Evidence map›Paper›PMID 10353908›Full record

ArticleGenetics1999

The causes of synonymous rate variation in the rodent genome. Can substitution rates be used to estimate the sex bias in mutation rate?

N G Smith, L D Hurst

Abstract read
In one paragraph

Article in Genetics, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
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

18 citing papers in PubMed.

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  15. Review
  16. Functional constraints and frequency of deleterious mutations in noncoding DNA of rodents.Proceedings of the National Academy of Sciences of the United States of America · 2003
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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

2 authors.

N G SmithDepartment of Biology and Biochemistry, University of Bath, Bath BA2 7AY, United Kingdom. n.smith@bath.ac.uk
L D Hurst

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Miyata et al. have suggested that the male-to-female mutation rate ratio (alpha) can be estimated by comparing the neutral substitution rates of X-linked (X), Y-linked (Y), and autosomal (A) genes. Rodent silent site X/A comparisons provide very different estimates from X/Y comparisons. We examine three explanations for this discrepancy: (1) statistical biases and artifacts, (2) nonneutral evolution, and (3) differences in mutation rate per germline replication. By estimating errors and using a variety of methodologies, we tentatively reject explanation 1. Our analyses of patterns of codon usage, synonymous rates, and nonsynonymous rates suggest that silent sites in rodents are evolving neutrally, and we can therefore reject explanation 2. We find both base composition and methylation differences between the different sets of chromosomes, a result consistent with explanation 3, but these differences do not appear to explain the observed discrepancies in estimates of alpha. Our finding of significantly low synonymous substitution rates in genomically imprinted genes suggests a link between hemizygous expression and an adaptive reduction in the mutation rate, which is consistent with explanation 3. Therefore our results provide circumstantial evidence in favor of the hypothesis that the discrepancies in estimates of alpha are due to differences in the mutation rate per germline replication between different parts of the genome. This explanation violates a critical assumption of the method of Miyata et al., and hence we suggest that estimates of alpha, obtained using this method, need to be treated with caution.

Indexed as

Genetic VariationGenomeAnimalsBase CompositionChromosomesCodonDNA MethylationEvolution, MolecularFemaleGene Expression RegulationGenes, RecessiveGenetic LinkageGenomic ImprintingMaleMiceMutationCodon

Identifiers

PMID10353908
PMCPMC1460631

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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.