Artif Intell Med - Identifying regulatory relationships among genomic loci, biological pathways, and disease.

Tópicos

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Resumo

JECTIVE: Elucidating genetic factors of complex diseases is one of the most important challenges in biomedical research. Recently, a genetical genomics approach of mapping genotype to transcripts has been used in complex disease analysis. This approach treats messenger ribonucleic acid (mRNA) expression as a quantitative trait and identifies putative regulatory loci for the expression of an individual gene. However, the single-gene approach could not detect single nucleotide polymorphisms (SNP's) associated with the concerted activity of multiple genes. Since complex diseases result from the interactions of multiple genes, it is important to consider associations between genotype and multiple gene expression.METHODS AND MATERIALS: We developed the differential allelic co-expression (DACE) that identifies regulatory loci that affect the inter-correlation structure of multiple genes or a gene set. We applied DACE to two benchmark datasets: the normal human lymphoblastoid cell dataset and the glioblastoma dataset. These datasets consist of both SNPs and mRNA expression profiles for each sample. When analyzing the lymphoblastoid cell dataset, principal component analysis (PCA) was compared with the DACE test.RESULTS: While PCA identified associations found by single-gene analysis, the DACE test detected associations not identified by the single-gene approach. Using the DACE test, seven putative regulatory loci of immune-related pathways were identified in lymphoblastoid cells after controlling for family-wise error rate. In the glioblastoma dataset, DACE identified 4582 SNPs associated with six pathways. In 231 of the 4582 SNPs, patient survival length was correlated significantly with the SNP genotype. This finding suggests that our integrative approach may provide a biological explanation for the putative relationship between sequence level variation and disease outcome, via expression of a functional pathway.CONCLUSION: The DACE test shows promise for finding regulatory relationships between a genomic locus and sets of genes which may be related to disease outcome.

Resumo Limpo

jectiv elucid genet factor complex diseas one import challeng biomed research recent genet genom approach map genotyp transcript use complex diseas analysi approach treat messeng ribonucl acid mrna express quantit trait identifi putat regulatori loci express individu gene howev singlegen approach detect singl nucleotid polymorph snps associ concert activ multipl gene sinc complex diseas result interact multipl gene import consid associ genotyp multipl gene expressionmethod materi develop differenti allel coexpress dace identifi regulatori loci affect intercorrel structur multipl gene gene set appli dace two benchmark dataset normal human lymphoblastoid cell dataset glioblastoma dataset dataset consist snps mrna express profil sampl analyz lymphoblastoid cell dataset princip compon analysi pca compar dace testresult pca identifi associ found singlegen analysi dace test detect associ identifi singlegen approach use dace test seven putat regulatori loci immunerel pathway identifi lymphoblastoid cell control familywis error rate glioblastoma dataset dace identifi snps associ six pathway snps patient surviv length correl signific snp genotyp find suggest integr approach may provid biolog explan putat relationship sequenc level variat diseas outcom via express function pathwayconclus dace test show promis find regulatori relationship genom locus set gene may relat diseas outcom

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