The ENCODE Project at UC Santa Cruz

Loss of the Atrial Fibrillation-Related Gene, Zfhx3, Results in Atrial Dilation and Arrhythmias

BACKGROUND

ZFHX3 (zinc finger homeobox 3), a gene that encodes a large transcription factor, is at the second-most significantly associated locus with atrial fibrillation (AF), but its function in the heart is unknown. This study aims to identify causative genetic variation related to AF at the ZFHX3 locus and examine the impact of Zfhx3 loss on cardiac function in mice.

METHODS

CRISPR-Cas9 genome editing, chromatin immunoprecipitation, and luciferase assays in pluripotent stem cell-derived cardiomyocytes were used to identify causative genetic variation related to AF at the ZFHX3 locus. Cardiac function was assessed by echocardiography, magnetic resonance imaging, electrophysiology studies, calcium imaging, and RNA sequencing in mice with heterozygous and homozygous cardiomyocyte-restricted Zfhx3 loss (Zfhx3 Het and knockout, respectively). Human cardiac single-nucleus ATAC (assay for transposase-accessible chromatin)-sequencing data was analyzed to determine which genes in atrial cardiomyocytes are directly regulated by ZFHX3.

RESULTS

We found single-nucleotide polymorphism (SNP) rs12931021 modulates an enhancer regulating ZFHX3 expression, and the AF risk allele is associated with decreased ZFHX3 transcription. We observed a gene-dose response in AF susceptibility with Zfhx3 knockout mice having higher incidence, frequency, and burden of AF than Zfhx3 Het and wild-type mice, with alterations in conduction velocity, atrial action potential duration, calcium handling and the development of atrial enlargement and thrombus, and dilated cardiomyopathy. Zfhx3 loss results in atrial-specific differential effects on genes and signaling pathways involved in cardiac pathophysiology and AF.

CONCLUSIONS

Our findings implicate ZFHX3 as the causative gene at the 16q22 locus for AF, and cardiac abnormalities caused by loss of cardiac Zfhx3 are due to atrial-specific dysregulation of pathways involved in AF susceptibility. Together, these data reveal a novel and important role for Zfhx3 in the control of cardiac genes and signaling pathways essential for normal atrial function.

circMeta: a unified computational framework for genomic feature annotation and differential expression analysis of circular RNAs

MOTIVATION

Circular RNAs (circRNAs), a class of non-coding RNAs generated from non-canonical back-splicing events, have emerged to play key roles in many biological processes. Though numerous tools have been developed to detect circRNAs from rRNA-depleted RNA-seq data based on back-splicing junction-spanning reads, computational tools to identify critical genomic features regulating circRNA biogenesis are still lacking. In addition, rigorous statistical methods to perform differential expression (DE) analysis of circRNAs remain under-developed.

RESULTS

We present circMeta, a unified computational framework for circRNA analyses. circMeta has three primary functional modules: (i) a pipeline for comprehensive genomic feature annotation related to circRNA biogenesis, including length of introns flanking circularized exons, repetitive elements such as Alu elements and SINEs, competition score for forming circulation and RNA editing in back-splicing flanking introns; (ii) a two-stage DE approach of circRNAs based on circular junction reads to quantitatively compare circRNA levels and (iii) a Bayesian hierarchical model for DE analysis of circRNAs based on the ratio of circular reads to linear reads in back-splicing sites to study spatial and temporal regulation of circRNA production. Both proposed DE methods without and with considering host genes outperform existing methods by obtaining better control of false discovery rate and comparable statistical power. Moreover, the identified DE circRNAs by the proposed two-stage DE approach display potential biological functions in Gene Ontology and circRNA-miRNA-mRNA networks that are not able to be detected using existing mRNA DE methods. Furthermore, top DE circRNAs have been further validated by RT-qPCR using divergent primers spanning back-splicing junctions.

AVAILABILITY AND IMPLEMENTATION

The software circMeta is freely available at https://github.com/lichen-lab/circMeta.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Analysis of Putative Epigenetic Regulatory Elements in the FXN Genomic Locus

Friedreich´s ataxia (FRDA) is an autosomal recessive disease caused by an abnormally expanded Guanine-Adenine-Adenine (GAA) repeat sequence within the first intron of the frataxin gene (FXN). The molecular mechanisms associated with FRDA are still poorly understood and most studies on FXN gene regulation have been focused on the region around the minimal promoter and the region in which triplet expansion occurs. Nevertheless, since there could be more epigenetic changes involved in the reduced levels of FXN transcripts, the aim of this study was to obtain a more detailed view of the possible regulatory elements by analyzing data from ENCODE and Roadmap consortia databases. This bioinformatic analysis indicated new putative regulatory regions within the FXN genomic locus, including exons, introns, and upstream and downstream regions. Moreover, the region next to the end of intron 4 is of special interest, since the enhancer signals in FRDA-affected tissues are weak or absent in this region, whilst they are strong in the rest of the analyzed tissues. Therefore, these results suggest that there could be a direct relationship between the absence of enhancer sequences in this specific region and their predisposition to be affected in this pathology.

Meta-analysis and prioritization of human skin pigmentation-associated GWAS-SNPs using ENCODE data-based web-tools

Skin pigmentation in human is a complex trait, which varies widely, both within and between human populations. The exact players governing the trait of skin pigmentation remain elusive till date. Various Genome Wide Association Studies (GWAS) have shown the association of different genomic variants with normal human skin pigmentation, often indicating genes with no direct implications in melanin biosynthesis or distribution. Little has been explained in terms of the functionality of the associated Single-Nucleotide Polymorphisms (SNPs) with respect to modulating the skin pigmentation phenotype. In the present study, which, to our knowledge, is the first of its kind, we tried to analyze and prioritize 519 non-coding SNPs and 24 3'UTR SNPs emerging from 14 different human skin pigmentation-related GWAS, primarily using several ENCODE-based web-tools like rSNPBase, RegulomeDB, HaploReg, etc., most of which incorporate experimentally validated evidences in their predictions. Using this comprehensive, in-silico, analytical approach, we successfully prioritized all the pigmentation-associated GWAS-SNPs and tried to annotate pigmentation-related functionality to them, which would pave the way for deeper understanding of the molecular basis of human skin pigmentation variations.

Trafficking of the human ether-a-go-go-related gene (hERG) potassium channel is regulated by the ubiquitin ligase rififylin (RFFL)

The QT interval is an important diagnostic feature on surface electrocardiograms because it reflects the duration of the ventricular action potential. A previous genome-wide association study has reported a significant linkage between a single-nucleotide polymorphism ∼11.7 kb downstream of the gene encoding the RING finger ubiquitin ligase rififylin (RFFL) and variability in the QT interval. This, along with results in animal studies, suggests that RFFL may have effects on cardiac repolarization. Here, we sought to determine the role of RFFL in cardiac electrophysiology. Adult rabbit cardiomyocytes with adenovirus-expressed RFFL exhibited reduced rapid delayed rectifier current (I _Kr). Neonatal rabbit cardiomyocytes transduced with RFFL-expressing adenovirus exhibited reduced total expression of the potassium channel ether-a-go-go-related gene (rbERG). Using transfections of 293A cells and Western blotting experiments, we observed that RFFL and the core-glycosylated form of the human ether-a-go-go-related gene (hERG) potassium channel interact. Furthermore, RFFL overexpression led to increased polyubiquitination and proteasomal degradation of hERG protein and to an almost complete disappearance of I _Kr, which depended on the intact RING domain of RFFL. Blocking the ER-associated degradation (ERAD) pathway with a dominant-negative form of the ERAD core component, valosin-containing protein (VCP), in 293A cells partially abolished RFFL-mediated hERG degradation. We further substantiated the link between RFFL and ERAD by showing an interaction between RFFL and VCP in vitro We conclude that RFFL is an important regulator of voltage-gated hERG potassium channel activity and therefore cardiac repolarization and that this ubiquitination-mediated regulation requires parts of the ERAD pathway.

Alternative splicing links histone modifications to stem cell fate decision

BACKGROUND

Understanding the embryonic stem cell (ESC) fate decision between self-renewal and proper differentiation is important for developmental biology and regenerative medicine. Attention has focused on mechanisms involving histone modifications, alternative pre-messenger RNA splicing, and cell-cycle progression. However, their intricate interrelations and joint contributions to ESC fate decision remain unclear.

RESULTS

We analyze the transcriptomes and epigenomes of human ESC and five types of differentiated cells. We identify thousands of alternatively spliced exons and reveal their development and lineage-dependent characterizations. Several histone modifications show dynamic changes in alternatively spliced exons and three are strongly associated with 52.8% of alternative splicing events upon hESC differentiation. The histone modification-associated alternatively spliced genes predominantly function in G2/M phases and ATM/ATR-mediated DNA damage response pathway for cell differentiation, whereas other alternatively spliced genes are enriched in the G1 phase and pathways for self-renewal. These results imply a potential epigenetic mechanism by which some histone modifications contribute to ESC fate decision through the regulation of alternative splicing in specific pathways and cell-cycle genes. Supported by experimental validations and extended datasets from Roadmap/ENCODE projects, we exemplify this mechanism by a cell-cycle-related transcription factor, PBX1, which regulates the pluripotency regulatory network by binding to NANOG. We suggest that the isoform switch from PBX1a to PBX1b links H3K36me3 to hESC fate determination through the PSIP1/SRSF1 adaptor, which results in the exon skipping of PBX1.

CONCLUSION

We reveal the mechanism by which alternative splicing links histone modifications to stem cell fate decision.

Diminished PRRX1 Expression Is Associated With Increased Risk of Atrial Fibrillation and Shortening of the Cardiac Action Potential

BACKGROUND

Atrial fibrillation (AF) affects over 33 million individuals worldwide. Genome-wide association studies have identified at least 30 AF loci, but the mechanisms through which individual variants lead to altered disease risk have remained unclear for the majority of these loci. At the 1q24 locus, we hypothesized that the transcription factor PRRX1 could be a strong candidate gene as it is expressed in the pulmonary veins, a source of AF in many individuals. We sought to identify the molecular mechanism, whereby variation at 1q24 may lead to AF susceptibility.

METHODS AND RESULTS

We sequenced a ≈158 kb region encompassing PRRX1 in 962 individuals with and without AF. We identified a broad region of association with AF at the 1q24 locus. Using in silico prediction and functional validation, we identified an enhancer that interacts with the promoter of PRRX1 in cells of cardiac lineage. Within this enhancer, we identified a single-nucleotide polymorphism, rs577676, which alters enhancer activity in a mouse atrial cell line and in embryonic zebrafish and differentially regulates PRRX1 expression in human left atria. We found that suppression of PRRX1 in human embryonic stem cell-derived cardiomyocytes and embryonic zebrafish resulted in shortening of the atrial action potential duration, a hallmark of AF.

CONCLUSIONS

We have identified a functional genetic variant that alters PRRX1 expression, ultimately resulting in electrophysiological alterations in atrial myocytes that may promote AF.

A statistical analysis on transcriptome sequences: The enrichment of Alu-element is associated with subcellular location

The Alu-element plays important roles in mediating alternative splicing, RNA editing and translation regulation. However, the distribution and function of the Alu-element are never analysed at the transcriptome level. This study presents a statistical analysis of the Alu-element on human transcriptome. We found that mRNAs and lncRNAs share the same sequence form for the Alu-element. The Alu-element covers 5.8% of the coding transcripts and 17.1% of the coding genes for mRNAs, and covers 9.3% of the transcripts and 13.6% of the genes for lncRNAs. The Alu-element is preferentially located at the 3' end. Statistical analysis demonstrates that the enrichment of Alu-element is associated with subcellular location. For instance, Alu-inclusive transcripts are overexpressed in nucleus, mitochondrion and Golgi apparatus membrane while under-expressed in cell membrane and extracellular space. We found that genes contain both Alu-element and S- domains of 7SL RNA are all associated with cellular activities carried out in mitochondrion.

Intragenic CNVs for epigenetic regulatory genes in intellectual disability: Survey identifies pathogenic and benign single exon changes

The disruption of genes involved in epigenetic regulation is well known to cause Intellectual Disability (ID). We reported a custom microarray study that interrogated among others, the epigenetic regulatory gene-class, at single exon resolution. Here we elaborate on identified intragenic CNVs involving epigenetic regulatory genes; specifically discussing those in three genes previously unreported in ID etiology-ARID2, KDM3A, and ARID4B. The changes in ARID2 and KDM3A are likely pathogenic while the ARID4B variant is uncertain. Previously, we found a CNV involving only exon 6 of the JARID2 gene occurred apparently de novo in seven patients. JARID2 is known to cause ID and other neurodevelopmental conditions. However, exon 6 of this gene encodes one of a series of repeated motifs. We therefore, investigated the impact of this variant in two cohorts and present a genotype-phenotype assessment. We find the JARID2 exon 6 CNV is benign, with a high population frequency (>14%), but nevertheless could have a contributory effect. We also present results from an interrogation of the exomes of 2,044 patients with neurocognitive phenotypes for the incidence of potentially damaging mutation in the epigenetic regulatory gene-class. This paper provides a survey of the fine-scale CNV landscape for epigenetic regulatory genes in the context of ID, describing likely pathogenic as well as benign single exon imbalances. © 2016 Wiley Periodicals, Inc.

C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search

Background

Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge.

Results

We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge.

Conclusions

C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1786-6) contains supplementary material, which is available to authorized users.

Identification of key genes induced by platelet-rich plasma in human dermal papilla cells using bioinformatics methods

Dermal papilla cells (DPCs) are located at the base of hair follicles, and are known to induce hair follicle regeneration. Platelet-rich plasma (PRP) functions in hair follicle regeneration. To investigate the influence of PRP on DPCs, the present study analyzed RNA-seq data of human hair dermal papilla cells (HHDPCs) that were treated or untreated by PRP. The data included in the RNA-seq were from two normal and two treated HHDPC samples. Following identification by Cuffdiff software, differentially expressed genes (DEGs) underwent enrichment analyses, and protein-protein interaction networks were constructed using Cytoscape software. Additionally, transcription factor (TF)-DEG and TF-long non-coding RNA (lncRNA) regulatory networks were constructed. A total of 178 differentially expressed lncRNA were screened, 365 were upregulated and 142 were downregulated. Notably, upregulated cyclin dependent kinase 1 (CDK1) (degree=76), polo-like kinase 1 (PLK1) (degree=65), cell division cycle 20 (degree=50), cyclin B1 (degree=49), aurora kinase B (degree=47), cyclin dependent kinase 2 (degree=46) and downregulated v-myc avian myelocytomatosis viral oncogene homolog (MYC) (degree=12) had higher degrees in networks. In addition, CCAAT/enhancer binding protein β, E2F transcription factor 1 (E2F1), early growth response 1 and MYC may be key TFs for their target genes, and were enriched in pathways associated with the cell cycle. They may also be involved in cell proliferation via various interactions with other genes, for example CDK1-PLK1 and E2F1→CDK1. These dysregulated genes induced by PRP may affect proliferation of HHDPCs.

A Functional Variant Associated with Atrial Fibrillation Regulates PITX2c Expression through TFAP2a

The most significantly associated genetic locus for atrial fibrillation (AF) is in chromosomal region 4q25, where four independent association signals have been identified. Although model-system studies suggest that altered PITX2c expression might underlie the association, the link between specific variants and the direction of effect on gene expression remains unknown for all four signals. In the present study, we analyzed the AF-associated region most proximal to PITX2 at 4q25. First, we identified candidate regulatory variants that might confer AF risk through a combination of mammalian conservation, DNase hypersensitivity, and histone modification from ENCODE and the Roadmap Epigenomics Project, as well as through in vivo analysis of enhancer activity in embryonic zebrafish. Within candidate regions, we then identified a single associated SNP, rs2595104, which displayed dramatically reduced enhancer activity with the AF risk allele. CRISPR-Cas9-mediated deletion of the rs2595104 region and editing of the rs2595104 risk allele in human stem-cell-derived cardiomyocytes resulted in diminished PITX2c expression in comparison to that of the non-risk allele. This differential activity was mediated by activating enhancer binding protein 2 alpha (TFAP2a), which bound robustly to the non-risk allele at rs2595104, but not to the risk allele, in cardiomyocytes. In sum, we found that the AF-associated SNP rs2595104 altered PITX2c expression via interaction with TFAP2a. Such a pathway could ultimately contribute to AF susceptibility at the PITX2 locus associated with AF.

rAAV-compatible MiniPromoters for restricted expression in the brain and eye

BACKGROUND

Small promoters that recapitulate endogenous gene expression patterns are important for basic, preclinical, and now clinical research. Recently, there has been a promising revival of gene therapy for diseases with unmet therapeutic needs. To date, most gene therapies have used viral-based ubiquitous promoters-however, promoters that restrict expression to target cells will minimize off-target side effects, broaden the palette of deliverable therapeutics, and thereby improve safety and efficacy. Here, we take steps towards filling the need for such promoters by developing a high-throughput pipeline that goes from genome-based bioinformatic design to rapid testing in vivo.

METHODS

For much of this work, therapeutically interesting Pleiades MiniPromoters (MiniPs; ~4 kb human DNA regulatory elements), previously tested in knock-in mice, were "cut down" to ~2.5 kb and tested in recombinant adeno-associated virus (rAAV), the virus of choice for gene therapy of the central nervous system. To evaluate our methods, we generated 29 experimental rAAV2/9 viruses carrying 19 different MiniPs, which were injected intravenously into neonatal mice to allow broad unbiased distribution, and characterized in neural tissues by X-gal immunohistochemistry for icre, or immunofluorescent detection of GFP.

RESULTS

The data showed that 16 of the 19 (84 %) MiniPs recapitulated the expression pattern of their design source. This included expression of: Ple67 in brain raphe nuclei; Ple155 in Purkinje cells of the cerebellum, and retinal bipolar ON cells; Ple261 in endothelial cells of brain blood vessels; and Ple264 in retinal Müller glia.

CONCLUSIONS

Overall, the methodology and MiniPs presented here represent important advances for basic and preclinical research, and may enable a paradigm shift in gene therapy.

Regulation of functional KCNQ1OT1 lncRNA by β-catenin

Long noncoding RNAs (lncRNAs) have been implicated in many biological processes through epigenetic mechanisms. We previously reported that KCNQ1OT1, an imprinted antisense lncRNA in the human KCNQ1 locus on chromosome 11p15.5, is involved in cis-limited silencing within an imprinted KCNQ1 cluster. Furthermore, aberration of KCNQ1OT1 transcription was observed with a high frequency in colorectal cancers. However, the molecular mechanism of the transcriptional regulation and the functional role of KCNQ1OT1 in colorectal cancer remain unclear. Here, we show that the KCNQ1OT1 transcriptional level was significantly increased in human colorectal cancer cells in which β-catenin was excessively accumulated in the nucleus. Additionally, overexpression of β-catenin resulted in an increase in KCNQ1OT1 lncRNA-coated territory. On the other hand, knockdown of β-catenin resulted in significant decrease of KCNQ1OT1 lncRNA-coated territory and an increase in the mRNA expression of the SLC22A18 and PHLDA2 genes that are regulated by KCNQ1OT1. We showed that β-catenin can promote KCNQ1OT1 transcription through direct binding to the KCNQ1OT1 promoter. Our evidence indicates that β-catenin signaling may contribute to development of colorectal cancer by functioning as a novel lncRNA regulatory factor via direct targeting of KCNQ1OT1.

Genome Sequencing of Autism-Affected Families Reveals Disruption of Putative Noncoding Regulatory DNA

We performed whole-genome sequencing (WGS) of 208 genomes from 53 families affected by simplex autism. For the majority of these families, no copy-number variant (CNV) or candidate de novo gene-disruptive single-nucleotide variant (SNV) had been detected by microarray or whole-exome sequencing (WES). We integrated multiple CNV and SNV analyses and extensive experimental validation to identify additional candidate mutations in eight families. We report that compared to control individuals, probands showed a significant (p = 0.03) enrichment of de novo and private disruptive mutations within fetal CNS DNase I hypersensitive sites (i.e., putative regulatory regions). This effect was only observed within 50 kb of genes that have been previously associated with autism risk, including genes where dosage sensitivity has already been established by recurrent disruptive de novo protein-coding mutations (ARID1B, SCN2A, NR3C2, PRKCA, and DSCAM). In addition, we provide evidence of gene-disruptive CNVs (in DISC1, WNT7A, RBFOX1, and MBD5), as well as smaller de novo CNVs and exon-specific SNVs missed by exome sequencing in neurodevelopmental genes (e.g., CANX, SAE1, and PIK3CA). Our results suggest that the detection of smaller, often multiple CNVs affecting putative regulatory elements might help explain additional risk of simplex autism.

MIR retrotransposon sequences provide insulators to the human genome

Insulators are regulatory elements that help to organize eukaryotic chromatin via enhancer-blocking and chromatin barrier activity. Although there are several examples of transposable element (TE)-derived insulators, the contribution of TEs to human insulators has not been systematically explored. Mammalian-wide interspersed repeats (MIRs) are a conserved family of TEs that have substantial regulatory capacity and share sequence characteristics with tRNA-related insulators. We sought to evaluate whether MIRs can serve as insulators in the human genome. We applied a bioinformatic screen using genome sequence and functional genomic data from CD4(+) T cells to identify a set of 1,178 predicted MIR insulators genome-wide. These predicted MIR insulators were computationally tested to serve as chromatin barriers and regulators of gene expression in CD4(+) T cells. The activity of predicted MIR insulators was experimentally validated using in vitro and in vivo enhancer-blocking assays. MIR insulators are enriched around genes of the T-cell receptor pathway and reside at T-cell-specific boundaries of repressive and active chromatin. A total of 58% of the MIR insulators predicted here show evidence of T-cell-specific chromatin barrier and gene regulatory activity. MIR insulators appear to be CCCTC-binding factor (CTCF) independent and show a distinct local chromatin environment with marked peaks for RNA Pol III and a number of histone modifications, suggesting that MIR insulators recruit transcriptional complexes and chromatin modifying enzymes in situ to help establish chromatin and regulatory domains in the human genome. The provisioning of insulators by MIRs across the human genome suggests a specific mechanism by which TE sequences can be used to modulate gene regulatory networks.

LncRNA HOTAIR: A master regulator of chromatin dynamics and cancer

Non-coding RNAs (ncRNAs) are emerging classes of regulatory RNA that play key roles in various cellular and physiological processes such as in gene regulation, chromatin dynamics, cell differentiation, and development. NcRNAs are dysregulated in a variety of human disorders including cancers, neurological disorders, and immunological disorders. The mechanisms through which ncRNAs regulate various biological processes and human diseases still remain elusive. HOX antisense intergenic RNA (HOTAIR) is a recently discovered long non-coding RNA (lncRNA) that plays critical role in gene regulation and chromatin dynamics, appears to be misregulated in a variety of cancers. HOTAIR interacts with key epigenetic regulators such as histone methyltransferase PRC2 and histone demethylase LSD1 and regulates gene silencing. Here, we have reviewed recent advancements in understanding the functions and regulation of HOTAIR and its association with cancer and other diseases.

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets

MOTIVATION

ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed.

RESULTS

In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones.

AVAILABILITY AND IMPLEMENTATION

An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html.

Histone modifications involved in cassette exon inclusions: a quantitative and interpretable analysis

Background

Chromatin structure and epigenetic modifications have been shown to involve in the co-transcriptional splicing of RNA precursors. In particular, some studies have suggested that some types of histone modifications (HMs) may participate in the alternative splicing and function as exon marks. However, most existing studies pay attention to the qualitative relationship between epigenetic modifications and exon inclusion. The quantitative analysis that reveals to what extent each type of epigenetic modification is responsible for exon inclusion is very helpful for us to understand the splicing process.

Results

In this paper, we focus on the quantitative analysis of HMs’ influence on the inclusion of cassette exons (CEs) into mature RNAs. With the high-throughput ChIP-seq and RNA-seq data obtained from ENCODE website, we modeled the association of HMs with CE inclusions by logistic regression whose coefficients are meaningful and interpretable for us to reveal the effect of each type of HM. Three type of HMs, H3K36me3, H3K9me3 and H4K20me1, were found to play major role in CE inclusions. HMs’ effect on CE inclusions is conservative across cell types, and does not depend on the expression levels of the genes hosting CEs. HMs located in the flanking regions of CEs were also taken into account in our analysis, and HMs within bounded flanking regions were shown to affect moderately CE inclusions. Moreover, we also found that HMs on CEs whose length is approximately close to nucleosomal-DNA length affect greatly on CE inclusion.

Conclusions

We suggested that a few types of HMs correlate closely to alternative splicing and perhaps function jointly with splicing machinery to regulate the inclusion level of exons. Our findings are helpful to understand HMs’ effect on exon definition, as well as the mechanism of co-transcriptional splicing.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1148) contains supplementary material, which is available to authorized users.

JNK suppresses tumor formation via a gene-expression program mediated by ATF2

JNK and p38 phosphorylate a diverse set of substrates and, consequently, can act in a context-dependent manner to either promote or inhibit tumor growth. Elucidating the functions of specific substrates of JNK and p38 is therefore critical for our understanding of these kinases in cancer. ATF2 is a phosphorylation-dependent transcription factor and substrate of both JNK and p38. Here, we show ATF2 suppresses tumor formation in an orthotopic model of liver cancer and cellular transformation in vitro. Furthermore, we find that suppression of tumorigenesis by JNK requires ATF2. We identify a transcriptional program activated by JNK via ATF2 and provide examples of JNK- and ATF2-dependent genes that block cellular transformation. Significantly, we also show that ATF2-dependent gene expression is frequently downregulated in human cancers, indicating that amelioration of JNK-ATF2-mediated suppression may be a common event during tumor development.

The common marmoset genome provides insight into primate biology and evolution

A first analysis of the genome sequence of the common marmoset (Callithrix jacchus), assembled using traditional Sanger methods and Ensembl annotation, has permitted genomic comparison with apes and that old world monkeys and the identification of specific molecular features a rapid reproductive capacity partly due to may contribute to the unique biology of diminutive The common marmoset has prevalence of this dizygotic primate. twins. Remarkably, these twins share placental circulation and exchange hematopoietic stem cells in utero, resulting in adults that are hematopoietic chimeras.

We observed positive selection or non-synonymous substitutions for genes encoding growth hormone / insulin-like growth factor (growth pathways), respiratory complex I (metabolic pathways), immunobiology, and proteases (reproductive and immunity pathways). In addition, both protein-coding and microRNA genes related to reproduction exhibit rapid sequence evolution. This New World monkey genome sequence enables significantly increased power for comparative analyses among available primate genomes and facilitates biomedical research application.

Long noncoding RNAs: emerging stars in gene regulation, epigenetics and human disease

Noncoding RNAs (ncRNAs) are classes of transcripts that are encoded by the genome and transcribed but never get translated into proteins. Though not translated into proteins, ncRNAs play pivotal roles in a variety of cellular functions. Here, we review the functions of long noncoding RNAs (lncRNAs) and their implications in various human diseases. Increasing numbers of studies demonstrate that lncRNAs play critical roles in regulation of protein-coding genes, maintenance of genomic integrity, dosage compensation, genomic imprinting, mRNA processing, cell differentiation, and development. Misregulation of lncRNAs is associated with a variety of human diseases, including cancer, immune and neurological disorders. Different classes of lncRNAs, their functions, mechanisms of action, and associations with different human diseases are summarized in detail, highlighting their as yet untapped potential in therapy.

Regulation of metabolism by long, non-coding RNAs

Our understanding of genomic regulation was revolutionized by the discovery that the genome is pervasively transcribed, giving rise to thousands of mostly uncharacterized non-coding ribonucleic acids (ncRNAs). Long, ncRNAs (lncRNAs) have thus emerged as a novel class of functional RNAs that impinge on gene regulation by a broad spectrum of mechanisms such as the recruitment of epigenetic modifier proteins, control of mRNA decay and DNA sequestration of transcription factors. We review those lncRNAs that are implicated in differentiation and homeostasis of metabolic tissues and present novel concepts on how lncRNAs might act on energy and glucose homeostasis. Finally, the control of circadian rhythm by lncRNAs is an emerging principles of lncRNA-mediated gene regulation.

PolyaPeak: detecting transcription factor binding sites from ChIP-seq using peak shape information

ChIP-seq is a powerful technology for detecting genomic regions where a protein of interest interacts with DNA. ChIP-seq data for mapping transcription factor binding sites (TFBSs) have a characteristic pattern: around each binding site, sequence reads aligned to the forward and reverse strands of the reference genome form two separate peaks shifted away from each other, and the true binding site is located in between these two peaks. While it has been shown previously that the accuracy and resolution of binding site detection can be improved by modeling the pattern, efficient methods are unavailable to fully utilize that information in TFBS detection procedure.

We present PolyaPeak, a new method to improve TFBS detection by incorporating the peak shape information. PolyaPeak describes peak shapes using a flexible Pólya model. The shapes are automatically learnt from the data using Minorization-Maximization (MM) algorithm, then integrated with the read count information via a hierarchical model to distinguish true binding sites from background noises.

Extensive real data analyses show that PolyaPeak is capable of robustly improving TFBS detection compared with existing methods. An R package is freely available.

Integrative analysis of many RNA-seq datasets to study alternative splicing

Alternative splicing is an important gene regulatory mechanism that dramatically increases the complexity of the proteome. However, how alternative splicing is regulated and how transcription and splicing are coordinated are still poorly understood, and functions of transcript isoforms have been studied only in a few limited cases. Nowadays, RNA-seq technology provides an exceptional opportunity to study alternative splicing on genome-wide scales and in an unbiased manner. With the rapid accumulation of data in public repositories, new challenges arise from the urgent need to effectively integrate many different RNA-seq datasets for study alterative splicing. This paper discusses a set of advanced computational methods that can integrate and analyze many RNA-seq datasets to systematically identify splicing modules, unravel the coupling of transcription and splicing, and predict the functions of splicing isoforms on a genome-wide scale.

PAVIS: a tool for Peak Annotation and Visualization

We introduce a web-based tool, Peak Annotation and Visualization (PAVIS), for annotating and visualizing ChIP-seq peak data. PAVIS is designed with non-bioinformaticians in mind and presents a straightforward user interface to facilitate biological interpretation of ChIP-seq peak or other genomic enrichment data. PAVIS, through association with annotation, provides relevant genomic context for each peak, such as peak location relative to genomic features including transcription start site, intron, exon or 5'/3'-untranslated region. PAVIS reports the relative enrichment P-values of peaks in these functionally distinct categories, and provides a summary plot of the relative proportion of peaks in each category. PAVIS, unlike many other resources, provides a peak-oriented annotation and visualization system, allowing dynamic visualization of tens to hundreds of loci from one or more ChIP-seq experiments, simultaneously. PAVIS enables rapid, and easy examination and cross-comparison of the genomic context and potential functions of the underlying genomic elements, thus supporting downstream hypothesis generation.

Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging

The functional potential of hematopoietic stem cells (HSCs) declines during aging, and in doing so, significantly contributes to hematopoietic pathophysiology in the elderly. To explore the relationship between age-associated HSC decline and the epigenome, we examined global DNA methylation of HSCs during ontogeny in combination with functional analysis. Although the DNA methylome is generally stable during aging, site-specific alterations of DNA methylation occur at genomic regions associated with hematopoietic lineage potential and selectively target genes expressed in downstream progenitor and effector cells. We found that age-associated HSC decline, replicative limits, and DNA methylation are largely dependent on the proliferative history of HSCs, yet appear to be telomere-length independent. Physiological aging and experimentally enforced proliferation of HSCs both led to DNA hypermethylation of genes regulated by Polycomb Repressive Complex 2. Our results provide evidence that epigenomic alterations of the DNA methylation landscape contribute to the functional decline of HSCs during aging.

Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics

The Human Genome Project (HGP) provided the initial draft of mankind's DNA sequence in 2001. The HGP was produced by 23 collaborating laboratories using Sanger sequencing of mapped regions as well as shotgun sequencing techniques in a process that occupied 13 years at a cost of ~$3 billion. Today, Next Generation Sequencing (NGS) techniques represent the next phase in the evolution of DNA sequencing technology at dramatically reduced cost compared to traditional Sanger sequencing. A single laboratory today can sequence the entire human genome in a few days for a few thousand dollars in reagents and staff time. Routine whole exome or even whole genome sequencing of clinical patients is well within the realm of affordability for many academic institutions across the country. This paper reviews current sequencing technology methods and upcoming advancements in sequencing technology as well as challenges associated with data generation, data manipulation and data storage. Implementation of routine NGS data in cancer genomics is discussed along with potential pitfalls in the interpretation of the NGS data. The overarching importance of bioinformatics in the clinical implementation of NGS is emphasized.[7] We also review the issue of physician education which also is an important consideration for the successful implementation of NGS in the clinical workplace. NGS technologies represent a golden opportunity for the next generation of pathologists to be at the leading edge of the personalized medicine approaches coming our way. Often under-emphasized issues of data access and control as well as potential ethical implications of whole genome NGS sequencing are also discussed. Despite some challenges, it's hard not to be optimistic about the future of personalized genome sequencing and its potential impact on patient care and the advancement of knowledge of human biology and disease in the near future.

Algorithm to identify frequent coupled modules from two-layered network series: application to study transcription and splicing coupling

Current network analysis methods all focus on one or multiple networks of the same type. However, cells are organized by multi-layer networks (e.g., transcriptional regulatory networks, splicing regulatory networks, protein-protein interaction networks), which interact and influence each other. Elucidating the coupling mechanisms among those different types of networks is essential in understanding the functions and mechanisms of cellular activities. In this article, we developed the first computational method for pattern mining across many two-layered graphs, with the two layers representing different types yet coupled biological networks. We formulated the problem of identifying frequent coupled clusters between the two layers of networks into a tensor-based computation problem, and proposed an efficient solution to solve the problem. We applied the method to 38 two-layered co-transcription and co-splicing networks, derived from 38 RNA-seq datasets. With the identified atlas of coupled transcription-splicing modules, we explored to what extent, for which cellular functions, and by what mechanisms transcription-splicing coupling takes place.

Identifying multi-layer gene regulatory modules from multi-dimensional genomic data

Motivation: Eukaryotic gene expression (GE) is subjected to precisely coordinated multi-layer controls, across the levels of epigenetic, transcriptional and post-transcriptional regulations. Recently, the emerging multi-dimensional genomic dataset has provided unprecedented opportunities to study the cross-layer regulatory interplay. In these datasets, the same set of samples is profiled on several layers of genomic activities, e.g. copy number variation (CNV), DNA methylation (DM), GE and microRNA expression (ME). However, suitable analysis methods for such data are currently sparse.

Results: In this article, we introduced a sparse Multi-Block Partial Least Squares (sMBPLS) regression method to identify multi-dimensional regulatory modules from this new type of data. A multi-dimensional regulatory module contains sets of regulatory factors from different layers that are likely to jointly contribute to a local ‘gene expression factory’. We demonstrated the performance of our method on the simulated data as well as on The Cancer Genomic Atlas Ovarian Cancer datasets including the CNV, DM, ME and GE data measured on 230 samples. We showed that majority of identified modules have significant functional and transcriptional enrichment, higher than that observed in modules identified using only a single type of genomic data. Our network analysis of the modules revealed that the CNV, DM and microRNA can have coupled impact on expression of important oncogenes and tumor suppressor genes.

Availability and implementation: The source code implemented by MATLAB is freely available at: http://zhoulab.usc.edu/sMBPLS/.

Contact:xjzhou@usc.edu

Supplementary information:Supplementary material are available at Bioinformatics online.

Integrating many co-splicing networks to reconstruct splicing regulatory modules

BACKGROUND

Alternative splicing is a ubiquitous gene regulatory mechanism that dramatically increases the complexity of the proteome. However, the mechanism for regulating alternative splicing is poorly understood, and study of coordinated splicing regulation has been limited to individual cases. To study genome-wide splicing regulation, we integrate many human RNA-seq datasets to identify splicing module, which we define as a set of cassette exons co-regulated by the same splicing factors.

RESULTS

We have designed a tensor-based approach to identify co-splicing clusters that appear frequently across multiple conditions, thus very likely to represent splicing modules - a unit in the splicing regulatory network. In particular, we model each RNA-seq dataset as a co-splicing network, where the nodes represent exons and the edges are weighted by the correlations between exon inclusion rate profiles. We apply our tensor-based method to the 38 co-splicing networks derived from human RNA-seq datasets and indentify an atlas of frequent co-splicing clusters. We demonstrate that these identified clusters represent potential splicing modules by validating against four biological knowledge databases. The likelihood that a frequent co-splicing cluster is biologically meaningful increases with its recurrence across multiple datasets, highlighting the importance of the integrative approach.

CONCLUSIONS

Co-splicing clusters reveal novel functional groups which cannot be identified by co-expression clusters, particularly they can grant new insights into functions associated with post-transcriptional regulation, and the same exons can dynamically participate in different pathways depending on different conditions and different other exons that are co-spliced. We propose that by identifying splicing module, a unit in the splicing regulatory network can serve as an important step to decipher the splicing code.

Epithelial E- and P-cadherins: role and clinical significance in cancer

E-cadherin and P-cadherin are major contributors to cell-cell adhesion in epithelial tissues, playing pivotal roles in important morphogenetic and differentiation processes during development, and in maintaining integrity and homeostasis in adult tissues. It is now generally accepted that alterations in these two molecules are observed during tumour progression of most carcinomas. Genetic or epigenetic alterations in E- and P-cadherin-encoding genes (CDH1 and CDH3, respectively), or alterations in their proteins expression, often result in tissue disorder, cellular de-differentiation, increased invasiveness of tumour cells and ultimately in metastasis. In this review, we will discuss the major properties of E- and P-cadherin molecules, its regulation in normal tissue, and their alterations and role in cancer, with a specific focus on gastric and breast cancer models.

On the presence and role of human gene-body DNA methylation

DNA methylation of promoter sequences is a repressive epigenetic mark that down-regulates gene expression. However, DNA methylation is more prevalent within gene-bodies than seen for promoters, and gene-body methylation has been observed to be positively correlated with gene expression levels. This paradox remains unexplained, and accordingly the role of DNA methylation in gene-bodies is poorly understood. We addressed the presence and role of human gene-body DNA methylation using a meta-analysis of human genome-wide methylation, expression and chromatin data sets. Methylation is associated with transcribed regions as genic sequences have higher levels of methylation than intergenic or promoter sequences. We also find that the relationship between gene-body DNA methylation and expression levels is non-monotonic and bell-shaped. Mid-level expressed genes have the highest levels of gene-body methylation, whereas the most lowly and highly expressed sets of genes both have low levels of methylation. While gene-body methylation can be seen to efficiently repress the initiation of intragenic transcription, the vast majority of methylated sites within genes are not associated with intragenic promoters. In fact, highly expressed genes initiate the most intragenic transcription inconsistent with the previously held notion that gene-body methylation serves to repress spurious intragenic transcription to allow for efficient transcriptional elongation. These observations lead us to propose a model to explain the presence of human gene-body methylation. This model holds that the repression of intragenic transcription by gene-body methylation is largely epiphenomenal, and suggests that gene-body methylation levels are predominantly shaped via the accessibility of the DNA to methylating enzyme complexes.

Structural architecture of the human long non-coding RNA, steroid receptor RNA activator

While functional roles of several long non-coding RNAs (lncRNAs) have been determined, the molecular mechanisms are not well understood. Here, we report the first experimentally derived secondary structure of a human lncRNA, the steroid receptor RNA activator (SRA), 0.87 kB in size. The SRA RNA is a non-coding RNA that coactivates several human sex hormone receptors and is strongly associated with breast cancer. Coding isoforms of SRA are also expressed to produce proteins, making the SRA gene a unique bifunctional system. Our experimental findings (SHAPE, in-line, DMS and RNase V1 probing) reveal that this lncRNA has a complex structural organization, consisting of four domains, with a variety of secondary structure elements. We examine the coevolution of the SRA gene at the RNA structure and protein structure levels using comparative sequence analysis across vertebrates. Rapid evolutionary stabilization of RNA structure, combined with frame-disrupting mutations in conserved regions, suggests that evolutionary pressure preserves the RNA structural core rather than its translational product. We perform similar experiments on alternatively spliced SRA isoforms to assess their structural features.

Protein-binding microarray analysis of tumor suppressor AP2α target gene specificity

Cheap and massively parallel methods to assess the DNA-binding specificity of transcription factors are actively sought, given their prominent regulatory role in cellular processes and diseases. Here we evaluated the use of protein-binding microarrays (PBM) to probe the association of the tumor suppressor AP2α with 6000 human genomic DNA regulatory sequences. We show that the PBM provides accurate relative binding affinities when compared to quantitative surface plasmon resonance assays. A PBM-based study of human healthy and breast tumor tissue extracts allowed the identification of previously unknown AP2α target genes and it revealed genes whose direct or indirect interactions with AP2α are affected in the diseased tissues. AP2α binding and regulation was confirmed experimentally in human carcinoma cells for novel target genes involved in tumor progression and resistance to chemotherapeutics, providing a molecular interpretation of AP2α role in cancer chemoresistance. Overall, we conclude that this approach provides quantitative and accurate assays of the specificity and activity of tumor suppressor and oncogenic proteins in clinical samples, interfacing genomic and proteomic assays.

Tissue-specific prediction of directly regulated genes

Direct binding by a transcription factor (TF) to the proximal promoter of a gene is a strong evidence that the TF regulates the gene. Assaying the genome-wide binding of every TF in every cell type and condition is currently impractical. Histone modifications correlate with tissue/cell/condition-specific ('tissue specific') TF binding, so histone ChIP-seq data can be combined with traditional position weight matrix (PWM) methods to make tissue-specific predictions of TF-promoter interactions.

RESULTS

We use supervised learning to train a naïve Bayes predictor of TF-promoter binding. The predictor's features are the histone modification levels and a PWM-based score for the promoter. Training and testing uses sets of promoters labeled using TF ChIP-seq data, and we use cross-validation on 23 such datasets to measure the accuracy. A PWM+histone naïve Bayes predictor using a single histone modification (H3K4me3) is substantially more accurate than a PWM score or a conservation-based score (phylogenetic motif model). The naïve Bayes predictor is more accurate (on average) at all sensitivity levels, and makes only half as many false positive predictions at sensitivity levels from 10% to 80%. On average, it correctly predicts 80% of bound promoters at a false positive rate of 20%. Accuracy does not diminish when we test the predictor in a different cell type (and species) from training. Accuracy is barely diminished even when we train the predictor without using TF ChIP-seq data.

AVAILABILITY

Our tissue-specific predictor of promoters bound by a TF is called Dr Gene and is available at http://bioinformatics.org.au/drgene.

CONTACT

t.bailey@imb.uq.edu.au

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Copy number variants in candidate genes are genetic modifiers of Hirschsprung disease

Hirschsprung disease (HSCR) is a neurocristopathy characterized by absence of intramural ganglion cells along variable lengths of the gastrointestinal tract. The HSCR phenotype is highly variable with respect to gender, length of aganglionosis, familiality and the presence of additional anomalies. By molecular genetic analysis, a minimum of 11 neuro-developmental genes (RET, GDNF, NRTN, SOX10, EDNRB, EDN3, ECE1, ZFHX1B, PHOX2B, KIAA1279, TCF4) are known to harbor rare, high-penetrance mutations that confer a large risk to the bearer. In addition, two other genes (RET, NRG1) harbor common, low-penetrance polymorphisms that contribute only partially to risk and can act as genetic modifiers. To broaden this search, we examined whether a set of 67 proven and candidate HSCR genes harbored additional modifier alleles. In this pilot study, we utilized a custom-designed array CGH with ∼33,000 test probes at an average resolution of ∼185 bp to detect gene-sized or smaller copy number variants (CNVs) within these 67 genes in 18 heterogeneous HSCR patients. Using stringent criteria, we identified CNVs at three loci (MAPK10, ZFHX1B, SOX2) that are novel, involve regulatory and coding sequences of neuro-developmental genes, and show association with HSCR in combination with other congenital anomalies. Additional CNVs are observed under relaxed criteria. Our research suggests a role for CNVs in HSCR and, importantly, emphasizes the role of variation in regulatory sequences. A much larger study will be necessary both for replication and for identifying the full spectrum of small CNV effects.

Integrative analysis of many weighted co-expression networks using tensor computation

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks.

SNPTransformer: a lightweight toolkit for genome-wide association studies

High-throughput genotyping chips have produced huge datasets for genome-wide association studies (GWAS) that have contributed greatly to discovering susceptibility genes for complex diseases. There are two strategies for performing data analysis for GWAS. One strategy is to use open-source or commercial packages that are designed for GWAS. The other is to take advantage of classic genetic programs with specific functions, such as linkage disequilibrium mapping, haplotype inference and transmission disequilibrium tests. However, most classic programs that are available are not suitable for analyzing chip data directly and require custom-made input, which results in the inconvenience of converting raw genotyping files into various data formats. We developed a powerful, user-friendly, lightweight program named SNPTransformer for GWAS that includes five major modules (Transformer, Operator, Previewer, Coder and Simulator). The toolkit not only works for transforming the genotyping files into ten input formats for use with classic genetics packages, but also carries out useful functions such as relational operations on IDs, previewing data files, recoding data formats and simulating marker files, among other functions. It bridges upstream raw genotyping data with downstream genetic programs, and can act as an in-hand toolkit for human geneticists, especially for non-programmers. SNPTransformer is freely available at http://snptransformer.sourceforge.net.

Bacterial artificial chromosomes as analytical basis for gene transcriptional machineries

Bacterial Artificial Chromosomes (BACs) had been minimal components of various genome-sequencing projects, constituting perfect analytical basis for functional genomics. Here we describe an enhancer screening strategy in which BAC clones that cover any genomic segments of interest are modified to harbor a reporter cassette by transposon tagging, then processed to carry selected combinations of gene regulatory modules by homologous recombination mediated systematic deletions. Such engineered BAC-reporter constructs in bacterial cells are ready for efficient transgenesis in mice to evaluate activities of gene regulatory modules intact or absent in the constructs. By utilizing the strategy, we could speedily identify a critical genomic fragment for spatio-temporally regulated expression of a mouse cadherin gene whose structure is extraordinarily huge and intricate. This BAC-based methodology would hence provide a novel screening platform for gene transcriptional machineries that dynamically fluctuate during development, pathogenesis and/or evolution.

The UCSC Genome Browser database: update 2011

The University of California, Santa Cruz Genome Browser (http://genome.ucsc.edu) offers online access to a database of genomic sequence and annotation data for a wide variety of organisms. The Browser also has many tools for visualizing, comparing and analyzing both publicly available and user-generated genomic data sets, aligning sequences and uploading user data. Among the features released this year are a gene search tool and annotation track drag-reorder functionality as well as support for BAM and BigWig/BigBed file formats. New display enhancements include overlay of multiple wiggle tracks through use of transparent coloring, options for displaying transformed wiggle data, a 'mean+whiskers' windowing function for display of wiggle data at high zoom levels, and more color schemes for microarray data. New data highlights include seven new genome assemblies, a Neandertal genome data portal, phenotype and disease association data, a human RNA editing track, and a zebrafish Conservation track. We also describe updates to existing tracks.

Genomic screening with RNAi: results and challenges

RNA interference (RNAi) is an effective tool for genome-scale, high-throughput analysis of gene function. In the past five years, a number of genome-scale RNAi high-throughput screens (HTSs) have been done in both Drosophila and mammalian cultured cells to study diverse biological processes, including signal transduction, cancer biology, and host cell responses to infection. Results from these screens have led to the identification of new components of these processes and, importantly, have also provided insights into the complexity of biological systems, forcing new and innovative approaches to understanding functional networks in cells. Here, we review the main findings that have emerged from RNAi HTS and discuss technical issues that remain to be improved, in particular the verification of RNAi results and validation of their biological relevance. Furthermore, we discuss the importance of multiplexed and integrated experimental data analysis pipelines to RNAi HTS.

Most transcription factor binding sites are in a few mosaic classes of the human genome

Background

Many algorithms for finding transcription factor binding sites have concentrated on the characterisation of the binding site itself: and these algorithms lead to a large number of false positive sites. The DNA sequence which does not bind has been modeled only to the extent necessary to complement this formulation.

Results

We find that the human genome may be described by 19 pairs of mosaic classes, each defined by its base frequencies, (or more precisely by the frequencies of doublets), so that typically a run of 10 to 100 bases belongs to the same class. Most experimentally verified binding sites are in the same four pairs of classes. In our sample of seventeen transcription factors — taken from different families of transcription factors — the average proportion of sites in this subset of classes was 75%, with values for individual factors ranging from 48% to 98%. By contrast these same classes contain only 26% of the bases of the genome and only 31% of occurrences of the motifs of these factors — that is places where one might expect the factors to bind. These results are not a consequence of the class composition in promoter regions.

Conclusions

This method of analysis will help to find transcription factor binding sites and assist with the problem of false positives. These results also imply a profound difference between the mosaic classes.

The UCSC Genome Browser

The University of California Santa Cruz (UCSC) Genome Browser is a popular Web-based tool for quickly displaying a requested portion of a genome at any scale, accompanied by a series of aligned annotation "tracks." The annotations-generated by the UCSC Genome Bioinformatics Group and external collaborators-display gene predictions, mRNA and expressed sequence tag alignments, simple nucleotide polymorphisms, expression and regulatory data, phenotype and variation data, and pairwise and multiple-species comparative genomics data. All information relevant to a region is presented in one window, facilitating biological analysis and interpretation. The database tables underlying the Genome Browser tracks can be viewed, downloaded, and manipulated using another Web-based application, the UCSC Table Browser. Users can upload data as custom annotation tracks in both browsers for research or educational use. This unit describes how to use the Genome Browser and Table Browser for genome analysis, download the underlying database tables, and create and display custom annotation tracks.

ENCODE whole-genome data in the UCSC Genome Browser

The Encyclopedia of DNA Elements (ENCODE) project is an international consortium of investigators funded to analyze the human genome with the goal of producing a comprehensive catalog of functional elements. The ENCODE Data Coordination Center at The University of California, Santa Cruz (UCSC) is the primary repository for experimental results generated by ENCODE investigators. These results are captured in the UCSC Genome Bioinformatics database and download server for visualization and data mining via the UCSC Genome Browser and companion tools (Rhead et al. The UCSC Genome Browser Database: update 2010, in this issue). The ENCODE web portal at UCSC (http://encodeproject.org or http://genome.ucsc.edu/ENCODE) provides information about the ENCODE data and convenient links for access.