In a recent study published in the Proceedings of the National Academy of Sciences, researchers explored micro-ribonucleic acids (RNAs) associated with diabetes and related characteristics in human pancreatic islets.
Study: Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis. Image Credit: Proxima Studio/Shutterstock
Background
Approximately 240 loci have been found in genetic research as being related to type 2 diabetes (T2D) risk, although most of these loci are located in non-coding areas, hiding the underlying molecular mechanisms. Some of the most significant insights into the molecular determinants of normal islet function and T2D pathogenesis are from recent research examining messenger RNA (mRNA) expression within human pancreatic islets.
The expression of microRNAs (miRNAs) has also been a subject of research, yet knowledge regarding the same still needs to be improved.
About the study
In the present study, researchers defined miRNA expression regulation by dissecting the expression of heritable miRNAs into trans- and cis-acting genetic elements.
The team collected 69 HPI samples and conducted RNA-sequencing (RNAseq), small-RNA-sequencing (smRNA-seq), and genotyping while retaining 39 specimens with RNA-seq, 63 specimens with smRNA-seq, and 57 specimens with genotypes after performing quality control. The smRNA-seq data was sourced from two different experiments: library preparation 1 (LP1) and LP2.
SNP-based heritability (h2g) was assessed for mRNA and miRNA transcripts utilizing imputed genotypes related to common single nucleotide polymorphisms (SNPs) to examine the patterns of genetic regulation of mRNA and miRNA species. miRNA-expression quantitative trait loci (eQTLs) were identified by examining genetic correlations with miRNA expression. The team also conducted colocalization analysis to investigate further the relationship between the miRNA-eQTLs and T2D-associated genetic loci and glycemic characteristics such as fasting blood glucose, blood glucose, fasting insulin, and glycated hemoglobin.
The overlap of mature miRNA genomic coordinates and genomic coordinates for anticipated miRNA target sites were employed to detect genetic variations linked with T2D and related phenotypes that may alter islet miRNA function. The team also searched for candidate target transcripts of miR-1908 by investigating the cis-effects of rs174559 on protein-coding gene transcription in HPIs as well as the trans-effects of rs174559 on protein-coding genes present across the genome.
Results
The average number of read pairs produced per sample in LP1 was 38.87 million, with an average read length of 23.24 nucleotides. On average, each LP2 sample produced 64.36 million read pairs, with a mean read length of 22.62 nucleotides. The miRNAs, such as miR-375 were also found to be the most abundant miRNAs among the islets across both LPs. Overall, 2,959 distinct miRNAs, along with 1,989 miRNA isoforms, were discovered.
All miRNA transcripts showed a much lower heritability compared to mRNA transcripts, indicating that miRNAs are subject to more stringent selection pressure as compared to mRNAs. Furthermore, the variation accounted for by trans-effects (htrans) was larger in heritable miRNA transcripts in comparison to heritable mRNA transcripts. Taken together, miRNAs had a distinct genetic regulatory structure from mRNAs, with the former being largely influenced by trans-effects and the latter by a combination of cis and trans-effects.
The team detected no colocalizations with T2D. Yet, evidence of colocalization between blood glucose levels and glycated hemoglobin (HbA1c) was discovered for a single miRNA-eQTL which was an eQTL for miR-1908 tagged by rs174559. The lack of colocalization with triglycerides (TG) and the presence of colocalization with RCDW may indicate the pleiotropic impacts of this locus in different tissues. The team also discovered evidence of colocalization with numerous FADS1 exons as well as with gene-level FADS1 expression. A FADS1 exon contained miR-1908, but variants related to exons located almost 4.3 kb away from miR-1908 had the greatest colocalization signal.
No SNPs were found in the predicted mature miRNA positions. In projected miRNA target regions, however, SNPs associated with 16 T2D, eight HbA1c, and one blood glucose were identified. A single SNP, rs1464569, in high linkage disequilibrium having the tag SNP, rs4955440 was observed. This SNP is located within NICN1 at a miR-532-3p target location.
Conclusion
The study findings provided the most comprehensive characterization of miRNA expression within HPIs using sequencing technology. To better understand the function of miRNAs in the pathogenesis of type 2 diabetes, the study detailed the genetic regulation of HPI miRNA expression.
More in-depth exploration of the genetics of HPI miRNAs, as well as the identification of more nuanced relationships between miRNA expression and T2D phenotypes of interest, would require larger investigations. However, this study's findings and connections are a first step in understanding HPIs concerning diabetes, and they will aid in the prioritizing of miRNAs for further mechanistic studies.
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