Evidence map›Paper›PMID 38860163›Full record

ArticleBioinformatics and biology insights2024

Rapid Targeted Assembly of the Proteome Reveals Evolutionary Variation of GC Content in Avian Lice.

Avery R Grant, Kevin P Johnson, Edward L Stanley, James Baldwin-Brown, Stanislav Kolenčík, Julie M Allen

Abstract read
In one paragraph

Article in Bioinformatics and biology insights, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

6 authors.

Avery R GrantDepartment of Biology, University of Nevada, Reno, Reno, NV, USA.ORCID https://orcid.org/0000-0002-7623-4060
Kevin P JohnsonIllinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Edward L StanleyDepartment of Natural History, Florida Museum of Natural History, University of Florida, Gainesville, FL, USA.
James Baldwin-BrownDepartment of Biology, The University of Utah, Salt Lake City, UT, USA.
Stanislav KolenčíkFaculty of Mathematics, Natural Sciences, and Information Technologies, University of Primorska, Koper, Slovenia.
Julie M AllenDepartment of Biological Sciences, Virginia Tech, Blacksburg, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleotide base composition plays an influential role in the molecular mechanisms involved in gene function, phenotype, and amino acid composition. GC content (proportion of guanine and cytosine in DNA sequences) shows a high level of variation within and among species. Many studies measure GC content in a small number of genes, which may not be representative of genome-wide GC variation. One challenge when assembling extensive genomic data sets for these studies is the significant amount of resources (monetary and computational) associated with data processing, and many bioinformatic tools have not been optimized for resource efficiency. Using a high-performance computing (HPC) cluster, we manipulated resources provided to the targeted gene assembly program, automated target restricted assembly method (aTRAM), to determine an optimum way to run the program to maximize resource use. Using our optimum assembly approach, we assembled and measured GC content of all of the protein-coding genes of a diverse group of parasitic feather lice. Of the 499 426 genes assembled across 57 species, feather lice were GC-poor (mean GC = 42.96%) with a significant amount of variation within and between species (GC range = 19.57%-73.33%). We found a significant correlation between GC content and standard deviation per taxon for overall GC and GC

Indexed as

AT (adenine/thymine) richbase compositionBioinformaticscomputational resource efficiencyfeather licephylogenetic signalprotein-coding genes

Identifiers

PMID38860163
PMCPMC11163934

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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.