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Analyses of copy number variation of GK rat reveal new putative type 2 diabetes susceptibility loci.

Ye ZQ, Niu S, Yu Y, Yu H, Liu BH, Li RX, Xiao HS, Zeng R, Li YX, Wu JR, Li YY - PLoS ONE (2010)

Bottom Line: The GK rat, a spontanous T2D model, offers us a superior opportunity to search for more diabetic genes.As a result, we prioritized 16 putative protein-coding genes and two microRNA genes (rno-mir-30b and rno-mir-30d) as good candidates.These findings would contribute to the research into the genetic basis of T2D, and thus shed light on its pathogenesis.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.

ABSTRACT
Large efforts have been taken to search for genes responsible for type 2 diabetes (T2D), but have resulted in only about 20 in humans due to its complexity and heterogeneity. The GK rat, a spontanous T2D model, offers us a superior opportunity to search for more diabetic genes. Utilizing array comparative genome hybridization (aCGH) technology, we identifed 137 non-redundant copy number variation (CNV) regions from the GK rats when using normal Wistar rats as control. These CNV regions (CNVRs) covered approximately 36 Mb nucleotides, accounting for about 1% of the whole genome. By integrating information from gene annotations and disease knowledge, we investigated the CNVRs comprehensively for mining new T2D genes. As a result, we prioritized 16 putative protein-coding genes and two microRNA genes (rno-mir-30b and rno-mir-30d) as good candidates. The catalogue of CNVRs between GK and Wistar rats identified in this work served as a repository for mining genes that might play roles in the pathogenesis of T2D. Moreover, our efforts in utilizing bioinformatics methods to prioritize good candidate genes provided a more specific set of putative candidates. These findings would contribute to the research into the genetic basis of T2D, and thus shed light on its pathogenesis.

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Chromosomal distribution of GK/Wistar CNVRs.Green bars on the left and red bars on the right of chromosomal axes represent CNV “loss” and “gain”, respectively. Chromosome “Un” represents the pseudo-chromosome consisting of contigs that can not be confidently mapped to a specific chromosome.
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pone-0014077-g001: Chromosomal distribution of GK/Wistar CNVRs.Green bars on the left and red bars on the right of chromosomal axes represent CNV “loss” and “gain”, respectively. Chromosome “Un” represents the pseudo-chromosome consisting of contigs that can not be confidently mapped to a specific chromosome.

Mentions: We plotted the GK/Wistar CNVRs along each chromosome (Figure 1), and found that they were non-uniformly distributed with the extreme cases that chromosome 12 and 18 contained none, while chromosome 7 and 15 contained more CNVRs than random (4.5 Mb and 2.7 Mb identified vs. only 1.8 Mb and 1.4 Mb expected, respectively). The non-uniform pattern of CNVRs' distribution was similar to some extent with the previous report of rat CNVRs [21].


Analyses of copy number variation of GK rat reveal new putative type 2 diabetes susceptibility loci.

Ye ZQ, Niu S, Yu Y, Yu H, Liu BH, Li RX, Xiao HS, Zeng R, Li YX, Wu JR, Li YY - PLoS ONE (2010)

Chromosomal distribution of GK/Wistar CNVRs.Green bars on the left and red bars on the right of chromosomal axes represent CNV “loss” and “gain”, respectively. Chromosome “Un” represents the pseudo-chromosome consisting of contigs that can not be confidently mapped to a specific chromosome.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2990713&req=5

pone-0014077-g001: Chromosomal distribution of GK/Wistar CNVRs.Green bars on the left and red bars on the right of chromosomal axes represent CNV “loss” and “gain”, respectively. Chromosome “Un” represents the pseudo-chromosome consisting of contigs that can not be confidently mapped to a specific chromosome.
Mentions: We plotted the GK/Wistar CNVRs along each chromosome (Figure 1), and found that they were non-uniformly distributed with the extreme cases that chromosome 12 and 18 contained none, while chromosome 7 and 15 contained more CNVRs than random (4.5 Mb and 2.7 Mb identified vs. only 1.8 Mb and 1.4 Mb expected, respectively). The non-uniform pattern of CNVRs' distribution was similar to some extent with the previous report of rat CNVRs [21].

Bottom Line: The GK rat, a spontanous T2D model, offers us a superior opportunity to search for more diabetic genes.As a result, we prioritized 16 putative protein-coding genes and two microRNA genes (rno-mir-30b and rno-mir-30d) as good candidates.These findings would contribute to the research into the genetic basis of T2D, and thus shed light on its pathogenesis.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.

ABSTRACT
Large efforts have been taken to search for genes responsible for type 2 diabetes (T2D), but have resulted in only about 20 in humans due to its complexity and heterogeneity. The GK rat, a spontanous T2D model, offers us a superior opportunity to search for more diabetic genes. Utilizing array comparative genome hybridization (aCGH) technology, we identifed 137 non-redundant copy number variation (CNV) regions from the GK rats when using normal Wistar rats as control. These CNV regions (CNVRs) covered approximately 36 Mb nucleotides, accounting for about 1% of the whole genome. By integrating information from gene annotations and disease knowledge, we investigated the CNVRs comprehensively for mining new T2D genes. As a result, we prioritized 16 putative protein-coding genes and two microRNA genes (rno-mir-30b and rno-mir-30d) as good candidates. The catalogue of CNVRs between GK and Wistar rats identified in this work served as a repository for mining genes that might play roles in the pathogenesis of T2D. Moreover, our efforts in utilizing bioinformatics methods to prioritize good candidate genes provided a more specific set of putative candidates. These findings would contribute to the research into the genetic basis of T2D, and thus shed light on its pathogenesis.

Show MeSH
Related in: MedlinePlus