Literature DB >> 12052146

SNPs on human chromosomes 21 and 22 -- analysis in terms of protein features and pseudogenes.

Suganthi Balasubramanian1, Paul Harrison, Hedi Hegyi, Paul Bertone, Nicholas Luscombe, Nathaniel Echols, Patrick McGarvey, ZhaoLei Zhang, Mark Gerstein.   

Abstract

SNPs are useful for genome-wide mapping and the study of disease genes. Previous studies have focused on SNPs in specific genes or SNPs pooled from a variety of different sources. Here, a systematic approach to the analysis of SNPs in relation to various features on a genome-wide scale, with emphasis on protein features and pseudogenes, is presented. We have performed a comprehensive analysis of 39,408 SNPs on human chromosomes 21 and 22 from the SNP consortium (TSC) database, where SNPs are obtained by random sequencing using consistent and uniform methods. Our study indicates that the occurrence of SNPs is lowest in exons and higher in repeats, introns and pseudogenes. Moreover, in comparing genes and pseudogenes, we find that the SNP density is higher in pseudogenes and the ratio of nonsynonymous to synonymous changes is also much higher. These observations may be explained by the increased rate of SNP accumulation in pseudogenes, which presumably are not under selective pressure. We have also performed secondary structure prediction on all coding regions and found that there is no preferential distribution of SNPs in a -helices, b -sheets or coils. This could imply that protein structures, in general, can tolerate a wide degree of substitutions. Tables relating to our results are available from http://genecensus.org/pseudogene.

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Year:  2002        PMID: 12052146     DOI: 10.1517/14622416.3.3.393

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  8 in total

1.  The transcriptional activity of human Chromosome 22.

Authors:  John L Rinn; Ghia Euskirchen; Paul Bertone; Rebecca Martone; Nicholas M Luscombe; Stephen Hartman; Paul M Harrison; F Kenneth Nelson; Perry Miller; Mark Gerstein; Sherman Weissman; Michael Snyder
Journal:  Genes Dev       Date:  2003-02-15       Impact factor: 11.361

2.  Identification of polymorphic motifs using probabilistic search algorithms.

Authors:  Analabha Basu; Probal Chaudhuri; Partha P Majumder
Journal:  Genome Res       Date:  2005-01       Impact factor: 9.043

3.  Comparative analysis of pseudogenes across three phyla.

Authors:  Cristina Sisu; Baikang Pei; Jing Leng; Adam Frankish; Yan Zhang; Suganthi Balasubramanian; Rachel Harte; Daifeng Wang; Michael Rutenberg-Schoenberg; Wyatt Clark; Mark Diekhans; Joel Rozowsky; Tim Hubbard; Jennifer Harrow; Mark B Gerstein
Journal:  Proc Natl Acad Sci U S A       Date:  2014-08-25       Impact factor: 11.205

4.  Cloning and genetic diversity analysis of a new P5CS gene from common bean (Phaseolus vulgaris L.).

Authors:  Jibao Chen; Xiaoyan Zhang; Ruilian Jing; Matthew W Blair; Xinguo Mao; Shumin Wang
Journal:  Theor Appl Genet       Date:  2010-02-09       Impact factor: 5.699

5.  Identification of single nucleotide polymorphism in ginger using expressed sequence tags.

Authors:  Arumugam Chandrasekar; Aikkal Riju; Kandiyl Sithara; Sahadevan Anoop; Santhosh J Eapen
Journal:  Bioinformation       Date:  2009-09-30

6.  Genomic evidence for non-random endemic populations of decaying exons from mammalian genes.

Authors:  David Delima Morais; Paul M Harrison
Journal:  BMC Genomics       Date:  2009-07-13       Impact factor: 3.969

7.  Signatures of natural selection are not uniform across genes of innate immune system, but purifying selection is the dominant signature.

Authors:  Souvik Mukherjee; Neeta Sarkar-Roy; Diane K Wagener; Partha P Majumder
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-09       Impact factor: 11.205

8.  The distribution of SNPs in human gene regulatory regions.

Authors:  Yongjian Guo; D Curtis Jamison
Journal:  BMC Genomics       Date:  2005-10-06       Impact factor: 3.969

  8 in total

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