Evidence map›Paper›PMID 34017944›Full record

ArticleNAR genomics and bioinformatics2021

PolyQ length co-evolution in neural proteins.

Serena Vaglietti, Ferdinando Fiumara

Open access · goldAbstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 43% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

2 authors at 1 institution in 1 country.

Serena VagliettiRita Levi Montalcini Department of Neuroscience, University of Torino, Torino 10125, Italy.
Ferdinando FiumaraRita Levi Montalcini Department of Neuroscience, University of Torino, Torino 10125, Italy.ORCID https://orcid.org/0000-0003-0715-7863
University of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intermolecular co-evolution optimizes physiological performance in functionally related proteins, ultimately increasing molecular co-adaptation and evolutionary fitness. Polyglutamine (polyQ) repeats, which are over-represented in nervous system-related proteins, are increasingly recognized as length-dependent regulators of protein function and interactions, and their length variation contributes to intraspecific phenotypic variability and interspecific divergence. However, it is unclear whether polyQ repeat lengths evolve independently in each protein or rather co-evolve across functionally related protein pairs and networks, as in an integrated regulatory system. To address this issue, we investigated here the length evolution and co-evolution of polyQ repeats in clusters of functionally related and physically interacting neural proteins in Primates. We observed function-/disease-related polyQ repeat enrichment and evolutionary hypervariability in specific neural protein clusters, particularly in the neurocognitive and neuropsychiatric domains. Notably, these analyses detected extensive patterns of intermolecular polyQ length co-evolution in pairs and clusters of functionally related, physically interacting proteins. Moreover, they revealed both direct and inverse polyQ length co-variation in protein pairs, together with complex patterns of coordinated repeat variation in entire polyQ protein sets. These findings uncover a whole system of co-evolving polyQ repeats in neural proteins with direct implications for understanding polyQ-dependent phenotypic variability, neurocognitive evolution and neuropsychiatric disease pathogenesis.

Identifiers

PMID34017944
PMCPMC8121095
OpenAlexW3162714996

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.