Literature DB >> 20864776

2nd generation DNA sequencing meets functional genomics.

Ivo G Gut1.   

Abstract

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Year:  2010        PMID: 20864776      PMCID: PMC2984602          DOI: 10.18632/aging.100199

Source DB:  PubMed          Journal:  Aging (Albany NY)        ISSN: 1945-4589            Impact factor:   5.682


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The introduction of the first 2nd generation DNA sequencing method five years ago heralded a paradigm shift and propelled us into a new era [1]. In contrast to the Sanger sequencing method that dominated DNA sequencing for nearly 30 years [2], 2nd generation sequencing analyzes clonal representations of the input DNA. Using highly parallel processing in microfluidic devices and stepwise addition of four nucleobases highly accurate sequencing results are obtained. Orders of magnitude larger amounts of data are generated at substantially decreased cost and effort. This has made it possible to sequence a human genome completely in less than one month using one 2nd generation sequencing instrument. At first 2nd generation sequencers were used for experiments with reduced representation of the genome such as ChIPseq and RNAseq [3,4]. These applications have now reached a very high level of sophistication and are replacing array-based versions of these kinds of analyses. The application of whole genome sequencing for genetic application has been slow on the uptake mainly due to cost, effort and resolution required. There are a few large international efforts to collect high value information such as for the 1000 Genomes Project and the International Cancer Genome Consortium (ICGC). Timmermann et al. use complete sequencing of a mutagenized S. cervisiae strain with a longevity phenotype of interest to identify the functionally effected gene [5]. By a clever sequence pruning procedure they rapidly arrive at a manageable number of putative variants responsible for the alteration of the phenotype. The mutated variants of the candidate genes are introduced into wildtype S. cerevisiae for identification and validation. Interestingly the causative variant of TSA1 does not result in a loss or gain but shows a modulation of function. The approach developed here highlights a way for functional genomics making use of the extensive collections of mutants of different model organisms. This functional analysis strategy could also be applied to reverse genetic characterization.
  5 in total

1.  Genome sequencing in microfabricated high-density picolitre reactors.

Authors:  Marcel Margulies; Michael Egholm; William E Altman; Said Attiya; Joel S Bader; Lisa A Bemben; Jan Berka; Michael S Braverman; Yi-Ju Chen; Zhoutao Chen; Scott B Dewell; Lei Du; Joseph M Fierro; Xavier V Gomes; Brian C Godwin; Wen He; Scott Helgesen; Chun Heen Ho; Chun He Ho; Gerard P Irzyk; Szilveszter C Jando; Maria L I Alenquer; Thomas P Jarvie; Kshama B Jirage; Jong-Bum Kim; James R Knight; Janna R Lanza; John H Leamon; Steven M Lefkowitz; Ming Lei; Jing Li; Kenton L Lohman; Hong Lu; Vinod B Makhijani; Keith E McDade; Michael P McKenna; Eugene W Myers; Elizabeth Nickerson; John R Nobile; Ramona Plant; Bernard P Puc; Michael T Ronan; George T Roth; Gary J Sarkis; Jan Fredrik Simons; John W Simpson; Maithreyan Srinivasan; Karrie R Tartaro; Alexander Tomasz; Kari A Vogt; Greg A Volkmer; Shally H Wang; Yong Wang; Michael P Weiner; Pengguang Yu; Richard F Begley; Jonathan M Rothberg
Journal:  Nature       Date:  2005-07-31       Impact factor: 49.962

2.  RNA-Seq-quantitative measurement of expression through massively parallel RNA-sequencing.

Authors:  Brian T Wilhelm; Josette-Renée Landry
Journal:  Methods       Date:  2009-03-29       Impact factor: 3.608

3.  A new dominant peroxiredoxin allele identified by whole-genome re-sequencing of random mutagenized yeast causes oxidant-resistance and premature aging.

Authors:  Bernd Timmermann; Stefanie Jarolim; Hannes Russmayer; Martin Kerick; Steve Michel; Antje Krüger; Katharina Bluemlein; Peter Laun; Johannes Grillari; Hans Lehrach; Michael Breitenbach; Markus Ralser
Journal:  Aging (Albany NY)       Date:  2010-08       Impact factor: 5.682

4.  ChIP-seq: using high-throughput sequencing to discover protein-DNA interactions.

Authors:  Dominic Schmidt; Michael D Wilson; Christiana Spyrou; Gordon D Brown; James Hadfield; Duncan T Odom
Journal:  Methods       Date:  2009-03-09       Impact factor: 3.608

5.  DNA sequencing with chain-terminating inhibitors.

Authors:  F Sanger; S Nicklen; A R Coulson
Journal:  Proc Natl Acad Sci U S A       Date:  1977-12       Impact factor: 11.205

  5 in total

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