CisGenome Browser: a flexible tool for genomic data visualization

Bi-allelic variants in NAE1 cause intellectual disability, ischiopubic hypoplasia, stress-mediated lymphopenia and neurodegeneration

Neddylation has been implicated in various cellular pathways and in the pathophysiology of numerous diseases. We identified four individuals with bi-allelic variants in NAE1, which encodes the neddylation E1 enzyme. Pathogenicity was supported by decreased NAE1 abundance and overlapping clinical and cellular phenotypes. To delineate how cellular consequences of NAE1 deficiency would lead to the clinical phenotype, we focused primarily on the rarest phenotypic features, based on the assumption that these would best reflect the pathophysiology at stake. Two of the rarest features, neuronal loss and lymphopenia worsening during infections, suggest that NAE1 is required during cellular stress caused by infections to protect against cell death. In support, we found that stressing the proteasome system with MG132-requiring upregulation of neddylation to restore proteasomal function and proteasomal stress-led to increased cell death in fibroblasts of individuals with NAE1 genetic variants. Additionally, we found decreased lymphocyte counts after CD3/CD28 stimulation and decreased NF-κB translocation in individuals with NAE1 variants. The rarest phenotypic feature-delayed closure of the ischiopubic rami-correlated with significant downregulation of RUN2X and SOX9 expression in transcriptomic data of fibroblasts. Both genes are involved in the pathophysiology of ischiopubic hypoplasia. Thus, we show that NAE1 plays a major role in (skeletal) development and cellular homeostasis during stress. Our approach suggests that a focus on rare phenotypic features is able to provide significant pathophysiological insights in diseases caused by mutations in genes with pleiotropic effects.

Revisiting AGAMOUS-LIKE15, a Key Somatic Embryogenesis Regulator, Using Next Generation Sequencing Analysis in Arabidopsis

AGAMOUS-like 15 (AGL15) is a member of the MADS-domain transcription factor (TF) family. MADS proteins are named for a conserved domain that was originally from an acronym derived from genes expressed in a variety of eukaryotes (MCM1-AGAMOUS-DEFICIENS-SERUM RESPONSE FACTOR). In plants, this family has expanded greatly, with more than one-hundred members generally found in dicots, and the proteins encoded by these genes have often been associated with developmental identity. AGL15 transcript and protein accumulate primarily in embryos and has been found to promote an important process called plant regeneration via somatic embryogenesis (SE). To understand how this TF performs this function, we have previously used microarray technologies to assess direct and indirect responsive targets of this TF. We have now revisited this question using next generation sequencing (NGS) to both characterize in vivo binding sites for AGL15 as well as response to the accumulation of AGL15. We compared these data to the prior microarray results to evaluate the different platforms. The new NGS data brought to light an interaction with brassinosteroid (BR) hormone signaling that was "missed" in prior Gene Ontology analysis from the microarray studies.

The MADS-domain factor AGAMOUS-Like18 promotes somatic embryogenesis

AGAMOUS-Like 18 (AGL18) is a MADS domain transcription factor (TF) that is structurally related to AGL15. Here we show that, like AGL15, AGL18 can promote somatic embryogenesis (SE) when ectopically expressed in Arabidopsis (Arabidopsis thaliana). Based on loss-of-function mutants, AGL15 and AGL18 have redundant functions in developmental processes such as SE. To understand the nature of this redundancy, we undertook a number of studies to look at the interaction between these factors. We studied the genome-wide direct targets of AGL18 to characterize its roles at the molecular level using chromatin immunoprecipitation (ChIP)-SEQ combined with RNA-SEQ. The results demonstrated that AGL18 binds to thousands of sites in the genome. Comparison of ChIP-SEQ data for AGL15 and AGL18 revealed substantial numbers of genes bound by both AGL15 and AGL18, but there were also differences. Gene ontology analysis revealed that target genes were enriched for seed, embryo, and reproductive development as well as hormone and stress responses. The results also demonstrated that AGL15 and AGL18 interact in a complex regulatory loop, where AGL15 inhibited transcript accumulation of AGL18, while AGL18 increased AGL15 transcript accumulation. Co-immunoprecipitation revealed an interaction between AGL18 and AGL15 in somatic embryo tissue. The binding and expression analyses revealed a complex crosstalk and interactions among embryo TFs and their target genes. In addition, our study also revealed that phosphorylation of AGL18 and AGL15 was crucial for the promotion of SE.

An information system on genomic elements and predicted protein structures of buffalo (Bubalus bubalis)

Among the livestock species, buffalo remained as an integral part of the Indian rural economy. With the advent of genome sequencing technologies, it became possible to sequence the whole genome of Murrah buffalo. Also, significant amount of information on different genomic elements of buffalo is available at National Centre for Biotechnology Information (NCBI). However, the positions of these elements on the genome are not fully known. In addition, the 3D structures of buffalo proteins are not available and also there exist no browser to visualize important genic elements on buffalo genome. Hence, a study was taken up to develop a web-based information system having information on genomic elements, protein 3-D structures and genome browser. Initially, information on nucleotide and protein sequences were retrieved from NCBI and parsed suitably. Later, the protein structures were predicted, validated, refined and stabilized in silico. An Information System on Buffalo Genome (ISBG) with 3-tier architecture was developed containing the sequence and structural information. ISBG contains complete coding sequences (CDS), Mitochondrial DNAs, 1k upstream regions and Untranslated Regions (UTRs) of buffalo genome. The buffalo genes were also mapped onto the genome. The results revealed that maximum number of genes were found distributed on chromosome 4 followed by chromosome 18, which can also be visualized from the developed genome browser. ISBG can be accessed at http://cabgrid.res.in:8080/bgis. The proposed information system helps animal breeders and biotechnologist in animal improvement.

Chromatin accessibility of circulating CD8+ T cells predicts treatment response to PD-1 blockade in patients with gastric cancer

Although tumor genomic profiling has identified small subsets of gastric cancer (GC) patients with clinical benefit from anti-PD-1 treatment, not all responses can be explained by tumor sequencing alone. We investigate epigenetic elements responsible for the differential response to anti-PD-1 therapy by quantitatively assessing the genome-wide chromatin accessibility of circulating CD8⁺ T cells in patients’ peripheral blood. Using an assay for transposase-accessible chromatin using sequencing (ATAC-seq), we identify unique open regions of chromatin that significantly distinguish anti-PD-1 therapy responders from non-responders. GC patients with high chromatin openness of circulating CD8⁺ T cells are significantly enriched in the responder group. Concordantly, patients with high chromatin openness at specific genomic positions of their circulating CD8⁺ T cells demonstrate significantly better survival than those with closed chromatin. Here we reveal that epigenetic characteristics of baseline CD8⁺ T cells can be used to identify metastatic GC patients who may benefit from anti-PD-1 therapy.

Anti-PD-1 therapy could induce a durable response in patients with gastric cancer, however biomarkers to predict response to immunotherapy are generally lacking. Here the authors report that openness of chromatin in circulating CD8⁺ T cells predicts treatment outcome in patients with metastatic gastric cancer treated with pembrolizumab.

Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

Global transcriptional analysis identifies a novel role for SOX4 in tumor-induced angiogenesis

The expression of the transcription factor SOX4 is increased in many human cancers, however, the pro-oncogenic capacity of SOX4 can vary greatly depending on the type of tumor. Both the contextual nature and the mechanisms underlying the pro-oncogenic SOX4 response remain unexplored. Here, we demonstrate that in mammary tumorigenesis, the SOX4 transcriptional network is dictated by the epigenome and is enriched for pro-angiogenic processes. We show that SOX4 directly regulates endothelin-1 (ET-1) expression and can thereby promote tumor-induced angiogenesis both in vitro and in vivo. Furthermore, in breast tumors, SOX4 expression correlates with blood vessel density and size, and predicts poor-prognosis in patients with breast cancer. Our data provide novel mechanistic insights into context-dependent SOX4 target gene selection, and uncover a novel pro-oncogenic role for this transcription factor in promoting tumor-induced angiogenesis. These findings establish a key role for SOX4 in promoting metastasis through exploiting diverse pro-tumorigenic pathways.

Integrated analysis of DNA methylome and transcriptome identified CREB5 as a novel risk gene contributing to recurrent pregnancy loss

Background

Aberrant DNA methylation is considered to be a potential cause of recurrent pregnancy loss (RPL), while potential mechanism has not yet been elucidated.

Methods

In order to uncover the contribution of the perturbation of DNA methylation in RPL, we performed genome-wide DNA methylation analysis combined with genome-wide gene expression in decidua tissue.

Findings

Totally, 539 differentially methylated regions (DMRs) were identified and significantly correlated with gene expressions. We observed that hypo-methylated DMR near CREB5 recruited transcription factors binding, such as P53 and SP1, and in turn upregulated CREB5. Compromised cell migration and apoptosis were observed in human CREB5 overexpression trophoblast cell lines, indicating dysfunctional trophoblast cells might contribute to RPL after hypo-methylation of CREB5. In addition, overexpression of CREB5 altered cell cycle.

Interpretation

Our data highlights a role of CREB5 involved in the pathogenesis of RPL, and CREB5 maybe a potential diagnostic biomarker for RPL.

Integration of Kinase and Calcium Signaling at the Level of Chromatin Underlies Inducible Gene Activation in T Cells

TCR signaling pathways cooperate to activate the inducible transcription factors NF-κB, NFAT, and AP-1. In this study, using the calcium ionophore ionomycin and/or PMA on Jurkat T cells, we show that the gene expression program associated with activation of TCR signaling is closely related to specific chromatin landscapes. We find that calcium and kinase signaling cooperate to induce chromatin remodeling at ∼2100 chromatin regions, which demonstrate enriched binding motifs for inducible factors and correlate with target gene expression. We found that these regions typically function as inducible enhancers. Many of these elements contain composite NFAT/AP-1 sites, which typically support cooperative binding, thus further reinforcing the need for cooperation between calcium and kinase signaling in the activation of genes in T cells. In contrast, treatment with PMA or ionomycin alone induces chromatin remodeling at far fewer regions (∼600 and ∼350, respectively), which mostly represent a subset of those induced by costimulation. This suggests that the integration of TCR signaling largely occurs at the level of chromatin, which we propose plays a crucial role in regulating T cell activation.

Extensive Association of Common Disease Variants with Regulatory Sequence

Overlap between non-coding DNA regulatory sequences and common variant associations can help to identify specific cell and tissue types that are relevant for particular diseases. In a systematic manner, we analyzed variants from 94 genome-wide association studies (reporting at least 12 loci at p<5x10^-8) by projecting them onto 466 epigenetic datasets (characterizing DNase I hypersensitive sites; DHSs) derived from various adult and fetal tissue samples and cell lines including many biological replicates. We were able to confirm many expected associations, such as the involvement of specific immune cell types in immune-related diseases and tissue types in diseases that affect specific organs, for example, inflammatory bowel disease and coronary artery disease. Other notable associations include adrenal glands in coronary artery disease, the immune system in Alzheimer’s disease, and the kidney for bone marrow density. The association signals for some GWAS (for example, myopia or age at menarche) did not show a clear pattern with any of the cell or tissue types studied. In general, the identified variants from GWAS tend to be located outside coding regions. Altogether, we have performed an extensive characterization of GWAS signals in relation to cell and tissue-specific DHSs, demonstrating a key role for regulatory mechanisms in common diseases and complex traits.

TNF-α modulates genome-wide redistribution of ΔNp63α/TAp73 and NF-κB cREL interactive binding on TP53 and AP-1 motifs to promote an oncogenic gene program in squamous cancer

The Cancer Genome Atlas (TCGA) network study of 12 cancer types (PanCancer 12) revealed frequent mutation of TP53, and amplification and expression of related TP63 isoform ΔNp63 in squamous cancers. Further, aberrant expression of inflammatory genes and TP53/p63/p73 targets were detected in the PanCancer 12 project, reminiscent of gene programs comodulated by cREL/ΔNp63/TAp73 transcription factors we uncovered in head and neck squamous cell carcinomas (HNSCCs). However, how inflammatory gene signatures and cREL/p63/p73 targets are comodulated genome wide is unclear. Here, we examined how the inflammatory factor tumor necrosis factor-α (TNF-α) broadly modulates redistribution of cREL with ΔNp63α/TAp73 complexes and signatures genome wide in the HNSCC model UM-SCC46 using chromatin immunoprecipitation sequencing (ChIP-seq). TNF-α enhanced genome-wide co-occupancy of cREL with ΔNp63α on TP53/p63 sites, while unexpectedly promoting redistribution of TAp73 from TP53 to activator protein-1 (AP-1) sites. cREL, ΔNp63α and TAp73 binding and oligomerization on NF-κB-, TP53- or AP-1-specific sequences were independently validated by ChIP-qPCR (quantitative PCR), oligonucleotide-binding assays and analytical ultracentrifugation. Function of the binding activity was confirmed using TP53-, AP-1- and NF-κB-specific REs or p21, SERPINE1 and IL-6 promoter luciferase reporter activities. Concurrently, TNF-α regulated a broad gene network with cobinding activities for cREL, ΔNp63α and TAp73 observed upon array profiling and reverse transcription-PCR. Overlapping target gene signatures were observed in squamous cancer subsets and in inflamed skin of transgenic mice overexpressing ΔNp63α. Furthermore, multiple target genes identified in this study were linked to TP63 and TP73 activity and increased gene expression in large squamous cancer samples from PanCancer 12 TCGA by CircleMap. PARADIGM inferred pathway analysis revealed the network connection of TP63 and NF-κB complexes through an AP-1 hub, further supporting our findings. Thus, inflammatory cytokine TNF-α mediates genome-wide redistribution of the cREL/p63/p73, and AP-1 interactome, to diminish TAp73 tumor suppressor function and reciprocally activate NF-κB and AP-1 gene programs implicated in malignancy.

AP-1 family members act with Sox9 to promote chondrocyte hypertrophy

An analysis of Sox9 binding profiles in developing chondrocytes identified marked enrichment of an AP-1-like motif. Here, we have explored the functional interplay between Sox9 and AP-1 in mammalian chondrocyte development. Among AP-1 family members, Jun and Fosl2 were highly expressed within prehypertrophic and early hypertrophic chondrocytes. Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) showed a striking overlap in Jun- and Sox9-bound regions throughout the chondrocyte genome, reflecting direct binding of each factor to the same enhancers and a potential for protein-protein interactions within AP-1- and Sox9-containing complexes. In vitro reporter analysis indicated that direct co-binding of Sox9 and AP-1 at target motifs promoted gene activity. By contrast, where only one factor can engage its DNA target, the presence of the other factor suppresses target activation consistent with protein-protein interactions attenuating transcription. Analysis of prehypertrophic chondrocyte removal of Sox9 confirmed the requirement of Sox9 for hypertrophic chondrocyte development, and in vitro and ex vivo analyses showed that AP-1 promotes chondrocyte hypertrophy. Sox9 and Jun co-bound and co-activated a Col10a1 enhancer in Sox9 and AP-1 motif-dependent manners consistent with their combined action promoting hypertrophic gene expression. Together, the data support a model in which AP-1 family members contribute to Sox9 action in the transition of chondrocytes to the hypertrophic program.

Barcode Sequencing Screen Identifies SUB1 as a Regulator of Yeast Pheromone Inducible Genes

The yeast pheromone response pathway serves as a valuable model of eukaryotic mitogen-activated protein kinase (MAPK) pathways, and transcription of their downstream targets. Here, we describe application of a screening method combining two technologies: fluorescence-activated cell sorting (FACS), and barcode analysis by sequencing (Bar-Seq). Using this screening method, and pFUS1-GFP as a reporter for MAPK pathway activation, we readily identified mutants in known mating pathway components. In this study, we also include a comprehensive analysis of the FUS1 induction properties of known mating pathway mutants by flow cytometry, featuring single cell analysis of each mutant population. We also characterized a new source of false positives resulting from the design of this screen. Additionally, we identified a deletion mutant, sub1Δ, with increased basal expression of pFUS1-GFP. Here, in the first ChIP-Seq of Sub1, our data shows that Sub1 binds to the promoters of about half the genes in the genome (tripling the 991 loci previously reported), including the promoters of several pheromone-inducible genes, some of which show an increase upon pheromone induction. Here, we also present the first RNA-Seq of a sub1Δ mutant; the majority of genes have no change in RNA, but, of the small subset that do, most show decreased expression, consistent with biochemical studies implicating Sub1 as a positive transcriptional regulator. The RNA-Seq data also show that certain pheromone-inducible genes are induced less in the sub1Δ mutant relative to the wild type, supporting a role for Sub1 in regulation of mating pathway genes. The sub1Δ mutant has increased basal levels of a small subset of other genes besides FUS1, including IMD2 and FIG1, a gene encoding an integral membrane protein necessary for efficient mating.

An interactive environment for agile analysis and visualization of ChIP-sequencing data

To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.

Neonatal thymectomy reveals differentiation and plasticity within human naive T cells

The generation of naive T cells is dependent on thymic output, but in adults, the naive T cell pool is primarily maintained by peripheral proliferation. Naive T cells have long been regarded as relatively quiescent cells; however, it was recently shown that IL-8 production is a signatory effector function of naive T cells, at least in newborns. How this functional signature relates to naive T cell dynamics and aging is unknown. Using a cohort of children and adolescents who underwent neonatal thymectomy, we demonstrate that the naive CD4+ T cell compartment in healthy humans is functionally heterogeneous and that this functional diversity is lost after neonatal thymectomy. Thymic tissue regeneration later in life resulted in functional restoration of the naive T cell compartment, implicating the thymus as having functional regenerative capacity. Together, these data shed further light on functional differentiation within the naive T cell compartment and the importance of the thymus in human naive T cell homeostasis and premature aging. In addition, these results affect and alter our current understanding on the identification of truly naive T cells and recent thymic emigrants.

Loss of Endometrial Plasticity in Recurrent Pregnancy Loss

Menstruation drives cyclic activation of endometrial progenitor cells, tissue regeneration, and maturation of stromal cells, which differentiate into specialized decidual cells prior to and during pregnancy. Aberrant responsiveness of human endometrial stromal cells (HESCs) to deciduogenic cues is strongly associated with recurrent pregnancy loss (RPL), suggesting a defect in cellular maturation. MeDIP-seq analysis of HESCs did not reveal gross perturbations in CpG methylation in RPL cultures, although quantitative differences were observed in or near genes that are frequently deregulated in vivo. However, RPL was associated with a marked reduction in methylation of defined CA-rich motifs located throughout the genome but enriched near telomeres. Non-CpG methylation is a hallmark of cellular multipotency. Congruently, we demonstrate that RPL is associated with a deficiency in endometrial clonogenic cell populations. Loss of epigenetic stemness features also correlated with intragenic CpG hypomethylation and reduced expression of HMGB2, coding high mobility group protein 2. We show that knockdown of this sequence-independent chromatin protein in HESCs promotes senescence and impairs decidualization, exemplified by blunted time-dependent secretome changes. Our findings indicate that stem cell deficiency and accelerated stromal senescence limit the differentiation capacity of the endometrium and predispose for pregnancy failure.

The unique transcriptional response produced by concurrent estrogen and progesterone treatment in breast cancer cells results in upregulation of growth factor pathways and switching from a Luminal A to a Basal-like subtype

BACKGROUND

In breast cancer, progesterone receptor (PR) positivity or abundance is positively associated with survival and treatment response. It was initially believed that PR was a useful diagnostic marker of estrogen receptor activity, but increasingly PR has been recognised to play an important biological role in breast homeostasis, carcinogenesis and metastasis. Although PR expression is almost exclusively observed in estrogen receptor positive tumors, few studies have investigated the cellular mechanisms of PR action in the context of ongoing estrogen signalling.

METHODS

In this study, we contrast PR function in estrogen pretreated ZR-75-1 breast cancer cells with vehicle treated ZR-75-1 and T-47D breast cancer cells using expression microarrays and chromatin immunoprecipitation-sequencing.

RESULTS

Estrogen cotreatment caused a dramatic increase in the number of genes regulated by progesterone in ZR-75-1 cells. In T-47D cells that have naturally high levels of PR, estrogen and progesterone cotreatment resulted in a reduction in the number of regulated genes in comparison to treatment with either hormone alone. At a genome level, estrogen pretreatment of ZR-75-1 cells led to a 10-fold increase in the number of PR DNA binding sites detected using ChIP-sequencing. Time course assessment of progesterone regulated genes in the context of estrogen pretreatment highlighted a series of important regulatory pathways, including those driven by epithelial growth factor receptor (EGFR). Importantly, progesterone applied to cells pretreated with estradiol resulted in switching of the PAM50-determined intrinsic breast cancer subtype from Luminal A to Basal-like, and increased the Oncotype DX® Unscaled Recurrence Score.

CONCLUSION

Estrogen pretreatment of breast cancer cells increases PR steady state levels, resulting in an unequivocal progesterone response that upregulates key members of growth factor pathways. The transformative changes progesterone exerts on the breast cancer subtype suggest that these subtyping tools should be used with caution in premenopausal women.

Trends in IT Innovation to Build a Next Generation Bioinformatics Solution to Manage and Analyse Biological Big Data Produced by NGS Technologies

Sequencing the human genome began in 1994, and 10 years of work were necessary in order to provide a nearly complete sequence. Nowadays, NGS technologies allow sequencing of a whole human genome in a few days. This deluge of data challenges scientists in many ways, as they are faced with data management issues and analysis and visualization drawbacks due to the limitations of current bioinformatics tools. In this paper, we describe how the NGS Big Data revolution changes the way of managing and analysing data. We present how biologists are confronted with abundance of methods, tools, and data formats. To overcome these problems, focus on Big Data Information Technology innovations from web and business intelligence. We underline the interest of NoSQL databases, which are much more efficient than relational databases. Since Big Data leads to the loss of interactivity with data during analysis due to high processing time, we describe solutions from the Business Intelligence that allow one to regain interactivity whatever the volume of data is. We illustrate this point with a focus on the Amadea platform. Finally, we discuss visualization challenges posed by Big Data and present the latest innovations with JavaScript graphic libraries.

ChIP-Array 2: integrating multiple omics data to construct gene regulatory networks

Transcription factors (TFs) play an important role in gene regulation. The interconnections among TFs, chromatin interactions, epigenetic marks and cis-regulatory elements form a complex gene transcription apparatus. Our previous work, ChIP-Array, combined TF binding and transcriptome data to construct gene regulatory networks (GRNs). Here we present an enhanced version, ChIP-Array 2, to integrate additional types of omics data including long-range chromatin interaction, open chromatin region and histone modification data to dissect more comprehensive GRNs involving diverse regulatory components. Moreover, we substantially extended our motif database for human, mouse, rat, fruit fly, worm, yeast and Arabidopsis, and curated large amount of omics data for users to select as input or backend support. With ChIP-Array 2, we compiled a library containing regulatory networks of 18 TFs/chromatin modifiers in mouse embryonic stem cell (mESC). The web server and the mESC library are publicly free and accessible athttp://jjwanglab.org/chip-array.

A penalized likelihood approach for robust estimation of isoform expression

Ultra high-throughput sequencing of transcriptomes (RNA-Seq) has enabled the accurate estimation of gene expression at individual isoform level. However, systematic biases introduced during the sequencing and mapping processes as well as incompleteness of the transcript annotation databases may cause the estimates of isoform abundances to be unreliable, and in some cases, highly inaccurate. This paper introduces a penalized likelihood approach to detect and correct for such biases in a robust manner. Our model extends those previously proposed by introducing bias parameters for reads. An L1 penalty is used for the selection of non-zero bias parameters. We introduce an efficient algorithm for model fitting and analyze the statistical properties of the proposed model. Our experimental studies on both simulated and real datasets suggest that the model has the potential to improve isoform-specific gene expression estimates and identify incompletely annotated gene models.

Many inflammatory bowel disease risk loci include regions that regulate gene expression in immune cells and the intestinal epithelium

BACKGROUND & AIMS

The contribution of genetic factors to the pathogenesis of inflammatory bowel disease (IBD) has been established by twin, targeted-sequencing, and genome-wide association studies. These studies identified many risk loci, and research is underway to identify causal variants. These studies have focused mainly on protein-coding genes. We investigated other functional elements in the human genome, such as regulatory regions.

METHODS

Using acetylated histone 3 lysine 27 chromatin immunoprecipitation and sequencing, we identified tens of thousands of potential regulatory regions that are active in intestinal epithelium (primary intestinal crypts and cultured organoids) isolated from resected material and from biopsies collected during ileo-colonoscopies and immune cells (monocytes, macrophages, CD34(+), CD4(+), and CD8(+)). We correlated these regions with susceptibility loci for IBD.

RESULTS

We have generated acetylated histone 3 lysine 27 profiles from primary intestinal epithelium and cultured organoids, which we have made publically available. We found that 45 of 163 single nucleotide polymorphisms (SNPs) associated with IBD overlap specifically with active regulatory elements. In addition, by taking strong linkage disequilibrium into account, another 47 IBD-associated SNPs colocalized with active regulatory elements through other SNPs in their vicinity. Altogether, 92 of 163 IBD-associated SNPs correlated with distinct active regulatory elements-a frequency 2.5- to 3.5-fold greater than that expected from random sampling. The variations in these SNPs often create or disrupt known binding motifs; they might affect the binding of transcriptional regulators to alter expression of regulated genes.

CONCLUSIONS

In addition to variants in protein coding genes, variants in noncoding DNA regulatory regions that are active in intestinal epithelium and immune cells are potentially involved in the pathogenesis of IBD.

rSeqDiff: detecting differential isoform expression from RNA-Seq data using hierarchical likelihood ratio test

High-throughput sequencing of transcriptomes (RNA-Seq) has recently become a powerful tool for the study of gene expression. We present rSeqDiff, an efficient algorithm for the detection of differential expression and differential splicing of genes from RNA-Seq experiments across multiple conditions. Unlike existing approaches which detect differential expression of transcripts, our approach considers three cases for each gene: 1) no differential expression, 2) differential expression without differential splicing and 3) differential splicing. We specify statistical models characterizing each of these three cases and use hierarchical likelihood ratio test for model selection. Simulation studies show that our approach achieves good power for detecting differentially expressed or differentially spliced genes. Comparisons with competing methods on two real RNA-Seq datasets demonstrate that our approach provides accurate estimates of isoform abundances and biological meaningful rankings of differentially spliced genes. The proposed approach is implemented as an R package named rSeqDiff.

STAR: an integrated solution to management and visualization of sequencing data

MOTIVATION

Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data.

RESULTS

STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data.

AVAILABILITY AND IMPLEMENTATION

STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser.

Histone methyltransferase MLL3 contributes to genome-scale circadian transcription

Daily cyclical expression of thousands of genes in tissues such as the liver is orchestrated by the molecular circadian clock, the disruption of which is implicated in metabolic disorders and cancer. Although we understand much about the circadian transcription factors that can switch gene expression on and off, it is still unclear how global changes in rhythmic transcription are controlled at the genomic level. Here, we demonstrate circadian modification of an activating histone mark at a significant proportion of gene loci that undergo daily transcription, implicating widespread epigenetic modification as a key node regulated by the clockwork. Furthermore, we identify the histone-remodelling enzyme mixed lineage leukemia (MLL)3 as a clock-controlled factor that is able to directly and indirectly modulate over a hundred epigenetically targeted circadian "output" genes in the liver. Importantly, catalytic inactivation of the histone methyltransferase activity of MLL3 also severely compromises the oscillation of "core" clock gene promoters, including Bmal1, mCry1, mPer2, and Rev-erbα, suggesting that rhythmic histone methylation is vital for robust transcriptional oscillator function. This highlights a pathway by which the clockwork exerts genome-wide control over transcription, which is critical for sustaining temporal programming of tissue physiology.

Six2 and Wnt regulate self-renewal and commitment of nephron progenitors through shared gene regulatory networks

A balance between Six2-dependent self-renewal and canonical Wnt signaling-directed commitment regulates mammalian nephrogenesis. Intersectional studies using chromatin immunoprecipitation and transcriptional profiling identified direct target genes shared by each pathway within nephron progenitors. Wnt4 and Fgf8 are essential for progenitor commitment; cis-regulatory modules flanking each gene are cobound by Six2 and β-catenin and are dependent on conserved Lef/Tcf binding sites for activity. In vitro and in vivo analyses suggest that Six2 and Lef/Tcf factors form a regulatory complex that promotes progenitor maintenance while entry of β-catenin into this complex promotes nephrogenesis. Alternative transcriptional responses associated with Six2 and β-catenin cobinding events occur through non-Lef/Tcf DNA binding mechanisms, highlighting the regulatory complexity downstream of Wnt signaling in the developing mammalian kidney.

ChIP-Array: combinatory analysis of ChIP-seq/chip and microarray gene expression data to discover direct/indirect targets of a transcription factor

Chromatin immunoprecipitation (ChIP) coupled with high-throughput techniques (ChIP-X), such as next generation sequencing (ChIP-Seq) and microarray (ChIP–chip), has been successfully used to map active transcription factor binding sites (TFBS) of a transcription factor (TF). The targeted genes can be activated or suppressed by the TF, or are unresponsive to the TF. Microarray technology has been used to measure the actual expression changes of thousands of genes under the perturbation of a TF, but is unable to determine if the affected genes are direct or indirect targets of the TF. Furthermore, both ChIP-X and microarray methods produce a large number of false positives. Combining microarray expression profiling and ChIP-X data allows more effective TFBS analysis for studying the function of a TF. However, current web servers only provide tools to analyze either ChIP-X or expression data, but not both. Here, we present ChIP-Array, a web server that integrates ChIP-X and expression data from human, mouse, yeast, fruit fly and Arabidopsis. This server will assist biologists to detect direct and indirect target genes regulated by a TF of interest and to aid in the functional characterization of the TF. ChIP-Array is available at http://jjwanglab.hku.hk/ChIP-Array, with free access to academic users.

Statistical Modeling of RNA-Seq Data

Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest. This paper introduces a statistical model for estimating isoform abundance from RNA-Seq data and is flexible enough to accommodate both single end and paired end RNA-Seq data and sampling bias along the length of the transcript. Based on the derivation of minimal sufficient statistics for the model, a computationally feasible implementation of the maximum likelihood estimator of the model is provided. Further, it is shown that using paired end RNA-Seq provides more accurate isoform abundance estimates than single end sequencing at fixed sequencing depth. Simulation studies are also given.

The analysis of ChIP-Seq data

Chromatin immunoprecipitation coupled with ultra-high-throug put parallel DNA sequencing (ChIP-seq) is an effective technology for the investigation of genome-wide protein-DNA interactions. Examples of applications include the studies of RNA polymerases transcription, transcriptional regulation, and histone modifications. The technology provides accurate and high-resolution mapping of the protein-DNA binding loci that are important in the understanding of many processes in development and diseases. Since the introduction of ChIP-seq experiments in 2007, many statistical and computational methods have been developed to support the analysis of the massive datasets from these experiments. However, because of the complex, multistaged analysis workflow, it is still difficult for an experimental investigator to conduct the analysis of his or her own ChIP-seq data. In this chapter, we review the basic design of ChIP-seq experiments and provide an in-depth tutorial on how to prepare, to preprocess, and to analyze ChIP-seq datasets. The tutorial is based on a revised version of our software package CisGenome, which was designed to encompass most standard tasks in ChIP-seq data analysis. Relevant statistical and computational issues will be highlighted, discussed, and illustrated by means of real data examples.