Evidence map›Paper›PMID 35468141›Full record

ArticlePLoS computational biology2022

Micro-dissection and integration of long and short reads to create a robust catalog of kidney compartment-specific isoforms.

Hongyang Li, Ridvan Eksi, Daiyao Yi, Bradley Godfrey, Lisa R Mathew, Christopher L O'Connor, Markus Bitzer, Matthias Kretzler, Rajasree Menon, Yuanfang Guan

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

10 authors.

Hongyang LiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-7902-4157
Ridvan EksiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0003-2757-0057
Daiyao YiDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.
Bradley GodfreyDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.
Lisa R MathewHarvard College, Cambridge, Massachusetts, United States of America.ORCID 0000-0003-0793-5610
Christopher L O'ConnorDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.
Markus BitzerDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0002-3711-2984
Matthias KretzlerDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0003-4064-0582
Rajasree MenonDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.
Yuanfang GuanDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America.ORCID 0000-0001-8275-2852

Funding

Machine Learning for Drug Response PredictionR35GM133346 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yuanfang Guan · 2019 to 2026
$3.2M
NIGMS NIH HHS R35 GM133346
6 · The paper itself

Abstract

Studying isoform expression at the microscopic level has always been a challenging task. A classical example is kidney, where glomerular and tubulo-interstitial compartments carry out drastically different physiological functions and thus presumably their isoform expression also differs. We aim at developing an experimental and computational pipeline for identifying isoforms at microscopic structure-level. We microdissected glomerular and tubulo-interstitial compartments from healthy human kidney tissues from two cohorts. The two compartments were separately sequenced with the PacBio RS II platform. These transcripts were then validated using transcripts of the same samples by the traditional Illumina RNA-Seq protocol, distinct Illumina RNA-Seq short reads from European Renal cDNA Bank (ERCB) samples, and annotated GENCODE transcript list, thus identifying novel transcripts. We identified 14,739 and 14,259 annotated transcripts, and 17,268 and 13,118 potentially novel transcripts in the glomerular and tubulo-interstitial compartments, respectively. Of note, relying solely on either short or long reads would have resulted in many erroneous identifications. We identified distinct pathways involved in glomerular and tubulo-interstitial compartments at the isoform level, creating an important experimental and computational resource for the kidney research community.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansKidneyProtein IsoformsRNA, MessengerProtein IsoformsRNA, Messenger

Identifiers

PMID35468141
PMCPMC9037928

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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.