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Journal ArticleDOI

Sequencing and comparison of yeast species to identify genes and regulatory elements

TLDR
A comparative analysis of the yeast Saccharomyces cerevisiae based on high-quality draft sequences of three related species, which inferred a putative function for most of these motifs, and provided insights into their combinatorial interactions.
Abstract
Identifying the functional elements encoded in a genome is one of the principal challenges in modern biology. Comparative genomics should offer a powerful, general approach. Here, we present a comparative analysis of the yeast Saccharomyces cerevisiae based on high-quality draft sequences of three related species (S. paradoxus, S. mikatae and S. bayanus). We first aligned the genomes and characterized their evolution, defining the regions and mechanisms of change. We then developed methods for direct identification of genes and regulatory motifs. The gene analysis yielded a major revision to the yeast gene catalogue, affecting approximately 15% of all genes and reducing the total count by about 500 genes. The motif analysis automatically identified 72 genome-wide elements, including most known regulatory motifs and numerous new motifs. We inferred a putative function for most of these motifs, and provided insights into their combinatorial interactions. The results have implications for genome analysis of diverse organisms, including the human.

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Citations
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Journal ArticleDOI

Global analysis of protein localization in budding yeast

TL;DR: The construction and analysis of a collection of yeast strains expressing full-length, chromosomally tagged green fluorescent protein fusion proteins helps reveal the logic of transcriptional co-regulation, and provides a comprehensive view of interactions within and between organelles in eukaryotic cells.
Journal ArticleDOI

Finishing the euchromatic sequence of the human genome

Chris P. Ponting, +1 more
- 21 Oct 2004 - 
TL;DR: The current human genome sequence (Build 35) as discussed by the authors contains 2.85 billion nucleotides interrupted by only 341 gaps and is accurate to an error rate of approximately 1 event per 100,000 bases.
Journal ArticleDOI

Global analysis of protein expression in yeast

TL;DR: A Saccharomyces cerevisiae fusion library is created where each open reading frame is tagged with a high-affinity epitope and expressed from its natural chromosomal location, and it is found that about 80% of the proteome is expressed during normal growth conditions.
Journal ArticleDOI

Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes

TL;DR: A comprehensive search for conserved elements in vertebrate genomes is conducted, using genome-wide multiple alignments of five vertebrate species (human, mouse, rat, chicken, and Fugu rubripes), using a two-state phylogenetic hidden Markov model (phylo-HMM).
Journal ArticleDOI

The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing

TL;DR: A quantitative sequencing-based method is developed for mapping transcribed regions, in which complementary DNA fragments are subjected to high-throughput sequencing and mapped to the genome, and it is demonstrated that most (74.5%) of the nonrepetitive sequence of the yeast genome is transcribed.
References
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Journal ArticleDOI

Initial sequencing and analysis of the human genome.

Eric S. Lander, +248 more
- 15 Feb 2001 - 
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Journal ArticleDOI

Initial sequencing and comparative analysis of the mouse genome.

Robert H. Waterston, +222 more
- 05 Dec 2002 - 
TL;DR: The results of an international collaboration to produce a high-quality draft sequence of the mouse genome are reported and an initial comparative analysis of the Mouse and human genomes is presented, describing some of the insights that can be gleaned from the two sequences.
Proceedings Article

Fitting a mixture model by expectation maximization to discover motifs in biopolymers.

TL;DR: The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences.
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Initial sequencing and comparative analysis of the mouse genome.

Robert H. Waterston, +222 more
- 05 Dec 2002 -