1
|
Lukaszewicz M, Salia OI, Hohenlohe PA, Buzbas EO. Approximate Bayesian computational methods to estimate the strength of divergent selection in population genomics models. JOURNAL OF COMPUTATIONAL MATHEMATICS AND DATA SCIENCE 2024; 10:100091. [PMID: 38616846 PMCID: PMC11014422 DOI: 10.1016/j.jcmds.2024.100091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Statistical estimation of parameters in large models of evolutionary processes is often too computationally inefficient to pursue using exact model likelihoods, even with single-nucleotide polymorphism (SNP) data, which offers a way to reduce the size of genetic data while retaining relevant information. Approximate Bayesian Computation (ABC) to perform statistical inference about parameters of large models takes the advantage of simulations to bypass direct evaluation of model likelihoods. We develop a mechanistic model to simulate forward-in-time divergent selection with variable migration rates, modes of reproduction (sexual, asexual), length and number of migration-selection cycles. We investigate the computational feasibility of ABC to perform statistical inference and study the quality of estimates on the position of loci under selection and the strength of selection. To expand the parameter space of positions under selection, we enhance the model by implementing an outlier scan on summarized observed data. We evaluate the usefulness of summary statistics well-known to capture the strength of selection, and assess their informativeness under divergent selection. We also evaluate the effect of genetic drift with respect to an idealized deterministic model with single-locus selection. We discuss the role of the recombination rate as a confounding factor in estimating the strength of divergent selection, and emphasize its importance in break down of linkage disequilibrium (LD). We answer the question for which part of the parameter space of the model we recover strong signal for estimating the selection, and determine whether population differentiation-based summary statistics or LD-based summary statistics perform well in estimating selection.
Collapse
Affiliation(s)
- Martyna Lukaszewicz
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America
| | - Ousseini Issaka Salia
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America
- Department of Horticulture, Washington State University, Pullman, WA, United States of America
| | - Paul A. Hohenlohe
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
- Department of Biological Sciences, University of Idaho, Moscow, ID, United States of America
| | - Erkan O. Buzbas
- Institute for Interdisciplinary Data Sciences (IIDS), University of Idaho, Moscow, ID, United States of America
- Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID, United States of America
| |
Collapse
|
2
|
Ferguson S, Jones A, Murray K, Andrew RL, Schwessinger B, Bothwell H, Borevitz J. Exploring the role of polymorphic interspecies structural variants in reproductive isolation and adaptive divergence in Eucalyptus. Gigascience 2024; 13:giae029. [PMID: 38869149 PMCID: PMC11170218 DOI: 10.1093/gigascience/giae029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 03/11/2024] [Accepted: 05/14/2024] [Indexed: 06/14/2024] Open
Abstract
Structural variations (SVs) play a significant role in speciation and adaptation in many species, yet few studies have explored the prevalence and impact of different categories of SVs. We conducted a comparative analysis of long-read assembled reference genomes of closely related Eucalyptus species to identify candidate SVs potentially influencing speciation and adaptation. Interspecies SVs can be either fixed differences or polymorphic in one or both species. To describe SV patterns, we employed short-read whole-genome sequencing on over 600 individuals of Eucalyptus melliodora and Eucalyptus sideroxylon, along with recent high-quality genome assemblies. We aligned reads and genotyped interspecies SVs predicted between species reference genomes. Our results revealed that 49,756 of 58,025 and 39,536 of 47,064 interspecies SVs could be typed with short reads in E. melliodora and E. sideroxylon, respectively. Focusing on inversions and translocations, symmetric SVs that are readily genotyped within both populations, 24 were found to be structural divergences, 2,623 structural polymorphisms, and 928 shared structural polymorphisms. We assessed the functional significance of fixed interspecies SVs by examining differences in estimated recombination rates and genetic differentiation between species, revealing a complex history of natural selection. Shared structural polymorphisms displayed enrichment of potentially adaptive genes. Understanding how different classes of genetic mutations contribute to genetic diversity and reproductive barriers is essential for understanding how organisms enhance fitness, adapt to changing environments, and diversify. Our findings reveal the prevalence of interspecies SVs and elucidate their role in genetic differentiation, adaptive evolution, and species divergence within and between populations.
Collapse
Affiliation(s)
- Scott Ferguson
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2600 Australia
| | - Ashley Jones
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2600 Australia
| | - Kevin Murray
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2600 Australia
- Department of Molecular Biology, Max Planck Institute for Biology Tübingen, Tübingen, 72076 Germany
| | - Rose L Andrew
- Botany & N.C.W. Beadle Herbarium, School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia
| | - Benjamin Schwessinger
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2600 Australia
| | - Helen Bothwell
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2600 Australia
- Warnell School of Forestry & Natural Resources, University of Georgia, Athens 30602 GA, United States
| | - Justin Borevitz
- Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2600 Australia
| |
Collapse
|
3
|
Wang X, Peischl S, Heckel G. Demographic history and genomic consequences of 10,000 generations of isolation in a wild mammal. Curr Biol 2023; 33:2051-2062.e4. [PMID: 37178689 DOI: 10.1016/j.cub.2023.04.042] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/20/2022] [Accepted: 04/17/2023] [Indexed: 05/15/2023]
Abstract
Increased human activities caused the isolation of populations in many species-often associated with genetic depletion and negative fitness effects. The effects of isolation are predicted by theory, but long-term data from natural populations are scarce. We show, with full genome sequences, that common voles (Microtus arvalis) in the Orkney archipelago have remained genetically isolated from conspecifics in continental Europe since their introduction by humans over 5,000 years ago. Modern Orkney vole populations are genetically highly differentiated from continental conspecifics as a result of genetic drift processes. Colonization likely started on the biggest Orkney island and vole populations on smaller islands were gradually split off, without signs of secondary admixture. Despite having large modern population sizes, Orkney voles are genetically depauperate and successive introductions to smaller islands resulted in further reduction of genetic diversity. We detected high levels of fixation of predicted deleterious variation compared with continental populations, particularly on smaller islands, yet the fitness effects realized in nature are unknown. Simulations showed that predominantly mildly deleterious mutations were fixed in populations, while highly deleterious mutations were purged early in the history of the Orkney population. Relaxation of selection overall due to benign environmental conditions on the islands and the effects of soft selection may have contributed to the repeated, successful establishment of Orkney voles despite potential fitness loss. Furthermore, the specific life history of these small mammals, resulting in relatively large population sizes, has probably been important for their long-term persistence in full isolation.
Collapse
Affiliation(s)
- Xuejing Wang
- Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland
| | - Stephan Peischl
- Interfaculty Bioinformatics Unit, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland; Swiss Institute of Bioinformatics, Amphipôle, Quartier UNIL-Sorge, 1015 Lausanne, Switzerland
| | - Gerald Heckel
- Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland; Swiss Institute of Bioinformatics, Amphipôle, Quartier UNIL-Sorge, 1015 Lausanne, Switzerland.
| |
Collapse
|
4
|
Krishnan S, DeMaere MZ, Beck D, Ostrowski M, Seymour JR, Darling AE. Rhometa: Population recombination rate estimation from metagenomic read datasets. PLoS Genet 2023; 19:e1010683. [PMID: 36972309 PMCID: PMC10079220 DOI: 10.1371/journal.pgen.1010683] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 04/06/2023] [Accepted: 02/27/2023] [Indexed: 03/29/2023] Open
Abstract
Prokaryotic evolution is influenced by the exchange of genetic information between species through a process referred to as recombination. The rate of recombination is a useful measure for the adaptive capacity of a prokaryotic population. We introduce Rhometa (https://github.com/sid-krish/Rhometa), a new software package to determine recombination rates from shotgun sequencing reads of metagenomes. It extends the composite likelihood approach for population recombination rate estimation and enables the analysis of modern short-read datasets. We evaluated Rhometa over a broad range of sequencing depths and complexities, using simulated and real experimental short-read data aligned to external reference genomes. Rhometa offers a comprehensive solution for determining population recombination rates from contemporary metagenomic read datasets. Rhometa extends the capabilities of conventional sequence-based composite likelihood population recombination rate estimators to include modern aligned metagenomic read datasets with diverse sequencing depths, thereby enabling the effective application of these techniques and their high accuracy rates to the field of metagenomics. Using simulated datasets, we show that our method performs well, with its accuracy improving with increasing numbers of genomes. Rhometa was validated on a real S. pneumoniae transformation experiment, where we show that it obtains plausible estimates of the rate of recombination. Finally, the program was also run on ocean surface water metagenomic datasets, through which we demonstrate that the program works on uncultured metagenomic datasets.
Collapse
Affiliation(s)
- Sidaswar Krishnan
- Climate Change Cluster, Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia
| | - Matthew Z. DeMaere
- Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia
- * E-mail:
| | - Dominik Beck
- Centre for Health Technologies and the School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, Australia
| | - Martin Ostrowski
- Climate Change Cluster, Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia
| | - Justin R. Seymour
- Climate Change Cluster, Faculty of Science, University of Technology Sydney, Sydney, NSW, Australia
| | - Aaron E. Darling
- Australian Institute for Microbiology & Infection, University of Technology Sydney, Sydney, NSW, Australia
- Illumina Australia Pty Ltd, Ultimo, NSW, Australia
| |
Collapse
|
5
|
Lynch M, Ye Z, Urban L, Maruki T, Wei W. The Linkage-Disequilibrium and Recombinational Landscape in Daphnia pulex. Genome Biol Evol 2022; 14:evac145. [PMID: 36170345 PMCID: PMC9642108 DOI: 10.1093/gbe/evac145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2022] [Indexed: 11/24/2022] Open
Abstract
By revealing the influence of recombinational activity beyond what can be achieved with controlled crosses, measures of linkage disequilibrium (LD) in natural populations provide a powerful means of defining the recombinational landscape within which genes evolve. In one of the most comprehensive studies of this sort ever performed, involving whole-genome analyses on nearly 1,000 individuals of the cyclically parthenogenetic microcrustacean Daphnia pulex, the data suggest a relatively uniform pattern of recombination across the genome. Patterns of LD are quite consistent among populations; average rates of recombination are quite similar for all chromosomes; and although some chromosomal regions have elevated recombination rates, the degree of inflation is not large, and the overall spatial pattern of recombination is close to the random expectation. Contrary to expectations for models in which crossing-over is the primary mechanism of recombination, and consistent with data for other species, the distance-dependent pattern of LD indicates excessively high levels at both short and long distances and unexpectedly low levels of decay at long distances, suggesting significant roles for factors such as nonindependent mutation, population subdivision, and recombination mechanisms unassociated with crossing over. These observations raise issues regarding the classical LD equilibrium model widely applied in population genetics to infer recombination rates across various length scales on chromosomes.
Collapse
Affiliation(s)
- Michael Lynch
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
| | - Zhiqiang Ye
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
| | - Lina Urban
- Department for Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany
| | - Takahiro Maruki
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
| | - Wen Wei
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA
| |
Collapse
|
6
|
Winbush A, Singh ND. Variation in fine-scale recombination rate in temperature-evolved Drosophila melanogaster populations in response to selection. G3 GENES|GENOMES|GENETICS 2022; 12:6663992. [PMID: 35961026 PMCID: PMC9526048 DOI: 10.1093/g3journal/jkac208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/05/2022] [Indexed: 11/16/2022]
Abstract
Meiotic recombination plays a critical evolutionary role in maintaining fitness in response to selective pressures due to changing environments. Variation in recombination rate has been observed amongst and between species and populations and within genomes across numerous taxa. Studies have demonstrated a link between changes in recombination rate and selection, but the extent to which fine-scale recombination rate varies between evolved populations during the evolutionary period in response to selection is under active research. Here, we utilize a set of 3 temperature-evolved Drosophila melanogaster populations that were shown to have diverged in several phenotypes, including recombination rate, based on the temperature regime in which they evolved. Using whole-genome sequencing data from these populations, we generated linkage disequilibrium-based fine-scale recombination maps for each population. With these maps, we compare recombination rates and patterns among the 3 populations and show that they have diverged at fine scales but are conserved at broader scales. We further demonstrate a correlation between recombination rates and genomic variation in the 3 populations. Lastly, we show variation in localized regions of enhanced recombination rates, termed warm spots, between the populations with these warm spots and associated genes overlapping areas previously shown to have diverged in the 3 populations due to selection. These data support the existence of recombination modifiers in these populations which are subject to selection during evolutionary change.
Collapse
Affiliation(s)
- Ari Winbush
- Department of Biology, Institute of Ecology and Evolution, University of Oregon , Eugene, OR 97403, USA
| | - Nadia D Singh
- Department of Biology, Institute of Ecology and Evolution, University of Oregon , Eugene, OR 97403, USA
| |
Collapse
|
7
|
Samuk K, Noor MAF. Gene flow biases population genetic inference of recombination rate. G3 GENES|GENOMES|GENETICS 2022; 12:6698695. [PMID: 36103705 PMCID: PMC9635666 DOI: 10.1093/g3journal/jkac236] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 08/30/2022] [Indexed: 11/21/2022]
Abstract
Accurate estimates of the rate of recombination are key to understanding a host of evolutionary processes as well as the evolution of the recombination rate itself. Model-based population genetic methods that infer recombination rates from patterns of linkage disequilibrium in the genome have become a popular method to estimate rates of recombination. However, these linkage disequilibrium-based methods make a variety of simplifying assumptions about the populations of interest that are often not met in natural populations. One such assumption is the absence of gene flow from other populations. Here, we use forward-time population genetic simulations of isolation-with-migration scenarios to explore how gene flow affects the accuracy of linkage disequilibrium-based estimators of recombination rate. We find that moderate levels of gene flow can result in either the overestimation or underestimation of recombination rates by up to 20–50% depending on the timing of divergence. We also find that these biases can affect the detection of interpopulation differences in recombination rate, causing both false positives and false negatives depending on the scenario. We discuss future possibilities for mitigating these biases and recommend that investigators exercise caution and confirm that their study populations meet assumptions before deploying these methods.
Collapse
Affiliation(s)
- Kieran Samuk
- Department of Biology, Duke University , Durham, NC 27708, USA
- Department of Evolution, Ecology, and Organismal Biology, The University of California, Riverside ,Riverside, CA 92521, USA
| | | |
Collapse
|
8
|
Miao X, Yu Y, Zhao Z, Wang Y, Qian X, Wang Y, Li S, Wang C. Chromosome-Level Haplotype Assembly for Equus asinu. Front Genet 2022; 13:738105. [PMID: 35692816 PMCID: PMC9186339 DOI: 10.3389/fgene.2022.738105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Haplotype provides significant insights into understanding genomes at both individual and population levels. However, research on many non-model organisms is still based on independent genetic variations due to the lack of haplotype.Results: We conducted haplotype assembling for Equus asinu, a non-model organism that plays a vital role in human civilization. We described the hybrid single individual assembled haplotype of the Dezhou donkey based on the high-depth sequencing data from single-molecule real-time sequencing (×30), Illumina short-read sequencing (×211), and high-throughput chromosome conformation capture (×56). We assembled a near-complete haplotype for the high-depth sequenced Dezhou donkey individual and a phased cohort for the resequencing data of the donkey population.Conclusion: Here, we described the complete chromosome-scale haplotype of the Dezhou donkey with more than a 99.7% phase rate. We further phased a cohort of 156 donkeys to form a donkey haplotype dataset with more than 39 million genetic variations.
Collapse
Affiliation(s)
- Xinyao Miao
- Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng, China
- Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
- College of Forensic & Medicine, Xi’an Jiaotong University, Xi’an, China
| | - Yonghan Yu
- Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Zicheng Zhao
- Shenzhen Byoryn Technology Co., Ltd., Shenzhen, China
| | - Yinan Wang
- College of Forensic & Medicine, Xi’an Jiaotong University, Xi’an, China
| | - Xiaobo Qian
- Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng, China
| | - Yonghui Wang
- Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng, China
| | - Shengbin Li
- College of Forensic & Medicine, Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Shengbin Li, ; Changfa Wang,
| | - Changfa Wang
- Liaocheng Research Institute of Donkey High-Efficiency Breeding and Ecological Feeding, Liaocheng University, Liaocheng, China
- *Correspondence: Shengbin Li, ; Changfa Wang,
| |
Collapse
|
9
|
Valiente-Mullor C, Beamud B, Ansari I, Francés-Cuesta C, García-González N, Mejía L, Ruiz-Hueso P, González-Candelas F. One is not enough: On the effects of reference genome for the mapping and subsequent analyses of short-reads. PLoS Comput Biol 2021; 17:e1008678. [PMID: 33503026 PMCID: PMC7870062 DOI: 10.1371/journal.pcbi.1008678] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 02/08/2021] [Accepted: 01/05/2021] [Indexed: 12/17/2022] Open
Abstract
Mapping of high-throughput sequencing (HTS) reads to a single arbitrary reference genome is a frequently used approach in microbial genomics. However, the choice of a reference may represent a source of errors that may affect subsequent analyses such as the detection of single nucleotide polymorphisms (SNPs) and phylogenetic inference. In this work, we evaluated the effect of reference choice on short-read sequence data from five clinically and epidemiologically relevant bacteria (Klebsiella pneumoniae, Legionella pneumophila, Neisseria gonorrhoeae, Pseudomonas aeruginosa and Serratia marcescens). Publicly available whole-genome assemblies encompassing the genomic diversity of these species were selected as reference sequences, and read alignment statistics, SNP calling, recombination rates, dN/dS ratios, and phylogenetic trees were evaluated depending on the mapping reference. The choice of different reference genomes proved to have an impact on almost all the parameters considered in the five species. In addition, these biases had potential epidemiological implications such as including/excluding isolates of particular clades and the estimation of genetic distances. These findings suggest that the single reference approach might introduce systematic errors during mapping that affect subsequent analyses, particularly for data sets with isolates from genetically diverse backgrounds. In any case, exploring the effects of different references on the final conclusions is highly recommended. Mapping consists in the alignment of reads (i.e., DNA fragments) obtained through high-throughput genome sequencing to a previously assembled reference sequence. It is a common practice in genomic studies to use a single reference for mapping, usually the ‘reference genome’ of a species—a high-quality assembly. However, the selection of an optimal reference is hindered by intrinsic intra-species genetic variability, particularly in bacteria. It is known that genetic differences between the reference genome and the read sequences may produce incorrect alignments during mapping. Eventually, these errors could lead to misidentification of variants and biased reconstruction of phylogenetic trees (which reflect ancestry between different bacterial lineages). To our knowledge, this is the first work to systematically examine the effect of different references for mapping on the inference of tree topology as well as the impact on recombination and natural selection inferences. Furthermore, the novelty of this work relies on a procedure that guarantees that we are evaluating only the effect of the reference. This effect has proved to be pervasive in the five bacterial species that we have studied and, in some cases, alterations in phylogenetic trees could lead to incorrect epidemiological inferences. Hence, the use of different reference genomes may be prescriptive to assess the potential biases of mapping.
Collapse
Affiliation(s)
- Carlos Valiente-Mullor
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
| | - Beatriz Beamud
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
- * E-mail: (BB); (FG-C)
| | - Iván Ansari
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
| | - Carlos Francés-Cuesta
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
| | - Neris García-González
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
| | - Lorena Mejía
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
- Instituto de Microbiología, Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador
| | - Paula Ruiz-Hueso
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
| | - Fernando González-Candelas
- Joint Research Unit “Infection and Public Health” FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), Valencia, Spain
- CIBER in Epidemiology and Public Health, Valencia, Spain
- * E-mail: (BB); (FG-C)
| |
Collapse
|
10
|
van Eeden G, Uren C, Möller M, Henn BM. Inferring recombination patterns in African populations. Hum Mol Genet 2021; 30:R11-R16. [PMID: 33445180 DOI: 10.1093/hmg/ddab020] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 01/04/2021] [Accepted: 01/06/2021] [Indexed: 11/14/2022] Open
Abstract
Although several high-resolution recombination maps exist for European-descent populations, the recombination landscape of African populations remains relatively understudied. Given that there is high genetic divergence among groups in Africa, it is possible that recombination hotspots also diverge significantly. Both limitations and opportunities exist for developing recombination maps for these populations. In this review, we discuss various recombination inference methods, and the strengths and weaknesses of these methods in analyzing recombination in African-descent populations. Furthermore, we provide a decision tree and recommendations for which inference method to use in various research contexts. Establishing an appropriate methodology for recombination rate inference in a particular study will improve the accuracy of various downstream analyses including but not limited to local ancestry inference, haplotype phasing, fine-mapping of GWAS loci and genome assemblies.
Collapse
Affiliation(s)
- Gerald van Eeden
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa
| | - Caitlin Uren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch 7602, South Africa
| | - Marlo Möller
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch 7602, South Africa
| | - Brenna M Henn
- Department of Anthropology, Center for Population Biology and the Genome Center, University of California Davis, Davis, CA 95616, USA
| |
Collapse
|
11
|
From molecules to populations: appreciating and estimating recombination rate variation. Nat Rev Genet 2020; 21:476-492. [DOI: 10.1038/s41576-020-0240-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/15/2020] [Indexed: 02/07/2023]
|
12
|
Narum S, Kelley J, Sibbett B. Editorial 2020. Mol Ecol Resour 2020; 20:1-7. [DOI: 10.1111/1755-0998.13125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 12/09/2019] [Indexed: 11/29/2022]
|
13
|
Spence JP, Song YS. Inference and analysis of population-specific fine-scale recombination maps across 26 diverse human populations. SCIENCE ADVANCES 2019; 5:eaaw9206. [PMID: 31681842 PMCID: PMC6810367 DOI: 10.1126/sciadv.aaw9206] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 09/13/2019] [Indexed: 05/28/2023]
Abstract
Fine-scale rates of meiotic recombination vary by orders of magnitude across the genome and differ between species and even populations. Studying cross-population differences has been stymied by the confounding effects of demographic history. To address this problem, we developed a demography-aware method to infer fine-scale recombination rates and applied it to 26 diverse human populations, inferring population-specific recombination maps. These maps recapitulate many aspects of the history of these populations including signatures of the trans-Atlantic slave trade and the Iberian colonization of the Americas. We also investigated modulators of the local recombination rate, finding further evidence that Polycomb group proteins and the trimethylation of H3K27 elevate recombination rates. Further differences in the recombination landscape across the genome and between populations are driven by variation in the gene that encodes the DNA binding protein PRDM9, and we quantify the weak effect of meiotic drive acting to remove its binding sites.
Collapse
Affiliation(s)
- Jeffrey P. Spence
- Graduate Group in Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Yun S. Song
- Computer Science Division and Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| |
Collapse
|
14
|
Howie JM, Mazzucco R, Taus T, Nolte V, Schlötterer C. DNA Motifs Are Not General Predictors of Recombination in Two Drosophila Sister Species. Genome Biol Evol 2019; 11:1345-1357. [PMID: 30980655 PMCID: PMC6490297 DOI: 10.1093/gbe/evz082] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/09/2019] [Indexed: 12/11/2022] Open
Abstract
Meiotic recombination is crucial for chromosomal segregation and facilitates the spread of beneficial and removal of deleterious mutations. Recombination rates frequently vary along chromosomes and Drosophila melanogaster exhibits a remarkable pattern. Recombination rates gradually decrease toward centromeres and telomeres, with a dramatic impact on levels of variation in natural populations. Two close sister species, Drosophila simulans and Drosophila mauritiana do not only have higher recombination rates but also exhibit a much more homogeneous recombination rate that only drops sharply very close to centromeres and telomeres. Because certain sequence motifs are associated with recombination rate variation in D. melanogaster, we tested whether the difference in recombination landscape between D. melanogaster and D. simulans can be explained by the genomic distribution of recombination rate–associated sequence motifs. We constructed the first high-resolution recombination map for D. simulans based on 189 haplotypes from a natural D. simulans population and searched for short sequence motifs linked with higher than average recombination in both sister species. We identified five consensus motifs significantly associated with higher than average chromosome-wide recombination rates in at least one species and present in both. Testing fine resolution associations between motif density and recombination, we found strong and positive associations genome-wide over a range of scales in D. melanogaster, while the results were equivocal in D. simulans. Despite the strong association in D. melanogaster, we did not find a decreasing density of these short-repeat motifs toward centromeres and telomeres. We conclude that the density of recombination-associated repeat motifs cannot explain the large-scale recombination landscape in D. melanogaster, nor the differences to D. simulans. The strong association seen for the sequence motifs in D. melanogaster likely reflects their impact influencing local differences in recombination rates along the genome.
Collapse
Affiliation(s)
- James M Howie
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
| | | | - Thomas Taus
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria.,Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
| | | |
Collapse
|
15
|
Hermann P, Heissl A, Tiemann-Boege I, Futschik A. LDJump: Estimating variable recombination rates from population genetic data. Mol Ecol Resour 2019; 19:623-638. [PMID: 30666785 PMCID: PMC6519033 DOI: 10.1111/1755-0998.12994] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 12/13/2018] [Accepted: 01/11/2019] [Indexed: 11/27/2022]
Abstract
As recombination plays an important role in evolution, its estimation and the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating population recombination rates based on genotyping or sequence data that involves a sequential multiscale change point estimator. Our method also permits demography to be taken into account. It uses several summary statistics within a regression model fitted on suitable scenarios. Our proposed method is accurate, computationally fast, and provides a parsimonious solution by ensuring a type I error control against too many changes in the recombination rate. An application to human genome data suggests a good congruence between our estimated and experimentally identified hotspots. Our method is implemented in the R‐package LDJump, which is freely available at https://github.com/PhHermann/LDJump.
Collapse
Affiliation(s)
- Philipp Hermann
- Department of Applied Statistics, Johannes Kepler University Linz, Linz, Austria
| | - Angelika Heissl
- Institute of Biophysics, Johannes Kepler University Linz, Linz, Austria
| | | | - Andreas Futschik
- Department of Applied Statistics, Johannes Kepler University Linz, Linz, Austria
| |
Collapse
|