LargeScale Integration of MicroRNA and Gene Expre

Authors: Preethi H Gunaratne Chad J Creighton Michael Watson Jayantha B Tennakoon

Publish Date: 2010

Volume: , Issue: , Pages: 297-315

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Abstract

The discovery of microRNAs miRNAs revealed a hidden layer of gene regulation that is able to integrate multiple genes into biologically meaningful networks A number of computational prediction programs have been developed to identify putative miRNA targets Collectively the miRNAs that have been discovered so far have the potential to target over 60 of genes in our genome A minimum of six consecutive nucleotides in the 5′seed nucleotides 2–8 in the miRNA must bind through complimentary base pairing to the 3′untranslated 3′UTRs of target genes Given the small sequence match required a given miRNA has the potential to target hundreds of genes and a given mRNA can have 0–50 miRNA binding sites The lowthroughput nature of the query design gene by gene or miRNA by miRNA and a fairly high rate of false positives and negatives uncovered by the limited number of functional studies remain as the major limitations Programs that integrate genomewide gene and miRNA expression data determined by microarray and/or nextgeneration sequencing NGS technologies with the publicly available target prediction algorithms are extremely valuable on two fronts First they allow the investigator to fully capitalize on all the data generated to reveal new genes and pathways underlying the biological process under study Second these programs allow the investigator to lift a small network of genes they are currently following into a larger network through the integrative properties of miRNAs In this chapter we discuss the latest methodologies for determining genomewide miRNA and gene expression changes and three programs Sigterms CORNA and MMIA that allow the investigator to generate short lists of enriched miRNAtarget mRNA candidates for largescale miRNAtarget mRNA validation These efforts are essential for determining false positive and negative rates of existing algorithms and refining our knowledge on the rules of miRNA–mRNA relationshipsPHG and JBT are supported by a 1 R01 HL09538201 grant The authors would like to thank Gayani Rajapakse Ana Hernandez and Rajib Ghosh at University of Houston Department of Biology and Biochemistry for their assistance in preparing this manuscript

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