Literature DB >> 18435570

Delineating slowly and rapidly evolving fractions of the Drosophila genome.

Jonathan M Keith1, Peter Adams, Stuart Stephen, John S Mattick.   

Abstract

Evolutionary conservation is an important indicator of function and a major component of bioinformatic methods to identify non-protein-coding genes. We present a new Bayesian method for segmenting pairwise alignments of eukaryotic genomes while simultaneously classifying segments into slowly and rapidly evolving fractions. We also describe an information criterion similar to the Akaike Information Criterion (AIC) for determining the number of classes. Working with pairwise alignments enables detection of differences in conservation patterns among closely related species. We analyzed three whole-genome and three partial-genome pairwise alignments among eight Drosophila species. Three distinct classes of conservation level were detected. Sequences comprising the most slowly evolving component were consistent across a range of species pairs, and constituted approximately 62-66% of the D. melanogaster genome. Almost all (>90%) of the aligned protein-coding sequence is in this fraction, suggesting much of it (comprising the majority of the Drosophila genome, including approximately 56% of non-protein-coding sequences) is functional. The size and content of the most rapidly evolving component was species dependent, and varied from 1.6% to 4.8%. This fraction is also enriched for protein-coding sequence (while containing significant amounts of non-protein-coding sequence), suggesting it is under positive selection. We also classified segments according to conservation and GC content simultaneously. This analysis identified numerous sub-classes of those identified on the basis of conservation alone, but was nevertheless consistent with that classification. Software, data, and results available at www.maths.qut.edu.au/-keithj/. Genomic segments comprising the conservation classes available in BED format.

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Year:  2008        PMID: 18435570     DOI: 10.1089/cmb.2007.0173

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  8 in total

1.  Massive turnover of functional sequence in human and other mammalian genomes.

Authors:  Stephen Meader; Chris P Ponting; Gerton Lunter
Journal:  Genome Res       Date:  2010-08-06       Impact factor: 9.043

2.  Computational characterization of 3' splice variants in the GFAP isoform family.

Authors:  Sarah E Boyd; Betina Nair; Sze Woei Ng; Jonathan M Keith; Jacqueline M Orian
Journal:  PLoS One       Date:  2012-03-30       Impact factor: 3.240

3.  Discovery of putative small non-coding RNAs from the obligate intracellular bacterium Wolbachia pipientis.

Authors:  Megan Woolfit; Manjula Algama; Jonathan M Keith; Elizabeth A McGraw; Jean Popovici
Journal:  PLoS One       Date:  2015-03-04       Impact factor: 3.240

Review 4.  Investigating genomic structure using changept: A Bayesian segmentation model.

Authors:  Manjula Algama; Jonathan M Keith
Journal:  Comput Struct Biotechnol J       Date:  2014-08-27       Impact factor: 7.271

5.  Genome-wide identification of conserved intronic non-coding sequences using a Bayesian segmentation approach.

Authors:  Manjula Algama; Edward Tasker; Caitlin Williams; Adam C Parslow; Robert J Bryson-Richardson; Jonathan M Keith
Journal:  BMC Genomics       Date:  2017-03-27       Impact factor: 3.969

6.  Detection and identification of cis-regulatory elements using change-point and classification algorithms.

Authors:  Mirana Ramialison; Jonathan Keith; Dominic Maderazo; Jennifer A Flegg; Manjula Algama
Journal:  BMC Genomics       Date:  2022-01-25       Impact factor: 3.969

7.  Drosophila 3' UTRs are more complex than protein-coding sequences.

Authors:  Manjula Algama; Christopher Oldmeadow; Edward Tasker; Kerrie Mengersen; Jonathan M Keith
Journal:  PLoS One       Date:  2014-05-13       Impact factor: 3.240

8.  Bayesian change-point modeling with segmented ARMA model.

Authors:  Farhana Sadia; Sarah Boyd; Jonathan M Keith
Journal:  PLoS One       Date:  2018-12-31       Impact factor: 3.240

  8 in total

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