Evidence map›Paper›PMID 35699494›Full record

ArticleG3 (Bethesda, Md.)2022

Substitution rate heterogeneity across hexanucleotide contexts in noncoding chloroplast DNA.

Brian R Morton

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 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
0.3field-weighted citation impact, top 49% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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

1 author at 1 institution in 1 country.

Brian R MortonDepartment of Biology, Barnard College, Columbia University, New York, NY 10027, USA.ORCID 0000-0003-0115-8590
Columbia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Substitutions between closely related noncoding chloroplast DNA sequences are studied with respect to the composition of the 3 bases on each side of the substitution, that is the hexanucleotide context. There is about 100-fold variation in rate, among the contexts, particularly on substitutions of A and T. Rate heterogeneity of transitions differs from that of transversions, resulting in a more than 200-fold variation in the transitions: transversion bias. The data are consistent with a CpG effect, and it is shown that both the A + T content and the arrangement of purines/pyrimidines along the same DNA strand are correlated with rate variation. Expected equilibrium A + T content ranges from 36.4% to 82.8% across contexts, while G-C skew ranges from -77.4 to 72.2 and A-T skew ranges from -63.9 to 68.2. The predicted equilibria are associated with specific features of the content of the hexanucleotide context, and also show close agreement with the observed context-dependent compositions. Finally, by controlling for the content of nucleotides closer to the substitution site, it is shown that both the third and fourth nucleotide removed on each side of the substitution directly influence substitution dynamics at that site. Overall, the results demonstrate that noncoding sites in different contexts are evolving along very different evolutionary trajectories and that substitution dynamics are far more complex than typically assumed. This has important implications for a number of types of sequence analysis, particularly analyses of natural selection, and the context-dependent substitution matrices developed here can be applied in future analyses.

Indexed as

ChloroplastsDNA, ChloroplastBase SequenceEvolution, MolecularMutationSelection, GeneticDNA, Chloroplastchloroplast DNAcontextgenome evolutionmutationsubstitution model

Identifiers

PMID35699494
PMCPMC9339276
OpenAlexW4282840107

What OpenQuestion holds

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LicenceCC BY
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.