Identification of common genetic variants that account for transcript isoform variation between human populations

Variation of microRNA expression in the human placenta driven by population identity and sex of the newborn

BACKGROUND

Analysis of lymphocyte cell lines revealed substantial differences in the expression of mRNA and microRNA (miRNA) among human populations. The extent of such population-associated differences in actual human tissues remains largely unexplored. The placenta is one of the few solid human tissues that can be collected in substantial numbers in a controlled manner, enabling quantitative analysis of transient biomolecules such as RNA transcripts. Here, we analyzed microRNA (miRNA) expression in human placental samples derived from 36 individuals representing four genetically distinct human populations: African Americans, European Americans, South Asians, and East Asians. All samples were collected at the same hospital following a unified protocol, thus minimizing potential biases that might influence the results.

RESULTS

Sequence analysis of the miRNA fraction yielded 938 annotated and 70 novel miRNA transcripts expressed in the placenta. Of them, 82 (9%) of annotated and 11 (16%) of novel miRNAs displayed quantitative expression differences among populations, generally reflecting reported genetic and mRNA-expression-based distances. Several co-expressed miRNA clusters stood out from the rest of the population-associated differences in terms of miRNA evolutionary age, tissue-specificity, and disease-association characteristics. Among three non-environmental influenced demographic parameters, the second largest contributor to miRNA expression variation after population was the sex of the newborn, with 32 miRNAs (3% of detected) exhibiting significant expression differences depending on whether the newborn was male or female. Male-associated miRNAs were evolutionarily younger and correlated inversely with the expression of target mRNA involved in neuron-related functions. In contrast, both male and female-associated miRNAs appeared to mediate different types of hormonal responses. Demographic factors further affected reported imprinted expression of 66 placental miRNAs: the imprinting strength correlated with the mother's weight, but not height.

CONCLUSIONS

Our results showed that among 12 assessed demographic variables, population affiliation and fetal sex had a substantial influence on miRNA expression variation among human placental samples. The effect of newborn-sex-associated miRNA differences further led to expression inhibition of the target genes clustering in specific functional pathways. By contrast, population-driven miRNA differences might mainly represent neutral changes with minimal functional impacts.

The framework for population epigenetic study

At present, understanding of DNA methylation at the population level is still limited. Here, we first extended the classical framework of population genetics, such as single nucleotide polymorphism allele frequency, linkage disequilibrium (LD), LD block and haplotype, to epigenetics. Then, as an example, we compared the DNA methylation disequilibrium (MD) maps between HapMap CEU (Caucasian residents of European ancestry from Utah) population and YRI (Yoruba people from Ibadan) population (lymphoblastoid cell lines). We analyzed the differences and similarities between CEU and YRI from the following aspects: SMP (single methylation polymorphism) allele frequency, SMP allele association, MD, MD block and methylation haplotype (meplotype) frequency. The results showed that CEU and YRI had similar distribution of SMP allele frequency, and shared many MD block region. We believe that the framework of population genetics can be used in the population epigenetics. The population epigenetic framework also has potential prospects in the study of complex diseases, such as epigenome-wide association study.

Dominant functional role of the novel phosphorylation site S811 in the human renal NaCl cotransporter

The NaCl cotransporter (NCC) is essential for electrolyte homeostasis and control of blood pressure. The human SLC12A3 gene, which encodes NCC, gives rise to 3 isoforms, of which only the shortest isoform [NaCl cotransporter isoform 3 (NCC₃)] has been studied extensively. All NCC isoforms share key phosphorylation sites at T55 and T60 that are essential mediators of NCC function. Recently, a novel phosphorylation site at S811 was identified in isoforms 1 and 2 [NaCl cotransporter splice variant (NCC_SV)], which are only present in humans and higher primates. The aim of the current study, therefore, is to investigate the role of S811 phosphorylation in the regulation of NCC by a combination of biochemical and fluorescent microscopy analyses. We demonstrate that hypotonic low-chloride buffer increases S811 phosphorylation, whereas phosphorylation-deficient S811A mutant hinders phosphorylation at T55 and T60 in NCC_SV and NCC₃. NCC_SV S811A impairs NCC₃ activity in a dominant-negative fashion, although it does not affect plasma membrane abundance. This effect may be explained by the heterodimerization of NCC_SV with NCC₃. Taken together, our study highlights the dominant-negative effect of NCC_SV on T55 and T60 phosphorylation and NCC activity. Here, we reveal a new function of NCC_SV in humans that broadens the understanding on NCC regulation in blood pressure control.-Tutakhel, O. A. Z., Bianchi, F., Smits, D. A., Bindels, R. J. M., Hoenderop, J. G. J., van der Wijst, J. Dominant functional role of the novel phosphorylation site S811 in the human renal NaCl cotransporter.

Simultaneous genome-wide gene expression and transcript isoform profiling in the human malaria parasite

Gene expression DNA microarrays have been vital for characterizing whole-genome transcriptional profiles. Nevertheless, their effectiveness relies heavily on the accuracy of genome sequences, the annotation of gene structures, and the sequence-dependent performance of individual probes. Currently available gene expression arrays for the malaria parasite Plasmodium falciparum rely on an average of 2 probes per gene, usually positioned near the 3′ end of genes; consequently, existing designs are prone to measurement bias and cannot capture complexities such as the occurrence of transcript isoforms arising from alternative splicing or alternative start/ stop sites. Here, we describe two novel gene expression arrays with exon-focused probes designed with an average of 12 and 20 probes spanning each gene. This high probe density minimizes signal noise inherent in probe-to-probe sequence-dependent hybridization intensity. We demonstrate that these exon arrays accurately profile genome-wide expression, comparing favorably to currently available arrays and RNA-seq profiling, and can detect alternatively spliced transcript isoforms as well as non-coding RNAs (ncRNAs). Of the 964 candidate alternate splicing events from published RNA-seq studies, 162 are confirmed using the exon array. Furthermore, the exon array predicted 330 previously unidentified alternate splicing events. Gene expression microarrays continue to offer a cost-effective alternative to RNA-seq for the simultaneous monitoring of gene expression and alternative splicing events. Microarrays may even be preferred in some cases due to their affordability and the rapid turn-around of results when hundreds of samples are required for fine-scale systems biology investigations, including the monitoring of the networks of gene co-expression in the emergence of drug resistance.

Domestication reduces alternative splicing expression variations in sorghum

Domestication is known to strongly reduce genomic diversity through population bottlenecks. The resulting loss of polymorphism has been thoroughly documented in numerous cultivated species. Here we investigate the impact of domestication on the diversity of alternative transcript expressions using RNAseq data obtained on cultivated and wild sorghum accessions (ten accessions for each pool). In that aim, we focus on genes expressing two isoforms in sorghum and estimate the ratio between expression levels of those isoforms in each accession. Noticeably, for a given gene, one isoform can either be overexpressed or underexpressed in some wild accessions, whereas in the cultivated accessions, the balance between the two isoforms of the same gene appears to be much more homogenous. Indeed, we observe in sorghum significantly more variation in isoform expression balance among wild accessions than among domesticated accessions. The possibility exists that the loss of nucleotide diversity due to domestication could affect regulatory elements, controlling transcription or degradation of these isoforms. Impact on the isoform expression balance is discussed. As far as we know, this is the first time that the impact of domestication on transcript isoform balance has been studied at the genomic scale. This could pave the way towards the identification of key domestication genes with finely tuned isoform expressions in domesticated accessions while being highly variable in their wild relatives.

Homozygous carriers of the TCF7L2 rs7903146 T-allele show altered postprandial response in triglycerides and triglyceride-rich lipoproteins

The TCF7L2 rs7903146 T-allele shows the strongest association with type 2 diabetes (T2D) among common gene variants. The aim of this study was to assess circulating levels of metabolites following a meal test in individuals carrying the high risk rs790346 TT genotype (cases) and low-risk CC genotype (controls). Sixty-two men were recruited based on TCF7L2 genotype, 31 were TT carriers and 31 were age- and BMI-matched CC carriers. All participants consumed a test meal after 12 hours of fasting. Metabolites were measured using proton nuclear magnetic resonance (NMR) spectroscopy. Metabolomic profiling of TCF7L2 carriers were performed for 141 lipid estimates. TT carriers had lower fasting levels of L-VLDL-L (total lipids in large very low density lipoproteins, p = 0.045), L-VLDL-CE (cholesterol esters in large VLDL, p = 0.03), and L-VLDL-C (total cholesterol in large VLDL, p = 0.045) compared to CC carriers. Additionally, TT carriers had lower postprandial levels of total triglycerides (TG) (q = 0.03), VLDL-TG (q = 0.05, including medium, small and extra small, q = 0.048, q = 0.0009, q = 0.04, respectively), HDL-TG (triglycerides in high density lipoproteins q = 0.037) and S-HDL-TG (q = 0.00003). In conclusion, TT carriers show altered postprandial triglyceride response, mainly influencing VLDL and HDL subclasses suggesting a genotype-mediated effect on hepatic lipid regulation.

The roles of RNA processing in translating genotype to phenotype

A goal of human genetics studies is to determine the mechanisms by which genetic variation produces phenotypic differences that affect human health. Efforts in this respect have previously focused on genetic variants that affect mRNA levels by altering epigenetic and transcriptional regulation. Recent studies show that genetic variants that affect RNA processing are at least equally as common as, and are largely independent from, those variants that affect transcription. We highlight the impact of genetic variation on pre-mRNA splicing and polyadenylation, and on the stability, translation and structure of mRNAs as mechanisms that produce phenotypic traits. These results emphasize the importance of including RNA processing signals in analyses to identify functional variants.

The roles of RNA processing in translating genotype to phenotype

A goal of human genetics studies is to determine the mechanisms by which genetic variation produces phenotypic differences that affect human health. Efforts in this respect have previously focused on genetic variants that affect mRNA levels by altering epigenetic and transcriptional regulation. Recent studies show that genetic variants that affect RNA processing are at least equally as common as, and are largely independent from, those variants that affect transcription. We highlight the impact of genetic variation on pre-mRNA splicing and polyadenylation, and on the stability, translation and structure of mRNAs as mechanisms that produce phenotypic traits. These results emphasize the importance of including RNA processing signals in analyses to identify functional variants.

Characterization of visceral and subcutaneous adipose tissue transcriptome in pregnant women with and without spontaneous labor at term: implication of alternative splicing in the metabolic adaptations of adipose tissue to parturition

OBJECTIVE

The aim of this study was to determine gene expression and splicing changes associated with parturition and regions (visceral vs. subcutaneous) of the adipose tissue of pregnant women.

STUDY DESIGN

The transcriptome of visceral and abdominal subcutaneous adipose tissue from pregnant women at term with (n=15) and without (n=25) spontaneous labor was profiled with the Affymetrix GeneChip Human Exon 1.0 ST array. Overall gene expression changes and the differential exon usage rate were compared between patient groups (unpaired analyses) and adipose tissue regions (paired analyses). Selected genes were tested by quantitative reverse transcription-polymerase chain reaction.

RESULTS

Four hundred and eighty-two genes were differentially expressed between visceral and subcutaneous fat of pregnant women with spontaneous labor at term (q-value <0.1; fold change >1.5). Biological processes enriched in this comparison included tissue and vasculature development as well as inflammatory and metabolic pathways. Differential splicing was found for 42 genes [q-value <0.1; differences in Finding Isoforms using Robust Multichip Analysis scores >2] between adipose tissue regions of women not in labor. Differential exon usage associated with parturition was found for three genes (LIMS1, HSPA5, and GSTK1) in subcutaneous tissues.

CONCLUSION

We show for the first time evidence of implication of mRNA splicing and processing machinery in the subcutaneous adipose tissue of women in labor compared to those without labor.

Sequence variation between 462 human individuals fine-tunes functional sites of RNA processing

Recent advances in the cost-efficiency of sequencing technologies enabled the combined DNA- and RNA-sequencing of human individuals at the population-scale, making genome-wide investigations of the inter-individual genetic impact on gene expression viable. Employing mRNA-sequencing data from the Geuvadis Project and genome sequencing data from the 1000 Genomes Project we show that the computational analysis of DNA sequences around splice sites and poly-A signals is able to explain several observations in the phenotype data. In contrast to widespread assessments of statistically significant associations between DNA polymorphisms and quantitative traits, we developed a computational tool to pinpoint the molecular mechanisms by which genetic markers drive variation in RNA-processing, cataloguing and classifying alleles that change the affinity of core RNA elements to their recognizing factors. The in silico models we employ further suggest RNA editing can moonlight as a splicing-modulator, albeit less frequently than genomic sequence diversity. Beyond existing annotations, we demonstrate that the ultra-high resolution of RNA-Seq combined from 462 individuals also provides evidence for thousands of bona fide novel elements of RNA processing-alternative splice sites, introns, and cleavage sites-which are often rare and lowly expressed but in other characteristics similar to their annotated counterparts.

Transcriptional similarity in couples reveals the impact of shared environment and lifestyle on gene regulation through modified cytosines

Gene expression is a complex and quantitative trait that is influenced by both genetic and non-genetic regulators including environmental factors. Evaluating the contribution of environment to gene expression regulation and identifying which genes are more likely to be influenced by environmental factors are important for understanding human complex traits. We hypothesize that by living together as couples, there can be commonly co-regulated genes that may reflect the shared living environment (e.g., diet, indoor air pollutants, behavioral lifestyle). The lymphoblastoid cell lines (LCLs) derived from unrelated couples of African ancestry (YRI, Yoruba people from Ibadan, Nigeria) from the International HapMap Project provided a unique model for us to characterize gene expression pattern in couples by comparing gene expression levels between husbands and wives. Strikingly, 778 genes were found to show much smaller variances in couples than random pairs of individuals at a false discovery rate (FDR) of 5%. Since genetic variation between unrelated family members in a general population is expected to be the same assuming a random-mating society, non-genetic factors (e.g., epigenetic systems) are more likely to be the mediators for the observed transcriptional similarity in couples. We thus evaluated the contribution of modified cytosines to those genes showing transcriptional similarity in couples as well as the relationships these CpG sites with other gene regulatory elements, such as transcription factor binding sites (TFBS). Our findings suggested that transcriptional similarity in couples likely reflected shared common environment partially mediated through cytosine modifications.

Transcript Isoform Variation Associated with Cytosine Modification in Human Lymphoblastoid Cell Lines

Cytosine modification on DNA is variable among individuals, which could correlate with gene expression variation. The effect of cytosine modification on interindividual transcript isoform variation (TIV), however, remains unclear. In this study, we assessed the extent of cytosine modification-specific TIV in lymphoblastoid cell lines (LCLs) derived from unrelated individuals of European and African descent. Our study detected cytosine modification-specific TIVs for 17% of the analyzed genes at a 5% false discovery rate. Forty-five percent of the TIV-associated cytosine modifications correlated with the overall gene expression levels as well, with the corresponding CpG sites overrepresented in transcript initiation sites, transcription factor binding sites, and distinct histone modification peaks, suggesting that alternative isoform transcription underlies the TIVs. Our analysis also revealed 33% of the TIV-associated cytosine modifications that affected specific exons, with the corresponding CpG sites overrepresented in exon/intron junctions, splicing branching points, and transcript termination sites, implying that the TIVs are attributable to alternative splicing or transcription termination. Genetic and epigenetic regulation of TIV shared target preference but exerted independent effects on 61% of the common exon targets. Cytosine modification-specific TIVs detected from LCLs were differentially enriched in those detected from various tissues in The Cancer Genome Atlas, indicating their developmental dependency. Genes containing cytosine modification-specific TIVs were enriched in pathways of cancers and metabolic disorders. Our study demonstrated a prominent effect of cytosine modification variation on the transcript isoform spectrum over gross transcript abundance and revealed epigenetic contributions to diseases that were mediated through cytosine modification-specific TIV.

Linking short tandem repeat polymorphisms with cytosine modifications in human lymphoblastoid cell lines

Inter-individual variation in cytosine modifications has been linked to complex traits in humans. Cytosine modification variation is partially controlled by single nucleotide polymorphisms (SNPs), known as modified cytosine quantitative trait loci (mQTL). However, little is known about the role of short tandem repeat polymorphisms (STRPs), a class of structural genetic variants, in regulating cytosine modifications. Utilizing the published data on the International HapMap Project lymphoblastoid cell lines (LCLs), we assessed the relationships between 721 STRPs and the modification levels of 283,540 autosomal CpG sites. Our findings suggest that, in contrast to the predominant cis-acting mode for SNP-based mQTL, STRPs are associated with cytosine modification levels in both cis-acting (local) and trans-acting (distant) modes. In local scans within the ±1 Mb windows of target CpGs, 21, 9, and 21 cis-acting STRP-based mQTL were detected in CEU (Caucasian residents from Utah, USA), YRI (Yoruba people from Ibadan, Nigeria), and the combined samples, respectively. In contrast, 139,420, 76,817, and 121,866 trans-acting STRP-based mQTL were identified in CEU, YRI, and the combined samples, respectively. A substantial proportion of CpG sites detected with local STRP-based mQTL were not associated with SNP-based mQTL, suggesting that STRPs represent an independent class of mQTL. Functionally, genetic variants neighboring CpG-associated STRPs are enriched with genome-wide association study (GWAS) loci for a variety of complex traits and diseases, including cancers, based on the National Human Genome Research Institute (NHGRI) GWAS Catalog. Therefore, elucidating these STRP-based mQTL in addition to SNP-based mQTL can provide novel insights into the genetic architectures of complex traits.

Characterization of Visceral and Subcutaneous Adipose Tissue Transcriptome and Biological Pathways in Pregnant and Non-Pregnant Women: Evidence for Pregnancy-Related Regional-Specific Differences in Adipose Tissue

Objective

The purpose of this study was to compare the transcriptome of visceral and subcutaneous adipose tissues between pregnant and non-pregnant women.

Study Design

The transcriptome of paired visceral and abdominal subcutaneous adipose tissues from pregnant women at term and matched non-pregnant women (n = 11) was profiled with the Affymetrix Human Exon 1.0 ST array. Differential expression of selected genes was validated with the use of quantitative reverse transcription–polymerase chain reaction.

Results

Six hundred forty-four transcripts from 633 known genes were differentially expressed (false discovery rate (FDR) <0.1; fold-change >1.5), while 42 exons from 36 genes showed differential usage (difference in FIRMA scores >2 and FDR<0.1) between the visceral and subcutaneous fat of pregnant women. Fifty-six known genes were differentially expressed between pregnant and non-pregnant subcutaneous fat and three genes in the visceral fat. Enriched biological processes in the subcutaneous adipose tissue of pregnant women were mostly related to inflammation.

Conclusion

The transcriptome of visceral and subcutaneous fat depots reveals pregnancy-related gene expression and splicing differences in both visceral and subcutaneous adipose tissue. Furthermore, for the first time, alternative splicing in adipose tissue has been associated with regional differences and human parturition.

In vitro human cell line models to predict clinical response to anticancer drugs

In vitro human cell line models have been widely used for cancer pharmacogenomic studies to predict clinical response, to help generate pharmacogenomic hypothesis for further testing, and to help identify novel mechanisms associated with variation in drug response. Among cell line model systems, immortalized cell lines such as Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines (LCLs) have been used most often to test the effect of germline genetic variation on drug efficacy and toxicity. Another model, especially in cancer research, uses cancer cell lines such as the NCI-60 panel. These models have been used mainly to determine the effect of somatic alterations on response to anticancer therapy. Even though these cell line model systems are very useful for initial screening, results from integrated analyses of multiple omics data and drug response phenotypes using cell line model systems still need to be confirmed by functional validation and mechanistic studies, as well as validation studies using clinical samples. Future models might include the use of patient-specific inducible pluripotent stem cells and the incorporation of 3D culture which could further optimize in vitro cell line models to improve their predictive validity.

Genome-wide analysis links NFATC2 with asparaginase hypersensitivity

Asparaginase is used to treat acute lymphoblastic leukemia (ALL); however, hypersensitivity reactions can lead to suboptimal asparaginase exposure. Our objective was to use a genome-wide approach to identify loci associated with asparaginase hypersensitivity in children with ALL enrolled on St. Jude Children's Research Hospital (SJCRH) protocols Total XIIIA (n = 154), Total XV (n = 498), and Total XVI (n = 271), or Children's Oncology Group protocols POG 9906 (n = 222) and AALL0232 (n = 2163). Germline DNA was genotyped using the Affymetrix 500K, Affymetrix 6.0, or the Illumina Exome BeadChip array. In multivariate logistic regression, the intronic rs6021191 variant in nuclear factor of activated T cells 2 (NFATC2) had the strongest association with hypersensitivity (P = 4.1 × 10(-8); odds ratio [OR] = 3.11). RNA-seq data available from 65 SJCRH ALL tumor samples and 52 Yoruba HapMap samples showed that samples carrying the rs6021191 variant had higher NFATC2 expression compared with noncarriers (P = 1.1 × 10(-3) and 0.03, respectively). The top ranked nonsynonymous polymorphism was rs17885382 in HLA-DRB1 (P = 3.2 × 10(-6); OR = 1.63), which is in near complete linkage disequilibrium with the HLA-DRB1*07:01 allele we previously observed in a candidate gene study. The strongest risk factors for asparaginase allergy are variants within genes regulating the immune response.

Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing

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

In order to better understand how genetic differences between individuals can cause diseases, it is crucial to understand how genetic variants affect cellular functions in the different tissues that compose the human body. From the umbilical cord of 195 newborn babies, we previously obtained three different cell-types: fibroblasts, T-cells and immortalized B-cells. From every individual in each cell type we measured four features across the genome: 1) genetic differences, 2) DNA methylation, an epigenetic modification of DNA that can affect its functional state, 3) gene expression—the amount of gene activity, 4) alternative splicing—which of the different versions of a gene is manifested. We find thousands of genetic variants of the DNA sequence that affect methylation, gene expression, and splicing. We show that while these genetic effects often affect multiple cell-types, the strength of these effects varies between cell-types. Also epigenetic methylation marks of DNA associate to gene expression and particularly often to splicing. Since abnormalities in gene expression, DNA methylation and alternative splicing are associated to diseases, it is important to continue studying how these traits are inter-related and affected by genetic variation across cell-types.

Integrative genomics and transcriptomics analysis of human embryonic and induced pluripotent stem cells

Background

Human genomic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), are associated with several phenotypic traits varying from mild features to hereditary diseases. Several genome-wide studies have reported genomic variants that correlate with gene expression levels in various tissue and cell types.

Results

We studied human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) measuring the SNPs and CNVs with Affymetrix SNP 6 microarrays and expression values with Affymetrix Exon microarrays. We computed the linear relationships between SNPs and expression levels of exons, transcripts and genes, and the associations between gene CNVs and gene expression levels. Further, for a few of the resulted genes, the expression value was associated with both CNVs and SNPs. Our results revealed altogether 217 genes and 584 SNPs whose genomic alterations affect the transcriptome in the same cells. We analyzed the enriched pathways and gene ontologies within these groups of genes, and found out that the terms related to alternative splicing and development were enriched.

Conclusions

Our results revealed that in the human pluripotent stem cells, the expression values of several genes, transcripts and exons were affected due to the genomic variation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-014-0032-2) contains supplementary material, which is available to authorized users.

Transcriptome sequencing from diverse human populations reveals differentiated regulatory architecture

Large-scale sequencing efforts have documented extensive genetic variation within the human genome. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. While regulatory variation influencing gene expression has been studied within a handful of populations, the breadth of transcriptome differences across diverse human populations has not been systematically analyzed. To better understand the spectrum of gene expression variation, alternative splicing, and the population genetics of regulatory variation in humans, we have sequenced the genomes, exomes, and transcriptomes of EBV transformed lymphoblastoid cell lines derived from 45 individuals in the Human Genome Diversity Panel (HGDP). The populations sampled span the geographic breadth of human migration history and include Namibian San, Mbuti Pygmies of the Democratic Republic of Congo, Algerian Mozabites, Pathan of Pakistan, Cambodians of East Asia, Yakut of Siberia, and Mayans of Mexico. We discover that approximately 25.0% of the variation in gene expression found amongst individuals can be attributed to population differences. However, we find few genes that are systematically differentially expressed among populations. Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations. Allelic expression analyses indicate that previously mapped common regulatory variants identified in eight populations from the International Haplotype Map Phase 3 project have similar effects in our seven sampled HGDP populations, suggesting that the cellular effects of common variants are shared across diverse populations. Together, these results provide a resource for studies analyzing functional differences across populations by estimating the degree of shared gene expression, alternative splicing, and regulatory genetics across populations from the broadest points of human migration history yet sampled.

Previous gene expression studies have identified factors influencing population-level variation in gene regulation. However, these efforts have been limited to a small set of well-studied populations. By leveraging the high resolution of RNA sequencing and broad population sampling, we survey the landscape of transcriptome variation across a globally distributed set of seven populations that span a breadth of human genetic variation and major dispersal events. We assess differences in gene expression, transcript structure, and regulatory variation. We find only 44 transcripts that show significant differences in expression, likely as a result of the small sample size, but we find that 25% of the variance in gene expression is due to population differences. This is a larger fraction than previously observed, and it is likely due to the greater breadth of human diversity assayed in this study. We also find that population-specific variance is mostly due to transcription variability rather than the configuration of expressed gene products. Additionally, known common regulatory variants have similar effects across populations including those we study here. These data and results serve as a resource cataloging the wide array of gene expression regulation affecting population variation among diverse groups, improving our understanding of transcriptional diversity.

Identification and validation of genetic variants that influence transcription factor and cell signaling protein levels

Many genetic variants associated with human disease have been found to be associated with alterations in mRNA expression. Although it is commonly assumed that mRNA expression changes will lead to consequent changes in protein levels, methodological challenges have limited our ability to test the degree to which this assumption holds true. Here, we further developed the micro-western array approach and globally examined relationships between human genetic variation and cellular protein levels. We collected more than 250,000 protein level measurements comprising 441 transcription factor and signaling protein isoforms across 68 Yoruba (YRI) HapMap lymphoblastoid cell lines (LCLs) and identified 12 cis and 160 trans protein level QTLs (pQTLs) at a false discovery rate (FDR) of 20%. Whereas up to two thirds of cis mRNA expression QTLs (eQTLs) were also pQTLs, many pQTLs were not associated with mRNA expression. Notably, we replicated and functionally validated a trans pQTL relationship between the KARS lysyl-tRNA synthetase locus and levels of the DIDO1 protein. This study demonstrates proof of concept in applying an antibody-based microarray approach to iteratively measure the levels of human proteins and relate these levels to human genome variation and other genomic data sets. Our results suggest that protein-based mechanisms might functionally buffer genetic alterations that influence mRNA expression levels and that pQTLs might contribute phenotypic diversity to a human population independently of influences on mRNA expression.

Digital genotyping of macrosatellites and multicopy genes reveals novel biological functions associated with copy number variation of large tandem repeats

Tandem repeats are common in eukaryotic genomes, but due to difficulties in assaying them remain poorly studied. Here, we demonstrate the utility of Nanostring technology as a targeted approach to perform accurate measurement of tandem repeats even at extremely high copy number, and apply this technology to genotype 165 HapMap samples from three different populations and five species of non-human primates. We observed extreme variability in copy number of tandemly repeated genes, with many loci showing 5–10 fold variation in copy number among humans. Many of these loci show hallmarks of genome assembly errors, and the true copy number of many large tandem repeats is significantly under-represented even in the high quality ‘finished’ human reference assembly. Importantly, we demonstrate that most large tandem repeat variations are not tagged by nearby SNPs, and are therefore essentially invisible to SNP-based GWAS approaches. Using association analysis we identify many cis correlations of large tandem repeat variants with nearby gene expression and DNA methylation levels, indicating that variations of tandem repeat length are associated with functional effects on the local genomic environment. This includes an example where expansion of a macrosatellite repeat is associated with increased DNA methylation and suppression of nearby gene expression, suggesting a mechanism termed “repeat induced gene silencing”, which has previously been observed only in transgenic organisms. We also observed multiple signatures consistent with altered selective pressures at tandemly repeated loci, suggesting important biological functions. Our studies show that tandemly repeated loci represent a highly variable fraction of the genome that have been systematically ignored by most previous studies, copy number variation of which can exert functionally significant effects. We suggest that future studies of tandem repeat loci will lead to many novel insights into their role in modulating both genomic and phenotypic diversity.

Here we utilize Nanostring digital assays and show their utility for estimating copy number of 186 multicopy genes and tandem repeats. By analyzing patterns of single nucleotide variation around these variants, we show that copy number variation at the vast majority of tandem repeat variations is not effectively tagged by nearby SNPs, and thus standard genome-wide association studies that focus on SNPs provide little or no information about such variants. By comparing patterns of tandem repeat copy number with variation in local gene expression and DNA methylation, we also identify extensive functional effects on local genome function. This includes an example of a non-coding macrosatellite repeat, expansion of which exerts a repressive effect on a nearby gene accompanied by accumulations of local DNA methylation. Finally, comparison of diverse human populations with a number of primate genomes shows that many of these sequences have undergone extreme changes in copy number during recent human and primate evolution, and show signatures that suggest possible selective effects. Overall, we conclude that multicopy genes and macrosatellites represent a highly variable fraction of the genome with important functional effects that has been systematically ignored by previous studies.

The contribution of the functional IL6R polymorphism rs2228145, eQTLs and other genome-wide SNPs to the heritability of plasma sIL-6R levels

The non-synonymous SNP rs2228145 in the IL6R gene on chromosome 1q21.3 is associated with a wide range of common diseases, including asthma, rheumatoid arthritis, type 1 diabetes and coronary heart disease. We examined the contribution of this functional IL6R gene polymorphism rs2228145 versus other genome-wide SNPs to the variance of sIL-6R levels in blood plasma in a large population-based sample (N ~5,000), and conducted an expression QTL analysis to identify SNPs associated with IL6R gene expression. Based on data from 2,360 twin families, the broad heritability of sIL-6R was estimated at 72 and 51% of the total variance was explained by the functional SNP rs2228145. Converging findings from GWAS, linkage, and GCTA analyses indicate that additional variance of sIL-6R levels can be explained by other variants in the IL6R region, including variants at the 3'-end of IL6R tagged by rs60760897 that are associated with IL6R RNA expression.

Discovery and functional assessment of gene variants in the vascular endothelial growth factor pathway

Angiogenesis is a host-mediated mechanism in disease pathophysiology. The vascular endothelial growth factor (VEGF) pathway is a major determinant of angiogenesis, and a comprehensive annotation of the functional variation in this pathway is essential to understand the genetic basis of angiogenesis-related diseases. We assessed the allelic heterogeneity of gene expression, population specificity of cis expression quantitative trait loci (eQTLs), and eQTL function in luciferase assays in CEU and Yoruba people of Ibadan, Nigeria (YRI) HapMap lymphoblastoid cell lines in 23 resequenced genes. Among 356 cis-eQTLs, 155 and 174 were unique to CEU and YRI, respectively, and 27 were shared between CEU and YRI. Two cis-eQTLs provided mechanistic evidence for two genome-wide association study findings. Five eQTLs were tested for function in luciferase assays and the effect of two KRAS variants was concordant with the eQTL effect. Two eQTLs found in each of PRKCE, PIK3C2A, and MAP2K6 could predict 44%, 37%, and 45% of the variance in gene expression, respectively. This is the first analysis focusing on the pattern of functional genetic variation of the VEGF pathway genes in CEU and YRI populations and providing mechanistic evidence for genetic association studies of diseases for which angiogenesis plays a pathophysiologic role.

Transcriptome sequencing of Chinese and Caucasian population identifies ethnic-associated differential transcript abundance of heterogeneous nuclear ribonucleoprotein K (hnRNPK)

Gene expression variations (GEV) among different ethnic groups have been a subject matter for extensive study. Relatively less known is the extent of alternative splicing variations (ASV) in the context of ethnicity. We conducted a transcriptome sequencing study of 20 lymphoblastoid cell lines obtained from Caucasian and Han Chinese, and identified known genes that exhibit differential isoform abundance between the two ethnic groups. Among them hnRNPK, a co-factor of p53 (TP53), could be further replicated in a 39-sample cohort with TaqMan assay. Although within-population novel splice variants are common, inter-population novel splice variants are rare. We further analyzed 5.63 billion sequencing reads retrieved from the NCBI Sequence Read Archive and identified potential ethnic-specific transcribed regions.

EPS8 inhibition increases cisplatin sensitivity in lung cancer cells

Cisplatin, a commonly used chemotherapeutic, is associated with ototoxicity, renal toxicity and neurotoxicity, thus identifying means to increase the therapeutic index of cisplatin may allow for improved outcomes. A SNP (rs4343077) within EPS8, discovered through a genome wide association study of cisplatin-induced cytotoxicity and apoptosis in lymphoblastoid cell lines (LCLs), provided impetus to further study this gene. The purpose of this work was to evaluate the role of EPS8 in cellular susceptibility to cisplatin in cancerous and non-cancerous cells. We used EPS8 RNA interference to determine the effect of decreased EPS8 expression on LCL and A549 lung cancer cell sensitivity to cisplatin. EPS8 knockdown in LCLs resulted in a 7.9% increase in cisplatin-induced survival (P = 1.98 × 10(-7)) and an 8.7% decrease in apoptosis (P = 0.004) compared to control. In contrast, reduced EPS8 expression in lung cancer cells resulted in a 20.6% decrease in cisplatin-induced survival (P = 5.08 × 10(-5)). We then investigated an EPS8 inhibitor, mithramycin A, as a potential agent to increase the therapeutic index of cisplatin. Mithramycin A decreased EPS8 expression in LCLs resulting in decreased cellular sensitivity to cisplatin as evidenced by lower caspase 3/7 activation following cisplatin treatment (42.7% ± 6.8% relative to control P = 0.0002). In 5 non-small-cell lung carcinoma (NSCLC) cell lines, mithramycin A also resulted in decreased EPS8 expression. Adding mithramycin to 4 NSCLC cell lines and a bladder cancer cell line, resulted in increased sensitivity to cisplatin that was significantly more pronounced in tumor cell lines than in LCL lines (p<0.0001). An EGFR mutant NSCLC cell line (H1975) showed no significant change in sensitivity to cisplatin with the addition of mithramycin treatment. Therefore, an inhibitor of EPS8, such as mithramycin A, could improve cisplatin treatment by increasing sensitivity of tumor relative to normal cells.

Gene-environment interactions and health inequalities: views of underserved communities

This article examines the beliefs and experiences of individuals living in underserved ethnically diverse communities in Cleveland, Ohio, regarding the influence of genetic, social, and environmental factors on health and health inequalities. Using a community-engaged methodological approach, 13 focus groups were conducted with African American, Hispanic, and White individuals residing in the Cleveland area to explore attitudes and beliefs about genetics, genetic research, and health disparities and inequalities. Results of this study highlight the range of meanings that individuals attach to genetic variation, genomic research, and gene-environment interactions, and their implications for addressing health inequalities. The majority of participants in all focus groups reported that social and environmental factors were more important than genetics in contributing to health inequalities. Most participants were unfamiliar with genetic research. These data have implications for how genetic information and research might be applied in conjunction with addressing social determinants of health to improve prevention strategies in underserved communities and ultimately reduce health inequalities.

Pharmacogenomic Discovery Delineating the Genetic Basis of Drug Response

Personalized medicine has the promise to tailor medical care based on the patient's genetic make-up and clinical variables such as gender, race and exposure to environmental stimuli. Recent progress in pharmacogenetic and pharmacogenomic studies has suggested that drug response to therapeutic treatments is likely a complex trait influenced by a variety of genetic and non-genetic factors. Identifying molecular targets (e.g., genetic variants) delineating the genetic basis of drug response could help understand the complex nature of drug response. The last decade has witnessed significant advances in genome-wide profiling technologies for genetic/epigenetic variations and gene expression. As an unbiased, cell-based model for pharmacogenomic discovery, a tremendous resource of whole-genome molecular targets has been accumulated for the HapMap lymphoblastoid cell lines (LCLs) during the past decade. The current progress, particularly in cancer pharmacogenomics, using the LCL model was reviewed to illustrate the potential impact of systems biology approaches on pharmacogenomic discovery.

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.

SCN1A IVS5N+5 polymorphism and response to sodium valproate: a multicenter study

AIM

Approximately 30% of epilepsy patients do not response to antiepileptic drugs (AEDs). The functional SCN1A IVS5N+5 polymorphism may play a role in response to some AEDs. The purpose of this study was to examine this hypothesis in a cohort study of Malaysian and Hong Kong Chinese epilepsy patients on sodium valproate (VPA) monotherapy and in a meta-analysis.

PATIENTS & METHODS

The SCN1A IVS5N+5 polymorphism was genotyped in 583 Malaysian (84%) and Hong Kong Chinese (16%) epilepsy patients receiving VPA monotherapy. The related association studies, including the current study, were meta-analyzed by using fixed- and random-effects models under various genetic models.

RESULTS

A total of 277 (47.5%) and 306 (52.5%) patients were VPA nonresponsive and responsive, respectively. Unlike Chinese and Indian patients, Malay nonresponsive patients with idiopathic generalized epilepsy showed significant association, probably caused by the small sample size.

CONCLUSION

The cohort study and meta-analysis did not demonstrate an association between AED responsiveness and this polymorphism. Future studies with a larger sample size of Malays with idiopathic generalized epilepsy are suggested.

Xenomic networks variability and adaptation traits in wood decaying fungi

Fungal degradation of wood is mainly restricted to basidiomycetes, these organisms having developed complex oxidative and hydrolytic enzymatic systems. Besides these systems, wood-decaying fungi possess intracellular networks allowing them to deal with the myriad of potential toxic compounds resulting at least in part from wood degradation but also more generally from recalcitrant organic matter degradation. The members of the detoxification pathways constitute the xenome. Generally, they belong to multigenic families such as the cytochrome P450 monooxygenases and the glutathione transferases. Taking advantage of the recent release of numerous genomes of basidiomycetes, we show here that these multigenic families are extended and functionally related in wood-decaying fungi. Furthermore, we postulate that these rapidly evolving multigenic families could reflect the adaptation of these fungi to the diversity of their substrate and provide keys to understand their ecology. This is of particular importance for white biotechnology, this xenome being a putative target for improving degradation properties of these fungi in biomass valorization purposes.

SCAN: a systems biology approach to pharmacogenomic discovery

Genome-wide association (GWA) studies have identified thousands of genetic variants that contribute to disease and pharmacologic traits. More recently, high-throughput sequencing studies promise to provide a more complete catalog of genetic variants with roles in human phenotypic variation. Yet, characterizing the influence of functional variants on genes, RNAs, proteins, and ultimately disease or pharmacologic traits is a critical challenge for a vast majority of the implicated susceptibility loci. Here we describe SCAN, a bioinformatics resource we have developed to elucidate the functional consequences of genetic variants identified by genome-wide scans. In particular, this public resource implements a systems biology approach to pharmacogenomic discovery.

Variants affecting exon skipping contribute to complex traits

DNA variants that affect alternative splicing and the relative quantities of different gene transcripts have been shown to be risk alleles for some Mendelian diseases. However, for complex traits characterized by a low odds ratio for any single contributing variant, very few studies have investigated the contribution of splicing variants. The overarching goal of this study is to discover and characterize the role that variants affecting alternative splicing may play in the genetic etiology of complex traits, which include a significant number of the common human diseases. Specifically, we hypothesize that single nucleotide polymorphisms (SNPs) in splicing regulatory elements can be characterized in silico to identify variants affecting splicing, and that these variants may contribute to the etiology of complex diseases as well as the inter-individual variability in the ratios of alternative transcripts. We leverage high-throughput expression profiling to 1) experimentally validate our in silico predictions of skipped exons and 2) characterize the molecular role of intronic genetic variations in alternative splicing events in the context of complex human traits and diseases. We propose that intronic SNPs play a role as genetic regulators within splicing regulatory elements and show that their associated exon skipping events can affect protein domains and structure. We find that SNPs we would predict to affect exon skipping are enriched among the set of SNPs reported to be associated with complex human traits.

Alternative splicing is a common eukaryotic cellular mechanism that allows for the production of multiple proteins from one gene and occurs in 40%–90% of all human genes. Alternative splicing has been shown to be important for many critical biological processes, including development, evolution, and even psychological behavior. Additionally, alternative splicing has been associated with 15%–50% of human genetic diseases, including breast cancer; however, the precise mechanism by which genetic variations regulate this process remains to be fully elucidated. In this study, we develop an integrative approach that utilizes sequence-based analysis and genome-wide expression profiling to identify genetic variations that may affect alternative splicing. We also evaluate their enrichment among established disease-associated variations. Our study provides insights into the functionality of these variations and emphasizes their importance for complex human traits and diseases.

Detection of parent-of-origin specific expression quantitative trait loci by cis-association analysis of gene expression in trios

Parent-of-origin (PofO) effects, such as imprinting are a phenomenon in which homologous chromosomes exhibit differential gene expression and epigenetic modifications according to their parental origin. Such non-Mendelian inheritance patterns are generally ignored by conventional association studies, as these tests consider the maternal and paternal alleles as equivalent. To identify regulatory regions that show PofO effects on gene expression (imprinted expression Quantitative Trait Loci, ieQTLs), here we have developed a novel method in which we associate SNP genotypes of defined parental origin with gene expression levels. We applied this method to study 59 HapMap phase II parent-offspring trios. By analyzing mother/father/child trios, rules of Mendelian inheritance allowed the parental origin to be defined for ∼95% of SNPs in each child. We used 680,475 informative SNPs and corresponding expression data for 92,167 probe sets from Affymetrix GeneChip Human Exon 1.0 ST arrays and performed four independent cis-association analyses with the expression level of RefSeq genes within 1 Mb using PLINK. Independent analyses of maternal and paternal genotypes identified two significant cis-ieQTLs (p<10⁻⁷) at which expression of genes SFT2D2 and SRRT associated exclusively with maternally inherited SNPs rs3753292 and rs6945374, respectively. 28 additional suggestive cis-associations with only maternal or paternal SNPs were found at a lower stringency threshold of p<10⁻⁶, including associations with two known imprinted genes PEG10 and TRAPPC9, demonstrating the efficacy of our method. Furthermore, comparison of our method that utilizes independent analyses of maternal and paternal genotypes with the Likelihood Ratio Test (LRT) showed it to be more effective for detecting imprinting effects than the LRT. Our method represents a novel approach that can identify imprinted regulatory elements that control gene expression, suggesting novel PofO effects in the human genome.

Calling sample mix-ups in cancer population studies

Sample tracking errors have been and always will be a part of the practical implementation of large experiments. It has recently been proposed that expression quantitative trait loci (eQTLs) and their associated effects could be used to identify sample mix-ups and this approach has been applied to a number of large population genomics studies to illustrate the prevalence of the problem. We had adopted a similar approach, termed ‘BADGER’, in the METABRIC project. METABRIC is a large breast cancer study that may have been the first in which eQTL-based detection of mismatches was used during the study, rather than after the event, to aid quality assurance. We report here on the particular issues associated with large cancer studies performed using historical samples, which complicate the interpretation of such approaches. In particular we identify the complications of using tumour samples, of considering cellularity and RNA quality, of distinct subgroups existing in the study population (including family structures), and of choosing eQTLs to use. We also present some results regarding the design of experiments given consideration of these matters. The eQTL-based approach to identifying sample tracking errors is seen to be of value to these studies, but requiring care in its implementation.

Integrating heterogeneous high-throughput data for meta-dimensional pharmacogenomics and disease-related studies

The current paradigm of human genetics research is to analyze variation of a single data type (i.e., DNA sequence or RNA levels) to detect genes and pathways that underlie complex traits such as disease state or drug response. While these studies have detected thousands of variations that associate with hundreds of complex phenotypes, much of the estimated heritability, or trait variability due to genetic factors, remain unexplained. We may be able to account for a portion of the missing heritability if we incorporate a systems biology approach into these analyses. Rapid technological advances will make it possible for scientists to explore this hypothesis via the generation of high-throughput omics data - transcriptomic, proteomic and methylomic to name a few. Analyzing this 'meta-dimensional' data will require clever statistical techniques that allow for the integration of qualitative and quantitative predictor variables. For this article, we examine two major categories of approaches for integrated data analysis, give examples of their use in experimental and in silico datasets, and assess the limitations of each method.

Bioinformatic Resources of microRNA Sequences, Gene Targets, and Genetic Variation

Variation in quantitative gene expression has been observed in natural populations and associated with various complex traits/phenotypes such as risks for common diseases and drug response. MicroRNAs (miRNAs), a family of small, non-coding RNA molecules, have been demonstrated to be an important class of gene regulators that mostly downregulate gene expression at the post-transcriptional level. A comprehensive and reliable catalogue of miRNAs and miRNA gene targets is critical to understanding the gene regulatory networks. Though experimental approaches have been used to identify many miRNAs and their gene targets, due to cost and efficiency, currently miRNA and target identification still largely relies on computational algorithms. We reviewed several widely used bioinformatic resources of miRNA sequences and gene targets that take advantage of the unique characteristics of miRNA–mRNA interactions, experimental validation, as well as the integration of sequence-based evidence and microarray expression data. Furthermore, given the importance of miRNAs in regulating gene expression, elucidating expression quantitative trait loci involved with miRSNPs or miR-polymorphisms will help improve our understanding of complex traits. We reviewed the available resources of miRNA genetic variation, and the current progress (e.g., the 1000 Genomes Project) in detailing the genetic variation in miRNA-related single nucleotide polymorphisms (SNPs). We also provided our perspectives of the potential impact of next-generation sequencing on the research of miRNAs, gene targets, and miRSNPs. These bioinformatic resources may help interpret experimental and association study results, thus enhancing our knowledge of the dynamic gene regulatory networks and the physiological pathways for complex traits/phenotypes. Prospectively, these bioinformatic resources of miRNAs will need to address the challenges raised by the application of next-generation sequencing in miRNA research.

miRNA-mediated relationships between Cis-SNP genotypes and transcript intensities in lymphocyte cell lines

In metazoans, miRNAs regulate gene expression primarily through binding to target sites in the 3' UTRs (untranslated regions) of messenger RNAs (mRNAs). Cis-acting variants within, or close to, a gene are crucial in explaining the variability of gene expression measures. Single nucleotide polymorphisms (SNPs) in the 3' UTRs of genes can affect the base-pairing between miRNAs and mRNAs, and hence disrupt existing target sites (in the reference sequence) or create novel target sites, suggesting a possible mechanism for cis regulation of gene expression. Moreover, because the alleles of different SNPs within a DNA sequence of limited length tend to be in strong linkage disequilibrium (LD), we hypothesize the variants of miRNA target sites caused by SNPs potentially function as bridges linking the documented cis-SNP markers to the expression of the associated genes. A large-scale analysis was herein performed to test this hypothesis. By systematically integrating multiple latest information sources, we found 21 significant gene-level SNP-involved miRNA-mediated post-transcriptional regulation modules (SNP-MPRMs) in the form of SNP-miRNA-mRNA triplets in lymphocyte cell lines for the CEU and YRI populations. Among the cognate genes, six including ALG8, DGKE, GNA12, KLF11, LRPAP1, and MMAB are related to multiple genetic diseases such as depressive disorder and Type-II diabetes. Furthermore, we found that ~35% of the documented transcript intensity-related cis-SNPs (~950) in a recent publication are identical to, or in significant linkage disequilibrium (LD) (p<0.01) with, one or multiple SNPs located in miRNA target sites. Based on these associations (or identities), 69 significant exon-level SNP-MPRMs and 12 disease genes were further determined for two populations. These results provide concrete in silico evidence for the proposed hypothesis. The discovered modules warrant additional follow-up in independent laboratory studies.

Estimation of alternative splicing variability in human populations

DNA arrays have been widely used to perform transcriptome-wide analysis of gene expression, and many methods have been developed to measure gene expression variability and to compare gene expression between conditions. Because RNA-seq is also becoming increasingly popular for transcriptome characterization, the possibility exists for further quantification of individual alternative transcript isoforms, and therefore for estimating the relative ratios of alternative splice forms within a given gene. Changes in splicing ratios, even without changes in overall gene expression, may have important phenotypic effects. Here we have developed statistical methodology to measure variability in splicing ratios within conditions, to compare it between conditions, and to identify genes with condition-specific splicing ratios. Furthermore, we have developed methodology to deconvolute the relative contribution of variability in gene expression versus variability in splicing ratios to the overall variability of transcript abundances. As a proof of concept, we have applied this methodology to estimates of transcript abundances obtained from RNA-seq experiments in lymphoblastoid cells from Caucasian and Yoruban individuals. We have found that protein-coding genes exhibit low splicing variability within populations, with many genes exhibiting constant ratios across individuals. When comparing these two populations, we have found that up to 10% of the studied protein-coding genes exhibit population-specific splicing ratios. We estimate that ~60% of the total variability observed in the abundance of transcript isoforms can be explained by variability in transcription. A large fraction of the remaining variability can likely result from variability in splicing. Finally, we also detected that variability in splicing is uncommon without variability in transcription.

Genetic variation of pre-mRNA alternative splicing in human populations

The precise splicing outcome of a transcribed gene is controlled by complex interactions between cis regulatory splicing signals and trans-acting regulators. In higher eukaryotes, alternative splicing is a prevalent mechanism for generating transcriptome and proteome diversity. Alternative splicing can modulate gene function, affect organismal phenotype and cause disease. Common genetic variation that affects splicing regulation can lead to differences in alternative splicing between human individuals and consequently impact expression level or protein function. In several well-documented examples, such natural variation of alternative splicing has indeed been shown to influence disease susceptibility and drug response. With new microarray and sequencing-based genomic technologies that can analyze eukaryotic transcriptomes at the exon or nucleotide level, it has become possible to globally compare the alternative splicing profiles across human individuals in any tissue or cell type of interest. Recent large-scale transcriptome studies using high-density splicing-sensitive microarray and deep RNA sequencing (RNA-Seq) have revealed widespread genetic variation of alternative splicing in humans. In the future, an extensive catalog of alternative splicing variation in human populations will help elucidate the molecular underpinnings of complex traits and human diseases, and shed light on the mechanisms of splicing regulation in human cells.

GALC deletions increase the risk of primary open-angle glaucoma: the role of Mendelian variants in complex disease

DNA copy number variants (CNVs) have been reported in many human diseases including autism and schizophrenia. Primary Open Angle Glaucoma (POAG) is a complex adult-onset disorder characterized by progressive optic neuropathy and vision loss. Previous studies have identified rare CNVs in POAG; however, their low frequencies prevented formal association testing. We present here the association between POAG risk and a heterozygous deletion in the galactosylceramidase gene (GALC). This CNV was initially identified in a dataset containing 71 Caucasian POAG cases and 478 ethnically matched controls obtained from dbGAP (study accession phs000126.v1.p1.) (p = 0.017, fisher's exact test). It was validated with array comparative genomic hybridization (arrayCGH) and realtime PCR, and replicated in an independent POAG dataset containing 959 cases and 1852 controls (p = 0.021, OR (odds ratio) = 3.5, 95% CI -1.1-12.0). Evidence for association was strengthened when the discovery and replication datasets were combined (p = 0.002; OR = 5.0, 95% CI 1.6-16.4). Several deletions with different endpoints were identified by array CGH of POAG patients. Homozygous deletions that eliminate GALC enzymatic activity cause Krabbe disease, a recessive Mendelian disorder of childhood displaying bilateral optic neuropathy and vision loss. Our findings suggest that heterozygous deletions that reduce GALC activity are a novel mechanism increasing risk of POAG. This is the first report of a statistically-significant association of a CNV with POAG risk, contributing to a growing body of evidence that CNVs play an important role in complex, inherited disorders. Our findings suggest an attractive biomarker and potential therapeutic target for patients with this form of POAG.

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.

MixupMapper: correcting sample mix-ups in genome-wide datasets increases power to detect small genetic effects

MOTIVATION

Sample mix-ups can arise during sample collection, handling, genotyping or data management. It is unclear how often sample mix-ups occur in genome-wide studies, as there currently are no post hoc methods that can identify these mix-ups in unrelated samples. We have therefore developed an algorithm (MixupMapper) that can both detect and correct sample mix-ups in genome-wide studies that study gene expression levels.

RESULTS

We applied MixupMapper to five publicly available human genetical genomics datasets. On average, 3% of all analyzed samples had been assigned incorrect expression phenotypes: in one of the datasets 23% of the samples had incorrect expression phenotypes. The consequences of sample mix-ups are substantial: when we corrected these sample mix-ups, we identified on average 15% more significant cis-expression quantitative trait loci (cis-eQTLs). In one dataset, we identified three times as many significant cis-eQTLs after correction. Furthermore, we show through simulations that sample mix-ups can lead to an underestimation of the explained heritability of complex traits in genome-wide association datasets.

AVAILABILITY AND IMPLEMENTATION

MixupMapper is freely available at http://www.genenetwork.nl/mixupmapper/

The use of genomic information to optimize cancer chemotherapy

The field of pharmacogenomics is focused on the characterization of genetic factors contributing to the response of patients to pharmacological interventions. Drug response and toxicity are complex traits; therefore the effects are likely influenced by multiple genes. The investigation of the genetic basis of drug response has evolved from a focus on single genes to relevant pathways to the entire genome. Preclinical (cell-based models) and clinical genome-wide association studies (GWAS) in oncology provide an unprecedented opportunity for a comprehensive and unbiased assessment of the heritable factors associated with drug response. The primary challenge with attempting to identify pharmacogenomic markers from clinical studies is that they require a homogeneous population of patients treated with the same dosage regimen and minimal confounding variables. Therefore, the development of cell-based models for pharmacogenomic marker identification has utility for the field since performing these types of studies in humans is difficult and costly. This review intends to provide a current report on the status of genomic studies in oncology, the methods for discovery, and implications for patient care. We present a perspective and summary of the challenges and opportunities in translating heritable genomic discoveries to patients.

Gene expression and genetic variation data implicate PCLO in bipolar disorder

BACKGROUND

Genetic variation may contribute to differential gene expression in the brain of individuals with psychiatric disorders. To test this hypothesis, we identified genes that were differentially expressed in individuals with bipolar disorder, along with nearby single nucleotide polymorphisms (SNPs) that were associated with expression of the same genes. We then tested these SNPs for association with bipolar disorder in large case-control samples.

METHODS

We used the Stanley Genomics Database to extract gene expression and SNP microarray data from individuals with bipolar disorder (n = 40) and unaffected controls (n = 43). We identified 367 genes that were differentially expressed in the prefrontal cortex of cases vs. controls (fold change > 1.3 and FDR q-value < .05) and 45 nearby SNPs that were associated with expression of those same genes (FDR q-value < .05). We tested these SNPs for association with bipolar disorder in a meta-analysis of genome-wide association studies (GWAS) including 4,936 cases and 6,654 healthy controls.

RESULTS

We identified 45 SNPs that were associated with expression of differentially expressed genes, including HBS1L (15 SNPs), HLA-DPB1 (15 SNPs), AMFR (8 SNPs), PCLO (2 SNPs) and WDR41 (2 SNPs). Of these, one SNP (rs13438494), in an intron of the piccolo (PCLO) gene, was significantly associated with bipolar disorder (FDR adjusted p < .05) in the meta-analysis of GWAS.

CONCLUSIONS

These results support the previous findings implicating PCLO in mood disorders and demonstrate the utility of combining gene expression and genetic variation data to improve our understanding of the genetic contribution to bipolar disorder.

A study of CNVs as trait-associated polymorphisms and as expression quantitative trait loci

We conducted a comprehensive study of copy number variants (CNVs) well-tagged by SNPs (r(2)≥ 0.8) by analyzing their effect on gene expression and their association with disease susceptibility and other complex human traits. We tested whether these CNVs were more likely to be functional than frequency-matched SNPs as trait-associated loci or as expression quantitative trait loci (eQTLs) influencing phenotype by altering gene regulation. Our study found that CNV-tagging SNPs are significantly enriched for cis eQTLs; furthermore, we observed that trait associations from the NHGRI catalog show an overrepresentation of SNPs tagging CNVs relative to frequency-matched SNPs. We found that these SNPs tagging CNVs are more likely to affect multiple expression traits than frequency-matched variants. Given these findings on the functional relevance of CNVs, we created an online resource of expression-associated CNVs (eCNVs) using the most comprehensive population-based map of CNVs to inform future studies of complex traits. Although previous studies of common CNVs that can be typed on existing platforms and/or interrogated by SNPs in genome-wide association studies concluded that such CNVs appear unlikely to have a major role in the genetic basis of several complex diseases examined, our findings indicate that it would be premature to dismiss the possibility that even common CNVs may contribute to complex phenotypes and at least some common diseases.

Statistical Modeling of RNA-Seq Data

Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest. This paper introduces a statistical model for estimating isoform abundance from RNA-Seq data and is flexible enough to accommodate both single end and paired end RNA-Seq data and sampling bias along the length of the transcript. Based on the derivation of minimal sufficient statistics for the model, a computationally feasible implementation of the maximum likelihood estimator of the model is provided. Further, it is shown that using paired end RNA-Seq provides more accurate isoform abundance estimates than single end sequencing at fixed sequencing depth. Simulation studies are also given.

Constant splice-isoform ratios in human lymphoblastoid cells support the concept of a splico-stat

Splicing generates mature transcripts from genes in pieces in eukaryotic cells. Overwhelming evidence has accumulated that alternative routes in splicing are possible for most human and mammalian genes, thereby allowing formation of different transcripts from one gene. No function has been assigned to the majority of identified alternative splice forms, and it has been assumed that they compose inert or tolerated waste from aberrant or noisy splicing. Here we demonstrate that five human transcription units (WT1, NOD2, GNAS, RABL2A, RABL2B) have constant splice-isoform ratios in genetically diverse lymphoblastoid cell lines independent of the type of alternative splicing (exon skipping, alternative donor/acceptor, tandem splice sites) and gene expression level. Even splice events that create premature stop codons and potentially trigger nonsense-mediated mRNA decay are found at constant fractions. The analyzed alternative splicing events were qualitatively but not quantitatively conserved in corresponding chimpanzee cell lines. Additionally, subtle splicing at tandem acceptor splice sites (GNAS, RABL2A/B) was highly constrained and strongly depends on the upstream donor sequence content. These results also demonstrate that unusual and unproductive splice variants are produced in a regulated manner.

Context-dependent robustness to 5' splice site polymorphisms in human populations

There has been growing evidence for extensive diversity of alternative splicing in human populations. Genetic variants within the 5' splice site can cause splicing differences among human individuals and constitute an important class of human disease mutations. In this study, we explored whether natural variations of splicing could reveal important signals of 5' splice site recognition. In seven lymphoblastoid cell lines of Asian, European and African ancestry, we identified 1174 single nucleotide polymorphisms (SNPs) within the consensus 5' splice site. We selected 129 SNPs predicted to significantly alter the splice site activity, and quantitatively examined their splicing impact in the seven individuals. Surprisingly, outside of the essential GT dinucleotide position, only ∼14% of the tested SNPs altered splicing. Bioinformatic and minigene analyses identified signals that could modify the impact of 5' splice site polymorphisms, most notably a strong 3' splice site and the presence of intronic motifs downstream of the 5' splice site. Strikingly, we found that the poly-G run, a known intronic splicing enhancer, was the most significantly enriched motif downstream of exons unaffected by 5' splice site SNPs. In TRIM62, the upstream 3' splice site and downstream intronic poly-G runs functioned redundantly to protect an exon from its 5' splice site polymorphism. Collectively, our study reveals widespread context-dependent robustness to 5' splice site polymorphisms in human transcriptomes. Consequently, certain exons are more susceptible to 5' splice site mutations. Additionally, our work demonstrates that genetic diversity of alternative splicing can provide significant insights into the splicing code of mammalian cells.

Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts

MicroRNAs (miRNAs) are regulatory noncoding RNAs that affect the production of a significant fraction of human mRNAs via post-transcriptional regulation. Interindividual variation of the miRNA expression levels is likely to influence the expression of miRNA target genes and may therefore contribute to phenotypic differences in humans, including susceptibility to common disorders. The extent to which miRNA levels are genetically controlled is largely unknown. In this report, we assayed the expression levels of miRNAs in primary fibroblasts from 180 European newborns of the GenCord project and performed association analysis to identify eQTLs (expression quantitative traits loci). We detected robust expression for 121 miRNAs out of 365 interrogated. We have identified significant cis- (10%) and trans- (11%) eQTLs. Furthermore, we detected one genomic locus (rs1522653) that influences the expression levels of five miRNAs, thus unraveling a novel mechanism for coregulation of miRNA expression.