Evidence map›Paper›PMID 39605366›Full record

ArticlebioRxiv : the preprint server for biology2024

A pedigree-based map of crossovers and non-crossovers in aye-ayes (

Cyril J Versoza, Audald Lloret-Villas, Jeffrey D Jensen, Susanne P Pfeifer

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Cyril J VersozaCenter for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA.
Audald Lloret-VillasCenter for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA.
Jeffrey D JensenCenter for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA.ORCID 0000-0002-4786-8064
Susanne P PfeiferCenter for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, USA.ORCID 0000-0003-1378-2913

Funding

On differentiating selective and neutral evolutionary processesR35GM139383 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI JENSEN, JEFFREY D · 2021 to 2025
$3.0M
Characterizing the full spectrum of genomic variation in biomedically-relevant primatesR35GM151008 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI Susanne P Pfeifer · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM139383NIGMS NIH HHS R35 GM151008
6 · The paper itself

Abstract

Gaining a better understanding of rates and patterns of meiotic recombination is crucial for improving evolutionary genomic modelling, with applications ranging from demographic to selective inference. Although previous research has provided important insights into the landscape of crossovers in humans and other haplorrhines, our understanding of both the considerably more common outcome of recombination (i.e., non-crossovers) as well as the landscapes in more distantly-related primates (i.e., strepsirrhines) remains limited owing to difficulties associated with both the identification of non-crossover tracts as well as species sampling. Thus, in order to elucidate recombination patterns in this under-studied branch of the primate clade, we here characterize crossover and non-crossover landscapes in aye-ayes utilizing whole-genome sequencing data from six three-generation pedigrees as well as three two-generation multi-sibling families, and in so doing provide novel insights into this important evolutionary process shaping genomic diversity in one of the world's most critically endangered primate species.

Indexed as

Daubentoniidaepopulation genomicsprimaterecombinationstrepsirrhine

Identifiers

PMID39605366
PMCPMC11601232

What OpenQuestion holds

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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.