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Ali Oghabian

@gacatag.bsky.social

PostDoc at Myofin lab at Folkhälhsan RC & Uni of Helsinki. Interested in RNA splicing, Bioinformatics & Machine Learning.

25 Posts35 Follower45 Folgt
Ali Oghabian@gacatag.bsky.social · 5mo ago

New paper out in BMC Genomics ! Poly(A)+ & rRNA-depleted #RNAseq capture long transcripts differently, introducing major biases in transcript & splice-junction detection with important implications for disease studies. doi.org/10.1186/s128... #Transcriptomics #Splicing #Genomics #Bioinformatics

Poly(A)+ selection limits detection of long and alternatively spliced transcripts compared with rRNA depletion in RNA-Sequencing - BMC Genomics

The eukaryotic transcriptome diversity arises largely from alternative splicing. One of the widely used high-throughput methods to study this diversity is RNA sequencing. RNA sequencing has become a cornerstone of both basic biology and precision medicine, facilitating the quantification of gene and transcript expression, as well as the characterization of alternative splicing events and regulatory biological pathways in these studies. As there is a wide interest in studying non-ribosomal RNAs, which constitute about 20% of cellular RNAs, it is common to either select for poly(A)+ RNAs or to deplete ribosomal RNAs during the library preparation stage of RNA sequencing. At the time of library preparation, poly(A)+ selected RNA-Seq captures the polyadenylated transcripts, whereas rRNA-depleted RNA-Seq pools a broader spectrum of RNA species, including non-polyadenylated and premature transcripts. Using blood and skeletal muscle transcriptomics datasets, we examined how these two library enrichment techniques influence transcript representation, transcript-body coverage, and splice junction detection. We observed that poly(A)+ selected libraries display length-dependent differences, reduced splice junction representation and pronounced 3’ end coverage bias for transcripts of total transcription length over 5 kb. In contrast, rRNA depletion provides a more uniform 5′-3′ coverage, an improved detection of splice junctions, and a robust detection of long disease-relevant transcripts. These differences are evident in the detection of extremely large transcripts, such as the sarcomeric genes OBSCN (~ 39 kb) and TTN (> 100 kb). This study discusses how RNA-Seq library preparation techniques capture different RNA types and emphasizes the importance of interpreting poly(A)+ selected and rRNA depleted data in the appropriate biological and clinical contexts.

doi.org

Ali Oghabian@gacatag.bsky.social · 8mo ago

AI may help scientists go deeper, though not always wider. Higher output and faster careers, possibly alongside a narrowing of scientific focus. A paradox explored in @nature.com . nature.com/articles/d41... #AI #MachineLearning

AI tools boost individual scientists but could limit research as a whole

Analyses of hundreds of thousands of papers in the natural sciences reveal a paradox: scientists who use AI tools produce more research but on a more confined set of topics.

nature.com

Ali Oghabian@gacatag.bsky.social · 9mo ago

#EuroBioC2026 (i.e. The European #Bioconductor Conference) will take place, in Turku, Finland, on June 3-5, 2026. For more info see eurobioc2026.bioconductor.org. #Bioinformatics #Rprogramming

European Bioconductor Conference 2026 – EuroBioC2026

The European Bioconductor Conference (EuroBioC2026) will take place on June 3rd to 5th, 2026, in Turku, Finland EuroBioC2026 will bring together the Bioconductor community to showcase the latest cutti...

eurobioc2026.bioconductor.org

Ali Oghabian@gacatag.bsky.social · 10mo ago

Our new preprint on the limitations of PolyA+ selection vs rRNA-depleted RNA-seq, especially its effects on analysis of splicing and expression of long transcripts (and on findings of diseases linked to these transcripts), is now out: doi.org/10.21203/rs.... #RNAseq #RNASplicing #Bioinformatics

Poly(A) selection limits detection of long and alternatively spliced transcripts compared with rRNA depletion in RNA-Sequencing

The eukaryotic transcriptome diversity arises largely from alternative splicing. One of the widely used high-throughput methods to study this diversity is RNA sequencing. RNA sequencing has become a c...

doi.org