Searching journal content for articles similar to Varabyou et al. 31 (2): 301.

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  1. Method: Analysis of coding gene expression from small RNA sequencing
    • Aygun Azadova,
    • Anthonia Ekperuoh,
    • Greg N. Brooke,
    • and Antonio Marco
    Genome Res. March 2026 36: 611-618; Published in Advance February 10, 2026, doi:10.1101/gr.281364.125
    ...determinant of whether small RNA libraries can be used to successfully measure coding gene expression levels.Transcript half-life has a negligible effect on small RNA expression estimates across tissuesTo evaluate potential biases in the transcript coverage between total and small RNA libraries, we computed...
  2. Research: Nanopore direct RNA sequencing reveals METTL2A-mediated m3C sites in poly(A) RNA
    • Shuhei Mitsutomi,
    • Anzu Sugawara,
    • Masahide Seki,
    • Yutaka Suzuki,
    • Sotaro Miyao,
    • Haozhe Du,
    • Kenji Takahashi,
    • Yusuke Mizukami,
    • Kenzui Taniue,
    • and Nobuyoshi Akimitsu
    Genome Res. November 2025 35: 2406-2417; Published in Advance October 30, 2025, doi:10.1101/gr.280269.124
    ...motif and coding sequences. METTL2A knockdown alters expression of S100A4 mRNA isoforms, which contains METTL2A-mediated m3C sites. Notably, many transcripts with METTL2A-mediated m3C sites are upregulated upon METTL2A knockdown. We reveal the transcriptome-wide presence of m3C sites in poly(A) RNA...
  3. Resource: Full-length RNA transcript sequencing traces brain isoform diversity in house mouse natural populations
    • Wenyu Zhang,
    • Anja Guenther,
    • Yuanxiao Gao,
    • Kristian Ullrich,
    • Bruno Huettel,
    • Aftab Ahmad,
    • Lei Duan,
    • Kaizong Wei,
    • and Diethard Tautz
    Genome Res. November 2024 34: 2118-2132; Published in Advance September 17, 2024, doi:10.1101/gr.279166.124
    ...: wyzhang@nwpu.edu.cn, tautz@evolbio.mpg.deAbstractThe ability to generate multiple RNA transcript isoforms from the same gene is a general phenomenon in eukaryotes. However, the complexity and diversity of alternative isoforms in natural populations remain largely unexplored. Using a newly developed full...
  4. Method: Deep structural clustering reveals hidden systematic biases in RNA sequencing data
    • Qiang Su,
    • Yi Long,
    • Deming Gou,
    • Junmin Quan,
    • Xiaoming Zhou,
    • and Qizhou Lian
    Genome Res. November 2025 35: 2563-2577; Published in Advance September 19, 2025, doi:10.1101/gr.280713.125
    ...analysis, providing comprehensive exploration of gene expression across diverse biological contexts. However, RNA-seq data are susceptible to various biases that can significantly compromise the accuracy and reliability of transcript quantification. This study investigates the influence of high...
  5. Method: Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution
    • Qian Qin,
    • Victoria Popic,
    • Kirsty Wienand,
    • Houlin Yu,
    • Emily White,
    • Akanksha Khorgade,
    • Asa Shin,
    • Christophe Georgescu,
    • Catarina D. Campbell,
    • Arthur Dondi,
    • Niko Beerenwinkel,
    • Francisca Vazquez,
    • Aziz M. Al'Khafaji,
    • and Brian J. Haas
    Genome Res. April 2025 35: 967-986; Published in Advance March 14, 2025, doi:10.1101/gr.279200.124
    .... During the past decade, RNA-seq has been the preferred assay for comprehensive gene fusion detection due to its lower cost than whole- sequencing (WGS) and directly measuring the transcripts arising from the gene fusions. Illumina short-read RNA-seq has become routine for such studies, and numerous...
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  6. Perspective: Challenges in identifying mRNA transcript starts and ends from long-read sequencing data
    • Ezequiel Calvo-Roitberg,
    • Rachel F. Daniels,
    • and Athma A. Pai
    Genome Res. November 2024 34: 1719-1734; doi:10.1101/gr.279559.124
    ...alternative transcript starts (TSSs) and ends (PASs), leading to different isoforms expressed from the same gene with variable cellular consequences. (B) Representative example of long-read RNA sequencing reads for CDC42 in K562 cells. To aid visualization, 280 randomly sampled reads from each sequencing...
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  7. Method: Long-read RNA sequencing reveals allele-specific N6-methyladenosine modifications
    • Dayea Park and
    • Can Cenik
    Genome Res. April 2025 35: 999-1011; Published in Advance October 29, 2024, doi:10.1101/gr.279270.124
    ...as only one allele is expressed. Allele-specific DNA methylation and chromatin composition are two well-established epigenetic systems that control imprinted gene expression (Fournier et al. 2002; Singh et al. 2010; Prendergast et al. 2012).ASE can reflect differential rates of transcription, mRNA...
  8. Method: Kinetic measurement of gene-specific RNA polymerase II transcription elongation rates
    • Haiyue Liu and
    • Lea H. Gregersen
    Genome Res. November 2025 35: 2550-2562; Published in Advance October 22, 2025, doi:10.1101/gr.280852.125
    ...and proceeds along the gene body to transcribe RNA (Jonkers and Lis 2015; Core and Adelman 2019; Noe Gonzalez et al. 2021; Aoi and Shilatifard 2023). As with all steps in the transcription process, elongation is tightly regulated to ensure that RNAPII travels along the gene at a proper speed (i.e., elongation...
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  9. Perspective: Notable challenges posed by long-read sequencing for the study of transcriptional diversity and genome annotation
    • Carolina Monzó,
    • Adam Frankish,
    • and Ana Conesa
    Genome Res. April 2025 35: 583-592; Published in Advance March 3, 2025, doi:10.1101/gr.279865.124
    ...-seq) can be compromised by factors such as RNA degradation, biases introduced during library preparation, sequencing errors, and inaccurate bioinformatic processing during mapping, transcript assembly, and quantification, which may lead to the incorrect identification of transcript models, i...
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  10. Method: Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks
    • Prashanthi Ravichandran,
    • Princy Parsana,
    • Rebecca Keener,
    • Kasper D. Hansen,
    • and Alexis Battle
    Genome Res. September 2025 35: 2087-2103; Published in Advance July 17, 2025, doi:10.1101/gr.280808.125
    ...and AI Institute, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding author: ajbattle@jhu.eduAbstractGene coexpression networks (GCNs) describe relationships among genes that maintain cellular identity and homeostasis. However, typical RNA-seq experiments often lack sufficient sample...
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