LOcating non-unique matched tags (LONUT) to improve the detection of the enriched regions for ChIP-seq data

Taming transposable elements in livestock and poultry: a review of their roles and applications

Livestock and poultry play a significant role in human nutrition by converting agricultural by-products into high-quality proteins. To meet the growing demand for safe animal protein, genetic improvement of livestock must be done sustainably while minimizing negative environmental impacts. Transposable elements (TE) are important components of livestock and poultry genomes, contributing to their genetic diversity, chromatin states, gene regulatory networks, and complex traits of economic value. However, compared to other species, research on TE in livestock and poultry is still in its early stages. In this review, we analyze 72 studies published in the past 20 years, summarize the TE composition in livestock and poultry genomes, and focus on their potential roles in functional genomics. We also discuss bioinformatic tools and strategies for integrating multi-omics data with TE, and explore future directions, feasibility, and challenges of TE research in livestock and poultry. In addition, we suggest strategies to apply TE in basic biological research and animal breeding. Our goal is to provide a new perspective on the importance of TE in livestock and poultry genomes.

Locus-specific chromatin profiling of evolutionarily young transposable elements

Despite a vast expansion in the availability of epigenomic data, our knowledge of the chromatin landscape at interspersed repeats remains highly limited by difficulties in mapping short-read sequencing data to these regions. In particular, little is known about the locus-specific regulation of evolutionarily young transposable elements (TEs), which have been implicated in genome stability, gene regulation and innate immunity in a variety of developmental and disease contexts. Here we propose an approach for generating locus-specific protein-DNA binding profiles at interspersed repeats, which leverages information on the spatial proximity between repetitive and non-repetitive genomic regions. We demonstrate that the combination of HiChIP and a newly developed mapping tool (PAtChER) yields accurate protein enrichment profiles at individual repetitive loci. Using this approach, we reveal previously unappreciated variation in the epigenetic profiles of young TE loci in mouse and human cells. Insights gained using our method will be invaluable for dissecting the molecular determinants of TE regulation and their impact on the genome.

Mobile genomics: tools and techniques for tackling transposons

Next-generation sequencing approaches have fundamentally changed the types of questions that can be asked about gene function and regulation. With the goal of approaching truly genome-wide quantifications of all the interaction partners and downstream effects of particular genes, these quantitative assays have allowed for an unprecedented level of detail in exploring biological interactions. However, many challenges remain in our ability to accurately describe and quantify the interactions that take place in those hard to reach and extremely repetitive regions of our genome comprised mostly of transposable elements (TEs). Tools dedicated to TE-derived sequences have lagged behind, making the inclusion of these sequences in genome-wide analyses difficult. Recent improvements, both computational and experimental, allow for the better inclusion of TE sequences in genomic assays and a renewed appreciation for the importance of TE biology. This review will discuss the recent improvements that have been made in the computational analysis of TE-derived sequences as well as the areas where such analysis still proves difficult. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

Ritornello: high fidelity control-free chromatin immunoprecipitation peak calling

With the advent of next generation high-throughput DNA sequencing technologies, omics experiments have become the mainstay for studying diverse biological effects on a genome wide scale. Chromatin immunoprecipitation (ChIP-seq) is the omics technique that enables genome wide localization of transcription factor (TF) binding or epigenetic modification events. Since the inception of ChIP-seq in 2007, many methods have been developed to infer ChIP-target binding loci from the resultant reads after mapping them to a reference genome. However, interpreting these data has proven challenging, and as such these algorithms have several shortcomings, including susceptibility to false positives due to artifactual peaks, poor localization of binding sites and the requirement for a total DNA input control which increases the cost of performing these experiments. We present Ritornello, a new approach for finding TF-binding sites in ChIP-seq, with roots in digital signal processing that addresses all of these problems. We show that Ritornello generally performs equally or better than the peak callers tested and recommended by the ENCODE consortium, but in contrast, Ritornello does not require a matched total DNA input control to avoid false positives, effectively decreasing the sequencing cost to perform ChIP-seq. Ritornello is freely available at https://github.com/KlugerLab/Ritornello.

DNA Methylation Targets Influenced by Bisphenol A and/or Genistein Are Associated with Survival Outcomes in Breast Cancer Patients

Early postnatal exposures to Bisphenol A (BPA) and genistein (GEN) have been reported to predispose for and against mammary cancer, respectively, in adult rats. Since the changes in cancer susceptibility occurs in the absence of the original chemical exposure, we have investigated the potential of epigenetics to account for these changes. DNA methylation studies reveal that prepubertal BPA exposure alters signaling pathways that contribute to carcinogenesis. Prepubertal exposure to GEN and BPA + GEN revealed pathways involved in maintenance of cellular function, indicating that the presence of GEN either reduces or counters some of the alterations caused by the carcinogenic properties of BPA. We subsequently evaluated the potential of epigenetic changes in the rat mammary tissues to predict survival in breast cancer patients via the Cancer Genomic Atlas (TCGA). We identified 12 genes that showed strong predictive values for long-term survival in estrogen receptor positive patients. Importantly, two genes associated with improved long term survival, HPSE and RPS9, were identified to be hypomethylated in mammary glands of rats exposed prepuberally to GEN or to GEN + BPA respectively, reinforcing the suggested cancer suppressive properties of GEN.

Methyl-binding DNA capture Sequencing for Patient Tissues

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable development and differentiation of different tissue types. Dysregulation of this process is often the hallmark of various diseases like cancer. Here, we outline one of the recent sequencing techniques, Methyl-Binding DNA Capture sequencing (MBDCap-seq), used to quantify methylation in various normal and disease tissues for large patient cohorts. We describe a detailed protocol of this affinity enrichment approach along with a bioinformatics pipeline to achieve optimal quantification. This technique has been used to sequence hundreds of patients across various cancer types as a part of the 1,000 methylome project (Cancer Methylome System).

Roles of Distal and Genic Methylation in the Development of Prostate Tumorigenesis Revealed by Genome-wide DNA Methylation Analysis

Aberrant DNA methylation at promoters is often linked to tumorigenesis. But many aspects of DNA methylation remain unexplored, including the individual roles of distal and gene body methylation, as well as their collaborative roles with promoter methylation. Here we performed a MBD-seq analysis on prostate specimens classified into low, high, and very high risk group based on Gleason score and TNM stages. We identified gene sets with differential methylation regions (DMRs) in Distal, TSS, gene body and TES. To understand the collaborative roles, TSS was compared with the other three DMRs, resulted in 12 groups of genes with collaborative differential methylation patterns (CDMPs). We found several groups of genes that show opposite methylation patterns in Distal and Genic regions compared to TSS region, and in general they are differentially expressed genes (DEGs) in tumors in TCGA RNA-seq data. IPA (Ingenuity Pathway Analysis) reveals AR/TP53 signaling network to be a major signaling pathway, and survival analysis indicates genes subsets significantly associated with prostate cancer recurrence. Our results suggest that DNA methylation in Distal and Genic regions also plays critical roles in contributing to prostate tumorigenesis, and may act either positively or negatively with TSSs to alter gene regulation in tumors.

Perm-seq: Mapping Protein-DNA Interactions in Segmental Duplication and Highly Repetitive Regions of Genomes with Prior-Enhanced Read Mapping

Segmental duplications and other highly repetitive regions of genomes contribute significantly to cells' regulatory programs. Advancements in next generation sequencing enabled genome-wide profiling of protein-DNA interactions by chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq). However, interactions in highly repetitive regions of genomes have proven difficult to map since short reads of 50-100 base pairs (bps) from these regions map to multiple locations in reference genomes. Standard analytical methods discard such multi-mapping reads and the few that can accommodate them are prone to large false positive and negative rates. We developed Perm-seq, a prior-enhanced read allocation method for ChIP-seq experiments, that can allocate multi-mapping reads in highly repetitive regions of the genomes with high accuracy. We comprehensively evaluated Perm-seq, and found that our prior-enhanced approach significantly improves multi-read allocation accuracy over approaches that do not utilize additional data types. The statistical formalism underlying our approach facilitates supervising of multi-read allocation with a variety of data sources including histone ChIP-seq. We applied Perm-seq to 64 ENCODE ChIP-seq datasets from GM12878 and K562 cells and identified many novel protein-DNA interactions in segmental duplication regions. Our analysis reveals that although the protein-DNA interactions sites are evolutionarily less conserved in repetitive regions, they share the overall sequence characteristics of the protein-DNA interactions in non-repetitive regions.

CNV-guided multi-read allocation for ChIP-seq

MOTIVATION

In chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) and other short-read sequencing experiments, a considerable fraction of the short reads align to multiple locations on the reference genome (multi-reads). Inferring the origin of multi-reads is critical for accurately mapping reads to repetitive regions. Current state-of-the-art multi-read allocation algorithms rely on the read counts in the local neighborhood of the alignment locations and ignore the variation in the copy numbers of these regions. Copy-number variation (CNV) can directly affect the read densities and, therefore, bias allocation of multi-reads.

RESULTS

We propose cnvCSEM (CNV-guided ChIP-Seq by expectation-maximization algorithm), a flexible framework that incorporates CNV in multi-read allocation. cnvCSEM eliminates the CNV bias in multi-read allocation by initializing the read allocation algorithm with CNV-aware initial values. Our data-driven simulations illustrate that cnvCSEM leads to higher read coverage with satisfactory accuracy and lower loss in read-depth recovery (estimation). We evaluate the biological relevance of the cnvCSEM-allocated reads and the resultant peaks with the analysis of several ENCODE ChIP-seq datasets.

AVAILABILITY AND IMPLEMENTATION

Available at http://www.stat.wisc.edu/∼qizhang/

CONTACT

: qizhang@stat.wisc.edu or keles@stat.wisc.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Practical guidelines for the comprehensive analysis of ChIP-seq data

Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.