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      Widespread contribution of transposable elements to the innovation of gene regulatory networks.

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          Abstract

          Transposable elements (TEs) have been shown to contain functional binding sites for certain transcription factors (TFs). However, the extent to which TEs contribute to the evolution of TF binding sites is not well known. We comprehensively mapped binding sites for 26 pairs of orthologous TFs in two pairs of human and mouse cell lines (representing two cell lineages), along with epigenomic profiles, including DNA methylation and six histone modifications. Overall, we found that 20% of binding sites were embedded within TEs. This number varied across different TFs, ranging from 2% to 40%. We further identified 710 TF-TE relationships in which genomic copies of a TE subfamily contributed a significant number of binding peaks for a TF, and we found that LTR elements dominated these relationships in human. Importantly, TE-derived binding peaks were strongly associated with open and active chromatin signatures, including reduced DNA methylation and increased enhancer-associated histone marks. On average, 66% of TE-derived binding events were cell type-specific with a cell type-specific epigenetic landscape. Most of the binding sites contributed by TEs were species-specific, but we also identified binding sites conserved between human and mouse, the functional relevance of which was supported by a signature of purifying selection on DNA sequences of these TEs. Interestingly, several TFs had significantly expanded binding site landscapes only in one species, which were linked to species-specific gene functions, suggesting that TEs are an important driving force for regulatory innovation. Taken together, our data suggest that TEs have significantly and continuously shaped gene regulatory networks during mammalian evolution.

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          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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            BEDTools: a flexible suite of utilities for comparing genomic features

            Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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              Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.

              Genome-scale studies have revealed extensive, cell type-specific colocalization of transcription factors, but the mechanisms underlying this phenomenon remain poorly understood. Here, we demonstrate in macrophages and B cells that collaborative interactions of the common factor PU.1 with small sets of macrophage- or B cell lineage-determining transcription factors establish cell-specific binding sites that are associated with the majority of promoter-distal H3K4me1-marked genomic regions. PU.1 binding initiates nucleosome remodeling, followed by H3K4 monomethylation at large numbers of genomic regions associated with both broadly and specifically expressed genes. These locations serve as beacons for additional factors, exemplified by liver X receptors, which drive both cell-specific gene expression and signal-dependent responses. Together with analyses of transcription factor binding and H3K4me1 patterns in other cell types, these studies suggest that simple combinations of lineage-determining transcription factors can specify the genomic sites ultimately responsible for both cell identity and cell type-specific responses to diverse signaling inputs. Copyright 2010 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Genome Res.
                Genome research
                1549-5469
                1088-9051
                Dec 2014
                : 24
                : 12
                Affiliations
                [1 ] Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63108, USA;
                [2 ] Department of Genetics, Stanford University, Stanford, California 94305, USA;
                [3 ] Department of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, Minnesota 55455, USA.
                [4 ] Department of Genetics, Stanford University, Stanford, California 94305, USA; mpsnyder@stanford.edu twang@genetics.wustl.edu.
                [5 ] Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63108, USA; mpsnyder@stanford.edu twang@genetics.wustl.edu.
                Article
                gr.168872.113
                10.1101/gr.168872.113
                25319995
                7922912c-69ab-4351-81a8-33e5f433d81a
                © 2014 Sundaram et al.; Published by Cold Spring Harbor Laboratory Press.
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