Exonic enhancers: proceed with caution in exome and genome sequencing studies

A systematic strategy for identifying causal single nucleotide polymorphisms and their target genes on Juvenile arthritis risk haplotypes

BACKGROUND

Although genome-wide association studies (GWAS) have identified multiple regions conferring genetic risk for juvenile idiopathic arthritis (JIA), we are still faced with the task of identifying the single nucleotide polymorphisms (SNPs) on the disease haplotypes that exert the biological effects that confer risk. Until we identify the risk-driving variants, identifying the genes influenced by these variants, and therefore translating genetic information to improved clinical care, will remain an insurmountable task. We used a function-based approach for identifying causal variant candidates and the target genes on JIA risk haplotypes.

METHODS

We used a massively parallel reporter assay (MPRA) in myeloid K562 cells to query the effects of 5,226 SNPs in non-coding regions on JIA risk haplotypes for their ability to alter gene expression when compared to the common allele. The assay relies on 180 bp oligonucleotide reporters ("oligos") in which the allele of interest is flanked by its cognate genomic sequence. Barcodes were added randomly by PCR to each oligo to achieve > 20 barcodes per oligo to provide a quantitative read-out of gene expression for each allele. Assays were performed in both unstimulated K562 cells and cells stimulated overnight with interferon gamma (IFNg). As proof of concept, we then used CRISPRi to demonstrate the feasibility of identifying the genes regulated by enhancers harboring expression-altering SNPs.

RESULTS

We identified 553 expression-altering SNPs in unstimulated K562 cells and an additional 490 in cells stimulated with IFNg. We further filtered the SNPs to identify those plausibly situated within functional chromatin, using open chromatin and H3K27ac ChIPseq peaks in unstimulated cells and open chromatin plus H3K4me1 in stimulated cells. These procedures yielded 42 unique SNPs (total = 84) for each set. Using CRISPRi, we demonstrated that enhancers harboring MPRA-screened variants in the TRAF1 and LNPEP/ERAP2 loci regulated multiple genes, suggesting complex influences of disease-driving variants.

CONCLUSION

Using MPRA and CRISPRi, JIA risk haplotypes can be queried to identify plausible candidates for disease-driving variants. Once these candidate variants are identified, target genes can be identified using CRISPRi informed by the 3D chromatin structures that encompass the risk haplotypes.

Integrative regulation of hLMR1 by dietary and genetic factors in nonalcoholic fatty liver disease and hyperlipidemia

Long non-coding RNA (lncRNA) genes represent a large class of transcripts that are widely expressed across species. As most human lncRNAs are non-conserved, we recently employed a unique humanized liver mouse model to study lncRNAs expressed in human livers. We identified a human hepatocyte-specific lncRNA, hLMR1 (human lncRNA metabolic regulator 1), which is induced by feeding and promotes hepatic cholesterol synthesis. Recent genome-wide association studies (GWAS) found that several single-nucleotide polymorphisms (SNPs) from the hLMR1 gene locus are associated with blood lipids and markers of liver damage. These results suggest that dietary and genetic factors may regulate hLMR1 to affect disease progression. In this study, we first screened for nutritional/hormonal factors and found that hLMR1 was robustly induced by insulin/glucose in cultured human hepatocytes, and this induction is dependent on the transcription factor SREBP1. We then tested if GWAS SNPs genetically linked to hLMR1 could regulate hLMR1 expression. We found that DNA sequences flanking rs9653945, a SNP from the last exon of the hLMR1 gene, functions as an enhancer that can be robustly activated by SREBP1c depending on the presence of rs9653945 major allele (G). We further performed CRISPR base editing in human HepG2 cells and found that rs9653945 major (G) to minor (A) allele modification resulted in blunted insulin/glucose-induced expression of hLMR1. Finally, we performed genotyping and gene expression analyses using a published human NAFLD RNA-seq dataset and found that individuals homozygous for rs9653945-G have a higher expression of hLMR1 and risk of NAFLD. Taken together, our data support a model that rs9653945-G predisposes individuals to insulin/glucose-induced hLMR1, contributing to the development of hyperlipidemia and NAFLD.

Evolution of a Human-Specific De Novo Open Reading Frame and Its Linked Transcriptional Silencer

In the human genome, two short open reading frames (ORFs) separated by a transcriptional silencer and a small intervening sequence stem from the gene SMIM45. The two ORFs show different translational characteristics, and they also show divergent patterns of evolutionary development. The studies presented here describe the evolution of the components of SMIM45. One ORF consists of an ultra-conserved 68 amino acid (aa) sequence, whose origins can be traced beyond the evolutionary age of divergence of the elephant shark, ~462 MYA. The silencer also has ancient origins, but it has a complex and divergent pattern of evolutionary formation, as it overlaps both at the 68 aa ORF and the intervening sequence. The other ORF consists of 107 aa. It develops during primate evolution but is found to originate de novo from an ancestral non-coding genomic region with root origins within the Afrothere clade of placental mammals, whose evolutionary age of divergence is ~99 MYA. The formation of the complete 107 aa ORF during primate evolution is outlined, whereby sequence development is found to occur through biased mutations, with disruptive random mutations that also occur but lead to a dead-end. The 107 aa ORF is of particular significance, as there is evidence to suggest it is a protein that may function in human brain development. Its evolutionary formation presents a view of a human-specific ORF and its linked silencer that were predetermined in non-primate ancestral species. The genomic position of the silencer offers interesting possibilities for the regulation of transcription of the 107 aa ORF. A hypothesis is presented with respect to possible spatiotemporal expression of the 107 aa ORF in embryonic tissues.

Analysis of the landscape of human enhancer sequences in biological databases

The process of gene regulation extends as a network in which both genetic sequences and proteins are involved. The levels of regulation and the mechanisms involved are multiple. Transcription is the main control mechanism for most genes, being the downstream steps responsible for refining the transcription patterns. In turn, gene transcription is mainly controlled by regulatory events that occur at promoters and enhancers. Several studies are focused on analyzing the contribution of enhancers in the development of diseases and their possible use as therapeutic targets. The study of regulatory elements has advanced rapidly in recent years with the development and use of next generation sequencing techniques. All this information has generated a large volume of information that has been transferred to a growing number of public repositories that store this information. In this article, we analyze the content of those public repositories that contain information about human enhancers with the aim of detecting whether the knowledge generated by scientific research is contained in those databases in a way that could be computationally exploited. The analysis will be based on three main aspects identified in the literature: types of enhancers, type of evidence about the enhancers, and methods for detecting enhancer-promoter interactions. Our results show that no single database facilitates the optimal exploitation of enhancer data, most types of enhancers are not represented in the databases and there is need for a standardized model for enhancers. We have identified major gaps and challenges for the computational exploitation of enhancer data.

RefSeq Functional Elements as experimentally assayed nongenic reference standards and functional interactions in human and mouse

Eukaryotic genomes contain many nongenic elements that function in gene regulation, chromosome organization, recombination, repair, or replication, and mutation of those elements can affect genome function and cause disease. Although numerous epigenomic studies provide high coverage of gene regulatory regions, those data are not usually exposed in traditional genome annotation and can be difficult to access and interpret without field-specific expertise. The National Center for Biotechnology Information (NCBI) therefore provides RefSeq Functional Elements (RefSeqFEs), which represent experimentally validated human and mouse nongenic elements derived from the literature. The curated data set is comprised of richly annotated sequence records, descriptive records in the NCBI Gene database, reference genome feature annotation, and activity-based interactions between nongenic regions, target genes, and each other. The data set provides succinct functional details and transparent experimental evidence, leverages data from multiple experimental sources, is readily accessible and adaptable, and uses a flexible data model. The data have multiple uses for basic functional discovery, bioinformatics studies, genetic variant interpretation; as known positive controls for epigenomic data evaluation; and as reference standards for functional interactions. Comparisons to other gene regulatory data sets show that the RefSeqFE data set includes a wider range of feature types representing more areas of biology, but it is comparatively smaller and subject to data selection biases. RefSeqFEs thus provide an alternative and complementary resource for experimentally assayed functional elements, with future data set growth expected.

Epigenetic landscapes of intracranial aneurysm risk haplotypes implicate enhancer function of endothelial cells and fibroblasts in dysregulated gene expression

BACKGROUND

Genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with increased risk for intracranial aneurysm (IA). However, how such variants affect gene expression within IA is poorly understood. We used publicly-available ChIP-Seq data to study chromatin landscapes surrounding risk loci to determine whether IA-associated SNPs affect functional elements that regulate gene expression in cell types comprising IA tissue.

METHODS

We mapped 16 significant IA-associated SNPs to linkage disequilibrium (LD) blocks within human genome. Using ChIP-Seq data, we examined these regions for presence of H3K4me1, H3K27ac, and H3K9ac histone marks (typically associated with latent/active enhancers). This analysis was conducted in several cell types that are present in IA tissue (endothelial cells, smooth muscle cells, fibroblasts, macrophages, monocytes, neutrophils, T cells, B cells, NK cells). In cell types with significant histone enrichment, we used HiC data to investigate topologically associated domains (TADs) encompassing the LD blocks to identify genes that may be affected by IA-associated variants. Bioinformatics were performed to determine the biological significance of these genes. Genes within HiC-defined TADs were also compared to differentially expressed genes from RNA-seq/microarray studies of IA tissues.

RESULTS

We found that endothelial cells and fibroblasts, rather than smooth muscle or immune cells, have significant enrichment for enhancer marks on IA risk haplotypes (p < 0.05). Bioinformatics demonstrated that genes within TADs subsuming these regions are associated with structural extracellular matrix components and enzymatic activity. The majority of histone marked TADs (83% fibroblasts [IMR90], 77% HUVEC) encompassed at least one differentially expressed gene from IA tissue studies.

CONCLUSIONS

These findings provide evidence that genetic variants associated with IA risk act on endothelial cells and fibroblasts. There is strong circumstantial evidence that this may be mediated through altered enhancer function, as genes in TADs encompassing enhancer marks have also been shown to be differentially expressed in IA tissue. These genes are largely related to organization and regulation of the extracellular matrix. This study builds upon our previous (Poppenberg et al., BMC Med Genomics, 2019) by including a more diverse set of data from additional cell types and by identifying potential affected genes (i.e. those in TADs).

Contribution of coding/non-coding variants in NUS1 to late-onset sporadic Parkinson's disease

INTRODUCTION

A recent study reported that rare variants in NUS1 were associated with Parkinson's disease (PD). We aimed to assess the relative contribution of rare and common coding/non-coding variants of NUS1 to late-onset PD patients (LOPD).

METHODS

Whole genome sequencing data were analyzed for target NUS1 regions, derived from a cohort of 1962 cases and 1279 controls. The genetic association analyses were performed using logistic regression analysis and Sequence Kernel association test. Expression quantitative trait loci (eQTL) analysis was conducted to further explore the association of variants with NUS1 expression based on the data from GTEx database.

RESULTS

We identified 18 rare coding variants. p.Y131C was first identified in LOPD. However, no significant burden of rare NUS1 coding variants in LOPD was found. The rare variant sets of two regulatory elements (GH06J117605 and GH06J117674) were significantly enriched in LOPD even after Bonferroni correction (adjusted P = 0.013; adjusted P = 0.010). Considering the joint effect of rare and common variants, all variant sets within GH06J117605 and GH06J117674 showed association with LOPD but were no longer significant after Bonferroni correction. None of the common variants within coding/non-coding regions were significant after Bonferroni correction. The eQTL results suggested these variants in GH06J117605 and GH06J117674 could potentially have eQTL effects on the brain tissues.

CONCLUSIONS

These findings provide novel insight into the role of NUS1 regulatory regions in the development of LOPD and indicate that the variants in regulatory elements of NUS1 may be associated with LOPD by influencing the gene expression level.

A Deep Learning Framework Identifies Pathogenic Noncoding Somatic Mutations from Personal Prostate Cancer Genomes

Our understanding of noncoding mutations in cancer genomes has been derived primarily from mutational recurrence analysis by aggregating clinical samples on a large scale. These cohort-based approaches cannot directly identify individual pathogenic noncoding mutations from personal cancer genomes. Therefore, although most somatic mutations are localized in the noncoding cancer genome, their effects on driving tumorigenesis and progression have not been systematically explored and noncoding somatic alleles have not been leveraged in current clinical practice to guide personalized screening, diagnosis, and treatment. Here, we present a deep learning framework to capture pathogenic noncoding mutations in personal cancer genomes, which perturb gene regulation by altering chromatin architecture. We deployed the system specifically for localized prostate cancer by integrating large-scale prostate cancer genomes and the prostate-specific epigenome. We exhaustively evaluated somatic mutations in each patient's genome and agnostically identified thousands of somatic alleles altering the prostate epigenome. Functional genomic analyses subsequently demonstrated that affected genes displayed differential expression in prostate tumor samples, were vulnerable to expression alterations, and were convergent onto androgen receptor-mediated signaling pathways. Accumulation of pathogenic regulatory mutations in these affected genes was predictive of clinical observations, suggesting potential clinical utility of this approach. Overall, the deep learning framework has significantly expanded our view of somatic mutations in the vast noncoding genome, uncovered novel genes in localized prostate cancer, and will foster the development of personalized screening and therapeutic strategies for prostate cancer. SIGNIFICANCE: This study's characterization of the noncoding genome in prostate cancer reveals mutational signatures predictive of clinical observations, which may serve as a powerful prognostic tool in this disease.

Epigenetic landscapes suggest that genetic risk for intracranial aneurysm operates on the endothelium

BACKGROUND

Genetics play an important role in intracranial aneurysm (IA) pathophysiology. Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are linked to IA but how they affect disease pathobiology remains poorly understood. We used Encyclopedia of DNA Elements (ENCODE) data to investigate the epigenetic landscapes surrounding genetic risk loci to determine if IA-associated SNPs affect functional elements that regulate gene expression and if those SNPs are most likely to impact a specific type of cells.

METHODS

We mapped 16 highly significant IA-associated SNPs to linkage disequilibrium (LD) blocks within the human genome. Within these regions, we examined the presence of H3K4me1 and H3K27ac histone marks and CCCTC-binding factor (CTCF) and transcription-factor binding sites using chromatin immunoprecipitation-sequencing (ChIP-Seq) data. This analysis was conducted in several cell types relevant to endothelial (human umbilical vein endothelial cells [HUVECs]) and inflammatory (monocytes, neutrophils, and peripheral blood mononuclear cells [PBMCs]) biology. Gene ontology analysis was performed on genes within extended IA-risk regions to understand which biological processes could be affected by IA-risk SNPs. We also evaluated recently published data that showed differential methylation and differential ribonucleic acid (RNA) expression in IA to investigate the correlation between differentially regulated elements and the IA-risk LD blocks.

RESULTS

The IA-associated LD blocks were statistically significantly enriched for H3K4me1 and/or H3K27ac marks (markers of enhancer function) in endothelial cells but not in immune cells. The IA-associated LD blocks also contained more binding sites for CTCF in endothelial cells than monocytes, although not statistically significant. Differentially methylated regions of DNA identified in IA tissue were also present in several IA-risk LD blocks, suggesting SNPs could affect this epigenetic machinery. Gene ontology analysis supports that genes affected by IA-risk SNPs are associated with extracellular matrix reorganization and endopeptidase activity.

CONCLUSION

These findings suggest that known genetic alterations linked to IA risk act on endothelial cell function. These alterations do not correlate with IA-associated gene expression signatures of circulating blood cells, which suggests that such signatures are a secondary response reflecting the presence of IA rather than indicating risk for IA.

An intron-derived motif strongly increases gene expression from transcribed sequences through a splicing independent mechanism in Arabidopsis thaliana

Certain introns significantly increase mRNA accumulation by a poorly understood mechanism. These introns have no effect when located upstream, or more than ~1 Kb downstream, of the start of transcription. We tested the ability of a formerly non-stimulating intron containing 11 copies of the sequence TTNGATYTG, which is over-represented in promoter-proximal introns in Arabidopsis thaliana, to affect expression from various positions. The activity profile of this intron at different locations was similar to that of a natural intron from the UBQ10 gene, suggesting that the motif increases mRNA accumulation by the same mechanism. A series of introns with different numbers of this motif revealed that the effect on expression is linearly dependent on motif copy number up to at least 20, with each copy adding another 1.5-fold increase in mRNA accumulation. Furthermore, 6 copies of the motif stimulated mRNA accumulation to a similar degree from within an intron or when introduced into the 5'-UTR and coding sequences of an intronless construct, demonstrating that splicing is not required for this sequence to boost expression. The ability of this motif to substantially elevate expression from several hundred nucleotides downstream of the transcription start site reveals a novel type of eukaryotic gene regulation.

CRISPR/Cas9 mediated mutation of mouse IL-1α nuclear localisation sequence abolishes expression

Inflammation is a host defense process against infection. Inflammatory mediators include cytokines of the interleukin-1 family, such as IL-1α and IL-1β. Unlike IL-1β, IL-1α carries an N-terminal nuclear localisation sequence (NLS) and is trafficked to the nucleus. The importance of IL-1α nuclear localisation is poorly understood. Here, we used CRISPR/Cas9 to make inactivating mutations to the NLS on the Il1a gene. A colony of NLS mutant mice was successfully generated with precise knock-in mutations to incapacitate NLS function. NLS mutant mice had no gross changes in immunophenotype or inflammatory response but, surprisingly, failed to express IL-1α. We deduced that, in making specific mutations in the Il1a gene, we also mutated a long-noncoding (lnc)RNA in the complementary strand which has cis-regulatory transcriptional control of the Il1a gene itself. The mutations generated in the Il1a gene also result in mutation of the lncRNA sequence and a predicted alteration of its secondary structure, potentially explaining a subsequent failure to function as a transcriptional activator of Il1a expression. Thus, lncRNA secondary structure may regulate IL-1α expression. Our results serve as a cautionary note that CRISPR -mediated genome editing without full knowledge of genomic context can result in unexpected, yet potentially informative observations.

Chromatin landscapes and genetic risk for juvenile idiopathic arthritis

Background

The transcriptomes of peripheral blood cells in children with juvenile idiopathic arthritis (JIA) have distinct transcriptional aberrations that suggest impairment of transcriptional regulation. To gain a better understanding of this phenomenon, we studied known JIA genetic risk loci, the majority of which are located in non-coding regions, where transcription is regulated and coordinated on a genome-wide basis. We examined human neutrophils and CD4 primary T cells to identify genes and functional elements located within those risk loci.

Methods

We analyzed RNA sequencing (RNA-Seq) data, H3K27ac and H3K4me1 chromatin immunoprecipitation-sequencing (ChIP-Seq) data, and previously published chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) data to characterize the chromatin landscapes within the known JIA-associated risk loci.

Results

In both neutrophils and primary CD4+ T cells, the majority of the JIA-associated linkage disequilibrium (LD) blocks contained H3K27ac and/or H3K4me1 marks. These LD blocks were also binding sites for a small group of transcription factors, particularly in neutrophils. Furthermore, these regions showed abundant intronic and intergenic transcription in neutrophils. In neutrophils, none of the genes that were differentially expressed between untreated patients with JIA and healthy children were located within the JIA-risk LD blocks. In CD4+ T cells, multiple genes, including HLA-DQA1, HLA-DQB2, TRAF1, and IRF1 were associated with the long-distance interacting regions within the LD regions as determined from ChIA-PET data.

Conclusions

These findings suggest that genetic risk contributes to the aberrant transcriptional control observed in JIA. Furthermore, these findings demonstrate the challenges of identifying the actual causal variants within complex genomic/chromatin landscapes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-017-1260-x) contains supplementary material, which is available to authorized users.

Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

We report a chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the amine/phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with sham operation, OA control group, and OA rats with treatment, separately, using glucosamine/Celecoxib and three traditional Chinese medicines (Epimedii folium, Chuanxiong Rhizoma and Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including 2-aminoadipic acid, saccharopine and GABA were selected as potential biomarkers of OA progression and OA treatment. This study illustrates that CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying disease progression and treatment in animal models.