Literature DB >> 21824289

Assessing the patterns of linkage disequilibrium in genic regions of the human genome.

Peng Sun1, Ruijie Zhang, Yongshuai Jiang, Xing Wang, Jin Li, Hongchao Lv, Guoping Tang, Xiaodan Guo, Xianwen Meng, Haikun Zhang, Ruimin Zhang.   

Abstract

We used the genotyping data generated by the International HapMap Project to study the patterns of linkage disequilibrium (LD) in human genic regions. LD patterns for 11,998 genes from 11 HapMap populations were identified by analyzing the distribution of haplotype blocks. The genes were prioritized using LD levels. The results showed that there were significant differences in the degree of LD between genes. Genes with high or low LD (the upper and lower quartiles of the LD levels) fell into different Gene Ontology functional categories. The high LD genes clustered preferentially in the metabolic process, macromolecule localization and cell-cycle categories, whereas the low LD genes clustered in the developmental process, ion transport, and immune and regulation system categories. Furthermore, we subdivided the genic region into 3'-UTR, 5'-UTR and CDS (coding region), and compared the different LD patterns in these subregions. We found that the LD patterns in low LD genes had a more interspersed block structure compared with the high LD genes. This was especially true in the CDS and 5'-UTR. The extent of LD was somewhat higher in 5'-UTRs compared with 3'-UTRs for both high and low LD genes. In addition, we assessed the overlap for the intragenic LD regions and found that the LD regions in high LD genes were more consistent among populations. Comprehensive information about the distribution of LD patterns in gene regions in populations may provide insights into the evolutionary history of humans and help in the selection of biomarkers for disease association studies.
© 2011 The Authors Journal compilation © 2011 FEBS.

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Year:  2011        PMID: 21824289     DOI: 10.1111/j.1742-4658.2011.08293.x

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  5 in total

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  5 in total

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