Evidence map›Paper›PMID 32703790›Full record

ArticleHaematologica2021

Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Luigi Grassi, Osagie G Izuogu, Natasha A N Jorge, Denis Seyres, Mariona Bustamante, Frances Burden, Samantha Farrow, Neda Farahi, Fergal J Martin, Adam Frankish and 17 more

Abstract read
In one paragraph

Article in Haematologica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  15. Activated αeLife · 2020
    Article
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

27 authors.

Luigi GrassiDepartment of Haematology, University of Cambridge, School of Clinical Medicine, Cambridge, UK.
Osagie G IzuoguEMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Natasha A N JorgeOswaldo Cruz Institute, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil.
Denis SeyresDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Mariona BustamanteCenter for Genomic Regulation.
Frances BurdenDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Samantha FarrowDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Neda FarahiDivision of Respiratory Medicine, Department of Medicine, University of Cambridge.
Fergal J MartinEMBL-EBI.
Adam FrankishEMBL-EBI.
Jonathan M MudgeEMBL-EBI.
Myrto KostadimaDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Romina PetersenDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
John J LambourneDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Sophia RowlstonDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Enca Martin-RendonRD Division, National Health Service (NHS)-Blood and Transplant, Oxford Centre, Oxford, United King.
Laura ClarkeEMBL-EBI.
Kate DownesDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Xavier EstivillGenes and Disease Research Group, Genetics and Genomics Program, Sidra Research Department, Sidra Me.
Paul FlicekEMBL-EBI.
Joost H A MartensNijmegen Centre for Molecul.
Marie-Laure YaspoMax Planck Institute for Molecular Genetics, Berlin, Germany.
Hendrik G StunnenbergRadboud Institute for Molecular Life Science.
Willem H OuwehandDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Fabio PassettiFundacao Oswaldo Cruz.
Ernest TurroDepartment of Haematology, University of Cambridge, School of Clinical Medicine.
Mattia FrontiniDepartment of Haematology, University of Cambridge, School of Clinical Medicine.

Funding

GENCODE Resource ProjectU41HG007234 · NHGRI · SANGER INSTITUTE · PI FLICEK, PAUL · 2013 to 2020
$20.3M
British Heart Foundation FS/18/53/33863Medical Research Council MR/J00345X/1NHGRI NIH HHS U41 HG007234Wellcome TrustWellcome Trust WT108749/Z/15/Z
6 · The paper itself

Abstract

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.

Indexed as

RNA, Long NoncodingTranscriptomeGene Expression ProfilingHigh-Throughput Nucleotide SequencingRNA, CircularSequence Analysis, RNARNA, CircularRNA, Long Noncoding

Identifiers

PMID32703790
PMCPMC8485671

What OpenQuestion holds

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LicenceCC BY-NC
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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.