On the estimation of genome-average recombination rates.
The rate at which recombination events occur in a population is an indicator of its effective population size and the organism's reproduction mode. It determines the extent of linkage disequilibrium along the genome and, thereby, the efficacy of both purifying and positive selection. The population...
| Publicado en: | Genetics Vol. 227; no. 2; pp. 1 - 11 |
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| Autor principal: | |
| Formato: | equations & formulas research tables/charts Journal Article |
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Oxford University Press / USA
Jun2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=177800882&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 177800882 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00166731 GNT jtl: Genetics issn: 00166731 maglogo: N pubinfo: dt: Jun2024 vid: 227 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 177800882 177800882 177800882 10.1093/genetics/iyae051 177800882 ppf: 1 ppct: 10 formats: tig: atl: On the estimation of genome-average recombination rates. aug: au: Dutheil, Julien Y affil: Max Planck Institute for Evolutionary Biology , August-Thienemann-Str. 2, Plön 24306 , Germany sug: subj: Genes Genetic Variation Mutation Genome Sequence Analysis Human Sample Size Algorithms Heterozygote Genetics Funding Source Chromosome Aberrations Genomics ab: The rate at which recombination events occur in a population is an indicator of its effective population size and the organism's reproduction mode. It determines the extent of linkage disequilibrium along the genome and, thereby, the efficacy of both purifying and positive selection. The population recombination rate can be inferred using models of genome evolution in populations. Classic methods based on the patterns of linkage disequilibrium provide the most accurate estimates, providing large sample sizes are used and the demography of the population is properly accounted for. Here, the capacity of approaches based on the sequentially Markov coalescent (SMC) to infer the genome-average recombination rate from as little as a single diploid genome is examined. SMC approaches provide highly accurate estimates even in the presence of changing population sizes, providing that (1) within genome heterogeneity is accounted for and (2) classic maximum-likelihood optimization algorithms are employed to fit the model. SMC-based estimates proved sensitive to gene conversion, leading to an overestimation of the recombination rate if conversion events are frequent. Conversely, methods based on the correlation of heterozygosity succeed in disentangling the rate of crossing over from that of gene conversion events, but only when the population size is constant and the recombination landscape homogeneous. These results call for a convergence of these two methods to obtain accurate and comparable estimates of recombination rates between populations. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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