Evidence map›Paper›PMID 40155769›Full record

ReviewNature reviews. Genetics2025

Transcriptomics in the era of long-read sequencing.

Carolina Monzó, Tianyuan Liu, Ana Conesa

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed.

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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Carolina Monzó *Institute for Integrative Systems Biology, Spanish National Research Council, Paterna, Valencia, Spain. carolina.monzo@csic.es.ORCID http://orcid.org/0000-0002-5043-8145
Tianyuan Liu *Institute for Integrative Systems Biology, Spanish National Research Council, Paterna, Valencia, Spain.ORCID http://orcid.org/0000-0002-8561-6239
Ana ConesaInstitute for Integrative Systems Biology, Spanish National Research Council, Paterna, Valencia, Spain. ana.conesa@csic.es.ORCID http://orcid.org/0000-0001-9597-311X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptome sequencing revolutionized the analysis of gene expression, providing an unbiased approach to gene detection and quantification that enabled the discovery of novel isoforms, alternative splicing events and fusion transcripts. However, although short-read sequencing technologies have surpassed the limited dynamic range of previous technologies such as microarrays, they have limitations, for example, in resolving full-length transcripts and complex isoforms. Over the past 5 years, long-read sequencing technologies have matured considerably, with improvements in instrumentation and analytical methods, enabling their application to RNA sequencing (RNA-seq). Benchmarking studies are beginning to identify the strengths and limitations of long-read RNA-seq, although there remains a need for comprehensive resources to guide newcomers through the intricacies of this approach. In this Review, we provide a comprehensive overview of the long-read RNA-seq workflow, from library preparation and sequencing challenges to core data processing, downstream analyses and emerging developments. We present an extensive inventory of experimental and analytical methods and discuss current challenges and prospects.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingRNA-SeqSequence Analysis, RNATranscriptomeAlternative SplicingAnimalsHumans

Identifiers

PMID40155769

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.