Literature DB >> 10746564

A simple and accurate method for determination of microsatellite total allele content differences between DNA pools.

H E Collins1, H Li, S E Inda, J Anderson, K Laiho, J Tuomilehto, M F Seldin.   

Abstract

DNA pooling is a potential tool for the efficient analysis of the large numbers of samples and DNA markers that are necessary for genome-wide association studies. A simple accurate method for measuring total allele differences in comparisons between two pools containing large numbers of DNA samples is presented. This method compares relative peak height differences between electrophoretograms for each allele of a microsatellite. The method was evaluated by the analysis of 11 microsatellite markers and DNA pooled sample sizes of 50, 100, and 200 individual DNA samples from the same number of different subjects. Pools were created from previously individually genotyped subjects and constructed so that the pool comparisons would provide real total allele differences varying from 0% to 55%. Calculated pool differences were then compared with the real total allele differences determined by individual genotyping results. Together over 200 comparisons demonstrated a correlation coefficient of 0.96, which compared favorably with other previous methods of analysis. This method could provide a rapid screen for total allele differences of greater than 10%, a threshold that should be applicable to detecting low relative risk genes in common diseases. Therefore, these studies suggest that DNA pooling could be a useful tool in association studies for the determination of candidate regions for a range of complex genetic diseases.

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Year:  2000        PMID: 10746564     DOI: 10.1007/s004390051031

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


  20 in total

1.  Ethnic-difference markers for use in mapping by admixture linkage disequilibrium.

Authors:  Heather E Collins-Schramm; Carolyn M Phillips; Darwin J Operario; Jane S Lee; James L Weber; Robert L Hanson; William C Knowler; Richard Cooper; Hongzhe Li; Michael F Seldin
Journal:  Am J Hum Genet       Date:  2002-02-11       Impact factor: 11.025

2.  Markers for mapping by admixture linkage disequilibrium in African American and Hispanic populations.

Authors:  M W Smith; J A Lautenberger; H D Shin; J P Chretien; S Shrestha; D A Gilbert; S J O'Brien
Journal:  Am J Hum Genet       Date:  2001-11       Impact factor: 11.025

3.  Estimation of haplotype frequencies, linkage-disequilibrium measures, and combination of haplotype copies in each pool by use of pooled DNA data.

Authors:  Toshikazu Ito; Suenori Chiku; Eisuke Inoue; Makoto Tomita; Takayuki Morisaki; Hiroko Morisaki; Naoyuki Kamatani
Journal:  Am J Hum Genet       Date:  2003-01-17       Impact factor: 11.025

4.  Validation of single nucleotide polymorphism quantification in pooled DNA samples with SNaPIT. A glycosylase-mediated methods for polymorphism detection method.

Authors:  Sarah Curran; Linzy Hill; Geraldine O'Grady; Dragana Turic; Philip Asherson; Eric Taylor; Pak Sham; Ian Craig; Pat Vaughan
Journal:  Mol Biotechnol       Date:  2002-11       Impact factor: 2.695

5.  Evaluation of microsatellite markers in association studies: a search for an immune-related susceptibility gene in sarcoidosis.

Authors:  Goh Tanaka; Ikumi Matsushita; Jun Ohashi; Naoyuki Tsuchiya; Soichiro Ikushima; Masaru Oritsu; Minako Hijikata; Taiji Nagata; Kazuhiko Yamamoto; Katsushi Tokunaga; Naoto Keicho
Journal:  Immunogenetics       Date:  2005-01-27       Impact factor: 2.846

6.  Constructing the parental linkage phase and the genetic map over distances <1 cM using pooled haploid DNA.

Authors:  Dario Gasbarra; Mikko J Sillanpää
Journal:  Genetics       Date:  2005-11-19       Impact factor: 4.562

7.  A genome-wide association scan for asthma in a general Australian population.

Authors:  J Hui; A Oka; A James; L J Palmer; A W Musk; J Beilby; H Inoko
Journal:  Hum Genet       Date:  2008-02-06       Impact factor: 4.132

8.  Megakaryoblastic leukemia factor-1 gene in the susceptibility to coronary artery disease.

Authors:  Kunihiko Hinohara; Toshiaki Nakajima; Michio Yasunami; Shigeru Houda; Taishi Sasaoka; Ken Yamamoto; Bok-Soo Lee; Hiroki Shibata; Yumiko Tanaka-Takahashi; Megumi Takahashi; Takuro Arimura; Akinori Sato; Taeko Naruse; Jimin Ban; Hidetoshi Inoko; Yoshiji Yamada; Motoji Sawabe; Jeong-Euy Park; Toru Izumi; Akinori Kimura
Journal:  Hum Genet       Date:  2009-06-10       Impact factor: 4.132

9.  A new approach to characterize populations of Schistosoma mansoni from humans: development and assessment of microsatellite analysis of pooled miracidia.

Authors:  B Hanelt; M L Steinauer; I N Mwangi; G M Maina; L E Agola; G M Mkoji; E S Loker
Journal:  Trop Med Int Health       Date:  2009-01-28       Impact factor: 2.622

10.  Genome wide screen identifies microsatellite markers associated with acute adverse effects following radiotherapy in cancer patients.

Authors:  Yuichi Michikawa; Tomo Suga; Atsuko Ishikawa; Hideki Hayashi; Akira Oka; Hidetoshi Inoko; Mayumi Iwakawa; Takashi Imai
Journal:  BMC Med Genet       Date:  2010-08-11       Impact factor: 2.103

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