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Evolutionary Bioinformatics

Synopsis: An open access, peer reviewed electronic journal that covers computational evolutionary biology and evolutionary bioinformatics.


Indexed by: Pubmed, Pubmed Central, CAS, DOAJ, Embase, Embiology, Science Citation Index Expanded (SciSearch®), Journal Citation Reports/Science Edition, Current Contents®/Agriculture, Biology and Environmental Sciences, Current Contents®/Life Sciences, Google Scholar, EBSCO Academic Search Complete, OAIster.


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Editor in chief:
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ISSN: 1176-9343


 
 
 


MapToGenome: A Comparative Genomic Tool that Aligns Transcript Maps to Sequenced Genomes

Authors: Srikrishna Putta, Jeramiah J. Smith, Chuck Staben and S. Randal Voss
Publication Date: 14 Feb 2007
Evolutionary Bioinformatics 2007:3 15-25

Srikrishna Putta1,2, Jeramiah J. Smith1,2, Chuck Staben1 and S. Randal Voss1,2

1Department of Biology, University of Kentucky, Lexington, KY, U.S.A. 2Spinal Cord and Brain Injury Research Center, University of Kentucky, Lexington, KY, U.S.A.

Abstract: Efforts to generate whole genome assemblies and dense genetic maps have provided a wealth of gene positional information for several vertebrate species. Comparing the relative location of orthologous genes among these genomes provides perspective on genome evolution and can aid in translating genetic information between distantly related organisms. However, large-scale comparisons between genetic maps and genome assemblies can prove challenging because genetic markers are commonly derived from transcribed sequences that are incompletely and variably annotated. We developed the program MapToGenome as a tool for comparing transcript maps and genome assemblies. MapToGenome processes sequence alignments between mapped transcripts and whole genome sequence while accounting for the presence of intronic sequences, and assigns orthology based on user-defined parameters. To illustrate the utility of this program, we used MapToGenome to process alignments between vertebrate genetic maps and genome assemblies 1) self/self alignments for maps and assemblies of the rat and zebrafish genome; 2) alignments between vertebrate transcript maps (rat, salamander, zebrafish, and medaka) and the chicken genome; and 3) alignments of the medaka and zebrafish maps to the pufferfish (Tetraodon nigroviridis) genome. Our results show that map-genome alignments can be improved by combining alignments across presumptive intron breaks and ignoring alignments for simple sequence length polymorphism (SSLP) marker sequences. Comparisons between vertebrate maps and genomes reveal broad patterns of conservation among vertebrate genomes and the differential effects of genome rearrangement over time and across lineages.



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