Evidence map›Paper›PMID 30957857›Full record

ArticleGenome biology and evolution2019

New Zealand Tree and Giant Wētā (Orthoptera) Transcriptomics Reveal Divergent Selection Patterns in Metabolic Loci.

Victoria G Twort, Richard D Newcomb, Thomas R Buckley

Open access · goldAbstract readComparative Study
In one paragraph

Article in Genome biology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Standard metabolic rate variation among New Zealand Orthoptera.Current research in insect science · 2024
    Article
  3. Review
  4. Review
  5. 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

3 authors at 2 institutions in 2 countries.

Victoria G TwortSchool of Biological Sciences, University of Auckland, New Zealand.
Richard D NewcombSchool of Biological Sciences, University of Auckland, New Zealand.
Thomas R BuckleySchool of Biological Sciences, University of Auckland, New Zealand.
University of Auckland · NZPlant & Food Research · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exposure to low temperatures requires an organism to overcome physiological challenges. New Zealand wētā belonging to the genera Hemideina and Deinacrida are found across a wide range of thermal environments and therefore subject to varying selective pressures. Here we assess the selection pressures across the wētā phylogeny, with a particular emphasis on identifying genes under positive or diversifying selection. We used RNA-seq to generate transcriptomes for all 18 Deinacrida and Hemideina species. A total of 755 orthologous genes were identified using a bidirectional best-hit approach, with the resulting gene set encompassing a diverse range of functional classes. Analysis of ortholog ratios of synonymous to nonsynonymous amino acid changes found 83 genes that are under positive selection for at least one codon. A wide variety of Gene Ontology terms, enzymes, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways are represented among these genes. In particular, enzymes involved in oxidative phosphorylation, melanin synthesis, and free-radical scavenging are represented, consistent with physiological and metabolic changes that are associated with adaptation to alpine environments. Structural alignment of the transcripts with the most codons under positive selection revealed that the majority of sites are surface residues, and therefore have the potential to influence the thermostability of the enzyme, with the exception of prophenoloxidase where two residues near the active site are under selection. These proteins provide interesting candidates for further analysis of protein evolution.

Indexed as

Evolution, MolecularSelection, GeneticTranscriptomeAnimalsFemaleMaleOrthopteraPhylogenydiversifying selectionmetabolic ratemolecular evolutiontranscriptome

Identifiers

PMID30957857
PMCPMC6486805
OpenAlexW2939585296

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.