Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.

Availability: http://samtools.sourceforge.net 

Contact: [email protected]

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The Sequence Alignment/Map format and SAMtools

Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

/pdf/the-genome-analysis-toolkit-a-mapreduce-framework-for-4aygfa9b66.pdf

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

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 webbased 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

/pdf/bedtools-a-flexible-suite-of-utilities-for-comparing-genomic-3q7qzmj6af.pdf

BEDTools: a flexible suite of utilities for comparing genomic features

RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.

/pdf/rsem-accurate-transcript-quantification-from-rna-seq-data-14sfzcg8a9.pdf

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

MOTIVATION: Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. RESULTS: We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. AVAILABILITY AND IMPLEMENTATION: featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

featureCounts: an efficient general-purpose program for assigning sequence reads to genomic features

As vertebrate genome sequences near completion and research refocuses to their analysis, the issue of effective genome annotation display becomes critical. A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu. This browser displays assembly contigs and gaps, mRNA and expressed sequence tag alignments, multiple gene predictions, cross-species homologies, single nucleotide polymorphisms, sequence-tagged sites, radiation hybrid data, transposon repeats, and more as a stack of coregistered tracks. Text and sequence-based searches provide quick and precise access to any region of specific interest. Secondary links from individual features lead to sequence details and supplementary off-site databases. One-half of the annotation tracks are computed at the University of California, Santa Cruz from publicly available sequence data; collaborators worldwide provide the rest. Users can stably add their own custom tracks to the browser for educational or research purposes. The conceptual and technical framework of the browser, its underlying MYSQL database, and overall use are described. The web site currently serves over 50,000 pages per day to over 3000 different users.

/pdf/the-human-genome-browser-at-ucsc-4zclgthyly.pdf

The Human Genome Browser at UCSC

We demonstrate that four different proteins from calf thymus are able to restore splicing in the same splicing-deficient extract using several different pre-mRNA substrates. These proteins are members of a conserved family of proteins recognized by a monoclonal antibody that binds to active sites of RNA polymerase II transcription. We purified this family of nuclear phosphoproteins to apparent homogeneity by two salt precipitations. The family, called SR proteins for their serine- and arginine-rich carboxy-terminal domains, consists of at least five different proteins with molecular masses of 20, 30, 40, 55, and 75 kD. Microsequencing revealed that they are related but not identical. In four of the family members a repeated protein sequence that encompasses an RNA recognition motif was observed. We discuss the potential role of this highly conserved, functionally related set of proteins in pre-mRNA splicing.

/pdf/sr-proteins-a-conserved-family-of-pre-mrna-splicing-factors-r6q39bfu5o.pdf

SR proteins: a conserved family of pre-mRNA splicing factors.

Alternative splicing of precursor messenger RNAs (pre-mRNAs) is a common mechanism of regulating gene expression. SR proteins are a family of pre-mRNA splicing factors that are structurally related and evolutionarily conserved. Any member of the SR family can complement a splicing-deficient extract that lacks the entire family of SR proteins. Here it is demonstrated that particular SR proteins have distinct functions in alternative pre-mRNA splicing in vitro. In addition, SR proteins are differentially expressed in a variety of tissues. These results suggest a fundamental role for SR proteins in the regulation of alternative splicing.

https://science.sciencemag.org/content/sci/260/5105/219.full.pdf

Distinct functions of SR proteins in alternative pre-mRNA splicing

An antibody was identified previously that recognizes sites of polymerase II transcription on lampbrush chromosomes, puffs on polytene chromosomes, and many small granules in the nucleoplasm of all cells tested. This antibody binds a conserved family of phosphorylated polypeptides in vertebrate and invertebrate cells. We developed a method for purifying these proteins that involves differential solubility in MgCl2. We isolated a Drosophila cDNA encoding one of the proteins using information obtained from microsequencing. In vivo expression studies show that this protein is concentrated on sites of polymerase II transcription and that it is highly phosphorylated. The protein shares a high degree of homology with proteins involved in alternative splicing of pre-mRNA suggesting the possibility that this protein plays a role in pre-mRNA splicing.

/pdf/a-conserved-family-of-nuclear-phosphoproteins-localized-to-3l6khzgwwj.pdf

A conserved family of nuclear phosphoproteins localized to sites of polymerase II transcription.

A new algorithm, WABA, was developed for doing large-scale alignments between genomic DNA of different species. WABA was used to align 8 million bases of Caenorhabditis briggsae genomic DNA against the entire 97-million-base Caenorhabditis elegans genome. The alignment, including C. briggsae homologs of 154 genetically characterized C. elegans genes and many times this number of largely uncharacterized ORFs, can be browsed and searched on the Web (http://www.cse.ucsc.edu/ approximately kent/intronerator). The alignment confirms that patterns of conservation can be useful in identifying regulatory regions and rarely expressed coding regions. Conserved regulatory elements can be identified inside coding exons by examining the level of divergence at the wobble position of codons. The alignment reveals a bimodal size distribution of syntenic regions. Over 250 introns are present in one species but not the other. The 3' and 5' intron splice sites have more similarity to each other in introns unique to one species than in C. elegans introns as a whole, suggesting a possible mechanism for intron removal.

/pdf/conservation-regulation-synteny-and-introns-in-a-large-scale-2pkbeb759v.pdf

Alan M. Zahler

Papers

The Human Genome Browser at UCSC

SR proteins: a conserved family of pre-mRNA splicing factors.

Distinct functions of SR proteins in alternative pre-mRNA splicing

A conserved family of nuclear phosphoproteins localized to sites of polymerase II transcription.

Conservation, Regulation, Synteny, and Introns in a Large-scale C. briggsae–C. elegans Genomic Alignment