Manoj Hariharan

Annotation of functional variation in personal genomes using RegulomeDB

As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences.

Architecture of the human regulatory network derived from ENCODE data

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

Variation in Transcription Factor Binding Among Humans

Like Father, Like Mother, Like Child Transcriptional regulation is mediated by chromatin structure, which may affect the binding of transcription factors, but the extent of how individual-to-individual genetic variation affects such regulation is not well understood. Kasowski et al. (p. 232, published online 18 March) investigated the binding of two transcription factors across the genomes of human individuals and one chimpanzee. Transcription factor binding was associated with genomic features such as nucleotide variation, insertions and deletions, and copy number variation. Thus, genomic sequence variation affects transcription factor binding and may explain expression difference among individuals. McDaniell et al. (p. 235, published online 18 March) provide a genome-wide catalog of variation in chromatin and transcription factor binding in two parent-child trios of European and African ancestry. Up to 10% of active chromatin binding sites were specific to a set of individuals and were often inherited. Furthermore, variation in active chromatin sites showed heritable allele-specific correlation with variation in gene expression. Transcription factor binding sites vary among individuals and are correlated with differences in expression. Differences in gene expression may play a major role in speciation and phenotypic diversity. We examined genome-wide differences in transcription factor (TF) binding in several humans and a single chimpanzee by using chromatin immunoprecipitation followed by sequencing. The binding sites of RNA polymerase II (PolII) and a key regulator of immune responses, nuclear factor κB (p65), were mapped in 10 lymphoblastoid cell lines, and 25 and 7.5% of the respective binding regions were found to differ between individuals. Binding differences were frequently associated with single-nucleotide polymorphisms and genomic structural variants, and these differences were often correlated with differences in gene expression, suggesting functional consequences of binding variation. Furthermore, comparing PolII binding between humans and chimpanzee suggests extensive divergence in TF binding. Our results indicate that many differences in individuals and species occur at the level of TF binding, and they provide insight into the genetic events responsible for these differences.

An encyclopedia of mouse DNA elements (Mouse ENCODE)

To complement the human Encyclopedia of DNA Elements (ENCODE) project and to enable a broad range of mouse genomics efforts, the Mouse ENCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome.

Human body epigenome maps reveal noncanonical DNA methylation variation

Understanding the diversity of human tissues is fundamental to disease and requires linking genetic information, which is identical in most of an individual’s cells, with epigenetic mechanisms that could have tissue-specific roles. Surveys of DNA methylation in human tissues have established a complex landscape including both tissue-specific and invariant methylation patterns. Here we report high coverage methylomes that catalogue cytosine methylation in all contexts for the major human organ systems, integrated with matched transcriptomes and genomic sequence. By combining these diverse data types with each individuals’ phased genome, we identified widespread tissue-specific differential CG methylation (mCG), partially methylated domains, allele-specific methylation and transcription, and the unexpected presence of non-CG methylation (mCH) in almost all human tissues. mCH correlated with tissue-specific functions, and using this mark, we made novel predictions of genes that escape X-chromosome inactivation in specific tissues. Overall, DNA methylation in several genomic contexts varies substantially among human tissues.

Abnormalities in human pluripotent cells due to reprogramming mechanisms

Human pluripotent stem cells hold potential for regenerative medicine, but available cell types have significant limitations. Although embryonic stem cells (ES cells) from in vitro fertilized embryos (IVF ES cells) represent the ‘gold standard’, they are allogeneic to patients. Autologous induced pluripotent stem cells (iPS cells) are prone to epigenetic and transcriptional aberrations. To determine whether such abnormalities are intrinsic to somatic cell reprogramming or secondary to the reprogramming method, genetically matched sets of human IVF ES cells, iPS cells and nuclear transfer ES cells (NT ES cells) derived by somatic cell nuclear transfer (SCNT) were subjected to genome-wide analyses. Both NT ES cells and iPS cells derived from the same somatic cells contained comparable numbers of de novo copy number variations. In contrast, DNA methylation and transcriptome profiles of NT ES cells corresponded closely to those of IVF ES cells, whereas iPS cells differed and retained residual DNA methylation patterns typical of parental somatic cells. Thus, human somatic cells can be faithfully reprogrammed to pluripotency by SCNT and are therefore ideal for cell replacement therapies.

Human cellular microRNA hsa-miR-29a interferes with viral nef protein expression and HIV-1 replication

BackgroundCellular miRNAs play an important role in the regulation of gene expression in eukaryotes. Recently, miRNAs have also been shown to be able to target and inhibit viral gene expression. Computational predictions revealed earlier that the HIV-1 genome includes regions that may be potentially targeted by human miRNAs. Here we report the functionality of predicted miR-29a target site in the HIV-1 nef gene.ResultsWe find that the human miRNAs hsa-miR-29a and 29b are expressed in human peripheral blood mononuclear cells. Expression of a luciferase reporter bearing the nef miR-29a target site was decreased compared to the luciferase construct without the target site. Locked nucleic acid modified anti-miRNAs targeted against hsa-miR-29a and 29b specifically reversed the inhibitory effect mediated by cellular miRNAs on the target site. Ectopic expression of the miRNA results in repression of the target Nef protein and reduction of virus levels.ConclusionOur results show that the cellular miRNA hsa-miR29a downregulates the expression of Nef protein and interferes with HIV-1 replication.

Host-virus interaction: a new role for microRNAs

MicroRNAs (miRNAs) are a new class of 18–23 nucleotide long non-coding RNAs that play critical roles in a wide spectrum of biological processes. Recent reports also throw light into the role of microRNAs as critical effectors in the intricate host-pathogen interaction networks. Evidence suggests that both virus and hosts encode microRNAs. The exclusive dependence of viruses on the host cellular machinery for their propagation and survival also make them highly susceptible to the vagaries of the cellular environment like small RNA mediated interference. It also gives the virus an opportunity to fight and/or modulate the host to suite its needs. Thus the range of interactions possible through miRNA-mRNA cross-talk at the host-pathogen interface is large. These interactions can be further fine-tuned in the host by changes in gene expression, mutations and polymorphisms. In the pathogen, the high rate of mutations adds to the complexity of the interaction network. Though evidence regarding microRNA mediated cross-talk in viral infections is just emerging, it offers an immense opportunity not only to understand the intricacies of host-pathogen interactions, and possible explanations to viral tropism, latency and oncogenesis, but also to develop novel biomarkers and therapeutics.

High-throughput sequencing for biology and medicine

Advances in genome sequencing have progressed at a rapid pace, with increased throughput accompanied by plunging costs. But these advances go far beyond faster and cheaper. High‐throughput sequencing technologies are now routinely being applied to a wide range of important topics in biology and medicine, often allowing researchers to address important biological questions that were not possible before. In this review, we discuss these innovative new approaches—including ever finer analyses of transcriptome dynamics, genome structure and genomic variation—and provide an overview of the new insights into complex biological systems catalyzed by these technologies. We also assess the impact of genotyping, genome sequencing and personal omics profiling on medical applications, including diagnosis and disease monitoring. Finally, we review recent developments in single‐cell sequencing, and conclude with a discussion of possible future advances and obstacles for sequencing in biology and health.