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Record W2984915376 · doi:10.7554/elife.24139.022

Author response: Poly(A) tail length regulates PABPC1 expression to tune translation in the heart

2017· peer-review· en· W2984915376 on OpenAlexaff
Sandip Chorghade, Joseph Seimetz, Russell Emmons, Jing Yang, Stefan Bresson, Michael De Lisio, Gianni Parise, Nicholas K. Conrad, Auinash Kalsotra

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsMessenger RNATranslation (biology)Protein biosynthesisRibosomeBiologyCell biologyGeneMolecular biologyRNAGenetics

Abstract

fetched live from OpenAlex

Hundreds of thousands of different proteins are needed to build and maintain the cells in the human body. All proteins are produced when copies of genetic information in the form of molecules of messenger RNA (mRNAs) are translated by the ribosome. The rate at which proteins are made varies widely between different tissues and at different times. In particular, the adult heart has one of the lowest rates of protein production, though this rate can increase markedly during exercise and heart disease. The mechanisms that drive this kind of dynamic change in protein production remain unclear. A better understanding of this process would tell scientists more about how and why cells regulate the translation of mRNAs in general, and might uncover new ways for treating heart disease. Molecules of mRNA are composed of smaller building blocks called nucleotides. All mature mRNAs in humans have a long stretch at one end that contains the nucleotide adenosine – commonly referred to as A for short – repeated 200 to 300 times. This sequence is called the poly(A) tail, and specific proteins can bind to this tail and determine the final fate of the mRNA, such as how efficiently it is translated. One such poly(A) binding protein, called PABPC1, is known to promote mRNA translation. Now, Chorghade, Seimetz et al. examine how PABPC1 regulates protein production in mice and human cells. The experiments reveal that, before birth, ample amounts of PABPC1 are found in the heart, but that this protein is undetectable in the hearts of adults. Further experiments showed that the levels of the mRNA for PABPC1 in the heart are the same before birth and in adulthood. So why is the mRNA for PABPC1 translated inefficiently in adult hearts? In general, mRNAs with long tails tend to be translated more efficiently compared to those with short tails, and it turns out that the mRNA for PABPC1 has a substantially shorter poly(A) tail in the adult heart. This tail shortening limits the translation of this specific mRNA, which leads to reduced protein production. Chorghade, Seimetz et al. also showed that the length of the poly(A) tail on the mRNA and the levels of the PABPC1 protein are restored in adult hearts during a condition known as hypertrophy. This state of hypertrophy can be triggered by exercise or heart disease and is marked by an increase in the size of individual heart cells and enhanced protein production. Finally, Chorghade, Seimetz et al. found that experimentally raising the levels of PABPC1 in adult hearts could, by itself, make the heart cells produce more protein and the heart grow more. Further studies will explore if other mRNAs in the heart also undergo similar changes and whether this is a general mechanism for controlling protein production.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.127
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.1270.048

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.383
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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