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The functional engagement between an enhancer and its target promoter ensures precise gene transcription1. Understanding the basis of promoter choice by enhancers has important implications for health and disease. Here we report that functional loss of a preferred promoter can release its partner enhancer to loop to and activate an alternative promoter (or alternative promoters) in the neighbourhood. We refer to this target-switching process as 'enhancer release and retargeting'. Genetic deletion, motif perturbation or mutation, and dCas9-mediated CTCF tethering reveal that promoter choice by an enhancer can be determined by the binding of CTCF at promoters, in a cohesin-dependent manner-consistent with a model of 'enhancer scanning' inside the contact domain. Promoter-associated CTCF shows a lower affinity than that at chromatin domain boundaries and often lacks a preferred motif orientation or a partnering CTCF at the cognate enhancer, suggesting properties distinct from boundary CTCF. Analyses of cancer mutations, data from the GTEx project and risk loci from genome-wide association studies, together with a focused CRISPR interference screen, reveal that enhancer release and retargeting represents an overlooked mechanism that underlies the activation of disease-susceptibility genes, as exemplified by a risk locus for Parkinson's disease (NUCKS1-RAB7L1) and three loci associated with cancer (CLPTM1L-TERT, ZCCHC7-PAX5 and PVT1-MYC).

Alzheimer’s disease (AD) is a genetically complex, multifactorial neurodegenerative disease. It affects more than 45 million people worldwide and currently remains untreatable. Although genome-wide association studies (GWAS) have identified many AD-associated common variants, only about 25 genes are currently known to affect the risk of developing AD, despite its highly polygenic nature. Moreover, the risk variants underlying GWAS AD-association signals remain unknown. Here, we describe a deep post-GWAS analysis of AD-associated variants, using an integrated computational framework for predicting both disease genes and their risk variants. We identified 342 putative AD risk genes in 203 risk regions spanning 502 AD-associated common variants. 246 AD risk genes have not been identified as AD risk genes by previous GWAS collected in GWAS catalogs, and 115 of 342 AD risk genes are outside the risk regions, likely under the regulation of transcriptional regulatory elements contained therein. Even more significantly, for 109 AD risk genes, we predicted 150 risk variants, of both coding and regulatory (in promoters or enhancers) types, and 85 (57%) of them are supported by functional annotation. In-depth functional analyses showed that AD risk genes were overrepresented in AD-related pathways or GO terms—e.g., the complement and coagulation cascade and phosphorylation and activation of immune response—and their expression was relatively enriched in microglia, endothelia, and pericytes of the human brain. We found nine AD risk genes—e.g., IL1RAP, PMAIP1, LAMTOR4—as predictors for the prognosis of AD survival and genes such as ARL6IP5 with altered network connectivity between AD patients and normal individuals involved in AD progression. Our findings open new strategies for developing therapeutics targeting AD risk genes or risk variants to influence AD pathogenesis.

Gene variants associated with longevity are also associated with protection against cognitive decline, dementia and Alzheimer's disease, suggesting that common physiologic pathways act at the interface of longevity and cognitive function. To test the hypothesis that variants in genes implicated in cognitive function may promote exceptional longevity, we performed a comprehensive 3‐stage study to identify functional longevity‐associated variants in ~700 candidate genes in up to 450 centenarians and 500 controls by target capture sequencing analysis. We found an enrichment of longevity‐associated genes in the nPKC and NF‐κB signaling pathways by gene‐based association analyses. Functional analysis of the top three gene variants (NFKBIA, CLU, PRKCH) suggests that non‐coding variants modulate the expression of cognate genes, thereby reducing signaling through the nPKC and NF‐κB. This matches genetic studies in multiple model organisms, suggesting that the evolutionary conservation of reduced PKC and NF‐κB signaling pathways in exceptional longevity may include humans., To test the hypothesis that variants in genes implicated in cognitive function may promote exceptional longevity, we performed a 3‐stage study to identify functional longevity‐associated variants in ~700 candidate genes in up to 450 centenarians and 500 controls by target capture sequencing analysis. We found an enrichment of longevity‐associated genes in the nPKC and NF‐kB signaling pathways by gene‐based association analyses. Functional analysis of the top three gene variants (NFKBIA, CLU, PRKCH) suggests that non‐coding variants reduce signaling through the nPKC and NF‐kB.

The North American beaver (Castor canadensis) is an exceptionally long-lived and cancer-resistant rodent species, and thus an excellent model organism for comparative genomic studies of longevity. Here, we utilize a significantly improved beaver genome assembly to assess evolutionary changes in gene coding sequences, copy number, and expression. We found that the beaver Aldh1a1, a stem cell marker gene encoding an enzyme required for detoxification of ethanol and aldehydes, is expanded (~10 copies vs. two in mouse and one in human). We also show that the beaver cells are more resistant to ethanol, and beaver liver extracts show higher ability to metabolize aldehydes than the mouse samples. Furthermore, Hpgd, a tumor suppressor gene, is uniquely duplicated in the beaver among rodents. Our evolutionary analysis identified beaver genes under positive selection which are associated with tumor suppression and longevity. Genes involved in lipid metabolism show positive selection signals, changes in copy number and altered gene expression in beavers. Several genes involved in DNA repair showed a higher expression in beavers which is consistent with the trend observed in other long-lived mammals. In summary, we identified several genes that likely contribute to beaver longevity and cancer resistance, including increased ability to detoxify aldehydes, enhanced tumor suppression and DNA repair, and altered lipid metabolism.

Schizophrenia is a severe mental disorder with a large genetic component. Recent genome-wide association studies (GWAS) have identified many schizophrenia-associated common variants. For most of the reported associations, however, the underlying biological mechanisms are not clear. The critical first step for their elucidation is to identify the most likely disease genes as the source of the association signals. Here, we describe a general computational framework of post-GWAS analysis for complex disease gene prioritization. We identify 132 putative schizophrenia risk genes in 76 risk regions spanning 120 schizophrenia-associated common variants, 78 of which have not been recognized as schizophrenia disease genes by previous GWAS. Even more significantly, 29 of them are outside the risk regions, likely under regulation of transcriptional regulatory elements contained therein. These putative schizophrenia risk genes are transcriptionally active in both brain and the immune system, and highly enriched among cellular pathways, consistent with leading pathophysiological hypotheses about the pathogenesis of schizophrenia. With their involvement in distinct biological processes, these putative schizophrenia risk genes, with different association strengths, show distinctive temporal expression patterns, and play specific biological roles during brain development.

Gene regulatory analysis of highly diverse human tissues in vivo is essentially constrained by the challenge of performing genome-wide, integrated epigenetic and transcriptomic analysis in small selected groups of specific cell types. Here we performed genome-wide bisulfite sequencing and RNA-seq from the same small groups of bronchial and alveolar cells isolated by laser capture microdissection from flash-frozen lung tissue of 12 donors and their peripheral blood T cells. Methylation and transcriptome patterns differed between alveolar and bronchial cells, while each of these epithelia showed more differences from mesodermally-derived T cells. Differentially methylated regions (DMRs) between alveolar and bronchial cells tended to locate at regulatory regions affecting promoters of 4,350 genes. A large number of pathways enriched for these DMRs including GTPase signal transduction, cell death, and skeletal muscle. Similar patterns of transcriptome differences were observed: 4,108 differentially expressed genes (DEGs) enriched in GTPase signal transduction, inflammation, cilium assembly, and others. Prioritizing using DMR-DEG regulatory network, we highlighted genes, e.g., ETS1, PPARG, and RXRG, at prominent alveolar vs. bronchial cell discriminant nodes. Our results show that multi-omic analysis of small, highly specific cells is feasible and yields unique physiologic loci distinguishing human lung cell types in situ.

Differences in DNA repair capacity have been hypothesized to underlie the great range of maximum lifespans among mammals. However, measurements of individual DNA repair activities in cells and animals have not substantiated such a relationship because utilization of repair pathways among animals--depending on habitats, anatomical characteristics, and life styles--varies greatly between mammalian species. Recent advances in high-throughput genomics, in combination with increased knowledge of the genetic pathways involved in genome maintenance, now enable a comprehensive comparison of DNA repair transcriptomes in animal species with extreme lifespan differences. Here we compare transcriptomes of liver, an organ with high oxidative metabolism and abundant spontaneous DNA damage, from humans, naked mole rats, and mice, with maximum lifespans of ~120, 30, and 3 years, respectively, with a focus on genes involved in DNA repair. The results show that the longer-lived species, human and naked mole rat, share higher expression of DNA repair genes, including core genes in several DNA repair pathways. A more systematic approach of signaling pathway analysis indicates statistically significant upregulation of several DNA repair signaling pathways in human and naked mole rat compared with mouse. The results of this present work indicate, for the first time, that DNA repair is upregulated in a major metabolic organ in long-lived humans and naked mole rats compared with short-lived mice. These results strongly suggest that DNA repair can be considered a genuine longevity assurance system.

Genome maintenance (GM) is an essential defense system against aging and cancer, as both are characterized by increased genome instability. Here, we compared the copy number variation and mutation rate of 518 GM-associated genes in the naked mole rat (NMR), mouse, and human genomes. GM genes appeared to be strongly conserved, with copy number variation in only four genes. Interestingly, we found NMR to have a higher copy number of CEBPG, a regulator of DNA repair, and TINF2, a protector of telomere integrity. NMR, as well as human, was also found to have a lower rate of germline nucleotide substitution than the mouse. Together, the data suggest that the long-lived NMR, as well as human, has more robust GM than mouse and identifies new targets for the analysis of the exceptional longevity of the NMR.

Enhancers, as specialized genomic cis-regulatory elements, activate transcription of their target genes and play an important role in pathogenesis of many human complex diseases. Despite recent systematic identification of them in the human genome, currently there is an urgent need for comprehensive annotation databases of human enhancers with a focus on their disease connections. In response, we built the Human Enhancer Disease Database (HEDD) to facilitate studies of enhancers and their potential roles in human complex diseases. HEDD currently provides comprehensive genomic information for ∼2.8 million human enhancers identified by ENCODE, FANTOM5 and RoadMap with disease association scores based on enhancer–gene and gene–disease connections. It also provides Web-based analytical tools to visualize enhancer networks and score enhancers given a set of selected genes in a specific gene network. HEDD is freely accessible at http://zdzlab.einstein.yu.edu/1/hedd.php.

Mammalian lifespan differs by >100 fold, but the mechanisms associated with such longevity differences are not understood. Here, we conducted a study on primary skin fibroblasts isolated from 16 species of mammals and maintained under identical cell culture conditions. We developed a pipeline for obtaining species-specific ortholog sequences, profiled gene expression by RNA-seq and small molecules by metabolite profiling, and identified genes and metabolites correlating with species longevity. Cells from longer lived species up-regulated genes involved in DNA repair and glucose metabolism, down-regulated proteolysis and protein transport, and showed high levels of amino acids but low levels of lysophosphatidylcholine and lysophosphatidylethanolamine. The amino acid patterns were recapitulated by further analyses of primate and bird fibroblasts. The study suggests that fibroblast profiling captures differences in longevity across mammals at the level of global gene expression and metabolite levels and reveals pathways that define these differences. DOI: http://dx.doi.org/10.7554/eLife.19130.001

Although studies over the last decades have firmly connected a number of genes and molecular pathways to aging, the aging process as a whole still remains poorly understood. To gain novel insights into the mechanisms underlying aging, instead of considering aging genes individually, we studied their characteristics at the systems level in the context of biological networks. We calculated a comprehensive set of network characteristics for human aging-related genes from the GenAge database. By comparing them with other functional groups of genes, we identified a robust group of aging-specific network characteristics. To find the structural basis and the molecular mechanisms underlying this aging-related network specificity, we also analyzed protein domain interactions and gene expression patterns across different tissues. Our study revealed that aging genes not only tend to be network hubs, playing important roles in communication among different functional modules or pathways, but also are more likely to physically interact and be co-expressed with essential genes. The high expression of aging genes across a large number of tissue types also points to a high level of connectivity among aging genes. Unexpectedly, contrary to the depletion of interactions among hub genes in biological networks, we observed close interactions among aging hubs, which renders the aging subnetworks vulnerable to random attacks and thus may contribute to the aging process. Comparison across species reveals the evolution process of the aging subnetwork. As the organisms become more complex, the complexity of its aging mechanisms increases and their aging hub genes are more functionally connected.

Defective Gene Detective Identifying genes that give rise to diseases is one of the major goals of sequencing human genomes. However, putative loss-of-function genes, which are often some of the first identified targets of genome and exome sequencing, have often turned out to be sequencing errors rather than true genetic variants. In order to identify the true scope of loss-of-function genes within the human genome, MacArthur et al. (p. 823 ; see the Perspective by Quintana-Murci ) extensively validated the genomes from the 1000 Genomes Project, as well as an additional European individual, and found that the average person has about 100 true loss-of-function alleles of which approximately 20 have two copies within an individual. Because many known disease-causing genes were identified in “normal” individuals, the process of clinical sequencing needs to reassess how to identify likely causative alleles.

Epstein–Barr virus (EBV) is associated with several types of lymphomas and epithelial tumors including Burkitt's lymphoma (BL), HIV-associated lymphoma, posttransplant lymphoproliferative disorder, and nasopharyngeal carcinoma. EBV nuclear antigen 1 (EBNA1) is expressed in all EBV associated tumors and is required for latency and transformation. EBNA1 initiates latent viral replication in B cells, maintains the viral genome copy number, and regulates transcription of other EBV-encoded latent genes. These activities are mediated through the ability of EBNA1 to bind viral-DNA. To further elucidate the role of EBNA1 in the host cell, we have examined the effect of EBNA1 on cellular gene expression by microarray analysis using the B cell BJAB and the epithelial 293 cell lines transfected with EBNA1. Analysis of the data revealed distinct profiles of cellular gene changes in BJAB and 293 cell lines. Subsequently, chromatin immune-precipitation revealed a direct binding of EBNA1 to cellular promoters. We have correlated EBNA1 bound promoters with changes in gene expression. Sequence analysis of the 100 promoters most enriched revealed a DNA motif that differs from the EBNA1 binding site in the EBV genome.

Schizophrenia (SCZ) is a severe mental disorder with a large genetic component. While recent large-scale microarray- and sequencing-based genome wide association studies have made significant progress toward finding SCZ risk variants and genes of subtle effect, the interactions among them were not considered in those studies. Using a protein-protein interaction network both in our regression model and to generate a SCZ gene subnetwork, we developed an analytical framework with Logit-Lapnet, the graphical Laplacian-regularized logistic regression, for whole exome sequencing (WES) data analysis to detect SCZ gene subnetworks. Using simulated data from sequencing-based association study, we compared the performances of Logit-Lapnet with other logistic regression (LR)-based models. We use Logit-Lapnet to prioritize genes according to their coefficients and select top-ranked genes as seeds to generate the gene sub-network that is associated to SCZ. The comparison demonstrated not only the applicability but also better performance of Logit-Lapnet to score disease risk genes using sequencing-based association data. We applied our method to SCZ whole exome sequencing data and selected top-ranked risk genes, the majority of which are either known SCZ genes or genes potentially associated with SCZ. We then used the seed genes to construct SCZ gene subnetworks. This result demonstrates that by ranking gene according to their disease contributions our method scores and thus prioritizes disease risk genes for further investigation. An implementation of our approach in MATLAB is freely available for download at: http://zdzlab.einstein.yu.edu/1/publications/LapNet-MATLAB.zip.

Characterization of interspecies differences in gene regulation is crucial for understanding the molecular basis of both phenotypic diversity and evolution. By means of chromatin immunoprecipitation and DNA microarray analysis, the divergence in the binding sites of the pseudohyphal regulators Ste12 and Tec1 was determined in the yeasts Saccharomyces cerevisiae , S. mikatae , and S. bayanus under pseudohyphal conditions. We have shown that most of these sites have diverged across these species, far exceeding the interspecies variation in orthologous genes. A group of Ste12 targets was shown to be bound only in S. mikatae and S. bayanus under pseudohyphal conditions. Many of these genes are targets of Ste12 during mating in S. cerevisiae , indicating that specialization between the two pathways has occurred in this species. Transcription factor binding sites have therefore diverged substantially faster than ortholog content. Thus, gene regulation resulting from transcription factor binding is likely to be a major cause of divergence between related species.

The regulation of transcriptional initiation in the human genome is a critical component of global gene regulation, but a complete catalog of human promoters currently does not exist. In order to identify regulatory regions, we developed four computational methods to integrate 129 sets of ENCODE-wide chromatin immunoprecipitation data. They collectively predicted 1393 regions. Roughly 47% of the regions were unique to one method, as each method makes different assumptions about the data. Overall, predicted regions tend to localize to highly conserved, DNase I hypersensitive, and actively transcribed regions in the genome. Interestingly, a significant portion of the regions overlaps with annotated 3′-UTRs, suggesting that some of them might regulate anti-sense transcription. The majority of the predicted regions are >2 kb away from the 5′-ends of previously annotated human cDNAs and hence are novel. These novel regions may regulate unannotated transcripts or may represent new alternative transcription start sites of known genes. We tested 163 such regions for promoter activity in four cell lines using transient transfection assays, and 25% of them showed transcriptional activity above background in at least one cell line. We also performed 5′-RACE experiments on 62 novel regions, and 76% of the regions were associated with the 5′-ends of at least two RACE products. Our results suggest that there are at least 35% more functional promoters in the human genome than currently annotated.

Gene expression is a fundamental biological process under tight regulation at all levels in normal cells. Its dysregulation can cause abnormal cell behaviors and result in diseases, and thus gene expression profiling and analysis have been widely used to provide the first clue about the molecular mechanisms of human diseases. Because genes and their products interact with and regulate one another, it is essential to analyze gene expression data and understand the genetics of disease in a biological network context. In this chapter, we first introduce the state-of-the-art gene expression analysis (GEA) with network integration and the joint analysis of mRNA and miRNA expression to understand disease regulatory mechanisms and then discuss how disease genes are predicted by incorporating knowledge of gene regulation and characterized in biological networks.

Rare variants of major effect play an important role in human complex diseases and can be discovered by sequencing-based genome-wide association studies. Here, we introduce an integrated approach that combines the rare variant association test with gene network and phenotype information to identify risk genes implicated by rare variants for human complex diseases. Our data integration method follows a 'discovery-driven' strategy without relying on prior knowledge about the disease and thus maintains the unbiased character of genome-wide association studies. Simulations reveal that our method can outperform a widely-used rare variant association test method by 2 to 3 times. In a case study of a small disease cohort, we uncovered putative risk genes and the corresponding rare variants that may act as genetic modifiers of congenital heart disease in 22q11.2 deletion syndrome patients. These variants were missed by a conventional approach that relied on the rare variant association test alone., Author summary Case-control sequencing studies are a promising design to uncover risk genes of human complex diseases implicated by rare variants. The recent development of different types of rare variant association tests has improved the statistical power to identify disease genes that harbor risk rare variants. However, none of the recent sequencing-based genome-wide association studies identified robust disease association of rare variants or genes based on them. Due to limited sample sizes that can be feasibly achieved in real applications, current rare variant association tests can only generate marginal association signals for most risk genes. Here we proposed an integrated method that combined association signals with orthogonal biological evidence to uncover risk genes in sequencing studies. Designed to address the lack-of-power issue, our method was shown to effectively uncover risk genes with marginal association signals in data simulation. Indeed, in a real application demonstrated in our case study our method disclosed important risk genes of congenital heart disease in 22q11.2 deletion syndrome that were missed by the previous study.

A partial knockout compensation method to screen 5S ribosomal RNA sequence variants in vivo is described. The system utilizes an Escherichia coli strain in which five of eight genomic 5S rRNA genes were deleted in conjunction with a plasmid which is compensatory when carrying a functionally active 5S rRNA. The partial knockout strain is transformed with a population of potentially compensatory plasmids each carrying a randomly generated 5S rRNA gene variant. a The ability to compensate the slow growth rate of the knockout strain is used in conjunction with sequencing to rapidly identify variant 5S rRNAs that are functional as well as those that likely are not. The assay is validated by showing that the growth rate of 15 variants separately expressed in the partial knockout strain can be accurately correlated with in vivo assessments of the potential validity of the same variants. A region of 5S rRNA was mutagenized with this approach and nine novel variants were recovered and characterized. Unlike a complete knockout system, the method allows recovery of both deleterious and functional variants.. The method can be used to study variants of any 5S rRNA in the E. coli context including those of E. coli.

Transcription factor pseudogenes have not been systematically studied before. Nuclear receptors (NRs) constitute one of the largest groups of transcription factors in animals (e.g., 48 NRs in human). The availability of whole-genome sequences enables a global inventory of the NR pseudogenes in a number of vertebrate model organisms. Here we identify the NR pseudogenes in 8 vertebrate organisms and make our results available online at http://www.pseudogene.org/nr. The assignments reveal that NR pseudogenes as a group have characteristics related to generation and distribution contrary to expectations derived from previous large-scale pseudogene studies. In particular, 1) despite its large size, the NR gene family has only a very small number of pseudogenes in each of the vertebrate genomes examined; 2) despite the low transcription levels of NR genes, except for one, all other NR pseudogenes identified in this study are retropseudogenes; and 3) no duplicated NR pseudogenes are found, contrary to the fact that the NR gene family was expanded through several waves of gene duplication events. Our analyses further reveal a number of interesting aspects of NR pseudogenes. Specifically, through careful sequence analysis, we identify remnant introns in 2 mouse retropseudogenes, psiRev-erbbeta and psiLRH1. Generated from partially processed pre-mRNAs, they appear to be rare examples of highly unusual "semiprocessed" pseudogenes. Second, by comparing the genomic sequences, we uncover a pseudogene that is unique to the human lineage relative to chimpanzee. Generated by a recent duplication of a segment in the human genome, this pseudogene is a "duplicated-processed" pseudogene, belonging to a new pseudogene species. Finally, FXRbeta was nonfunctionalized in the human lineage and thus appears to be an example of a rare unitary pseudogene. By comparing orthologous sequences, we dated the FXR-FXRbeta duplication and the nonfunctionalization of FXRbeta in primates.

While sequencing of the human genome surprised us with how many protein-coding genes there are, it did not fundamentally change our perspective on what a gene is. In contrast, the complex patterns of dispersed regulation and pervasive transcription uncovered by the ENCODE project, together with non-genic conservation and the abundance of noncoding RNA genes, have challenged the notion of the gene. To illustrate this, we review the evolution of operational definitions of a gene over the past century—from the abstract elements of heredity of Mendel and Morgan to the present-day ORFs enumerated in the sequence databanks. We then summarize the current ENCODE findings and provide a computational metaphor for the complexity. Finally, we propose a tentative update to the definition of a gene: A gene is a union of genomic sequences encoding a coherent set of potentially overlapping functional products. Our definition sidesteps the complexities of regulation and transcription by removing the former altogether from the definition and arguing that final, functional gene products (rather than intermediate transcripts) should be used to group together entities associated with a single gene. It also manifests how integral the concept of biological function is in defining genes.

The comprehensive inventory of functional elements in 44 human genomic regions carried out by the ENCODE Project Consortium enables for the first time a global analysis of the genomic distribution of transcriptional regulatory elements. In this study we developed an intuitive and yet powerful approach to analyze the distribution of regulatory elements found in many different ChIP–chip experiments on a 10∼100-kb scale. First, we focus on the overall chromosomal distribution of regulatory elements in the ENCODE regions and show that it is highly nonuniform. We demonstrate, in fact, that regulatory elements are associated with the location of known genes. Further examination on a local, single-gene scale shows an enrichment of regulatory elements near both transcription start and end sites. Our results indicate that overall these elements are clustered into regulatory rich “islands” and poor “deserts.” Next, we examine how consistent the nonuniform distribution is between different transcription factors. We perform on all the factors a multivariate analysis in the framework of a biplot, which enhances biological signals in the experiments. This groups transcription factors into sequence-specific and sequence-nonspecific clusters. Moreover, with experimental variation carefully controlled, detailed correlations show that the distribution of sites was generally reproducible for a specific factor between different laboratories and microarray platforms. Data sets associated with histone modifications have particularly strong correlations. Finally, we show how the correlations between factors change when only regulatory elements far from the transcription start sites are considered.

Completion of the Rattus norvegicus genome sequence enabled a global inventory and analysis of the nuclear receptors (NRs) in three mammalian species. Forty-nine NR members were found in mouse, 48 in human. Forty-seven were found in the rat, with gaps at the locations expected for the other two. Pairwise comparisons of their distribution in rat, mouse, and human identified 11 syntenic NR gene blocks, including three small clusters of two or three closely related genes, each spanning 40 kb to 1700 kb. The exon structure of the ligand-binding domain suggests that exon shuffling has played a role in the evolution of this family. An invariant splice junction in all members of the NR family except LXRβ suggests a functional role for the intron. The ligand-binding domains of PXR and CAR are among the most divergent in the family. Their higher nucleotide substitution rates may be related to the central role played by these two NRs in the metabolism of the foreign compounds and may have resulted from limited positive selection.

The laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality 'draft' covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineage-independent evolutionary events such as expansion of gene families, orthology relations and protein evolution.

DNA mutational events are increasingly being identified in autism spectrum disorder (ASD), but the potential additional role of dysregulation of the epigenome in the pathogenesis of the condition remains unclear. The epigenome is of interest as a possible mediator of environmental effects during development, encoding a cellular memory reflected by altered function of progeny cells. Advanced maternal age (AMA) is associated with an increased risk of having a child with ASD for reasons that are not understood. To explore whether AMA involves covert aneuploidy or epigenetic dysregulation leading to ASD in the offspring, we tested a homogeneous ectodermal cell type from 47 individuals with ASD compared with 48 typically developing (TD) controls born to mothers of ≥35 years, using a quantitative genome-wide DNA methylation assay. We show that DNA methylation patterns are dysregulated in ectodermal cells in these individuals, having accounted for confounding effects due to subject age, sex and ancestral haplotype. We did not find mosaic aneuploidy or copy number variability to occur at differentially-methylated regions in these subjects. Of note, the loci with distinctive DNA methylation were found at genes expressed in the brain and encoding protein products significantly enriched for interactions with those produced by known ASD-causing genes, representing a perturbation by epigenomic dysregulation of the same networks compromised by DNA mutational mechanisms. The results indicate the presence of a mosaic subpopulation of epigenetically-dysregulated, ectodermally-derived cells in subjects with ASD. The epigenetic dysregulation observed in these ASD subjects born to older mothers may be associated with aging parental gametes, environmental influences during embryogenesis or could be the consequence of mutations of the chromatin regulatory genes increasingly implicated in ASD. The results indicate that epigenetic dysregulatory mechanisms may complement and interact with DNA mutations in the pathogenesis of the disorder., Author Summary Older mothers have a higher than expected risk of having a child with an autism spectrum disorder (ASD). The reason for this increased risk is unknown. The eggs of older mothers are more prone to abnormalities of chromosome numbers, suggesting this as one possible mechanism of the increased ASD risk. Age is also associated with a loss of control of epigenetic regulatory patterns that govern gene expression, indicating a second potential mechanism. To test both possibilities, we sampled cells from the same developmental origin as the brain, and performed genome-wide tests looking for unusual chromosome numbers and DNA methylation patterns. The studies were performed on individuals with ASD and typically developing controls, all born to mothers at least 35 years of age at the time of birth. We found the cells from individuals with ASD to have changes in DNA methylation at a number of loci, especially near genes encoding proteins known to interact with those already implicated in ASD. We conclude that epigenetic dysregulation occurring in gametes or early embryonic life may be one of the contributors to the development of ASD.

RACE sequencing of ENCODE regions shows that much of the human genome is represented in poly(A)+ RNA., Background Recent studies of the mammalian transcriptome have revealed a large number of additional transcribed regions and extraordinary complexity in transcript diversity. However, there is still much uncertainty regarding precisely what portion of the genome is transcribed, the exact structures of these novel transcripts, and the levels of the transcripts produced. Results We have interrogated the transcribed loci in 420 selected ENCyclopedia Of DNA Elements (ENCODE) regions using rapid amplification of cDNA ends (RACE) sequencing. We analyzed annotated known gene regions, but primarily we focused on novel transcriptionally active regions (TARs), which were previously identified by high-density oligonucleotide tiling arrays and on random regions that were not believed to be transcribed. We found RACE sequencing to be very sensitive and were able to detect low levels of transcripts in specific cell types that were not detectable by microarrays. We also observed many instances of sense-antisense transcripts; further analysis suggests that many of the antisense transcripts (but not all) may be artifacts generated from the reverse transcription reaction. Our results show that the majority of the novel TARs analyzed (60%) are connected to other novel TARs or known exons. Of previously unannotated random regions, 17% were shown to produce overlapping transcripts. Furthermore, it is estimated that 9% of the novel transcripts encode proteins. Conclusion We conclude that RACE sequencing is an efficient, sensitive, and highly accurate method for characterization of the transcriptome of specific cell/tissue types. Using this method, it appears that much of the genome is represented in polyA+ RNA. Moreover, a fraction of the novel RNAs can encode protein and are likely to be functional.

Background MicroRNAs (miRNAs) are small non-coding RNA molecules of about 22 nucleotides which function to silence the expression of their target genes. Numerous studies have shown that miRNAs are not only key regulators in important cellular processes but are also drivers in the development of many diseases, especially cancer. Estrogen receptor positive luminal B is the second most common but the least studied subtype of breast cancer. Only a few studies have examined the expression profiles of miRNAs in luminal B breast cancer, and their regulatory roles in cancer progression have yet to be investigated. Methods In this study, using polyoma middle T antigen (PyMT) mice, a widely used luminal B breast cancer model, we profiled microRNA (miRNA) expression at four time points that represent different key developmental stages of cancer progression. We considered the expression of both miRNAs and messenger RNAs (mRNAs) at these time points to improve the identification of regulatory targets of miRNAs. By combining gene functional and pathway annotation with miRNA-mRNA interactions, we created a PyMT-specific tripartite miRNA-mRNA-pathway network and identified novel functional regulatory programs (FRPs). Results We identified 151 differentially expressed miRNAs with a strict dual nature of either upregulation or downregulation during the whole course of disease progression. Among 82 newly discovered breast-cancer-related miRNAs, 35 can potentially regulate 271 protein-coding genes based on their sequence complementarity and expression profiles. We also identified miRNA-mRNA regulatory modules driving specific cancer-related biological processes. Conclusions In this study we profiled the expression of miRNAs during breast cancer progression in the PyMT mouse model. By integrating miRNA and mRNA expression profiles, we identified differentially expressed miRNAs and their target genes involved in several hallmarks of cancer. We applied a novel clustering method to an annotated miRNA-mRNA regulatory network and identified network modules involved in specific cancer-related biological processes. Electronic supplementary material The online version of this article (doi:10.1186/s13058-016-0735-z) contains supplementary material, which is available to authorized users.

Novel human pseudogenes are identified that had previous functionality and their age is estimated. The rate of loss-of-function occurred uniformly., Background Unitary pseudogenes are a class of unprocessed pseudogenes without functioning counterparts in the genome. They constitute only a small fraction of annotated pseudogenes in the human genome. However, as they represent distinct functional losses over time, they shed light on the unique features of humans in primate evolution. Results We have developed a pipeline to detect human unitary pseudogenes through analyzing the global inventory of orthologs between the human genome and its mammalian relatives. We focus on gene losses along the human lineage after the divergence from rodents about 75 million years ago. In total, we identify 76 unitary pseudogenes, including previously annotated ones, and many novel ones. By comparing each of these to its functioning ortholog in other mammals, we can approximately date the creation of each unitary pseudogene (that is, the gene 'death date') and show that for our group of 76, the functional genes appear to be disabled at a fairly uniform rate throughout primate evolution - not all at once, correlated, for instance, with the 'Alu burst'. Furthermore, we identify 11 unitary pseudogenes that are polymorphic - that is, they have both nonfunctional and functional alleles currently segregating in the human population. Comparing them with their orthologs in other primates, we find that two of them are in fact pseudogenes in non-human primates, suggesting that they represent cases of a gene being resurrected in the human lineage. Conclusions This analysis of unitary pseudogenes provides insights into the evolutionary constraints faced by different organisms and the timescales of functional gene loss in humans.