Evidence map›Paper›PMID 39982809›Full record

ArticleMolecular biology and evolution2025

Estimating Gene Conversion Tract Length and Rate From PacBio HiFi Data.

Anders Poulsen Charmouh, Peter Sørud Porsborg, Lasse Thorup Hansen, Søren Besenbacher, Sofia Boeg Winge, Kristian Almstrup, Asger Hobolth, Thomas Bataillon, Mikkel Heide Schierup

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2025. 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
–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

6 citing papers in PubMed.

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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

9 authors.

Anders Poulsen CharmouhBioinformatics Research Centre, Aarhus University, University City 81, DK-8000 Aarhus C, Denmark.ORCID 0000-0001-9573-184X
Peter Sørud PorsborgBioinformatics Research Centre, Aarhus University, University City 81, DK-8000 Aarhus C, Denmark.ORCID 0009-0000-9717-3642
Lasse Thorup HansenDepartment of Mathematics, Aarhus University, Ny Munkegade 118, DK-8000 Aarhus C, Denmark.ORCID 0009-0002-7538-4873
Søren BesenbacherDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark.ORCID 0000-0003-1455-1738
Sofia Boeg WingeDepartment of Growth and Reproduction, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark.ORCID 0000-0003-1666-1228
Kristian AlmstrupDepartment of Growth and Reproduction, Copenhagen University Hospital, DK-2100 Copenhagen, Denmark.ORCID 0000-0002-1832-0307
Asger HobolthDepartment of Mathematics, Aarhus University, Ny Munkegade 118, DK-8000 Aarhus C, Denmark.ORCID 0000-0003-4056-1286
Thomas BataillonBioinformatics Research Centre, Aarhus University, University City 81, DK-8000 Aarhus C, Denmark.ORCID 0000-0002-4730-2538
Mikkel Heide SchierupBioinformatics Research Centre, Aarhus University, University City 81, DK-8000 Aarhus C, Denmark.ORCID 0000-0002-5028-1790

Funding

ERCIndependent Research Fund Denmark 6108-00385Mikkel Heide SchierupNovo Nordisk Foundation NNF18OC0031004
6 · The paper itself

Abstract

Gene conversions are broadly defined as the transfer of genetic material from a "donor" to an "acceptor" sequence and can happen both in meiosis and mitosis. They are a subset of noncrossover (NCO) events and, like crossover (CO) events, gene conversion can generate new combinations of alleles and counteract mutation load by reverting germline mutations through GC-biased gene conversion. Estimating gene conversion rate and the distribution of gene conversion tract lengths remains challenging. We present a new method for estimating tract length, rate, and detection probability of NCO events directly in HiFi PacBio long read data. The method can be used to make inference from sequencing of gametes from a single individual. The method is unbiased even under low single nucleotide variant (SNV) densities and does not necessitate any demographic or evolutionary assumptions. We test the accuracy and robustness of our method using simulated datasets where we vary length of tracts, number of tracts, the genomic SNV density, and levels of correlation between SNV density and NCO event position. Our simulations show that under low SNV densities, like those found in humans, only a minute fraction (∼2%) of NCO events are expected to become visible as gene conversions by moving at least 1 SNV. We finally illustrate our method by applying it to PacBio sequencing data from human sperm.

Indexed as

Gene ConversionHumansModels, GeneticPolymorphism, Single Nucleotidegene conversiongenome evolutiongenomics methodsnoncrossoverrecombination

Identifiers

PMID39982809
PMCPMC11844249

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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.