The UCSC Genome Browser

Exploring transient global transcriptional changes induced by ascorbic acid revealed via atKAS-seq profiling

Transcription initiates the formation of single-stranded DNA (ssDNA) regions within the genome, delineating transcription bubbles, a highly dynamic genomic process. Kethoxal-assisted single-stranded DNA sequencing (KAS-seq) utilizing N3-kethoxal has emerged as a potent tool for mapping specific guanine positions in ssDNA on a genome-wide scale. However, the original KAS-seq method required the costly Accel-NGS Methyl-seq DNA library kit. This study introduces an optimized iteration of the KAS-seq technique, referred to as adapter-tagged KAS-seq (atKAS-seq), incorporating an adapter tagging strategy. This modification involves integrating sequencing adapters via complementary strand synthesis using random N9 tagging. Additionally, by harnessing the potential of ascorbic acid (ASC), recognized for inducing global epigenetic changes, we employed the atKAS-seq methodology to elucidate critical pathways influenced by short-term, high-dose ASC treatment. Our findings underscore that atKAS-seq enables rapid and precise analyses of transcription dynamics and enhancer activities concurrently. This method offers a streamlined, cost-efficient, and low-input approach, affirming its utility in probing intricate genomic regulatory mechanisms.

Genome-wide association study of thyroid-stimulating hormone highlights new genes, pathways and associations with thyroid disease

Thyroid hormones play a critical role in regulation of multiple physiological functions and thyroid dysfunction is associated with substantial morbidity. Here, we use electronic health records to undertake a genome-wide association study of thyroid-stimulating hormone (TSH) levels, with a total sample size of 247,107. We identify 158 novel genetic associations, more than doubling the number of known associations with TSH, and implicate 112 putative causal genes, of which 76 are not previously implicated. A polygenic score for TSH is associated with TSH levels in African, South Asian, East Asian, Middle Eastern and admixed American ancestries, and associated with hypothyroidism and other thyroid disease in South Asians. In Europeans, the TSH polygenic score is associated with thyroid disease, including thyroid cancer and age-of-onset of hypothyroidism and hyperthyroidism. We develop pathway-specific genetic risk scores for TSH levels and use these in phenome-wide association studies to identify potential consequences of pathway perturbation. Together, these findings demonstrate the potential utility of genetic associations to inform future therapeutics and risk prediction for thyroid diseases.

A deep population reference panel of tandem repeat variation

Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3,550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.7 million TR loci. Our catalog reveals novel sequence features influencing TR heterozygosity, identifies population-specific trinucleotide expansions, and finds hundreds of novel eQTL signals. Finally, we generate a phased haplotype panel which can be used to impute most TRs from nearby single nucleotide polymorphisms (SNPs) with high accuracy. Overall, the TR genotypes and reference haplotype panel generated here will serve as valuable resources for future genome-wide and population-wide studies of TRs and their role in human phenotypes.

Macrophages Promote Ovarian Cancer-Mesothelial Cell Adhesion by Upregulation of ITGA2 and VEGFC in Mesothelial Cells

Ovarian cancer is a metastatic disease that frequently exhibits extensive peritoneal dissemination. Recent studies have revealed that noncancerous cells inside the tumor microenvironment, such as macrophages and mesothelial cells, may play a role in ovarian cancer metastasis. In this study, we found that human ovarian cancer cells (A2780 and SKOV3) adhered more to human mesothelial Met5A cells stimulated by macrophages (M-Met5A) in comparison to unstimulated control Met5A cells. The mRNA sequencing revealed that 94 adhesion-related genes, including FMN1, ITGA2, COL13A1, VEGFC, and NRG1, were markedly upregulated in M-Met5A cells. Knockdown of ITGA2 and VEGFC in M-Met5A cells significantly inhibited the adhesion of ovarian cancer cells. Inhibition of the JNK and Akt signaling pathways suppressed ITGA2 and VEGFC expression in M-Met5A cells as well as ovarian cancer-mesothelial cell adhesion. Furthermore, increased production of CC chemokine ligand 2 (CCL2) and CCL5 by macrophages elevated ovarian cancer-mesothelial cell adhesion. These findings imply that macrophages may play a significant role in ovarian cancer-mesothelial cell adhesion by inducing the mesothelial expression of adhesion-related genes via the JNK and Akt pathways.

Computational prediction of disease related lncRNAs using machine learning

Long non-coding RNAs (lncRNAs), which were once considered as transcriptional noise, are now in the limelight of current research. LncRNAs play a major role in regulating various biological processes such as imprinting, cell differentiation, and splicing. The mutations of lncRNAs are involved in various complex diseases. Identifying lncRNA-disease associations has gained a lot of attention as predicting it efficiently will lead towards better disease treatment. In this study, we have developed a machine learning model that predicts disease-related lncRNAs by combining sequence and structure-based features. The features were trained on SVM and Random Forest classifiers. We have compared our method with the state-of-the-art and obtained the highest F1 score of 76% on SVM classifier. Moreover, this study has overcome two serious limitations of the reported method which are lack of redundancy checking and implementation of oversampling for balancing the positive and negative class. Our method has achieved improved performance among machine learning models reported for lncRNA-disease associations. Combining multiple features together specifically lncRNAs sequence mutation has a significant contribution to the disease related lncRNA prediction.

Adaptive sequence divergence forged new neurodevelopmental enhancers in humans

Searches for the genetic underpinnings of uniquely human traits have focused on human-specific divergence in conserved genomic regions, which reflects adaptive modifications of existing functional elements. However, the study of conserved regions excludes functional elements that descended from previously neutral regions. Here, we demonstrate that the fastest-evolved regions of the human genome, which we term "human ancestor quickly evolved regions" (HAQERs), rapidly diverged in an episodic burst of directional positive selection prior to the human-Neanderthal split, before transitioning to constraint within hominins. HAQERs are enriched for bivalent chromatin states, particularly in gastrointestinal and neurodevelopmental tissues, and genetic variants linked to neurodevelopmental disease. We developed a multiplex, single-cell in vivo enhancer assay to discover that rapid sequence divergence in HAQERs generated hominin-unique enhancers in the developing cerebral cortex. We propose that a lack of pleiotropic constraints and elevated mutation rates poised HAQERs for rapid adaptation and subsequent susceptibility to disease.

The role of miR-4469 as a tumor suppressor regulating inflammatory cell infiltration in colorectal cancer

Background

MicroRNA (miRNA) regulates gene expression posttranscriptionally, and some of them function in tumor suppression and can be used in drug development. As a result, identifying and screening miRNAs that suppress tumors would be a significant addition to tumor treatment.

Methods

In this study, we analyzed the miRNA expression profile of colorectal cancer (CRC), constructed a negative regulatory network of the miRNA-target genes, and identified miR-4469 as one of the key tumor suppressors miRNAs. We analyzed the expression and survival of miR-4469 in pan-cancer, experimentally verified the expression level of miR-4469 in CRC cells and the effect on CRC cell proliferation and migration. We screened miR-4469 target genes for enrichment analysis and immune cell infiltration analysis and validated target gene expression to clarify the regulatory mechanisms involved in miR-4469.

Results

miR-4469 was more highly expressed in normal colorectum tissues compared to CRC tissues and correlated with survival time in patients with multiple cancers. It was shown that miR-4469 was highly expressed in normal colon cells and miR-4469 expression could inhibit the proliferation and migration of CRC cells. In addition, studies on the mechanism showed that miR-4469 function is mainly related to the regulation of inflammatory cell infiltration, and the key target genes of miR-4469 in this process are SLC2A3, FGR, PLEKHO2, and MYO1F.

Conclusion

miR-4469 is a tumor suppressor in CRC, and its regulatory mechanism mainly affects the infiltration of inflammatory cells in the cancer tissue.

Methylenedioxy Piperamide-Derived Compound D5 Regulates Inflammatory Cytokine Secretion in a Culture of Human Glial Cells

Neuroinflammation is the cornerstone of most neuronal disorders, particularly neurodegenerative diseases. During the inflammatory process, various pro-inflammatory cytokines, chemokines, and enzymes—such as interleukin 1-β (IL1-β), tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), inducible nitric oxide synthases (iNOS), inhibitory kappa kinase (IKK), and inducible nitric oxide (NO)—are over-expressed in response to every stimulus. Methods: In the present study, we focused on the anti-neuroinflammatory efficacy of (2E,4E)-N,5-bis(benzo[d][1,3]dioxol-5-yl)penta-2,4-dienamide, encoded D5. We investigated the efficacy of D5 on the upstream and downstream products of inflammatory pathways in CHME3 and SVG cell lines corresponding to human microglia and astrocytes, respectively, using various in silico, in vitro, and in situ techniques. Results: The results showed that D5 significantly reduced the level of pro-inflammatory cytokines by up-regulating PPAR-γ expression and suppressing IKK-β, iNOS, NO production, and NF-κB activation in inflamed astrocytes (SVG) and microglia (CHME3) after 24 h of incubation. The data demonstrated remarkably higher efficacy of D5 compared to ASA (Aspirin) in reducing NF-κB-dependent neuroinflammation. Conclusions: We observed that the functional-group alteration had an extreme influence on the levels of druggability and the immunomodulatory properties of two analogs of piperamide, D5, and D4 ((2E,4E)-5-(benzo[d][1,3]dioxol-5-yl)-N-(4-(hydroxymethyl)phenyl)penta-2,4-dienamide)). The present study suggested D5 as a potential anti-neuroinflammatory agent for further in vitro, in vivo, and clinical investigations.

Molecular characterization of matrix metalloproteinase gene family across primates

Deregulation of matrix metalloproteinases (MMPs) contributes considerably to cancers, psychiatric disorders, macular degeneration and bone diseases. The use of humans in the development of MMPs as prognostic biomarkers and therapeutic targets is complicated by many factors, while primate models can be useful alternatives for this purpose. Here, we performed genome-enabled identification of putative MMPs across primate species, and comprehensively investigated the genes. Phylogenetic topology of the MMP family showed each type formulates a distinct clade, and was further clustered to classes, largely agreeing with classification based on biochemical properties and domain organization. Across primates, the excess of candidate sites of positive selection was detected for MMP-19, in addition to 1-3 sites in MMP-8, MMP-10 and MMP-26. MMP-26 showed Ka/Ks value above 1 between human and chimpanzee copies. We observed two copies of MMP-19 in the old-world monkey genomes, suggesting gene duplication at the early stage of or prior to the emergence of the lineage. Furin-activatable MMPs demonstrate the most variable properties regarding Domain organization and gene structure. During human aging, MMP-11 showed gradually decreased expression in testis, so as MMP-2, MMP-14, MMP15 and MMP-28 in ovary, while MMP-7 and MMP-21 showed elevated expression, implying their distinct roles in different reproductive organs. Co-expression clusters were formed among human MMPs both within and across classes, and expression correlation was observed in MMP genes across primates. Our results illuminate the utilization of MMPs for the discovery of prognostic biomarkers and therapeutic targets for aging-related diseases and carry new messages on MMP classification.

CRISPRs in the human genome are differentially expressed between malignant and normal adjacent to tumor tissue

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) have been identified in bacteria, archaea and mitochondria of plants, but not in eukaryotes. Here, we report the discovery of 12,572 putative CRISPRs randomly distributed across the human chromosomes, which we termed hCRISPRs. By using available transcriptome datasets, we demonstrate that hCRISPRs are distinctively expressed as small non-coding RNAs (sncRNAs) in cell lines and human tissues. Moreover, expression patterns thereof enabled us to distinguish normal from malignant tissues. In prostate cancer, we confirmed the differential hCRISPR expression between normal adjacent and malignant primary prostate tissue by RT-qPCR and demonstrate that the SHERLOCK and DETECTR dipstick tools are suitable to detect these sncRNAs. We anticipate that the discovery of CRISPRs in the human genome can be further exploited for diagnostic purposes in cancer and other medical conditions, which certainly will lead to the development of point-of-care tests based on the differential expression of the hCRISPRs.

CRISPR elements in the human genome are expressed in both healthy tissues and tumors but with distinct patterns, representing a potential biomarker for cancer.

Virtual Gene Concept and a Corresponding Pragmatic Research Program in Genetical Data Science

Mendel proposed an experimentally verifiable paradigm of particle-based heredity that has been influential for over 150 years. The historical arguments have been reflected in the near past as Mendel's concept has been diversified by new types of omics data. As an effect of the accumulation of omics data, a virtual gene concept forms, giving rise to genetical data science. The concept integrates genetical, functional, and molecular features of the Mendelian paradigm. I argue that the virtual gene concept should be deployed pragmatically. Indeed, the concept has already inspired a practical research program related to systems genetics. The program includes questions about functionality of structural and categorical gene variants, about regulation of gene expression, and about roles of epigenetic modifications. The methodology of the program includes bioinformatics, machine learning, and deep learning. Education, funding, careers, standards, benchmarks, and tools to monitor research progress should be provided to support the research program.

Meta-analysis and Consolidation of Farnesoid X Receptor Chromatin Immunoprecipitation Sequencing Data Across Different Species and Conditions

Farnesoid X receptor (FXR) is a nuclear receptor that controls gene regulation of different metabolic pathways and represents an upcoming drug target for various liver diseases. Several data sets on genome-wide FXR binding in different species and conditions exist. We have previously reported that these data sets are heterogeneous and do not cover the full spectrum of potential FXR binding sites. Here, we report the first meta-analysis of all publicly available FXR chromatin immunoprecipitation sequencing (ChIP-seq) data sets from mouse, rat, and human across different conditions using a newly generated analysis pipeline. All publicly available single data sets were biocurated in a standardized manner and compared on every relevant level from raw reads to affected functional pathways. Individual murine data sets were then virtually merged into a single unique "FXR binding atlas" spanning all potential binding sites across various conditions. Comparison of the single biocurated data sets showed that the overlap of FXR binding sites between different species is modest and ranges from 48% (mouse-human) to 55% (mouse-rat). Moreover, in vivo data among different species are more similar than human in vivo data compared to human in vitro data. The consolidated murine global FXR binding atlas virtually increases sequencing depth and allows recovering more and novel potential binding sites and signaling pathways that were missed in the individual data sets. The FXR binding atlas is publicly searchable (https://fxratlas.tugraz.at). Conclusion: Published single FXR ChIP-seq data sets and large-scale integrated omics data sets do not cover the full spectrum of FXR binding. Combining different individual data sets and creating an "FXR super-binding atlas" enhances understanding of FXR signaling capacities across different conditions. This is important when considering the potential wide spectrum for drugs targeting FXR in liver diseases.

DNA methylation profile of liver of mice conceived by in vitro fertilization

Offspring generated by in vitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

Bioinformatics Accelerates the Major Tetrad: A Real Boost for the Pharmaceutical Industry

With advanced technology and its development, bioinformatics is one of the avant-garde fields that has managed to make amazing progress in the pharmaceutical-medical field by modeling the infrastructural dimensions of healthcare and integrating computing tools in drug innovation, facilitating prevention, detection/more accurate diagnosis, and treatment of disorders, while saving time and money. By association, bioinformatics and pharmacovigilance promoted both sample analyzes and interpretation of drug side effects, also focusing on drug discovery and development (DDD), in which systems biology, a personalized approach, and drug repositioning were considered together with translational medicine. The role of bioinformatics has been highlighted in DDD, proteomics, genetics, modeling, miRNA discovery and assessment, and clinical genome sequencing. The authors have collated significant data from the most known online databases and publishers, also narrowing the diversified applications, in order to target four major areas (tetrad): DDD, anti-microbial research, genomic sequencing, and miRNA research and its significance in the management of current pandemic context. Our analysis aims to provide optimal data in the field by stratification of the information related to the published data in key sectors and to capture the attention of researchers interested in bioinformatics, a field that has succeeded in advancing the healthcare paradigm by introducing developing techniques and multiple database platforms, addressed in the manuscript.

Population-specific causal disease effect sizes in functionally important regions impacted by selection

Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.

Sex-specific epigenetic profile of inner cell mass of mice conceived in vivo or by IVF

The preimplantation stage of development is exquisitely sensitive to environmental stresses, and changes occurring during this developmental phase may have long-term health effects. Animal studies indicate that IVF offspring display metabolic alterations, including hypertension, glucose intolerance and cardiac hypertrophy, often in a sexual dimorphic fashion. The detailed nature of epigenetic changes following in-vitro culture is, however, unknown. This study was performed to evaluate the epigenetic (using whole-genome bisulfite sequencing (WGBS) and assay for transposase-accessible chromatin using sequencing (ATAC-seq)) and transcriptomic changes (using RNA-seq) occurring in the inner cell mass (ICM) of male or female mouse embryos generated in vivo or by IVF. We found that the ICM of IVF embryos, compared to the in-vivo ICM, differed in 3% of differentially methylated regions (DMRs), of which 0.1% were located on CpG islands. ATAC-seq revealed that 293 regions were more accessible and 101 were less accessible in IVF embryos, while RNA-seq revealed that 21 genes were differentially regulated in IVF embryos. Functional enrichment analysis revealed that stress signalling (STAT and NF-kB signalling), developmental processes and cardiac hypertrophy signalling showed consistent changes in WGBS and ATAC-seq platforms. In contrast, male and female embryos showed minimal changes. Male ICM had an increased number of significantly hyper-methylated DMRs, while only 27 regions showed different chromatin accessibility and only one gene was differentially expressed. In summary, this study provides the first comprehensive analysis of DNA methylation, chromatin accessibility and RNA expression changes induced by IVF in male and female ICMs. This dataset can be of value to all researchers interested in the developmental origin of health and disease (DOHaD) hypothesis and might lead to a better understanding of how early embryonic manipulation may affect adult health.

Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.

PACVr: plastome assembly coverage visualization in R

Background

Plastid genomes typically display a circular, quadripartite structure with two inverted repeat regions, which challenges automatic assembly procedures. The correct assembly of plastid genomes is a prerequisite for the validity of subsequent analyses on genome structure and evolution. The average coverage depth of a genome assembly is often used as an indicator of assembly quality. Visualizing coverage depth across a draft genome is a critical step, which allows users to inspect the quality of the assembly and, where applicable, identify regions of reduced assembly confidence. Despite the interplay between genome structure and assembly quality, no contemporary, user-friendly software tool can visualize the coverage depth of a plastid genome assembly while taking its quadripartite genome structure into account. A software tool is needed that fills this void.

Results

We introduce ’PACVr’, an R package that visualizes the coverage depth of a plastid genome assembly in relation to the circular, quadripartite structure of the genome as well as the individual plastome genes. By using a variable window approach, the tool allows visualizations on different calculation scales. It also confirms sequence equality of, as well as visualizes gene synteny between, the inverted repeat regions of the input genome. As a tool for plastid genomics, PACVr provides the functionality to identify regions of coverage depth above or below user-defined threshold values and helps to identify non-identical IR regions. To allow easy integration into bioinformatic workflows, PACVr can be invoked from a Unix shell, facilitating its use in automated quality control. We illustrate the application of PACVr on four empirical datasets and compare visualizations generated by PACVr with those of alternative software tools.

Conclusions

PACVr provides a user-friendly tool to visualize (a) the coverage depth of a plastid genome assembly on a circular, quadripartite plastome map and in relation to individual plastome genes, and (b) gene synteny across the inverted repeat regions. It contributes to optimizing plastid genome assemblies and increasing the reliability of publicly available plastome sequences. The software, example datasets, technical documentation, and a tutorial are available with the package at https://cran.r-project.org/package=PACVr.

Processing of big heterogeneous genomic datasets for tertiary analysis of Next Generation Sequencing data

MOTIVATION

We previously proposed a paradigm shift in genomic data management, based on the Genomic Data Model (GDM) for mediating existing data formats and on the GenoMetric Query Language (GMQL) for supporting, at a high level of abstraction, data extraction and the most common data-driven computations required by tertiary data analysis of Next Generation Sequencing datasets. Here, we present a new GMQL-based system with enhanced accessibility, portability, scalability and performance.

RESULTS

The new system has a well-designed modular architecture featuring: (i) an intermediate representation supporting many different implementations (including Spark, Flink and SciDB); (ii) a high-level technology-independent repository abstraction, supporting different repository technologies (e.g., local file system, Hadoop File System, database or others); (iii) several system interfaces, including a user-friendly Web-based interface, a Web Service interface, and a programmatic interface for Python language. Biological use case examples, using public ENCODE, Roadmap Epigenomics and TCGA datasets, demonstrate the relevance of our work.

AVAILABILITY AND IMPLEMENTATION

The GMQL system is freely available for non-commercial use as open source project at: http://www.bioinformatics.deib.polimi.it/GMQLsystem/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Hominoid-Specific Transposable Elements and KZFPs Facilitate Human Embryonic Genome Activation and Control Transcription in Naive Human ESCs

Expansion of transposable elements (TEs) coincides with evolutionary shifts in gene expression. TEs frequently harbor binding sites for transcriptional regulators, thus enabling coordinated genome-wide activation of species- and context-specific gene expression programs, but such regulation must be balanced against their genotoxic potential. Here, we show that Krüppel-associated box (KRAB)-containing zinc finger proteins (KZFPs) control the timely and pleiotropic activation of TE-derived transcriptional cis regulators during early embryogenesis. Evolutionarily recent SVA, HERVK, and HERVH TE subgroups contribute significantly to chromatin opening during human embryonic genome activation and are KLF-stimulated enhancers in naive human embryonic stem cells (hESCs). KZFPs of corresponding evolutionary ages are simultaneously induced and repress the transcriptional activity of these TEs. Finally, the same KZFP-controlled TE-based enhancers later serve as developmental and tissue-specific enhancers. Thus, by controlling the transcriptional impact of TEs during embryogenesis, KZFPs facilitate their genome-wide incorporation into transcriptional networks, thereby contributing to human genome regulation.

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KLFs foster EGA by activating enhancers embedded in young TEs (TEENhancers)

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TEENhancers confer a degree of species specificity to early genome activation

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TEENhancers stimulate the expression of KZFPs responsible for their repression

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These KZFPs in turn facilitate TEENhancers’ exaptation as tissue-specific regulators

A genome-wide association study of tramadol metabolism from post-mortem samples

Phase I tramadol metabolism requires cytochrome p450 family 2, subfamily D, polypeptide 6 (CYP2D6) to form O-desmethyltramadol (M1). CYP2D6 genetic variants may infer metabolizer phenotype; however, drug ADME (absorption, distribution, metabolism, and excretion) and response depend on protein pathway(s), not CYP2D6 alone. There is a paucity of data regarding the contribution of trans-acting proteins to idiosyncratic phenotypes following drug exposure. A genome-wide association study identified five markers (rs79983226/kgp11274252, rs9384825, rs62435418/kgp10370907, rs72732317/kgp3743668, and rs184199168/exm1592932) associated with the conversion of tramadol to M1 (M1:T). These SNPs reside within five genes previously implicated with adverse reactions. Analysis of accompanying toxicological meta-data revealed a significant positive linear relationship between M1:T and degree of sample polypharmacy. Taken together, these data identify candidate loci for potential clinical inferences of phenotype following exposure to tramadol and highlight sample polypharmacy as a possible diagnostic covariate in post-mortem genetic studies.

Predicting Genes in Single Genomes with AUGUSTUS

AUGUSTUS is a tool for finding protein-coding genes and their exon-intron structure in genomic sequences. It does not necessarily require additional experimental input, as it can be applied in so-called ab initio mode. However, extrinsic evidence from various sources such as transcriptome sequencing or the annotations of closely related genomes can be integrated in order to improve the accuracy and completeness of the annotation. AUGUSTUS can be applied to single genomes, or simultaneously to several aligned genomes. Here, we describe steps required for training AUGUSTUS for the annotation of individual genomes and the steps to do the actual structural annotation. Further, we describe the generation and integration of evidence from various sources of extrinsic evidence. © 2018 by John Wiley & Sons, Inc.

Widespread roles of enhancer-like transposable elements in cell identity and long-range genomic interactions

A few families of transposable elements (TEs) have been shown to evolve into cis-regulatory elements (CREs). Here, to extend these studies to all classes of TEs in the human genome, we identified widespread enhancer-like repeats (ELRs) and find that ELRs reliably mark cell identities, are enriched for lineage-specific master transcription factor binding sites, and are mostly primate-specific. In particular, elements of MIR and L2 TE families whose abundance co-evolved across chordate genomes, are found as ELRs in most human cell types examined. MIR and L2 elements frequently share long-range intra-chromosomal interactions and binding of physically interacting transcription factors. We validated that eight L2 and nine MIR elements function as enhancers in reporter assays, and among 20 MIR-L2 pairings, one MIR repressed and one boosted the enhancer activity of L2 elements. Our results reveal a previously unappreciated co-evolution and interaction between two TE families in shaping regulatory networks.

Genome wide analysis of meiotic recombination in yeast: For a few SNPs more

Diploid organisms undergo meiosis to produce haploid germ cells. Crossover events during meiosis promote genetic diversity and facilitate accurate chromosome segregation. The baker's yeast Saccharomyces cerevisiae is extensively used as a model for analysis of meiotic recombination. Conventional methods for measuring recombination events in S. cerevisiae have been limited by the number and density of genetic markers. Next generation sequencing (NGS)-based analysis of hybrid yeast genomes bearing thousands of heterozygous single nucleotide polymorphism (SNP) markers has revolutionized analysis of meiotic recombination. By facilitating analysis of marker segregation in the whole genome with unprecedented resolution, this method has resulted in the generation of high-resolution recombination maps in wild-type and meiotic mutants. These studies have provided novel insights into the mechanism of meiotic recombination. In this review, we discuss the methodology, challenges, insights and future prospects of using NGS-based methods for whole genome analysis of meiotic recombination. The objective is to facilitate the use of these high through-put sequencing methods for the analysis of meiotic recombination given their power to provide significant new insights into the process. © 2018 The Authors. IUBMB Life published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 70(8):743-752, 2018.

Minor zygotic gene activation is essential for mouse preimplantation development

In mice, transcription initiates at the mid-one-cell stage and transcriptional activity dramatically increases during the two-cell stage, a process called zygotic gene activation (ZGA). Associated with ZGA is a marked change in the pattern of gene expression that occurs after the second round of DNA replication. To distinguish ZGA before and after the second-round DNA replication, the former and latter are called minor and major ZGA, respectively. Although major ZGA are required for development beyond the two-cell stage, the function of minor ZGA is not well understood. Transiently inhibiting minor ZGA with 5, 6-dichloro-1-β-d-ribofuranosyl-benzimidazole (DRB) resulted in the majority of embryos arresting at the two-cell stage and retention of the H3K4me3 mark that normally decreases. After release from DRB, at which time major ZGA normally occurred, transcription initiated with characteristics of minor ZGA but not major ZGA, although degradation of maternal mRNA normally occurred. Thus, ZGA occurs sequentially starting with minor ZGA that is critical for the maternal-to-zygotic transition.

Purifying and positive selection in the evolution of stop codons

Modes of evolution of stop codons in protein-coding genes, especially the conservation of UAA, have been debated for many years. We reconstructed the evolution of stop codons in 40 groups of closely related prokaryotic and eukaryotic genomes. The results indicate that the UAA codons are maintained by purifying selection in all domains of life. In contrast, positive selection appears to drive switches from UAG to other stop codons in prokaryotes but not in eukaryotes. Changes in stop codons are significantly associated with increased substitution frequency immediately downstream of the stop. These positions are otherwise more strongly conserved in evolution compared to sites farther downstream, suggesting that such substitutions are compensatory. Although GC content has a major impact on stop codon frequencies, its contribution to the decreased frequency of UAA differs between bacteria and archaea, presumably, due to differences in their translation termination mechanisms.

The clinical value, regulatory mechanisms, and gene network of the cancer-testis gene STK31 in pancreatic cancer

We aimed to identify STK31 as a cancer-testis (CT) gene and to explore its potential clinical value, regulatory mechanisms, and gene network in pancreatic cancer (PC). Gene expression data were generated from normal organ samples and pancreatic cancer samples from three public databases. STK31 expression patterns in normal and PC tissues were identified, and we explored its regulatory mechanisms. Gene ontology (GO) and pathway analyses of STK31-related genes were performed and an STK31 protein-protein interaction (PPI) network was constructed. STK31 was confirmed as a CT gene in PC and its expression was significantly higher in patients with new neoplasm compared with patients without new neoplasm (P = 0.046) and in more advanced pathologic stages than in earlier stages (P = 0.002); methylation level correlated negatively with STK31 expression. In total, 757 STK31-related genes were identified, and were significantly enriched in terms of polymorphisms and alternative splicings. The PPI network predicted that STK31 was physically associated with the PIWI (originally P-element Induced WImpy testis in Drosophila) and Tudor families.

Associations among oxytocin receptor gene (OXTR) DNA methylation in adulthood, exposure to early life adversity, and childhood trajectories of anxiousness

Recent models propose deoxyribonucleic acid methylation of key neuro-regulatory genes as a molecular mechanism underlying the increased risk of mental disorder associated with early life adversity (ELA). The goal of this study was to examine the association of ELA with oxytocin receptor gene (OXTR) methylation among young adults. Drawing from a 21-year longitudinal cohort, we compared adulthood OXTR methylation frequency of 46 adults (23 males and 23 females) selected for high or low ELA exposure based on childhood socioeconomic status and exposure to physical and sexual abuse during childhood and adolescence. Associations between OXTR methylation and teacher-rated childhood trajectories of anxiousness were also assessed. ELA exposure was associated with one significant CpG site in the first intron among females, but not among males. Similarly, childhood trajectories of anxiousness were related to one significant CpG site within the promoter region among females, but not among males. This study suggests that females might be more sensitive to the impact of ELA on OXTR methylation than males.

Identification of candidate genes associated with triple negative breast cancer

When triple negative breast cancer (TNBC) are analyzed by gene expression profiling different subclasses are identified, at least one characterized by genes related to immune signaling mechanisms supporting the role of these genes in the cancers. In an earlier study we observed differences in TNBC cell lines with respect to their expression of the cytokine IL32. Our analyses showed that certain cell lines expressed higher levels of the cytokine compared to others. Because TNBC are heterogeneous and immune-related genes appear to play a pivotal role in these cancers, we chose to examine the transcriptomes of the different cell lines based on IL32 expression. We performed group analyses of TNBC cell lines demonstrating high IL32 compared to low IL32 levels and identified IL32, GATA3, MYBL1, ETS1, PTX3 and TMEM158 as differentially associated with a subpopulation of TNBC. The six candidate genes were validated experimental and in different patient datasets. The genes distinguished a subset of TNBC from other TNBC, and TNBC from normal, luminal A, luminal B, and HER2 patient samples. The current project serves as a preliminary study in which we outline the discovery and validation of our list of six candidate genes.

Using the NONCODE Database Resource

NONCODE is a comprehensive database that aims to present the most complete collection and annotation of non-coding RNAs, especially long non-coding RNAs (lncRNA genes), and thus NONCODE is essential to modern biological and medical research. Scientists are producing a flood of new data from which new lncRNA genes and lncRNA-disease relationships are continually being identified. NONCODE assimilates such information from a wide variety of sources including published articles, RNA-seq data, micro-array data and databases on genetic variation (dbSNP) and genome-wide associations (GWAS). NONCODE organizes all this information and makes it freely available to the public via the Internet. The NONCODE protocol provides step-by-step instructions on how to browse and search lncRNA information such as sequence, expression, and disease relationships, how to use the tools for functional prediction, species conservation assays, blast analysis, identifier conversion, and, finally, how to submit sequences to identify lncRNA genes. As of Dec 2016, NONCODE has cataloged 487,851 lncRNA genes sequenced from 16 species. © 2017 by John Wiley & Sons, Inc.

Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype

BACKGROUND

Genetic studies for complex diseases have predominantly discovered main effects at individual loci, but have not focused on genomic and environmental contexts important for a phenotype. Gene Set Enrichment Analysis (GSEA) aims to address this by identifying sets of genes or biological pathways contributing to a phenotype, through gene-gene interactions or other mechanisms, which are not the focus of conventional association methods.

RESULTS

Approaches that utilize GSEA can now take input from array chips, either gene-centric or genome-wide, but are highly sensitive to study design, SNP selection and pruning strategies, SNP-to-gene mapping, and pathway definitions. Here, we present lessons learned from our experience with GSEA of heart failure, a particularly challenging phenotype due to its underlying heterogeneous etiology.

CONCLUSIONS

This case study shows that proper data handling is essential to avoid false-positive results. Well-defined pipelines for quality control are needed to avoid reporting spurious results using GSEA.

Global genetic variation of select opiate metabolism genes in self-reported healthy individuals

CYP2D6 is a key pharmacogene encoding an enzyme impacting poor, intermediate, extensive and ultrarapid phase I metabolism of many marketed drugs. The pharmacogenetics of opiate drug metabolism is particularly interesting due to the relatively high incidence of addiction and overdose. Recently, trans-acting opiate metabolism and analgesic response enzymes (UGT2B7, ABCB1, OPRM1 and COMT) have been incorporated into pharmacogenetic studies to generate more comprehensive metabolic profiles of patients. With use of massively parallel sequencing, it is possible to identify additional polymorphisms that fine tune, or redefine, previous pharmacogenetic findings, which typically rely on targeted approaches. The 1000 Genomes Project data were analyzed to describe population genetic variation and statistics for these five genes in self-reported healthy individuals in five global super- and 26 sub-populations. Findings on the variation of these genes in various populations expand baseline understanding of pharmacogenetically relevant polymorphisms for future studies of affected cohorts.

Significant Role of Segmental Duplications and SIDD Sites in Chromosomal Translocations of Hematological Malignancies: A Multi-parametric Bioinformatic Analysis

Recurrent non-random chromosomal translocations are hallmark characteristics of leukemogenesis, and however, molecular mechanisms underlying these rearrangements are less explored. The fundamental question is, why and how chromosomes break and reunite so precisely in the genome. Meticulous understanding of mechanism leading to chromosomal rearrangement can be achieved by characterizing breakpoints. To address this hypothesis, a novel multi-parametric computational approach for characterization of major leukemic translocations within and around breakpoint region was performed. To best of our knowledge, this bioinformatic analysis is unique in finding the presence of segmental duplications (SDs) flanking breakpoints of all major leukemic translocation. Breakpoint islands (BpIs) were analyzed for stress-induced duplex destabilization (SIDD) sites along with other complex genomic architecture and physicochemical properties. Our study distinctly emphasizes on the probable correlative role of SDs, SIDD sites and various genomic features in the occurrence of breakpoints. Further, it also highlights potential features which may be playing a crucial role in causing double-strand breaks, leading to translocation.

MathIOmica: An Integrative Platform for Dynamic Omics

Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine approach. It provides multiple tools to facilitate bioinformatics analysis, including importing data, annotating datasets, tracking missing values, normalizing data, clustering and visualizing the classification of data, carrying out annotation and enumeration of ontology memberships and pathway analysis. We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science and engineering fields transitioning into genomics, bioinformatics and omics data integration.

Custom Gene Capture and Next-Generation Sequencing to Resolve Discordant ALK Status by FISH and IHC in Lung Adenocarcinoma

INTRODUCTION

We performed a genomic study in lung adenocarcinoma cases with discordant anaplastic lymphoma receptor tyrosine kinase gene (ALK) status by fluorescent in situ hybridization (FISH) and immunohistochemical (IHC) analysis.

METHODS

DNA from formalin-fixed paraffin-embedded tissues of 16 discordant (four FISH-positive/IHC-negative and 12 FISH-negative/IHC-positive) cases by Vysis ALK Break Apart FISH and ALK IHC testing (ALK1 clone) were subjected to whole gene capture and next-generation sequencing (NGS) of nine genes, including ALK, echinoderm microtubule associated protein like 4 gene (EML4), kinesin family member 5B gene (KIF5B), staphylococcal nuclease and tudor domain containing 1 gene (SND1), BRAF, ret proto-oncogene (RET), ezrin gene (EZR), ROS1, and telomerase reverse transcriptase (TERT). All discordant cases (except one FISH-negative/IHC-positive case without sufficient tissue) were analyzed by IHC with D5F3 antibody. In one case with fresh frozen tissue, whole transcriptome sequencing was also performed. Twenty-six concordant (16 FISH-positive/IHC-positive and 10 FISH-negative/IHC-negative) cases were included as controls.

RESULTS

In four ALK FISH-positive/IHC-negative cases, no EML4-ALK fusion gene was observed by NGS, but in one case using fresh frozen tissue, we identified EML4-baculoviral AIP repeat containing 6 gene (BIRC6) and AP2 associated kinase 1 gene (AAK1)-ALK fusion genes. Whole transcriptome sequencing revealed a highly expressed EML4-BIRC6 fusion transcript and a minimally expressed AAK1 transcript. Among the 12 FISH-negative/IHC-positive cases, no evidence of ALK gene rearrangement was detected by NGS. Eleven of 12 FISH-negative/IHC-positive cases detected by ALK1 clone were concordant by repeat ALK IHC with D5F3 antibody (i.e., FISH-negative/IHC-negative by D5F3 clone). Among the 16 ALK FISH-positive/IHC-positive positive controls, whole gene capture identified ALK gene fusion in 15 cases, including in one case with Huntington interacting protein 1 gene (HIP1)-ALK. No ALK fusion gene was observed in any of the 10 FISH-negative/IHC-negative cases. Other fusion genes involving ROS1, EZR, BRAF, and SND1 were also found.

CONCLUSIONS

ALK FISH results appeared to be false-positive in three of four FISH-positive/IHC-negative cases, whereas no false-negative ALK FISH case was identified among 12 ALK FISH-negative/IHC-positive cases by ALK1 clone, which was in keeping with the concordant FISH-negative/IHC-negative status by D5F3 clone. Our targeted whole gene capture approach using formalin-fixed paraffin embedded samples was effective for detecting rearrangements involving ALK and other actionable oncogenes.

Genome-Wide Identification of Regulatory Sequences Undergoing Accelerated Evolution in the Human Genome

Accelerated evolution of regulatory sequence can alter the expression pattern of target genes, and cause phenotypic changes. In this study, we used DNase I hypersensitive sites (DHSs) to annotate putative regulatory sequences in the human genome, and conducted a genome-wide analysis of the effects of accelerated evolution on regulatory sequences. Working under the assumption that local ancient repeat elements of DHSs are under neutral evolution, we discovered that ∼0.44% of DHSs are under accelerated evolution (ace-DHSs). We found that ace-DHSs tend to be more active than background DHSs, and are strongly associated with epigenetic marks of active transcription. The target genes of ace-DHSs are significantly enriched in neuron-related functions, and their expression levels are positively selected in the human brain. Thus, these lines of evidences strongly suggest that accelerated evolution on regulatory sequences plays important role in the evolution of human-specific phenotypes.

Massively parallel sequencing of 68 insertion/deletion markers identifies novel microhaplotypes for utility in human identity testing

Short tandem repeat (STR) loci are the traditional markers used for kinship, missing persons, and direct comparison human identity testing. These markers hold considerable value due to their highly polymorphic nature, amplicon size, and ability to be multiplexed. However, many STRs are still too large for use in analysis of highly degraded DNA. Small bi-allelic polymorphisms, such as insertions/deletions (INDELs), may be better suited for analyzing compromised samples, and their allele size differences are amenable to analysis by capillary electrophoresis. The INDEL marker allelic states range in size from 2 to 6 base pairs, enabling small amplicon size. In addition, heterozygote balance may be increased by minimizing preferential amplification of the smaller allele, as is more common with STR markers. Multiplexing a large number of INDELs allows for generating panels with high discrimination power. The Nextera™ Rapid Capture Custom Enrichment Kit (Illumina, Inc., San Diego, CA) and massively parallel sequencing (MPS) on the Illumina MiSeq were used to sequence 68 well-characterized INDELs in four major US population groups. In addition, the STR Allele Identification Tool: Razor (STRait Razor) was used in a novel way to analyze INDEL sequences and detect adjacent single nucleotide polymorphisms (SNPs) and other polymorphisms. This application enabled the discovery of unique allelic variants, which increased the discrimination power and decreased the single-locus random match probabilities (RMPs) of 22 of these well-characterized INDELs which can be considered as microhaplotypes. These findings suggest that additional microhaplotypes containing human identification (HID) INDELs may exist elsewhere in the genome.

How far from the SNP may the causative genes be?

While GWAS identify many disease-associated SNPs, using them to decipher disease mechanisms is hindered by the difficulty in mapping SNPs to genes. Most SNPs are in non-coding regions and it is often hard to identify the genes they implicate. To explore how far the SNP may be from the affected genes we used a pathway-based approach. We found that affected genes are often up to 2 Mbps away from the associated SNP, and are not necessarily the closest genes to the SNP. Existing approaches for mapping SNPs to genes leave many SNPs unmapped to genes and reveal only 86 significant phenotype-pathway associations for all known GWAS hits combined. Using the pathway-based approach we propose here allows mapping of virtually all SNPs to genes and reveals 435 statistically significant phenotype-pathway associations. In search for mechanisms that may explain the relationships between SNPs and distant genes, we found that SNPs that are mapped to distant genes have significantly more large insertions/deletions around them than other SNPs, suggesting that these SNPs may sometimes be markers for large insertions/deletions that may affect large genomic regions.

A Meta-Analysis of Retinoblastoma Copy Numbers Refines the List of Possible Driver Genes Involved in Tumor Progression

BACKGROUND

While RB1 loss initiates retinoblastoma development, additional somatic copy number alterations (SCNAs) can drive tumor progression. Although SCNAs have been identified with good concordance between studies at a cytoband resolution, accurate identification of single genes for all recurrent SCNAs is still challenging. This study presents a comprehensive meta-analysis of genome-wide SCNAs integrated with gene expression profiling data, narrowing down the list of plausible retinoblastoma driver genes.

METHODS

We performed SCNA profiling of 45 primary retinoblastoma samples and eight retinoblastoma cell lines by high-resolution microarrays. We combined our data with genomic, clinical and histopathological data of ten published genome-wide SCNA studies, which strongly enhanced the power of our analyses (N = 310).

RESULTS

Comprehensive recurrence analysis of SCNAs in all studies integrated with gene expression data allowed us to reduce candidate gene lists for 1q, 2p, 6p, 7q and 13q to a limited gene set. Besides the well-established driver genes RB1 (13q-loss) and MYCN (2p-gain) we identified CRB1 and NEK7 (1q-gain), SOX4 (6p-gain) and NUP205 (7q-gain) as novel retinoblastoma driver candidates. Depending on the sample subset and algorithms used, alternative candidates were identified including MIR181 (1q-gain) and DEK (6p gain). Remarkably, our study showed that copy number gains rarely exceeded change of one copy, even in pure tumor samples with 100% homozygosity at the RB1 locus (N = 34), which is indicative for intra-tumor heterogeneity. In addition, profound between-tumor variability was observed that was associated with age at diagnosis and differentiation grades.

INTERPRETATION

Since focal alterations at commonly altered chromosome regions were rare except for 2p24.3 (MYCN), further functional validation of the oncogenic potential of the described candidate genes is now required. For further investigations, our study provides a refined and revised set of candidate retinoblastoma driver genes.

miRepress: modelling gene expression regulation by microRNA with non-conventional binding sites

Some earlier studies have reported an alternative mode of microRNA-target interaction. We detected target regions within mRNA transcripts from AGO PAR-CLIP that did not contain any conventional microRNA seed pairing but only had non-conventional binding sites with microRNA 3' end. Our study from 7 set of data that measured global protein fold change after microRNA transfection pointed towards the association of target protein fold change with 6-mer and 7-mer target sites involving microRNA 3' end. We developed a model to predict the degree of microRNA target regulation in terms of protein fold changes from the number of different conventional and non-conventional target sites present in the target, and found significant correlation of its output with protein expression changes. We validated the effect of non-conventional interactions with target by modulating the abundance of microRNA in a human breast cancer cell line MCF-7. The validation was done using luciferase assay and immunoblot analysis for our predicted non-conventional microRNA-target pair WNT1 (3' UTR) and miR-367-5p and immunoblot analysis for another predicted non-conventional microRNA-target pair MYH10 (coding region) and miR-181a-5p. Both experiments showed inhibition of targets by transfection of microRNA mimics that were predicted to have only non-conventional sites.

Looking into the past - the reaction of three grouse species to climate change over the last million years using whole genome sequences

Tracking past population fluctuations can give insight into current levels of genetic variation present within species. Analysing population dynamics over larger timescales can be aligned to known climatic changes to determine the response of species to varying environments. Here, we applied the Pairwise Sequentially Markovian Coalescent (psmc) model to infer past population dynamics of three widespread grouse species; black grouse, willow grouse and rock ptarmigan. This allowed the tracking of the effective population size (Ne ) of all three species beyond 1 Mya, revealing that (i) early Pleistocene cooling (~2.5 Mya) caused an increase in the willow grouse and rock ptarmigan populations, (ii) the mid-Brunhes event (~430 kya) and following climatic oscillations decreased the Ne of willow grouse and rock ptarmigan, but increased the Ne of black grouse and (iii) all three species reacted differently to the last glacial maximum (LGM) - black grouse increased prior to it, rock ptarmigan experienced a severe bottleneck and willow grouse was maintained at large population size. We postulate that the varying psmc signal throughout the LGM depicts only the local history of the species. Nevertheless, the large population fluctuations in willow grouse and rock ptarmigan indicate that both species are opportunistic breeders while black grouse tracks the climatic changes more slowly and is maintained at lower Ne . Our results highlight the usefulness of the psmc approach in investigating species' reaction to climate change in the deep past, but also that caution should be taken in drawing general conclusions about the recent past.

BigQ: a NoSQL based framework to handle genomic variants in i2b2

Background

Precision medicine requires the tight integration of clinical and molecular data. To this end, it is mandatory to define proper technological solutions able to manage the overwhelming amount of high throughput genomic data needed to test associations between genomic signatures and human phenotypes. The i2b2 Center (Informatics for Integrating Biology and the Bedside) has developed a widely internationally adopted framework to use existing clinical data for discovery research that can help the definition of precision medicine interventions when coupled with genetic data. i2b2 can be significantly advanced by designing efficient management solutions of Next Generation Sequencing data.

Results

We developed BigQ, an extension of the i2b2 framework, which integrates patient clinical phenotypes with genomic variant profiles generated by Next Generation Sequencing. A visual programming i2b2 plugin allows retrieving variants belonging to the patients in a cohort by applying filters on genomic variant annotations. We report an evaluation of the query performance of our system on more than 11 million variants, showing that the implemented solution scales linearly in terms of query time and disk space with the number of variants.

Conclusions

In this paper we describe a new i2b2 web service composed of an efficient and scalable document-based database that manages annotations of genomic variants and of a visual programming plug-in designed to dynamically perform queries on clinical and genetic data. The system therefore allows managing the fast growing volume of genomic variants and can be used to integrate heterogeneous genomic annotations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0861-0) contains supplementary material, which is available to authorized users.

iRegulon and i-cisTarget: Reconstructing Regulatory Networks Using Motif and Track Enrichment

Gene expression profiling is often used to identify genes that are co-expressed in a biological process or disease. Downstream analyses of co-expressed gene sets using bioinformatics methods can reveal candidate transcription factors (TF) that co-regulate these genes, based on the presence of shared TF binding sites. Drawing gene regulatory networks that connect TFs to their predicted target genes can uncover gene modules that implement a particular function. Here, we describe several protocols to analyze any set of co-expressed genes using iRegulon and i-cisTarget. These tools perform regulatory sequence analysis (motif discovery) and integrate and mine large collections of existing regulatory data, such as ChIP-Seq, DHS-seq, and FAIRE-seq (track discovery). While iRegulon focuses on sets of co-expressed genes, i-cisTarget also analyses genomic regions as input. The following protocols describe how to install and use these tools, how to interpret the obtained results, and will thus help to create meaningful regulatory networks.

Repression of Esophageal Neoplasia and Inflammatory Signaling by Anti-miR-31 Delivery In Vivo

BACKGROUND

Overexpression of microRNA-31 (miR-31) is implicated in the pathogenesis of esophageal squamous cell carcinoma (ESCC), a deadly disease associated with dietary zinc deficiency. Using a rat model that recapitulates features of human ESCC, the mechanism whereby Zn regulates miR-31 expression to promote ESCC is examined.

METHODS

To inhibit in vivo esophageal miR-31 overexpression in Zn-deficient rats (n = 12-20 per group), locked nucleic acid-modified anti-miR-31 oligonucleotides were administered over five weeks. miR-31 expression was determined by northern blotting, quantitative polymerase chain reaction, and in situ hybridization. Physiological miR-31 targets were identified by microarray analysis and verified by luciferase reporter assay. Cellular proliferation, apoptosis, and expression of inflammation genes were determined by immunoblotting, caspase assays, and immunohistochemistry. The miR-31 promoter in Zn-deficient esophagus was identified by ChIP-seq using an antibody for histone mark H3K4me3. Data were analyzed with t test and analysis of variance. All statistical tests were two-sided.

RESULTS

In vivo, anti-miR-31 reduced miR-31 overexpression (P = .002) and suppressed the esophageal preneoplasia in Zn-deficient rats. At the same time, the miR-31 target Stk40 was derepressed, thereby inhibiting the STK40-NF-κΒ-controlled inflammatory pathway, with resultant decreased cellular proliferation and activated apoptosis (caspase 3/7 activities, fold change = 10.7, P = .005). This same connection between miR-31 overexpression and STK40/NF-κΒ expression was also documented in human ESCC cell lines. In Zn-deficient esophagus, the miR-31 promoter region and NF-κΒ binding site were activated. Zn replenishment restored the regulation of this genomic region and a normal esophageal phenotype.

CONCLUSIONS

The data define the in vivo signaling pathway underlying interaction of Zn deficiency and miR-31 overexpression in esophageal neoplasia and provide a mechanistic rationale for miR-31 as a therapeutic target for ESCC.

Sculpting the Transcriptome During the Oocyte-to-Embryo Transition in Mouse

In mouse, the oocyte-to-embryo transition entails converting a highly differentiated oocyte to totipotent blastomeres. This transition is driven by degradation of maternal mRNAs, which results in loss of oocyte identity, and reprogramming of gene expression during the course of zygotic gene activation, which occurs primarily during the two-cell stage and confers blastomere totipotency. Full-grown oocytes are transcriptionally quiescent and mRNAs are remarkably stable in oocytes due to the RNA-binding protein MSY2, which stabilizes mRNAs, and low activity of the 5' and 3' RNA degradation machinery. Oocyte maturation initiates a transition from mRNA stability to instability due to phosphorylation of MSY2, which makes mRNAs more susceptible to the RNA degradation machinery, and recruitment of dormant maternal mRNAs that encode for critical components of the 5' and 3' RNA degradation machinery. Small RNAs (miRNA, siRNA, and piRNA) play little, if any, role in mRNA degradation that occurs during maturation. Many mRNAs are totally degraded but a substantial fraction is only partially degraded, their degradation completed by the end of the two-cell stage. Genome activation initiates during the one-cell stage, is promiscuous, low level, and genome wide (and includes both inter- and intragenic regions) and produces transcripts that are inefficiently spliced and polyadenylated. The major wave of genome activation in two-cell embryos involves expression of thousands of new genes. This unique pattern of gene expression is the product of maternal mRNAs recruited during maturation that encode for transcription factors and chromatin remodelers, as well as dramatic changes in chromatin structure due to incorporation of histone variants and modified histones.

The Importance of Biological Databases in Biological Discovery

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed.

Cardiac gene expression data and in silico analysis provide novel insights into human and mouse taste receptor gene regulation

G protein-coupled receptors are the principal mediators of the sweet, umami, bitter, and fat taste qualities in mammals. Intriguingly, the taste receptors are also expressed outside of the oral cavity, including in the gut, airways, brain, and heart, where they have additional functions and contribute to disease. However, there is little known about the mechanisms governing the transcriptional regulation of taste receptor genes. Following our recent delineation of taste receptors in the heart, we investigated the genomic loci encoding for taste receptors to gain insight into the regulatory mechanisms that drive their expression in the heart. Gene expression analyses of healthy and diseased human and mouse hearts showed coordinated expression for a subset of chromosomally clustered taste receptors. This chromosomal clustering mirrored the cardiac expression profile, suggesting that a common gene regulatory block may control the taste receptor locus. We identified unique domains with strong regulatory potential in the vicinity of taste receptor genes. We also performed de novo motif enrichment in the proximal promoter regions and found several overrepresented DNA motifs in cardiac taste receptor gene promoters corresponding to ubiquitous and cardiac-specific transcription factor binding sites. Thus, combining cardiac gene expression data with bioinformatic analyses, this study has provided insights into the noncoding regulatory landscape for taste GPCRs. These findings also have broader relevance for the study of taste GPCRs outside of the classical gustatory system, where understanding the mechanisms controlling the expression of these receptors may have implications for future therapeutic development.