Heritable individual-specific and allele-specific chromatin signatures in humans

Statistical framework for calling allelic imbalance in high-throughput sequencing data

High-throughput sequencing facilitates large-scale studies of gene regulation and allows tracing the associations of individual genomic variants with changes in gene regulation and expression. Compared to classic association studies, the assessment of an allelic imbalance at heterozygous variants captures functional variant effects with smaller sample sizes, higher sensitivity, and better resolution. Yet, identification of allele-specific variants from allelic read counts remains challenging due to data-dependent biases and overdispersion arising from technical and biological variability. We present MIXALIME, a novel computational framework for calling allele-specific variants in diverse omics data with a repertoire of statistical models accounting for read mapping bias and copy number variation. We benchmark MIXALIME with DNase-Seq, ATAC-Seq, and CAGE-Seq data, and we demonstrate that the allelic imbalance highlights causal variants in GWAS results. Finally, as a showcase of the large-scale practical application of MIXALIME, we present an atlas of variants exhibiting allele-specific chromatin accessibility, built from thousands of available datasets obtained from diverse cell types.

Benchmarking and building DNA binding affinity models using allele-specific and allele-agnostic transcription factor binding data

BACKGROUND

Transcription factors (TFs) bind to DNA in a highly sequence-specific manner. This specificity manifests itself in vivo as differences in TF occupancy between the two alleles at heterozygous loci. Genome-scale assays such as ChIP-seq currently are limited in their power to detect allele-specific binding (ASB) both in terms of read coverage and representation of individual variants in the cell lines used. This makes prediction of allelic differences in TF binding from sequence alone desirable, provided that the reliability of such predictions can be quantitatively assessed.

RESULTS

We here propose methods for benchmarking sequence-to-affinity models for TF binding in terms of their ability to predict allelic imbalances in ChIP-seq counts. We use a likelihood function based on an over-dispersed binomial distribution to aggregate evidence for allelic preference across the genome without requiring statistical significance for individual variants. This allows us to systematically compare predictive performance when multiple binding models for the same TF are available. To facilitate the de novo inference of high-quality models from paired-end in vivo binding data such as ChIP-seq, ChIP-exo, and CUT&Tag without read mapping or peak calling, we introduce an extensible reimplementation of our biophysically interpretable machine learning framework named PyProBound. Explicitly accounting for assay-specific bias in DNA fragmentation rate when training on ChIP-seq yields improved TF binding models. Moreover, we show how PyProBound can leverage our threshold-free ASB likelihood function to perform de novo motif discovery using allele-specific ChIP-seq counts.

CONCLUSION

Our work provides new strategies for predicting the functional impact of non-coding variants.

CCAAT Promoter element regulates transgenerational expression of the MHC class I gene

Transgenerational gene expression depends on both underlying DNA sequences and epigenetic modifications. The latter, which can result in transmission of variegated gene expression patterns across multiple generations without DNA alterations, has been termed epigenetic inheritance and has been documented in plants, worms, flies and mammals. Whereas transcription factors binding to cognate DNA sequence elements regulate gene expression, the molecular basis for epigenetic inheritance has been linked to histone and DNA modifications and non-coding RNA. Here we report that mutation of the CCAAT box promoter element abrogates NF-Y binding and disrupts the stable transgenerational expression of an MHC class I transgene. Transgenic mice with a mutated CCAAT box in the MHC class I transgene display variegated expression of the transgene among littermates and progeny in multiple independently derived transgenic lines. After 4 generations, CCAAT mutant transgenic lines derived from a single founder stably displayed distinct patterns of expression. Histone modifications and RNA polymerase II binding correlate with expression of CCAAT mutant transgenic lines, whereas DNA methylation and nucleosome occupancy do not. Mutation of the CCAAT box also results in changes to CTCF binding and DNA looping patterns across the transgene that correlate with expression status. These studies identify the CCAAT promoter element as a regulator of stable transgenerational gene expression such that mutation of the CCAAT box results in variegated transgenerational inheritance. Considering that the CCAAT box is present in 30% of eukaryotic promoters, this study provides insights into how fidelity of gene expression patterns is maintained through multiple generations.

The GWAS SNP rs80207740 modulates erythrocyte traits via allele-specific binding of IKZF1 and targeting XPO7 gene

Genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with erythrocyte traits. However, the functional variants and their working mechanisms remain largely unknown. Here, we reported that the SNP of rs80207740, which was associated with red blood cell (RBC) volume and hemoglobin content across populations, conferred enhancer activity to XPO7 gene via allele-differentially binding to Ikaros family zinc finger 1 (IKZF1). We showed that the region around rs80207740 was an erythroid-specific enhancer using reporter assays, and that the G-allele further enhanced activity. 3D genome evidence showed that the enhancer interacted with the XPO7 promoter, and eQTL analysis suggested that the G-allele upregulated expression of XPO7. We further showed that the rs80207740-G allele facilitated the binding of transcription factor IKZF1 in EMSA and ChIP analyses. Knockdown of IKZF1 and GATA1 resulted in decreased expression of Xpo7 in both human and mouse erythroid cells. Finally, we constructed Xpo7 knockout mouse by CRISPR/Cas9 and observed anemic phenotype with reduced volume and hemoglobin content of RBC, consistent to the effect of rs80207740 on erythrocyte traits. Overall, our study demonstrated that rs80207740 modulated erythroid indices by regulating IKZF1 binding and Xpo7 expression.

PC Gene Affects Milk Production Traits in Dairy Cattle

In previous work, we found that PC was differentially expressed in cows at different lactation stages. Thus, we deemed that PC may be a candidate gene affecting milk production traits in dairy cattle. In this study, we found the polymorphisms of PC by resequencing and verified their genetic associations with milk production traits by using an animal model in a cattle population. In total, we detected six single-nucleotide polymorphisms (SNPs) in PC. The single marker association analysis showed that all SNPs were significantly associated with the five milk production traits (p < 0.05). Additionally, we predicted that allele G of 29:g.44965658 in the 5' regulatory region created binding sites for TF GATA1 and verified that this allele inhibited the transcriptional activity of PC by the dual-luciferase reporter assay. In conclusion, we proved that PC had a prominent genetic effect on milk production traits, and six SNPs with prominent genetic effects could be used as markers for genomic selection (GS) in dairy cattle, which is beneficial for accelerating the improvement in milk yield and quality in Chinese Holstein cows.

Benchmarking DNA binding affinity models using allele-specific transcription factor binding data

Transcription factors (TFs) bind to DNA in a highly sequence-specific manner. This specificity can manifest itself in vivo at heterozygous loci as a difference in TF occupancy between the two alleles. When applied on a genomic scale, functional genomic assays such as ChIP-seq typically lack the statistical power to detect allele-specific binding (ASB) at the level of individual variants. To address this, we propose a framework for benchmarking sequence-to-affinity models for TF binding in terms of their ability to predict allelic imbalances in ChIP-seq counts. We show that a likelihood function based on an over-dispersed binomial distribution can aggregate evidence for allelic preference across the genome without requiring statistical significance for individual variants. This allows us to systematically compare predictive performance when multiple binding models for the same TF are available. We introduce PyProBound, an easily extensible reimplementation of the ProBound biophysically interpretable machine learning framework. Configuring PyProBound to explicitly account for a confounding sequence-specific bias in DNA fragmentation rate yields improved TF binding models when training on ChIP-seq data. We also show how our likelihood function can be leveraged to perform de novo motif discovery on the raw allele-aware ChIP-seq counts.

Beyond conflict: Kinship theory of intragenomic conflict predicts individual variation in altruistic behaviour

Behavioural variation is essential for animals to adapt to different social and environmental conditions. The Kinship Theory of Intragenomic Conflict (KTIC) predicts that parent-specific alleles can support different behavioural strategies to maximize allele fitness. Previous studies, including in honey bees (Apis mellifera), supported predictions of the KTIC for parent-specific alleles to promote selfish behaviour. Here, we test the KTIC prediction that for altruism-promoting genes (i.e. those that promote behaviours that support the reproductive fitness of kin), the allele with the higher altruism optimum should be selected to be expressed while the other is silenced. In honey bee colonies, workers act altruistically when tending to the queen by performing a 'retinue' behaviour, distributing the queen's mandibular pheromone (QMP) throughout the hive. Workers exposed to QMP do not activate their ovaries, ensuring they care for the queen's brood instead of competing to lay unfertilized eggs. Due to the haplodiploid genetics of honey bees, the KTIC predicts that response to QMP is favoured by the maternal genome. We report evidence for parent-of-origin effects on the retinue response behaviour, ovarian development and gene expression in brains of worker honey bees exposed to QMP, consistent with the KTIC. Additionally, we show enrichment for genes with parent-of-origin expression bias within gene regulatory networks associated with variation in bees' response to QMP. Our study demonstrates that intragenomic conflict can shape diverse social behaviours and influence expression patterns of single genes as well as gene networks.

Allele specific binding of histone modifications and a transcription factor does not predict allele specific expression in correlated ChIP-seq peak-exon pairs

Allele specific expression (ASE) is widespread in many species including cows. Therefore, regulatory regions which control gene expression should show cis-regulatory variation which mirrors this differential expression within the animal. ChIP-seq peaks for histone modifications and transcription factors measure activity at functional regions and the height of some peaks have been shown to correlate across tissues with the expression of particular genes, suggesting these peaks are putative regulatory regions. In this study we identified ASE in the bovine genome in multiple tissues and investigated whether ChIP-seq peaks for four histone modifications and the transcription factor CTCF show allele specific binding (ASB) differences in the same tissues. We then investigate whether peak height and gene expression, which correlates across tissues, also correlates within the animal by investigating whether the direction of ASB in putative regulatory regions, mirrors that of the ASE in the genes they are putatively regulating. We found that ASE and ASB were widespread in the bovine genome but vary in extent between tissues. However, even when the height of a peak was positively correlated across tissues with expression of an exon, ASE of the exon and ASB of the peak were in the same direction only half the time. A likely explanation for this finding is that the correlations between peak height and exon expression do not indicate that the height of the peak causes the extent of exon expression, at least in some cases.

Allele-specific RNA N 6-methyladenosine modifications reveal functional genetic variants in human tissues

An intricate network of cis- and trans-elements acts on RNA N 6-methyladenosine (m6A), which in turn may affect gene expression and, ultimately, human health. A complete understanding of this network requires new approaches to accurately measure the subtle m6A differences arising from genetic variants, many of which have been associated with common diseases. To address this gap, we developed a method to accurately and sensitively detect transcriptome-wide allele-specific m6A (ASm6A) from MeRIP-seq data and applied it to uncover 12,056 high-confidence ASm6A modifications from 25 human tissues. We also identified 1184 putative functional variants for ASm6A regulation, a subset of which we experimentally validated. Importantly, we found that many of these ASm6A-associated genetic variants were enriched for common disease-associated and complex trait-associated risk loci, and verified that two disease risk variants can change m6A modification status. Together, this work provides a tool to detangle the dynamic network of RNA modifications at the allelic level and highlights the interplay of m6A and genetics in human health and disease.

The landscape of somatic mutations in lymphoblastoid cell lines

Somatic mutations have important biological ramifications while exerting substantial rate, type, and genomic location heterogeneity. Yet, their sporadic occurrence makes them difficult to study at scale and across individuals. Lymphoblastoid cell lines (LCLs), a model system for human population and functional genomics, harbor large numbers of somatic mutations and have been extensively genotyped. By comparing 1,662 LCLs, we report that the mutational landscape of the genome varies across individuals in terms of the number of mutations, their genomic locations, and their spectra; this variation may itself be modulated by somatic trans-acting mutations. Mutations attributed to the translesion DNA polymerase η follow two different modes of formation, with one mode accounting for the hypermutability of the inactive X chromosome. Nonetheless, the distribution of mutations along the inactive X chromosome appears to follow an epigenetic memory of the active form.

Transgenerational Epigenetic Inheritance of MHC Class I Gene Expression is Regulated by the CCAAT Promoter Element

Transgenerational epigenetic inheritance is defined as the transmission of traits or gene expression patterns across multiple generations that do not derive from DNA alterations. The effect of multiple stress factors or metabolic changes resulting in such inheritance have been documented in plants, worms and flies and mammals. The molecular basis for epigenetic inheritance has been linked to histone and DNA modifications and non-coding RNA. In this study, we show that mutation of a promoter element, the CCAAT box, disrupts stable expression of an MHC Class I transgene, resulting in variegated expression among progeny for at least 4 generations in multiple independently derived transgenic lines. Histone modifications and RNA polII binding correlate with expression, whereas DNA methylation and nucleosome occupancy do not. Mutation of the CCAAT box abrogates NF-Y binding and results in changes to CTCF binding and DNA looping patterns across the gene that correlate with expression status from one generation to the next. These studies identify the CCAAT promoter element as a regulator of stable transgenerational epigenetic inheritance. Considering that the CCAAT box is present in 30% of eukaryotic promoters, this study could provide important insights into how fidelity of gene expression patterns is maintained through multiple generations.

Abnormal Chromatin Folding in the Molecular Pathogenesis of Epilepsy and Autism Spectrum Disorder: a Meta-synthesis with Systematic Searching

How DNA is folded and packaged in nucleosomes is an essential regulator of gene expression. Abnormal patterns of chromatin folding are implicated in a wide range of diseases and disorders, including epilepsy and autism spectrum disorder (ASD). These disorders are thought to have a shared pathogenesis involving an imbalance in the number of excitatory-inhibitory neurons formed during neurodevelopment; however, the underlying pathological mechanism behind this imbalance is poorly understood. Studies are increasingly implicating abnormal chromatin folding in neural stem cells as one of the candidate pathological mechanisms, but no review has yet attempted to summarise the knowledge in this field. This meta-synthesis is a systematic search of all the articles on epilepsy, ASD, and chromatin folding. Its two main objectives were to determine to what extent abnormal chromatin folding is implicated in the pathogenesis of epilepsy and ASD, and secondly how abnormal chromatin folding leads to pathological disease processes. This search produced 22 relevant articles, which together strongly implicate abnormal chromatin folding in the pathogenesis of epilepsy and ASD. A range of mutations and chromosomal structural abnormalities lead to this effect, including single nucleotide polymorphisms, copy number variants, translocations and mutations in chromatin modifying. However, knowledge is much more limited into how abnormal chromatin organisation subsequently causes pathological disease processes, not yet showing, for example, whether it leads to abnormal excitation-inhibitory neuron imbalance in human brain organoids.

Genetic marker identification of SEC13 gene for milk production traits in Chinese holstein

SEC13 homolog, nuclear pore and COPII coat complex component (SEC13) is the core component of the cytoplasmic COPII complex, which mediates material transport from the endoplasmic reticulum to the Golgi complex. Our preliminary work found that SEC13 gene was differentially expressed in dairy cows during different stages of lactation, and involved in metabolic pathways of milk synthesis such as citric acid cycle, fatty acid, starch and sucrose metabolisms, so we considered that the SEC13 might be a candidate gene affecting milk production traits. In this study, we detected the polymorphisms of SEC13 gene and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. By sequencing the whole coding and partial flanking regions of SEC13, we found four single nucleotide polymorphisms (SNPs). Subsequent association analysis showed that these four SNPs were significantly associated with milk yield, fat yield, protein yield or protein percentage in the first and second lactations (p ≤.0351). We also found that two SNPs in SEC13 formed one haplotype block by Haploview4.2, and the block was significantly associated with milk yield, fat yield, fat percentage, protein yield or protein percentage (p ≤ .0373). In addition, we predicted the effect of SNP on 5'region on transcription factor binding sites (TFBSs), and found that the allele A of 22:g.54362761A>G could bind transcription factors (TFs) GATA5, GATA3, HOXD9, HOXA10, CDX1 and Hoxd13; and further dual-luciferase reporter assay verified that the allele A of this SNP inhibited the fluorescence activity. We speculate that the A allele of 22:g.54362761A>G might inhibit the transcriptional activity of SEC13 gene by binding the TFs, which may be a cause mutation affecting the formation of milk production traits in dairy cows. In summary, we proved that SEC13 has a significant genetic effect on milk production traits and the identified significant SNPs could be used as candidate genetic markers for GS SNP chips development; on the other hand, we verified the transcriptional regulation of 22:g.54362761A>G on SEC13 gene, providing research direction for further function validation tests.

DeCAF: a novel method to identify cell-type specific regulatory variants and their role in cancer risk

Here, we propose DeCAF (DEconvoluted cell type Allele specific Function), a new method to identify cell-fraction (cf) QTLs in tumors by leveraging both allelic and total expression information. Applying DeCAF to RNA-seq data from TCGA, we identify 3664 genes with cfQTLs (at 10% FDR) in 14 cell types, a 5.63× increase in discovery over conventional interaction-eQTL mapping. cfQTLs replicated in external cell-type-specific eQTL data are more enriched for cancer risk than conventional eQTLs. Our new method, DeCAF, empowers the discovery of biologically meaningful cfQTLs from bulk RNA-seq data in moderately sized studies.

Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data

Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.

Cell-type-specific epigenomic variations associated with BRCA1 mutation in pre-cancer human breast tissues

BRCA1 germline mutation carriers are predisposed to breast cancers. Epigenomic regulations have been known to strongly interact with genetic variations and potentially mediate biochemical cascades involved in tumorigenesis. Due to the cell-type specificity of epigenomic features, profiling of individual cell types is critical for understanding the molecular events in various cellular compartments within complex breast tissue. Here, we produced cell-type-specific profiles of genome-wide histone modifications including H3K27ac and H3K4me3 in basal, luminal progenitor, mature luminal and stromal cells extracted from a small pilot cohort of pre-cancer BRCA1 mutation carriers (BRCA1^mut/+) and non-carriers (BRCA1^+/+), using a low-input ChIP-seq technology that we developed. We discovered that basal and stromal cells present the most extensive epigenomic differences between mutation carriers (BRCA1^mut/+) and non-carriers (BRCA1^+/+), while luminal progenitor and mature luminal cells are relatively unchanged with the mutation. Furthermore, the epigenomic changes in basal cells due to BRCA1 mutation appear to facilitate their transformation into luminal progenitor cells. Taken together, epigenomic regulation plays an important role in the case of BRCA1 mutation for shaping the molecular landscape that facilitates tumorigenesis.

Functional analysis of the 1p34.3 risk locus implicates GNL2 in high-grade serous ovarian cancer

The high-grade serous ovarian cancer (HGSOC) risk locus at chromosome 1p34.3 resides within a frequently amplified genomic region signifying the presence of an oncogene. Here, we integrate in silico variant-to-function analysis with functional studies to characterize the oncogenic potential of candidate genes in the 1p34.3 locus. Fine mapping of genome-wide association statistics identified candidate causal SNPs local to H3K27ac-demarcated enhancer regions that exhibit allele-specific binding for CTCF in HGSOC and normal fallopian tube secretory epithelium cells (FTSECs). SNP risk associations colocalized with eQTL for six genes (DNALI1, GNL2, RSPO1, SNIP1, MEAF6, and LINC01137) that are more highly expressed in carriers of the risk allele, and three (DNALI1, GNL2, and RSPO1) were upregulated in HGSOC compared to normal ovarian surface epithelium cells and/or FTSECs. Increased expression of GNL2 and MEAF6 was associated with shorter survival in HGSOC with 1p34.3 amplifications. Despite its activation of β-catenin signaling, RSPO1 overexpression exerted no effects on proliferation or colony formation in our study of ovarian cancer and FTSECs. Instead, GNL2, MEAF6, and SNIP1 silencing impaired in vitro ovarian cancer cell growth. Additionally, GNL2 silencing diminished xenograft tumor formation, whereas overexpression stimulated proliferation and colony formation in FTSECs. GNL2 influences 60S ribosomal subunit maturation and global protein synthesis in ovarian cancer and FTSECs, providing a potential mechanism of how GNL2 upregulation might promote ovarian cancer development and mediate genetic susceptibility of HGSOC.

Advances in Genetics and Epigenetic Alterations in Alzheimer's Disease: A Notion for Therapeutic Treatment

Alzheimer's disease (AD) is a disabling neurodegenerative disorder that leads to long-term functional and cognitive impairment and greatly reduces life expectancy. Early genetic studies focused on tracking variations in genome-wide DNA sequences discovered several polymorphisms and novel susceptibility genes associated with AD. However, despite the numerous risk factors already identified, there is still no fully satisfactory explanation for the mechanisms underlying the onset of the disease. Also, as with other complex human diseases, the causes of low heritability are unclear. Epigenetic mechanisms, in which changes in gene expression do not depend on changes in genotype, have attracted considerable attention in recent years and are key to understanding the processes that influence age-related changes and various neurological diseases. With the recent use of massive sequencing techniques, methods for studying epigenome variations in AD have also evolved tremendously, allowing the discovery of differentially expressed disease traits under different conditions and experimental settings. This is important for understanding disease development and for unlocking new potential AD therapies. In this work, we outline the genomic and epigenomic components involved in the initiation and development of AD and identify potentially effective therapeutic targets for disease control.

Associations between polymorphisms of SLC22A7, NGFR, ARNTL and PPP2R2B genes and Milk production traits in Chinese Holstein

Background

Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bβ) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population.

Results

By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle.

Conclusions

In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-01002-0.

Genetic variants in histone modification regions are associated with the prognosis of lung adenocarcinoma

We investigated the association between genetic variants in the histone modification regions and the prognosis of lung adenocarcinoma after curative surgery. Potentially functional SNPs were selected using integrated analysis of ChIP-seq and RNA-seq. The SNPs were analyzed in a discovery set (n = 166) and a validation set (n = 238). The associations of the SNPs with overall survival (OS) and disease-free survival (DFS) were analyzed. A total of 279 SNPs were selected for genotyping. Among these, CAPN1 rs17583C>T was significantly associated with better OS and DFS (P = 0.001 and P = 0.007, respectively), and LINC00959 rs4751162A>G was significantly associated with worse DFS (P = 0.008). Luciferase assays showed a significantly lower promoter activity of CAPN1 in the rs17583 T allele than C allele (P = 0.008), and consistently the CT + TT genotypes had significantly lower CAPN1 expression than CC genotype (P = 0.01) in clinical samples. The rs4751162 G allele had higher promoter activity of GLRX3 than A allele (P = 0.05). The motif analyses and ChIP-qPCR confirmed that the variants are located in the active promoter/enhancer regions where transcription factor binding occurs. This study showed that genetic variants in the histone modification regions could predict the prognosis of lung adenocarcinoma after surgery.

The role of epigenetics in psychological resilience

There is substantial variation in people's responses to adversity, with a considerable proportion of individuals displaying psychological resilience. Epigenetic mechanisms are hypothesised to be one molecular pathway of how adverse and traumatic events can become biologically embedded and contribute to individual differences in resilience. However, not much is known regarding the role of epigenetics in the development of psychological resilience. In this Review, we propose a new conceptual model for the different functions of epigenetic mechanisms in psychological resilience. The model considers the initial establishment of the epigenome, epigenetic modification due to adverse and protective environments, the role of protective factors in counteracting adverse influences, and genetic moderation of environmentally induced epigenetic modifications. After reviewing empirical evidence for the various components of the model, we identify research that should be prioritised and discuss practical implications of the proposed model for epigenetic research on resilience.

Tissue context determines the penetrance of regulatory DNA variation

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

Allele Specific Expression (ASE) analysis between Bos Taurus and Bos Indicus cows using RNA-Seq data at SNP level and gene level

In the current study, allele specific expression analysis was performed in two subspecies cows (Bos taurus and Bos indicus) at SNP and gene levels. RNA-Seq data of 21,078,477 and 20940063 paired end reads from pooling of whole blood samples (Leukocyte) from 40 US Holstein (Bos Taurus) and 45 Cholistani cows (Bos indicus) obtained from SRA database in NCBI. Quality control and trimming of row RNA-Seq data were processed by FASTQC and Trimmomatic softwares. The transcriptome was assembled by TopHat2 software in two cow's population by aligning and mapping the RNA-Seq reads on bovine reference genome. The SNPs were discovered by Samtools software and ASE analysis was performed by Chi-square test. Results showed that 50183 and 137954 SNPs were discovered on the assembled transcriptome of Holstein and Cholistani cow samples, respectively, and 15308 SNPs were common in both breeds. 10158 SNPs from 50183 (20%) in Holstein and 31523 SNPs from 137954 (23%) in Cholistani cows were identified as ASE-SNPs. Reference allele and alternative allele count in Holstein and Cholistani cows were 3041 and 7155, respectively. Among 131 discovered SNPs in 41 genes with different expression in Holstein and Cholistani cows, 31 ASE-SNPs (5 in Holstein; 26 in Cholistani cows) were discovered.

Landscape of allele-specific transcription factor binding in the human genome

Sequence variants in gene regulatory regions alter gene expression and contribute to phenotypes of individual cells and the whole organism, including disease susceptibility and progression. Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Differential transcription factor binding in heterozygous genomic loci provides a natural source of information on such regulatory variants. We present a novel approach to call the allele-specific transcription factor binding events at single-nucleotide variants in ChIP-Seq data, taking into account the joint contribution of aneuploidy and local copy number variation, that is estimated directly from variant calls. We have conducted a meta-analysis of more than 7 thousand ChIP-Seq experiments and assembled the database of allele-specific binding events listing more than half a million entries at nearly 270 thousand single-nucleotide polymorphisms for several hundred human transcription factors and cell types. These polymorphisms are enriched for associations with phenotypes of medical relevance and often overlap eQTLs, making candidates for causality by linking variants with molecular mechanisms. Specifically, there is a special class of switching sites, where different transcription factors preferably bind alternative alleles, thus revealing allele-specific rewiring of molecular circuitry.

Muscle allele-specific expression QTLs may affect meat quality traits in Bos indicus

Single nucleotide polymorphisms (SNPs) located in transcript sequences showing allele-specific expression (ASE SNPs) were previously identified in the Longissimus thoracis muscle of a Nelore (Bos indicus) population consisting of 190 steers. Given that the allele-specific expression pattern may result from cis-regulatory SNPs, called allele-specific expression quantitative trait loci (aseQTLs), in this study, we searched for aseQTLs in a window of 1 Mb upstream and downstream from each ASE SNP. After this initial analysis, aiming to investigate variants with a potential regulatory role, we further screened our aseQTL data for sequence similarity with transcription factor binding sites and microRNA (miRNA) binding sites. These aseQTLs were overlapped with methylation data from reduced representation bisulfite sequencing (RRBS) obtained from 12 animals of the same population. We identified 1134 aseQTLs associated with 126 different ASE SNPs. For 215 aseQTLs, one allele potentially affected the affinity of a muscle-expressed transcription factor to its binding site. 162 aseQTLs were predicted to affect 149 miRNA binding sites, from which 114 miRNAs were expressed in muscle. Also, 16 aseQTLs were methylated in our population. Integration of aseQTL with GWAS data revealed enrichment for traits such as meat tenderness, ribeye area, and intramuscular fat . To our knowledge, this is the first report of aseQTLs identification in bovine muscle. Our findings indicate that various cis-regulatory and epigenetic mechanisms can affect multiple variants to modulate the allelic expression. Some of the potential regulatory variants described here were associated with the expression pattern of genes related to interesting phenotypes for livestock. Thus, these variants might be useful for the comprehension of the genetic control of these phenotypes.

Association of the Rheumatoid Arthritis Severity Variant rs26232 with the Invasive Activity of Synovial Fibroblasts

rs26232, located in intron one of C5orf30, is associated with the susceptibility to and severity of rheumatoid arthritis (RA). Here, we investigate the relationship between this variant and the biological activities of rheumatoid arthritis synovial fibroblasts (RASFs). RASFs were isolated from the knee joints of 33 RA patients. The rs26232 genotype was determined and cellular migration, invasion, and apoptosis were compared using in vitro techniques. The production of adhesion molecules, chemokines, and proteases was measured by ELISA or flow cytometry. Cohort genotypes were CC n = 16; CT n = 14; TT n = 3. In comparison with the RASFs of the CT genotype, the CC genotype showed a 1.48-fold greater invasiveness in vitro (p = 0.02), 1.6-fold higher expression intracellular adhesion molecule (ICAM)-1 (p = 0.001), and 5-fold IFN-γ inducible protein-10 (IP-10) (p = 0.01). There was no association of the rs26232 genotype with the expression levels of either total C5orf30 mRNA or any of the three transcript variants. The rs26232 C allele, which has previously been associated with both the risk and severity of RA, is associated with greater invasive activity of RASFs in vitro, and with higher expression of ICAM-1 and IP-10. In resting RASFs, rs26232 is not a quantitative trait locus for C5orf30 mRNA, indicating a more complex mechanism underlying the genotype‒phenotype relationship.

Predicting the effects of SNPs on transcription factor binding affinity

MOTIVATION

Genome-wide association studies have revealed that 88% of disease-associated single-nucleotide polymorphisms (SNPs) reside in noncoding regions. However, noncoding SNPs remain understudied, partly because they are challenging to prioritize for experimental validation. To address this deficiency, we developed the SNP effect matrix pipeline (SEMpl).

RESULTS

SEMpl estimates transcription factor-binding affinity by observing differences in chromatin immunoprecipitation followed by deep sequencing signal intensity for SNPs within functional transcription factor-binding sites (TFBSs) genome-wide. By cataloging the effects of every possible mutation within the TFBS motif, SEMpl can predict the consequences of SNPs to transcription factor binding. This knowledge can be used to identify potential disease-causing regulatory loci.

AVAILABILITY AND IMPLEMENTATION

SEMpl is available from https://github.com/Boyle-Lab/SEM_CPP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Disease classification: from phenotypic similarity to integrative genomics and beyond

A fundamental challenge of modern biomedical research is understanding how diseases that are similar on the phenotypic level are similar on the molecular level. Integration of various genomic data sets with the traditionally used phenotypic disease similarity revealed novel genetic and molecular mechanisms and blurred the distinction between monogenic (Mendelian) and complex diseases. Network-based medicine has emerged as a complementary approach for identifying disease-causing genes, genetic mediators, disruptions in the underlying cellular functions and for drug repositioning. The recent development of machine and deep learning methods allow for leveraging real-life information about diseases to refine genetic and phenotypic disease relationships. This review describes the historical development and recent methodological advancements for studying disease classification (nosology).

Minor alleles of genetic variants in second heart field increase the risk of hypoplastic right heart syndrome

Hypoplastic right heart syndrome(HRHS) is characterized by hypoplastic right ventricle (RV); Numerous transcriptional cascades in the second heart field (SHF) regulate RVdevelopment. The relationship of SHF gene variants with human HRHS remains unknown. The whole lengths of 17 SHF genes were sequenced in 16 HRHS, and the selected single-nucleotide variants (SNVs) were then genotyped in HRHS, other congenital heart disease (CHD) and healthy control. Luciferase assay was performed to verify the effect of FOXC2: rs34221221A>GandTBX20: rs59854940C>Gat the transcription level. There were 151 (12.86%) novel SNVs after sequence analysis, of which three were in exons (one was synonymous SNV and two were nonsynonymous SNVs), two in promoter, and most SNVs (89.95%) were in intronic regions. Genotype analyses revealed that the minor alleles of FOXC2: rs34221221 A>G and TBX20: rs59854940 C>G could increase HRHS risk (P<0.05), but not in other CHD or healthy control. Luciferase assay showed that the minor G allele in rs34221221 significantly increased FOXC2 transcription while in rs59854940 it decreased TBX20 transcription significantly. Novel variants of SHF gene associated with HRHS were identified. Minor alleles in two variants from FOXC2 and TBX20 could increase the risk of HRHS.

Quantification of allelic differential expression using a simple Fluorescence primer PCR-RFLP-based method

Allelic differential expression (ADE) is common in diploid organisms, and is often the key reason for specific phenotype variations. Thus, ADE detection is important for identification of major genes and causal mutations. To date, sensitive and simple methods to detect ADE are still lacking. In this study, we have developed an accurate, simple, and sensitive method, named fluorescence primer PCR-RFLP quantitative method (fPCR-RFLP), for ADE analysis. This method involves two rounds of PCR amplification using a pair of primers, one of which is double-labeled with an overhang 6-FAM. The two alleles are then separated by RFLP and quantified by fluorescence density. fPCR-RFLP could precisely distinguish ADE cross a range of 1- to 32-fold differences. Using this method, we verified PLAG1 and KIT, two candidate genes related to growth rate and immune response traits of pigs, to be ADE both at different developmental stages and in different tissues. Our data demonstrates that fPCR-RFLP is an accurate and sensitive method for detecting ADE on both DNA and RNA level. Therefore, this powerful tool provides a way to analyze mutations that cause ADE.

Introduction to Bioinformatics

How the scientific community looks at molecular biology today is very different from that 50 years ago. During this time technological developments have led to many significant findings that have shook one of the most important foundations of molecular biology: the central dogma. In this chapter, we will mention how these changes occurred and gave birth to a very important field of today's science, bioinformatics. We will also mention briefly the newest topics of molecular biology regarding bioinformatics technologies and skills.

Mass Spectrometry Genotyping of Human Papillomavirus Based on High-Efficiency Selective Enrichment of Nanoparticles

This work developed a novel spermine-modified nanodiamonds (SP-NDs)-based method to selectively enrich oligonucleotides for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) of human papillomavirus (HPV) virus. Our results showed that SP-NDs can effectively extract and enrich DNA oligonucleotides from sodium dodecyl sulfonate and urea solution. In addition, SP-NDs can also selectively extract oligonucleotides from enzymes digestion products of polymerase chain reaction-restriction fragment mass polymorphism (PCR-RFMP) of HPV virus. Then, the extract can be detected by MALDI-TOF MS directly without further purification. According to the MS results, the HPV genotyping can be achieved. More importantly, with SP-NDs extraction, clinical samples infected with HPV genotype 16 and 18 can be identified. The described method shows great advantages of simplicity, high selectivity, and good reliability in real clinical samples. Due to our methods improvement on DNA enrichment, extraction and purification, the PCR-based MALDI-TOF MS for the analysis of oligonucleotides maybe become more rapid, sensitive, and high-throughput, is promising for analysis for DNA methylation, single-nucleotide polymorphisms, and other virus typing.

Variation graph toolkit improves read mapping by representing genetic variation in the reference

Reference genomes guide our interpretation of DNA sequence data. However, conventional linear references represent only one version of each locus, ignoring variation in the population. Poor representation of an individual's genome sequence impacts read mapping and introduces bias. Variation graphs are bidirected DNA sequence graphs that compactly represent genetic variation across a population, including large-scale structural variation such as inversions and duplications. Previous graph genome software implementations have been limited by scalability or topological constraints. Here we present vg, a toolkit of computational methods for creating, manipulating, and using these structures as references at the scale of the human genome. vg provides an efficient approach to mapping reads onto arbitrary variation graphs using generalized compressed suffix arrays, with improved accuracy over alignment to a linear reference, and effectively removing reference bias. These capabilities make using variation graphs as references for DNA sequencing practical at a gigabase scale, or at the topological complexity of de novo assemblies.

A survey of inter-individual variation in DNA methylation identifies environmentally responsive co-regulated networks of epigenetic variation in the human genome

While population studies have resulted in detailed maps of genetic variation in humans, to date there are few robust maps of epigenetic variation. We identified sites containing clusters of CpGs with high inter-individual epigenetic variation, termed Variably Methylated Regions (VMRs) in five purified cell types. We observed that VMRs occur preferentially at enhancers and 3' UTRs. While the majority of VMRs have high heritability, a subset of VMRs within the genome show highly correlated variation in trans, forming co-regulated networks that have low heritability, differ between cell types and are enriched for specific transcription factor binding sites and biological pathways of functional relevance to each tissue. For example, in T cells we defined a network of 95 co-regulated VMRs enriched for genes with roles in T-cell activation; in fibroblasts a network of 34 co-regulated VMRs comprising all four HOX gene clusters enriched for control of tissue growth; and in neurons a network of 18 VMRs enriched for roles in synaptic signaling. By culturing genetically-identical fibroblasts under varying environmental conditions, we experimentally demonstrated that some VMR networks are responsive to the environment, with methylation levels at these loci changing in a coordinated fashion in trans dependent on cellular growth. Intriguingly these environmentally-responsive VMRs showed a strong enrichment for imprinted loci (p<10-80), suggesting that these are particularly sensitive to environmental conditions. Our study provides a detailed map of common epigenetic variation in the human genome, showing that both genetic and environmental causes underlie this variation.

VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis

Background

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts.

Results

Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses.

Conclusions

VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2139-9) contains supplementary material, which is available to authorized users.

Nucleus-specific expression in the multinuclear mushroom-forming fungus Agaricus bisporus reveals different nuclear regulatory programs

Fungi are a broad class of organisms that play crucial roles in a wide variety of natural and industrial processes. Some are also harmful, destroying crops or infecting immunocompromised patients. Many fungi, at some point during their life cycle, contain two different nuclei, each with different genetic content. We examine the regulation of genes from these nuclei in a mushroom-forming fungus. We find that these nuclei contribute differently to the regulation of the fungal cells, and may therefore have a different impact on their environment. Furthermore, these differences change throughout the development of different tissues. This work contributes to our understanding of fungal physiology by examining this process.

Many fungi are polykaryotic, containing multiple nuclei per cell. In the case of heterokaryons, there are different nuclear types within a single cell. It is unknown what the different nuclear types contribute in terms of mRNA expression levels in fungal heterokaryons. Each cell of the mushroom Agaricus bisporus contains two to 25 nuclei of two nuclear types originating from two parental strains. Using RNA-sequencing data, we assess the differential mRNA contribution of individual nuclear types and its functional impact. We studied differential expression between genes of the two nuclear types, P1 and P2, throughout mushroom development in various tissue types. P1 and P2 produced specific mRNA profiles that changed through mushroom development. Differential regulation occurred at the gene level, rather than at the locus, chromosomal, or nuclear level. P1 dominated mRNA production throughout development, and P2 showed more differentially up-regulated genes in important functional groups. In the vegetative mycelium, P2 up-regulated almost threefold more metabolism genes and carbohydrate active enzymes (cazymes) than P1, suggesting phenotypic differences in growth. We identified widespread transcriptomic variation between the nuclear types of A. bisporus. Our method enables studying nucleus-specific expression, which likely influences the phenotype of a fungus in a polykaryotic stage. Our findings have a wider impact to better understand gene regulation in fungi in a heterokaryotic state. This work provides insight into the transcriptomic variation introduced by genomic nuclear separation.

Identification and validation of regulatory SNPs that modulate transcription factor chromatin binding and gene expression in prostate cancer

Prostate cancer (PCa) is the second most common solid tumor for cancer related deaths in American men. Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with the increased risk of PCa. Because most of the susceptibility SNPs are located in noncoding regions, little is known about their functional mechanisms. We hypothesize that functional SNPs reside in cell type-specific regulatory elements that mediate the binding of critical transcription factors (TFs), which in turn result in changes in target gene expression. Using PCa-specific functional genomics data, here we identify 38 regulatory candidate SNPs and their target genes in PCa. Through risk analysis by incorporating gene expression and clinical data, we identify 6 target genes (ZG16B, ANKRD5, RERE, FAM96B, NAALADL2 and GTPBP10) as significant predictors of PCa biochemical recurrence. In addition, 5 SNPs (rs2659051, rs10936845, rs9925556, rs6057110 and rs2742624) are selected for experimental validation using Chromatin immunoprecipitation (ChIP), dual-luciferase reporter assay in LNCaP cells, showing allele-specific enhancer activity. Furthermore, we delete the rs2742624-containing region using CRISPR/Cas9 genome editing and observe the drastic downregulation of its target gene UPK3A. Taken together, our results illustrate that this new methodology can be applied to identify regulatory SNPs and their target genes that likely impact PCa risk. We suggest that similar studies can be performed to characterize regulatory variants in other diseases.

Practical Analysis of Hi-C Data: Generating A/B Compartment Profiles

Recent advances in next-generation sequencing (NGS) and chromosome conformation capture (3C) analysis have led to the development of Hi-C, a genome-wide version of the 3C method. Hi-C has identified new levels of chromosome organization such as A/B compartments, topologically associating domains (TADs) as well as large megadomains on the inactive X chromosome, while allowing the identification of chromatin loops at the genome scale. Despite its powerfulness, Hi-C data analysis is much more involved compared to conventional NGS applications such as RNA-seq or ChIP-seq and requires many more steps. This presents a significant hurdle for those who wish to implement Hi-C technology into their laboratory. On the other hand, genomics data repository sites sometimes contain processed Hi-C data sets, allowing researchers to perform further analysis without the need for high-spec workstations and servers. In this chapter, we provide a detailed description on how to calculate A/B compartment profiles from processed Hi-C data on the autosomes and the active/inactive X chromosomes.

Laminopathies disrupt epigenomic developmental programs and cell fate

The nuclear envelope protein lamin A is encoded by thelamin A/C(LMNA) gene, which can contain missense mutations that cause Emery-Dreifuss muscular dystrophy (EDMD) (p.R453W). We fused mutated forms of the lamin A protein to bacterial DNA adenine methyltransferase (Dam) to define euchromatic-heterochromatin (epigenomic) transitions at the nuclear envelope during myogenesis (using DamID-seq). Lamin A missense mutations disrupted appropriate formation of lamin A-associated heterochromatin domains in an allele-specific manner-findings that were confirmed by chromatin immunoprecipitation-DNA sequencing (ChIP-seq) in murine H2K cells and DNA methylation studies in fibroblasts from muscular dystrophy patient who carried a distinctLMNAmutation (p.H222P). Observed perturbations of the epigenomic transitions included exit from pluripotency and cell cycle programs [euchromatin (open, transcribed) to heterochromatin (closed, silent)], as well as induction of myogenic loci (heterochromatin to euchromatin). In muscle biopsies from patients with either a gain- or change-of-functionLMNAgene mutation or a loss-of-function mutation in theemeringene, both of which cause EDMD, we observed inappropriate loss of heterochromatin formation at theSox2pluripotency locus, which was associated with persistent mRNA expression ofSox2 Overexpression ofSox2inhibited myogenic differentiation in human immortalized myoblasts. Our findings suggest that nuclear envelopathies are disorders of developmental epigenetic programming that result from altered formation of lamina-associated domains.

Epigenetic regulation of AXL and risk of childhood asthma symptoms

Background

AXL is one of the TAM (TYRO3, AXL and MERTK) receptor tyrosine kinases and may affect numerous immune-related health conditions. However, the role for AXL in asthma, including its epigenetic regulation, has not been extensively studied.

Methods

We investigated the association between AXL DNA methylation at birth and risk of childhood asthma symptoms at age 6 years. DNA methylation of multiple CpG loci across the regulatory regions of AXL was measured in newborn bloodspots using the Illumina HumanMethylation450 array on a subset of 246 children from the Children's Health Study (CHS). Logistic regression models were fitted to assess the association between asthma symptoms and DNA methylation. Findings were evaluated for replication in a separate population of 1038 CHS subjects using Pyrosequencing on newborn bloodspot samples. AXL genotypes were extracted from genome-wide data.

Results

Higher average methylation of CpGs in the AXL gene at birth was associated with higher risk of parent-reported wheezing, and the association was stronger in girls than in boys. This relationship reflected the methylation status of the gene-body region near the 5' end, for which a 1% higher methylation level was significantly associated with a 72% increased risk of ever having wheezed by 6 years. The association of one CpG locus, cg00360107 was replicated using Pyrosequencing. Increased AXL methylation was also associated with lower mRNA expression level of this gene in lung tissue from the Cancer Genome Atlas (TCGA) dataset. Furthermore, AXL DNA methylation was strongly linked to underlying genetic polymorphisms.

Conclusions

AXL DNA methylation at birth was associated with higher risk for asthma-related symptoms in early childhood.

Intrinsic MYH7 expression regulation contributes to tissue level allelic imbalance in hypertrophic cardiomyopathy

HCM, the most common inherited cardiac disease, is mainly caused by mutations in sarcomeric genes. More than a third of the patients are heterozygous for mutations in the MYH7 gene encoding for the β-myosin heavy chain. In HCM-patients, expression of the mutant and the wildtype allele can be unequal, thus leading to fractions of mutant and wildtype mRNA and protein which deviate from 1:1. This so-called allelic imbalance was detected in whole tissue samples but also in individual cells. There is evidence that the severity of HCM not only depends on the functional effect of the mutation itself, but also on the fraction of mutant protein in the myocardial tissue. Allelic imbalance has been shown to occur in a broad range of genes. Therefore, we aimed to examine whether the MYH7-alleles are intrinsically expressed imbalanced or whether the allelic imbalance is solely associated with the disease. We compared the expression of MYH7-alleles in non-HCM donors and in HCM-patients with different MYH7-missense mutations. In the HCM-patients, we identified imbalanced as well as equal expression of both alleles. Also at the protein level, allelic imbalance was determined. Most interestingly, we also discovered allelic imbalance and balance in non-HCM donors. Our findings therefore strongly indicate that apart from mutation-specific mechanisms, also non-HCM associated allelic-mRNA expression regulation may account for the allelic imbalance of the MYH7 gene in HCM-patients. Since the relative amount of mutant mRNA and protein or the extent of allelic imbalance has been associated with the severity of HCM, individual analysis of the MYH7-allelic expression may provide valuable information for the prognosis of each patient.

Functional Genomics of Host-Microbiome Interactions in Humans

The human microbiome has been linked to various host phenotypes and has been implicated in many complex human diseases. Recent genome-wide association studies (GWASs) have used microbiome variation as a complex trait and have uncovered human genetic variants that are associated with the microbiome. Here we summarize results from these studies and illustrate potential regulatory mechanisms by which host genetic variation can interact with microbiome composition. We argue that, similar to human GWASs, it is important to use functional genomics techniques to gain a mechanistic understanding of causal host-microbiome interactions and their role in human disease. We highlight experimental, functional, and computational genomics methodologies for the study of the genomic basis of host-microbiome interactions and describe how these approaches can be utilized to explain how human genetic variation can modulate the effects of the microbiome on the host.

Genetic and epigenetic determinants of inter-individual variability in responses to toxicants

It is well established that genetic variability has a major impact on susceptibility to common diseases, responses to drugs and toxicants, and influences disease-related outcomes. The appreciation that epigenetic marks also vary across the population is growing with more data becoming available from studies in humans and model organisms. In addition, the links between genetic variability, toxicity outcomes and epigenetics are being actively explored. Recent studies demonstrate that gene-by-environment interactions involve both chromatin states and transcriptional regulation, and that epigenetics provides important mechanistic clues to connect expression-related quantitative trait loci (QTL) and disease outcomes. However, studies of Gene×Environment×Epigenetics further extend the complexity of the experimental designs and create a challenge for selecting the most informative epigenetic readouts that can be feasibly performed to interrogate multiple individuals, exposures, tissue types and toxicity phenotypes. We propose that among the many possible epigenetic experimental methodologies, assessment of chromatin accessibility coupled with total RNA levels provides a cost-effective and comprehensive option to sufficiently characterize the complexity of epigenetic and regulatory activity in the context of understanding the inter-individual variability in responses to toxicants.

PeakXus: comprehensive transcription factor binding site discovery from ChIP-Nexus and ChIP-Exo experiments

MOTIVATION

Transcription factor (TF) binding can be studied accurately in vivo with ChIP-exo and ChIP-Nexus experiments. Only fraction of TF binding mechanisms are yet fully understood and accurate knowledge of binding locations and patterns of TFs is key to understanding binding that is not explained by simple positional weight matrix models. ChIP-exo/Nexus experiments can also offer insight on the effect of single nucleotide polymorphism (SNP) at TF binding sites on expression of the target genes. This is an important mechanism of action for disease-causing SNPs at non-coding genomic regions.

RESULTS

We describe a peak caller PeakXus that is specifically designed to leverage the increased resolution of ChIP-exo/Nexus and developed with the aim of making as few assumptions of the data as possible to allow discoveries of novel binding patterns. We apply PeakXus to ChIP-Nexus and ChIP-exo experiments performed both in Homo sapiens and in Drosophila melanogaster cell lines. We show that PeakXus consistently finds more peaks overlapping with a TF-specific recognition sequence than published methods. As an application example we demonstrate how PeakXus can be coupled with unique molecular identifiers (UMIs) to measure the effect of a SNP overlapping with a TF binding site on the in vivo binding of the TF.

AVAILABILITY AND IMPLEMENTATION

Source code of PeakXus is available at https://github.com/hartonen/PeakXus

CONTACT

tuomo.hartonen@helsinki.fi or jussi.taipale@ki.se.

Genetic-epigenetic interactions in cis: a major focus in the post-GWAS era

Studies on genetic-epigenetic interactions, including the mapping of methylation quantitative trait loci (mQTLs) and haplotype-dependent allele-specific DNA methylation (hap-ASM), have become a major focus in the post-genome-wide-association-study (GWAS) era. Such maps can nominate regulatory sequence variants that underlie GWAS signals for common diseases, ranging from neuropsychiatric disorders to cancers. Conversely, mQTLs need to be filtered out when searching for non-genetic effects in epigenome-wide association studies (EWAS). Sequence variants in CCCTC-binding factor (CTCF) and transcription factor binding sites have been mechanistically linked to mQTLs and hap-ASM. Identifying these sites can point to disease-associated transcriptional pathways, with implications for targeted treatment and prevention.

Identification of genetic variants affecting vitamin D receptor binding and associations with autoimmune disease

Large numbers of statistically significant associations between sentinel SNPs and case-control status have been replicated by genome-wide association studies. Nevertheless, few underlying molecular mechanisms of complex disease are currently known. We investigated whether variation in binding of a transcription factor, the vitamin D receptor (VDR), whose activating ligand vitamin D has been proposed as a modifiable factor in multiple disorders, could explain any of these associations. VDR modifies gene expression by binding DNA as a heterodimer with the Retinoid X receptor (RXR). We identified 43,332 genetic variants significantly associated with altered VDR binding affinity (VDR-BVs) using a high-resolution (ChIP-exo) genome-wide analysis of 27 HapMap lymphoblastoid cell lines. VDR-BVs are enriched in consensus RXR::VDR binding motifs, yet most fell outside of these motifs, implying that genetic variation often affects the binding affinity only indirectly. Finally, we compared 341 VDR-BVs replicating by position in multiple individuals against background sets of variants lying within VDR-binding regions that had been matched in allele frequency and were independent with respect to linkage disequilibrium. In this stringent test, these replicated VDR-BVs were significantly (q < 0.1) and substantially (>2-fold) enriched in genomic intervals associated with autoimmune and other diseases, including inflammatory bowel disease, Crohn's disease and rheumatoid arthritis. The approach's validity is underscored by RXR::VDR motif sequence being predictive of binding strength and being evolutionarily constrained. Our findings are consistent with altered RXR::VDR binding contributing to immunity-related diseases. Replicated VDR-BVs associated with these disorders could represent causal disease risk alleles whose effect may be modifiable by vitamin D levels.

A promoter-proximal transcript targeted by genetic polymorphism controls E-cadherin silencing in human cancers

Long noncoding RNAs are emerging players in the epigenetic machinery with key roles in development and diseases. Here we uncover a complex network comprising a promoter-associated noncoding RNA (paRNA), microRNA and epigenetic regulators that controls transcription of the tumour suppressor E-cadherin in epithelial cancers. E-cadherin silencing relies on the formation of a complex between the paRNA and microRNA-guided Argonaute 1 that, together, recruit SUV39H1 and induce repressive chromatin modifications in the gene promoter. A single nucleotide polymorphism (rs16260) linked to increased cancer risk alters the secondary structure of the paRNA, with the risk allele facilitating the assembly of the microRNA-guided Argonaute 1 complex and gene silencing. Collectively, these data demonstrate the role of a paRNA in E-cadherin regulation and the impact of a noncoding genetic variant on its function. Deregulation of paRNA-based epigenetic networks may contribute to cancer and other diseases making them promising targets for drug discovery.