Dataset Information

No Evidence that MicroRNAs Coevolve with Genes Located in Copy Number Regions.

ABSTRACT: MicroRNAs (miRNAs) are a widespread class of regulatory noncoding RNAs with key roles in physiology and development, conferring robustness to noise in regulatory networks. Consistent with this buffering function, it was recently suggested that human miRNAs coevolve with genes in copy number regions (copy number variation [CNV] genes) to reduce dosage imbalance. Here, I compare miRNA regulation between CNV and non-CNV genes in four model organisms. miRNA regulation of CNV genes is elevated in human and fly but reduced in nematode and zebrafish. By analyzing 31 human CNV data sets, careful analysis of human and chimpanzee orthologs, resampling genes within species and comparing structural variant types, I show that the apparent coevolution between CNV genes and miRNAs is due to the strong dependency between 3'-untranslated region length and miRNA target prediction. Deciphering the interplay between CNVs and miRNAs will likely require a deeper understanding of how miRNAs are embedded in regulatory circuits.

SUBMITTER: Jovelin R

PROVIDER: S-EPMC4560049 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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No Evidence that MicroRNAs Coevolve with Genes Located in Copy Number Regions.

Jovelin Richard R

Molecular biology and evolution 20150324 7

MicroRNAs (miRNAs) are a widespread class of regulatory noncoding RNAs with key roles in physiology and development, conferring robustness to noise in regulatory networks. Consistent with this buffering function, it was recently suggested that human miRNAs coevolve with genes in copy number regions (copy number variation [CNV] genes) to reduce dosage imbalance. Here, I compare miRNA regulation between CNV and non-CNV genes in four model organisms. miRNA regulation of CNV genes is elevated in hum ...[more]

PMID: 25804521

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Project description:Recent large-scale genomic studies within human populations have identified numerous genomic regions as copy number variant (CNV). As these CNV regions often overlap coding regions of the genome, large lists of potentially copy number polymorphic genes have been produced that are candidates for disease association. Most of the current data regarding normal genic variation, however, has been generated using BAC or SNP microarrays, which lack precision especially with respect to exons. To address this, we assessed 2,790 candidate CNV genes defined from available studies in nine well-characterized HapMap individuals by designing a customized oligonucleotide microarray targeted specifically to exons. Using exon array comparative genomic hybridization (aCGH), we detected 255 (9%) of the candidates as true CNVs including 134 with evidence of variation over the entire gene. Individuals differed in copy number from the control by an average of 100 gene loci. Both partial- and whole-gene CNVs were strongly associated with segmental duplications (55 and 71%, respectively) as well as regions of positive selection. We confirmed 37% of the whole-gene CNVs using the fosmid end sequence pair (ESP) structural variation map for these same individuals. If we modify the end sequence pair mapping strategy to include low-sequence identity ESPs (98-99.5%) and ESPs with an everted orientation, we can capture 82% of the missed genes leading to more complete ascertainment of structural variation within duplicated genes. Our results indicate that segmental duplications are the source of the majority of full-length copy number polymorphic genes, most of the variant genes are organized as tandem duplications, and a significant fraction of these genes will represent paralogs with levels of sequence diversity beyond thresholds of allelic variation. In addition, these data provide a targeted set of CNV genes enriched for regions likely to be associated with human phenotypic differences due to copy number changes and present a source of copy number responsive oligonucleotide probes for future association studies.

Project description:Copy number variations (CNVs) are important structural variations that can cause significant phenotypic diversity. Reliable CNVs mapping can be achieved by identification of CNVs from different genetic backgrounds. Investigations on the characteristics of overlapping between CNV regions (CNVRs) and protein-coding genes (CNV genes) or miRNAs (CNV-miRNAs) can reveal the potential mechanisms of their regulation. In this study, we used 50 K SNP arrays to detect CNVs in Duroc purebred pig. A total number of 211 CNVRs were detected with a total length of 118.48 Mb, accounting for 5.23% of the autosomal genome sequence. Of these CNVRs, 32 were gains, 175 losses, and four contained both types (loss and gain within the same region). The CNVRs we detected were non-randomly distributed in the swine genome and were significantly enriched in the segmental duplication and gene density region. Additionally, these CNVRs were overlapping with 1,096 protein-coding genes (CNV-genes), and 39 miRNAs (CNV-miRNAs), respectively. The CNV-genes were enriched in terms of dosage-sensitive gene list. The expression of the CNV genes was significantly higher than that of the non-CNV genes in the adult Duroc prostate. Of all detected CNV genes, 22.99% genes were tissue-specific (TSI > 0.9). Strong negative selection had been underway in the CNV-genes as the ones that were located entirely within the loss CNVRs appeared to be evolving rapidly as determined by the median dN plus dS values. Non-CNV genes tended to be miRNA target than CNV-genes. Furthermore, CNV-miRNAs tended to target more genes compared to non-CNV-miRNAs, and a combination of two CNV-miRNAs preferentially synergistically regulated the same target genes. We also focused our efforts on examining CNV genes and CNV-miRNAs functions, which were also involved in the lipid metabolism, including DGAT1, DGAT2, MOGAT2, miR143, miR335, and miRLET7. Further molecular experiments and independent large studies are needed to confirm our findings.

Dataset Information

No Evidence that MicroRNAs Coevolve with Genes Located in Copy Number Regions.

Publications

No Evidence that MicroRNAs Coevolve with Genes Located in Copy Number Regions.

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