Abstract
BackgroundMicroRNAs (miRNAs) have been recognized as one of the key regulatory non-coding RNAs that are involved in a number of basic cellular processes. miRNA expression profiling helps to identify miRNAs that could serve as biomarkers. Next generation sequencing (NGS) platforms provide the most effective way of miRNA profiling, particularly as expression of different isoforms of miRNA (IsomiRs) can be estimated by NGS. Therefore, it is now possible to discern the overall complexity of miRNA populations that participate in gene regulatory networks. It is thus important to consider different isoforms of miRNA as part of total profiling in order to understand all aspects of the biology of miRNAs.ResultsHere next generation sequencing data of small RNAs derived from normal peripheral blood mononuclear cells (PBMC) and Chronic myeloid leukemia (CML) patients has been used to generate miRNA profiles using a computation pipeline which can identify isomiRs that are natural variants of mature miRNAs. IsomiR profiles have been generated for all the 5p and 3p miRNAs (previously known as major mature miRNA and minor or miRNA*) and the data has been presented as a composite total miRNA transcriptome. The results indicated that the most abundant isomiR sequence of about 68% miRNAs, did not match the reference miRNA sequence as entered in the miRBase and that there is a definite pattern in relative concentration of different isomiRs derived from same precursors. Finally, a total of 17 potential novel miRNA sequences were identified suggesting that there are still some new miRNAs yet to be discovered.ConclusionsInclusion of different isoforms provides a detailed miRnome of a cell type or tissues. Availability of miRnome will be useful for finding biomarkers of different cell types and disease states. Our results also indicate that the relative expression levels of different isoforms of a miRNA are likely to be dynamic and may change with respect to changes in the cell or differentiation status.
Highlights
MicroRNAs have been recognized as one of the key regulatory non-coding RNAs that are involved in a number of basic cellular processes. miRNA expression profiling helps to identify miRNAs that could serve as biomarkers
MicroRNAs are a major class of small noncoding RNAs of about 22 nucleotides that are involved in various cellular functions. miRNAs are transcribed as pri-miRNAs which are processed into pre-miRNAs by an RNase III enzyme, Drosha
Annotation and apportionment small RNA (sRNA) datasets comprising of two Normal peripheral blood mononuclear cells (PBMC) and two Chronic myeloid leukemia (CML) patients were pre-processed as described in “Methods” and the distribution of the length of the reads was plotted to determine the optimal read length cut-off (Figure 1)
Summary
MicroRNAs (miRNAs) have been recognized as one of the key regulatory non-coding RNAs that are involved in a number of basic cellular processes. miRNA expression profiling helps to identify miRNAs that could serve as biomarkers. MicroRNAs (miRNAs) have been recognized as one of the key regulatory non-coding RNAs that are involved in a number of basic cellular processes. It is important to consider different isoforms of miRNA as part of total profiling in order to understand all aspects of the biology of miRNAs. MicroRNAs (miRNA) are a major class of small noncoding RNAs of about 22 nucleotides that are involved in various cellular functions. Several reports have established miRNAs as important post transcriptional regulators of gene expression through different mechanisms, such as translational repression and destabilization and cleavage of the target mRNA. MiRNAs and mRNAs are part of intricate networks that regulate gene expression and cellular decision making [8,9]. In order to understand these networks, knowledge of complete miRNA expression profiles is necessary. It is generally believed that some of the miRNAs can be useful diagnostic and prognostic markers of different cancers with applications in patient care and therapy [14]
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