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SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach

Overview of attention for article published in BMC Genomics, August 2007
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Title
SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach
Published in
BMC Genomics, August 2007
DOI 10.1186/1471-2164-8-266
Pubmed ID
Authors

Jacob L McCauley, Shannon J Kenealy, Elliott H Margulies, Nathalie Schnetz-Boutaud, Simon G Gregory, Stephen L Hauser, Jorge R Oksenberg, Margaret A Pericak-Vance, Jonathan L Haines, Douglas P Mortlock

Abstract

Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families. Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest. Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.

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Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
United States 1 2%
Unknown 40 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 31%
Student > Ph. D. Student 9 21%
Professor > Associate Professor 4 10%
Student > Master 4 10%
Student > Postgraduate 3 7%
Other 8 19%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 43%
Biochemistry, Genetics and Molecular Biology 12 29%
Medicine and Dentistry 8 19%
Computer Science 1 2%
Neuroscience 1 2%
Other 0 0%
Unknown 2 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 November 2018.
All research outputs
#12,254,164
of 13,851,031 outputs
Outputs from BMC Genomics
#7,099
of 8,136 outputs
Outputs of similar age
#223,157
of 266,710 outputs
Outputs of similar age from BMC Genomics
#1
of 2 outputs
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