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Bioinformatics Basics: Analysis of MeRIP-Seq Datasets

Bioinformatics Basics: Analysis of MeRIP-Seq Datasets

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Introduction to MeRIP-Seq

The post-translational alterations to RNA that can affect a variety of biological procedures have achieved acknowledgment as a dynamic epigenetic threshold. The most diverse and traditional alteration in messenger RNA, N6-methyladenosine (m6A), has been related to a host of effects on mRNA fate. m6A is found near the stop codon, but also in the coding sequence, 3'UTR, and 5'UTR of mRNAs, according to a detailed analysis of its allocation and processes.

MeRIP-Seq Data Analysis

Mapping and Filtering Short Reads: Because MeRIP-Seq sequences mRNA indirectly from cDNA, spliced aligners should be used to enable reads to span exon-exon junctions An critical problem, as with many other NGS-based methods, is how to best cope with the widespread repetitive elements in a vast scope of species (roughly half of the human genome), which can result in multi-reads (reads that can be plotted to numerous genomic locations) and mapping inconsistencies in the alignment.

Fragment Length and Shifting Size: When utilizing 5' end position to signify the position of the reads (The distance is equal to 'fragment length' minus 'read length' when using 'Pos' in the SAM/BAM format to denote reads' positions), the most common RNA sequencing procedure (unstranded and single-end sequencing) creates two shifted peaks on the '+' and '' strands with a distance equivalent to the fragment length.

Peak Calling, Sequencing Bias and Control Sample: In ChIP-Seq, the identification of methylation sites are primarily constructed as a peak detection issue. Unlike ChIPSeq, which has a mild sequencing bias due to nucleosome loss around transcription starting locations, MeRIP-Seq has degradation at both the 5' and 3' ends due to RNA fragmentation, and significant variance in expression levels for different genes, and most essentially, the positional bias on the locus of the same gene due to various isoform transcripts.

Peak Annotation, Gene and Isoform Transcript: Isoform quantification, let alone the classification of sites on each individual isoform transcript, can be challenging with the current MeRIP-Seq protocol's 100bp fragment length. Nonetheless, an mRNA methylation site may be distinctively correlated with a transcript if it extends the closest exon(s) that are distinctive to that transcript.

Differential Methylation: In case-control research, MeRIP-Seq differential approach evaluates distinctions in RNA methylome.

Molecular Structure and Motif finding: Both ChIP-Seq and MeRIP-Seq can identify sequence motifs that are thought to have biological significance. The main difference in terms of computation is whether or not to scan the reverse complement strand While a DNA motif can occur on either strand of the two, an RNA motif should only occur on the strand that contains the transcript, so the strand data should be held at all times. When the strand data of an RNA fragment is lost during MeRIP-Seq unstranded library construction, the data of transcripts to which the fragments (reads) are mappable can still be distinguished.

Functional analysis: Various gene annotations, such as KEGG pathways, gene ontology (GO), TRANSFAC, and others, should still be used to perform functional analysis of RNA methylation.

References

  1. Zhang Z, Zhan Q, Eckert M, et al. RADAR: differential analysis of MeRIP-seq data with a random effect model. Genome biology. 2019, 20(1).
  2. Cui X, Zhang L, Meng J, et al. MeTDiff: a novel differential RNA methylation analysis for MeRIP-Seq data. IEEE/ACM transactions on computational biology and bioinformatics. 2015, 15(2).
  3. Meng J, Lu Z, Liu H, et al. A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package. Methods. 2014, 69(3).
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