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The distribution of human SNPs in ge...

Guo, Yongjian.

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The distribution of human SNPs in gene promoter and coding regions.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The distribution of human SNPs in gene promoter and coding regions./
作者:	Guo, Yongjian.
面頁冊數:	151 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-10, Section: B, page: 5230.
Contained By:	Dissertation Abstracts International65-10B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3151148
ISBN:	0496106767

The distribution of human SNPs in gene promoter and coding regions.
Guo, Yongjian.

The distribution of human SNPs in gene promoter and coding regions. - 151 p.

Source: Dissertation Abstracts International, Volume: 65-10, Section: B, page: 5230.

Thesis (Ph.D.)--George Mason University, 2005.

Genetic sequence variation not only affects an individual's anthropometric characteristics, but also influences his risk of disease and response to environment. As a result of high-throughput genotyping methods, millions of genetic variants have been reported in recent years. To explore those important to phenotype, a common strategy is to focus on the variants in functionally important gene regions. Here, the most abundant human genetic variants, Single Nucleotide Polymorphisms (SNPS), were studied in gene promoter and coding regions. Specifically, SNP distributions in transcription factor binding sites, DNA regions corresponding to protein motif and secondary structure were investigated for all of known human genes.

ISBN: 0496106767Subjects--Topical Terms:

626642
Computer Science.

The distribution of human SNPs in gene promoter and coding regions.
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245 1 4 $a The distribution of human SNPs in gene promoter and coding regions.
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500 $a Source: Dissertation Abstracts International, Volume: 65-10, Section: B, page: 5230.
500 $a Director: D. Curtis Jamison.
502 $a Thesis (Ph.D.)--George Mason University, 2005.
520 $a Genetic sequence variation not only affects an individual's anthropometric characteristics, but also influences his risk of disease and response to environment. As a result of high-throughput genotyping methods, millions of genetic variants have been reported in recent years. To explore those important to phenotype, a common strategy is to focus on the variants in functionally important gene regions. Here, the most abundant human genetic variants, Single Nucleotide Polymorphisms (SNPS), were studied in gene promoter and coding regions. Specifically, SNP distributions in transcription factor binding sites, DNA regions corresponding to protein motif and secondary structure were investigated for all of known human genes.
520 $a Analysis of promoter SNPS in the gene promoters shows that more SNPs occur in the region close to transcriptional start sites than in the region further. SNPs caused by genetic mutation in transversion class are increased more in the former region. Transcription factor binding sites were computationally derived in gene promoters. More SNPs were observed in the putative binding sites than in the non-binding site sequence region, suggesting that the current information about transcription factor binding site sequence pattern may not be exhaustive. It may also suggest that SNPs are actively involved in influencing gene expression during evolution by affecting the transcription factor binding sites.
520 $a Analysis of coding SNPs in the gene regions corresponding to protein motifs, alpha-helices and beta-sheets shows that the number of non-synonymous SNPs is significantly less than that of synonymous SNPs, although the total number of non-synonymous SNPs in all genes is larger. Non-synonymous SNPs are also more likely to influence amino acids in less conservative motif sites. There are only fewer than 10% of them may have functional impact to the gene products. A simulation on SNP occurrence also suggests that most non-synonymous SNPs only have neutral effects and are not under strong selection pressure.
520 $a A functional SNP database was created as a byproduct to include SNP and gene sequence feature data, which can be accessed by two types of web services. One is a Distributed Annotation System (DAS) server, which delivers gene annotation data in DAS XML format, and the other is a general web server which supports data view and visualization.
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