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Journal ArticleDOI

Next-generation DNA sequencing.

Jay Shendure, +1 more
- 01 Oct 2008 - 
- Vol. 26, Iss: 10, pp 1135-1145
TLDR
Next-generation DNA sequencing has the potential to dramatically accelerate biological and biomedical research, by enabling the comprehensive analysis of genomes, transcriptomes and interactomes to become inexpensive, routine and widespread, rather than requiring significant production-scale efforts.
Abstract
DNA sequence represents a single format onto which a broad range of biological phenomena can be projected for high-throughput data collection. Over the past three years, massively parallel DNA sequencing platforms have become widely available, reducing the cost of DNA sequencing by over two orders of magnitude, and democratizing the field by putting the sequencing capacity of a major genome center in the hands of individual investigators. These new technologies are rapidly evolving, and near-term challenges include the development of robust protocols for generating sequencing libraries, building effective new approaches to data-analysis, and often a rethinking of experimental design. Next-generation DNA sequencing has the potential to dramatically accelerate biological and biomedical research, by enabling the comprehensive analysis of genomes, transcriptomes and interactomes to become inexpensive, routine and widespread, rather than requiring significant production-scale efforts.

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Citations
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Journal ArticleDOI

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

TL;DR: 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.
Journal ArticleDOI

DnaSP v5

TL;DR: Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets, including visualizing sliding window results integrated with available genome annotations in the UCSC browser.
Journal ArticleDOI

Stacks: an analysis tool set for population genomics

TL;DR: The expanded population genomics functions in Stacks will make it a useful tool to harness the newest generation of massively parallel genotyping data for ecological and evolutionary genetics.
Journal ArticleDOI

The impact of the gut microbiota on human health: an integrative view.

TL;DR: It is suggested that a holistic approach to studying the microbiota that goes beyond characterization of community composition and encompasses dynamic interactions between all components of the microbiota and host tissue over time will be crucial for building predictive models for diagnosis and treatment of diseases linked to imbalances in the microbiota.
Journal ArticleDOI

The tomato genome sequence provides insights into fleshy fruit evolution

Shusei Sato, +323 more
- 31 May 2012 - 
TL;DR: A high-quality genome sequence of domesticated tomato is presented, a draft sequence of its closest wild relative, Solanum pimpinellifolium, is compared, and the two tomato genomes are compared to each other and to the potato genome.
References
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Journal ArticleDOI

Mapping and quantifying mammalian transcriptomes by RNA-Seq.

TL;DR: Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3′ untranscribed regions, as well as new candidate microRNA precursors.
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Database resources of the National Center for Biotechnology Information

TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
Journal ArticleDOI

Velvet: Algorithms for de novo short read assembly using de Bruijn graphs

TL;DR: Velvet represents a new approach to assembly that can leverage very short reads in combination with read pairs to produce useful assemblies and is in close agreement with simulated results without read-pair information.
Journal ArticleDOI

Base-calling of automated sequencer traces using Phred. I. accuracy assessment

TL;DR: In this article, a base-calling program for automated sequencer traces, phred, with improved accuracy was proposed. But it was not shown to achieve a lower error rate than the ABI software, averaging 40%-50% fewer errors in the data sets examined independent of position in read, machine running conditions, or sequencing chemistry.
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