Evidence map›Paper›PMID 32824315›Full record

ArticleGenes2020

Mode and Tempo of Microsatellite Evolution across 300 Million Years of Insect Evolution.

Michelle Jonika, Johnathan Lo, Heath Blackmon

Open access · goldAbstract read
In one paragraph

Article in Genes, 2020. 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
0.4field-weighted citation impact, top 40% 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, 11 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Michelle JonikaDepartment of Biology, Texas A & M University, College Station, TX 77843, USA.ORCID 0000-0002-1170-6418
Johnathan LoDepartment of Biology, Texas A & M University, College Station, TX 77843, USA.ORCID 0000-0002-3552-6753
Heath BlackmonDepartment of Biology, Texas A & M University, College Station, TX 77843, USA.ORCID 0000-0002-5433-4036
Texas A&M University · US

Funding

Integrating theory, genomics, and comparative approaches to break barriers to the understanding of genome structure and sex chromosome evolution.R35GM138098 · NIGMS · TEXAS A&M UNIVERSITY · PI BLACKMON, HEATH · 2020 to 2024
$1.8M
NIGMS NIH HHS R35 GM138098
6 · The paper itself

Abstract

Microsatellites are short, repetitive DNA sequences that can rapidly expand and contract due to slippage during DNA replication. Despite their impacts on transcription, genome structure, and disease, relatively little is known about the evolutionary dynamics of these short sequences across long evolutionary periods. To address this gap in our knowledge, we performed comparative analyses of 304 available insect genomes. We investigated the impact of sequence assembly methods and assembly quality on the inference of microsatellite content, and we explored the influence of chromosome type and number on the tempo and mode of microsatellite evolution across one of the most speciose clades on the planet. Diploid chromosome number had no impact on the rate of microsatellite evolution or the amount of microsatellite content in genomes. We found that centromere type (holocentric or monocentric) is not associated with a difference in the amount of microsatellite content; however, in those species with monocentric chromosomes, microsatellite content tends to evolve faster than in species with holocentric chromosomes.

Indexed as

Evolution, MolecularMicrosatellite RepeatsAnimalsChromosomes, InsectComputational BiologyDatabases, GeneticGenome, InsectGenomicsInsectaRepetitive Sequences, Nucleic Acidcentromerechromosome evolutiongenome sizeinsectsmicrosatellite evolutionrepetitive DNA

Identifiers

PMID32824315
PMCPMC7464534
OpenAlexW3049441716

What OpenQuestion holds

Textmetadata
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.