitative genetic traits. Peripheral blood and transformed lymphoblasts are particularly attractive for their ready availability and repeatability, respectively, and the advent of relatively inexpensive genotyping and microarray analysis technologies has facilitated genome-wide association for transcript abundance in numerous settings. Thousands of genes have been shown to harbour regulatory polymorphisms that have large local effects on transcription, explaining 20% or more of the variance in many cases, but the focus on such results obscures the reality that the vast majority of the genetic component of transcriptional variance remains to be ascertained. This mini-review surveys the inferences derived from genome-wide association studies (GWAS) for gene expression to date, and discusses some of the issues we face in finding the remainder of the heritability and understanding how environmental and genetic regulatory factors orchestrate the highly structured architecture of transcriptional variation.

The impact of cis-acting polymorphisms on the human phenotype

Cis-acting polymorphisms that affect gene expression are now known to be frequent, although the extent and mechanisms by which such variation affects the human phenotype are, as yet, only poorly understood. Key signatures of cis-acting variation are differences in gene expression that are tightly associated with regulatory SNPs or expression Quantitative Trait Loci (eQTL) and an imbalance of allelic expression (AEI) in heterozygous samples. Such cis-acting sequence differences appear often to have been under selection within and between populations and are also thought to be important in speciation. Here we describe the example of lactase persistence. In medical research, variants that affect regulation in cis have been implicated in both monogenic and polygenic disorders, and in the metabolism of drugs. In this review we suggest that by further understanding common regulatory variations and how they interact with other genetic and environmental variables it will be possible to gain insight into important mechanisms behind complex disease, with the potential to lead to new methods of diagnosis and treatments.