Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/72661
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Type: Journal article
Title: Anonymous nuclear loci in non-model organisms: making the most of high-throughput genome surveys
Author: Bertozzi, T.
Sanders, K.
Sistrom, M.
Gardner, M.
Citation: Bioinformatics, 2012; 28(14):1807-1810
Publisher: Oxford Univ Press
Issue Date: 2012
ISSN: 1367-4803
1460-2059
Statement of
Responsibility: 
Terry Bertozzi, Kate L. Sanders, Mark J. Sistrom and Michael G. Gardner
Abstract: Motivation: When working with non-model organisms, few if any species-specific markers are available for phylogenetic, phylogeographic and population studies. Therefore, researchers often try to adapt markers developed in distantly related taxa, resulting in poor amplification and ascertainment bias in their target taxa. Markers can be developed de novo and anonymous nuclear loci (ANL) are proving to be a boon for researchers seeking large numbers of fast-evolving, independent loci. However, the development of ANL can be laboratory intensive and expensive. A workflow is described to identify suitable low-copy anonymous loci from high-throughput shotgun sequences, dramatically reducing the cost and time required to develop these markers and produce robust multilocus datasets. Results: By successively removing repetitive and evolutionary conserved sequences from low coverage shotgun libraries, we were able to isolate thousands of potential ANL. Empirical testing of loci developed from two reptile taxa confirmed that our methodology yields markers with comparable amplification rates and nucleotide diversities to ANLs developed using other methodologies. Our approach capitalizes on next-generation sequencing technologies to enable the development of phylogenetic, phylogeographic and population markers for taxa lacking suitable genomic resources.
Keywords: Cell Nucleus
Animals
Reptiles
Sequence Analysis, DNA
Computational Biology
Genomics
Gene Library
Genetic Loci
Rights: © The Author 2012. Published by Oxford University Press. All rights reserved.
DOI: 10.1093/bioinformatics/bts284
Grant ID: ARC
Published version: http://dx.doi.org/10.1093/bioinformatics/bts284
Appears in Collections:Aurora harvest 5
Earth and Environmental Sciences publications
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