1
|
Soni V, Terbot JW, Jensen JD. Population genetic considerations regarding the interpretation of within-patient SARS-CoV-2 polymorphism data. Nat Commun 2024; 15:3240. [PMID: 38627371 PMCID: PMC11021480 DOI: 10.1038/s41467-024-46261-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 01/29/2024] [Indexed: 04/19/2024] Open
Affiliation(s)
- Vivak Soni
- Center for Evolution & Medicine, Arizona State University, School of Life Sciences, Tempe, AZ, USA
| | - John W Terbot
- Center for Evolution & Medicine, Arizona State University, School of Life Sciences, Tempe, AZ, USA
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Jeffrey D Jensen
- Center for Evolution & Medicine, Arizona State University, School of Life Sciences, Tempe, AZ, USA.
| |
Collapse
|
2
|
Soni V, Jensen JD. Temporal challenges in detecting balancing selection from population genomic data. G3 (Bethesda) 2024:jkae069. [PMID: 38551137 DOI: 10.1093/g3journal/jkae069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 12/21/2023] [Accepted: 03/19/2024] [Indexed: 04/28/2024]
Abstract
The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum (SFS)- and linkage disequilibrium (LD)-based methods under a variety of evolutionarily realistic null models. We find that whilst SFS-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, LD-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that SFS-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst LD-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g., population structure and admixture) as well as of alternative selective processes (e.g., partial selective sweeps).
Collapse
Affiliation(s)
- Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, 85281, USA
| | - Jeffrey D Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, 85281, USA
| |
Collapse
|
3
|
Soni V, Pfeifer SP, Jensen JD. The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects. Genome Biol Evol 2024; 16:evae004. [PMID: 38207127 PMCID: PMC10834165 DOI: 10.1093/gbe/evae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/12/2023] [Accepted: 01/07/2024] [Indexed: 01/13/2024] Open
Abstract
Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.
Collapse
Affiliation(s)
- Vivak Soni
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA
| | - Susanne P Pfeifer
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
4
|
Versoza CJ, Weiss S, Johal R, La Rosa B, Jensen JD, Pfeifer SP. Novel Insights into the Landscape of Crossover and Noncrossover Events in Rhesus Macaques (Macaca mulatta). Genome Biol Evol 2024; 16:evad223. [PMID: 38051960 PMCID: PMC10773715 DOI: 10.1093/gbe/evad223] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/04/2023] [Accepted: 11/28/2023] [Indexed: 12/07/2023] Open
Abstract
Meiotic recombination landscapes differ greatly between distantly and closely related taxa, populations, individuals, sexes, and even within genomes; however, the factors driving this variation are yet to be well elucidated. Here, we directly estimate contemporary crossover rates and, for the first time, noncrossover rates in rhesus macaques (Macaca mulatta) from four three-generation pedigrees comprising 32 individuals. We further compare these results with historical, demography-aware, linkage disequilibrium-based recombination rate estimates. From paternal meioses in the pedigrees, 165 crossover events with a median resolution of 22.3 kb were observed, corresponding to a male autosomal map length of 2,357 cM-approximately 15% longer than an existing linkage map based on human microsatellite loci. In addition, 85 noncrossover events with a mean tract length of 155 bp were identified-similar to the tract lengths observed in the only other two primates in which noncrossovers have been studied to date, humans and baboons. Consistent with observations in other placental mammals with PRDM9-directed recombination, crossover (and to a lesser extent noncrossover) events in rhesus macaques clustered in intergenic regions and toward the chromosomal ends in males-a pattern in broad agreement with the historical, sex-averaged recombination rate estimates-and evidence of GC-biased gene conversion was observed at noncrossover sites.
Collapse
Affiliation(s)
- Cyril J Versoza
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Sarah Weiss
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Ravneet Johal
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Bruno La Rosa
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
5
|
Soni V, Pfeifer SP, Jensen JD. The effects of mutation and recombination rate heterogeneity on the inference of demography and the distribution of fitness effects. bioRxiv 2023:2023.11.11.566703. [PMID: 38014252 PMCID: PMC10680612 DOI: 10.1101/2023.11.11.566703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavour; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modelled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination prior to utilizing population genomic data to quantify the effects of genetic drift (i.e., as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modelled in downstream inference.
Collapse
Affiliation(s)
- Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine
| | - Susanne P. Pfeifer
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine
| | - Jeffrey D. Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine
| |
Collapse
|
6
|
Terbot JW, Cooper BS, Good JM, Jensen JD. A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2. Genome Biol Evol 2023; 15:evad204. [PMID: 37950882 PMCID: PMC10664409 DOI: 10.1093/gbe/evad204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/31/2023] [Accepted: 11/07/2023] [Indexed: 11/13/2023] Open
Abstract
The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.
Collapse
Affiliation(s)
- John W Terbot
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, Arizona, USA
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | - Brandon S Cooper
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | - Jeffrey M Good
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, Arizona, USA
| |
Collapse
|
7
|
Soni V, Johri P, Jensen JD. Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models. Evolution 2023; 77:2113-2127. [PMID: 37395482 PMCID: PMC10547124 DOI: 10.1093/evolut/qpad120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/15/2023] [Accepted: 06/30/2023] [Indexed: 07/04/2023]
Abstract
The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.
Collapse
Affiliation(s)
- Vivak Soni
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| |
Collapse
|
8
|
Moström MJ, Yu S, Tran D, Saccoccio FM, Versoza CJ, Malouli D, Mirza A, Valencia S, Gilbert M, Blair RV, Hansen S, Barry P, Früh K, Jensen JD, Pfeifer SP, Kowalik TF, Permar SR, Kaur A. Protective effect of pre-existing natural immunity in a nonhuman primate reinfection model of congenital cytomegalovirus infection. PLoS Pathog 2023; 19:e1011646. [PMID: 37796819 PMCID: PMC10553354 DOI: 10.1371/journal.ppat.1011646] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 08/29/2023] [Indexed: 10/07/2023] Open
Abstract
Congenital cytomegalovirus (cCMV) is the leading infectious cause of neurologic defects in newborns with particularly severe sequelae in the setting of primary CMV infection in the first trimester of pregnancy. The majority of cCMV cases worldwide occur after non-primary infection in CMV-seropositive women; yet the extent to which pre-existing natural CMV-specific immunity protects against CMV reinfection or reactivation during pregnancy remains ill-defined. We previously reported on a novel nonhuman primate model of cCMV in rhesus macaques where 100% placental transmission and 83% fetal loss were seen in CD4+ T lymphocyte-depleted rhesus CMV (RhCMV)-seronegative dams after primary RhCMV infection. To investigate the protective effect of preconception maternal immunity, we performed reinfection studies in CD4+ T lymphocyte-depleted RhCMV-seropositive dams inoculated in late first / early second trimester gestation with RhCMV strains 180.92 (n = 2), or RhCMV UCD52 and FL-RhCMVΔRh13.1/SIVgag, a wild-type-like RhCMV clone with SIVgag inserted as an immunological marker, administered separately (n = 3). An early transient increase in circulating monocytes followed by boosting of the pre-existing RhCMV-specific CD8+ T lymphocyte and antibody response was observed in the reinfected dams but not in control CD4+ T lymphocyte-depleted dams. Emergence of SIV Gag-specific CD8+ T lymphocyte responses in macaques inoculated with the FL-RhCMVΔRh13.1/SIVgag virus confirmed reinfection. Placental transmission was detected in only one of five reinfected dams and there were no adverse fetal sequelae. Viral whole genome, short-read, deep sequencing analysis confirmed transmission of both reinfection RhCMV strains across the placenta with ~30% corresponding to FL-RhCMVΔRh13.1/SIVgag and ~70% to RhCMV UCD52, consistent with the mixed human CMV infections reported in infants with cCMV. Our data showing reduced placental transmission and absence of fetal loss after non-primary as opposed to primary infection in CD4+ T lymphocyte-depleted dams indicates that preconception maternal CMV-specific CD8+ T lymphocyte and/or humoral immunity can protect against cCMV infection.
Collapse
Affiliation(s)
- Matilda J. Moström
- Tulane National Primate Research Center, Tulane University, Covington, Louisiana, United States of America
| | - Shan Yu
- Tulane National Primate Research Center, Tulane University, Covington, Louisiana, United States of America
| | - Dollnovan Tran
- Tulane National Primate Research Center, Tulane University, Covington, Louisiana, United States of America
| | - Frances M. Saccoccio
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, United States of America
| | - Cyril J. Versoza
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Daniel Malouli
- Oregon Health and Sciences University, Beaverton, Oregon, United States of America
| | - Anne Mirza
- University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America
| | - Sarah Valencia
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, United States of America
| | - Margaret Gilbert
- Tulane National Primate Research Center, Tulane University, Covington, Louisiana, United States of America
| | - Robert V. Blair
- Tulane National Primate Research Center, Tulane University, Covington, Louisiana, United States of America
| | - Scott Hansen
- Oregon Health and Sciences University, Beaverton, Oregon, United States of America
| | - Peter Barry
- University of California, Davis, California, United States of America
| | - Klaus Früh
- Oregon Health and Sciences University, Beaverton, Oregon, United States of America
| | - Jeffrey D. Jensen
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Susanne P. Pfeifer
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Timothy F. Kowalik
- University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America
| | - Sallie R. Permar
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, United States of America
- Weill Cornell Medicine, New York, New York State, United States of America
| | - Amitinder Kaur
- Tulane National Primate Research Center, Tulane University, Covington, Louisiana, United States of America
| |
Collapse
|
9
|
Terbot JW, Cooper BS, Good JM, Jensen JD. A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2. bioRxiv 2023:2023.07.13.548462. [PMID: 37503016 PMCID: PMC10370031 DOI: 10.1101/2023.07.13.548462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (~5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.
Collapse
Affiliation(s)
- John W Terbot
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Brandon S. Cooper
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey M. Good
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey D. Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| |
Collapse
|
10
|
Soni V, Johri P, Jensen JD. Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models. bioRxiv 2023:2023.06.15.545166. [PMID: 37398347 PMCID: PMC10312679 DOI: 10.1101/2023.06.15.545166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong. Teaser Text Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.
Collapse
Affiliation(s)
- Vivak Soni
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Present address: Department of Biology, Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | | |
Collapse
|
11
|
Johri P, Pfeifer SP, Jensen JD. Developing an evolutionary baseline model for humans: jointly inferring purifying selection with population history. Mol Biol Evol 2023; 40:7147633. [PMID: 37128989 DOI: 10.1093/molbev/msad100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 05/03/2023] Open
Abstract
Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics - including quantifying the relative contributions of adaptive vs. non-adaptive processes - but it is also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection (e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome (i.e., purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, while strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | | | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
12
|
Howell AA, Terbot Ii JW, Soni V, Johri P, Jensen JD, Pfeifer SP. Developing an appropriate evolutionary baseline model for the study of human cytomegalovirus. Genome Biol Evol 2023; 15:7128054. [PMID: 37071785 PMCID: PMC10139446 DOI: 10.1093/gbe/evad059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 04/05/2023] [Accepted: 04/09/2023] [Indexed: 04/20/2023] Open
Abstract
Human cytomegalovirus (HCMV) represents a major threat to human health, contributing to both birth defects in neonates as well as organ transplant failure and opportunistic infections in immunocompromised individuals. HCMV exhibits considerable inter- and intra-host diversity, which likely influences the pathogenicity of the virus. Therefore, understanding the relative contributions of various evolutionary forces in shaping patterns of variation is of critical importance both mechanistically as well as clinically. Herein we present the individual components of an evolutionary baseline model for HCMV, with a particular focus on congenital infections for the sake of illustration - including mutation and recombination rates, the distribution of fitness effects, infection dynamics, as well as compartmentalization - and describe the current state of knowledge of each. By building this baseline model, researchers will be able to better describe the range of possible evolutionary scenarios contributing to observed variation, as well as improve power and reduce false-positive rates when scanning for adaptive mutations in the HCMV genome.
Collapse
Affiliation(s)
- Abigail A Howell
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Phoenix, Arizona, USA
| | - John W Terbot Ii
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Phoenix, Arizona, USA
- University of Montana, Division of Biological Sciences, Missoula, Montana, USA
| | - Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Phoenix, Arizona, USA
| | - Parul Johri
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Phoenix, Arizona, USA
| | - Jeffrey D Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Phoenix, Arizona, USA
| | - Susanne P Pfeifer
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Phoenix, Arizona, USA
| |
Collapse
|
13
|
Johri P, Pfeifer SP, Jensen JD. Developing an evolutionary baseline model for humans: jointly inferring purifying selection with population history. bioRxiv 2023:2023.04.11.536488. [PMID: 37090533 PMCID: PMC10120674 DOI: 10.1101/2023.04.11.536488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics - including quantifying the relative contributions of adaptive vs. non-adaptive processes - but it is also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection ( e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome ( i.e. , purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, while strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.
Collapse
|
14
|
Moström M, Yu S, Tran D, Saccoccio F, Versoza CJ, Malouli D, Mirza A, Valencia S, Gilbert M, Blair R, Hansen S, Barry P, Früh K, Jensen JD, Pfeifer SP, Kowalik TF, Permar SR, Kaur A. Protective effect of pre-existing natural immunity in a nonhuman primate reinfection model of congenital cytomegalovirus infection. bioRxiv 2023:2023.04.10.536057. [PMID: 37090643 PMCID: PMC10120644 DOI: 10.1101/2023.04.10.536057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Congenital cytomegalovirus (cCMV) is the leading infectious cause of neurologic defects in newborns with particularly severe sequelae in the setting of primary CMV infection in the first trimester of pregnancy. The majority of cCMV cases worldwide occur after non-primary infection in CMV-seropositive women; yet the extent to which pre-existing natural CMV-specific immunity protects against CMV reinfection or reactivation during pregnancy remains ill-defined. We previously reported on a novel nonhuman primate model of cCMV in rhesus macaques where 100% placental transmission and 83% fetal loss were seen in CD4 + T lymphocyte-depleted rhesus CMV (RhCMV)-seronegative dams after primary RhCMV infection. To investigate the protective effect of preconception maternal immunity, we performed reinfection studies in CD4+ T lymphocyte-depleted RhCMV-seropositive dams inoculated in late first / early second trimester gestation with RhCMV strains 180.92 ( n =2), or RhCMV UCD52 and FL-RhCMVΔRh13.1/SIV gag , a wild-type-like RhCMV clone with SIV gag inserted as an immunological marker ( n =3). An early transient increase in circulating monocytes followed by boosting of the pre-existing RhCMV-specific CD8+ T lymphocyte and antibody response was observed in the reinfected dams but not in control CD4+ T lymphocyte-depleted dams. Emergence of SIV Gag-specific CD8+ T lymphocyte responses in macaques inoculated with the FL-RhCMVΔRh13.1/SIV gag virus confirmed reinfection. Placental transmission was detected in only one of five reinfected dams and there were no adverse fetal sequelae. Viral whole genome, short-read, deep sequencing analysis confirmed transmission of both reinfection RhCMV strains across the placenta with ∼30% corresponding to FL-RhCMVΔRh13.1/SIV gag and ∼70% to RhCMV UCD52, consistent with the mixed human CMV infections reported in infants with cCMV. Our data showing reduced placental transmission and absence of fetal loss after non-primary as opposed to primary infection in CD4+ T lymphocyte-depleted dams indicates that preconception maternal CMV-specific CD8+ T lymphocyte and/or humoral immunity can protect against cCMV infection. Author Summary Globally, pregnancies in CMV-seropositive women account for the majority of cases of congenital CMV infection but the immune responses needed for protection against placental transmission in mothers with non-primary infection remains unknown. Recently, we developed a nonhuman primate model of primary rhesus CMV (RhCMV) infection in which placental transmission and fetal loss occurred in RhCMV-seronegative CD4+ T lymphocyte-depleted macaques. By conducting similar studies in RhCMV-seropositive dams, we demonstrated the protective effect of pre-existing natural CMV-specific CD8+ T lymphocytes and humoral immunity against congenital CMV after reinfection. A 5-fold reduction in congenital transmission and complete protection against fetal loss was observed in dams with pre-existing immunity compared to primary CMV in this model. Our study is the first formal demonstration in a relevant model of human congenital CMV that natural pre-existing CMV-specific maternal immunity can limit congenital CMV transmission and its sequelae. The nonhuman primate model of non-primary congenital CMV will be especially relevant to studying immune requirements of a maternal vaccine for women in high CMV seroprevalence areas at risk of repeated CMV reinfections during pregnancy.
Collapse
Affiliation(s)
- Matilda Moström
- Tulane National Primate Research Center, Tulane University, Covington LA
| | - Shan Yu
- Tulane National Primate Research Center, Tulane University, Covington LA
| | - Dollnovan Tran
- Tulane National Primate Research Center, Tulane University, Covington LA
| | | | - Cyril J. Versoza
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, AZ
| | | | - Anne Mirza
- University of Massachusetts Chan Medical School, Worcester, MA
| | - Sarah Valencia
- Duke Human Vaccine Institute, Duke University, Durham, NC
| | - Margaret Gilbert
- Tulane National Primate Research Center, Tulane University, Covington LA
| | - Robert Blair
- Tulane National Primate Research Center, Tulane University, Covington LA
| | - Scott Hansen
- Oregon Health and Sciences University, Beaverton, OR
| | | | - Klaus Früh
- Oregon Health and Sciences University, Beaverton, OR
| | - Jeffrey D. Jensen
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, AZ
| | - Susanne P. Pfeifer
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, AZ
| | | | - Sallie R. Permar
- Duke Human Vaccine Institute, Duke University, Durham, NC
- Weill Cornell Medicine, New York, NY
| | - Amitinder Kaur
- Tulane National Primate Research Center, Tulane University, Covington LA
| |
Collapse
|
15
|
Terbot JW, Johri P, Liphardt SW, Soni V, Pfeifer SP, Cooper BS, Good JM, Jensen JD. Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples. PLoS Pathog 2023; 19:e1011265. [PMID: 37018331 PMCID: PMC10075409 DOI: 10.1371/journal.ppat.1011265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023] Open
Abstract
Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.
Collapse
Affiliation(s)
- John W Terbot
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Parul Johri
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Schuyler W Liphardt
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Susanne P Pfeifer
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Brandon S Cooper
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey M Good
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey D Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| |
Collapse
|
16
|
Freund F, Kerdoncuff E, Matuszewski S, Lapierre M, Hildebrandt M, Jensen JD, Ferretti L, Lambert A, Sackton TB, Achaz G. Interpreting the pervasive observation of U-shaped Site Frequency Spectra. PLoS Genet 2023; 19:e1010677. [PMID: 36952570 PMCID: PMC10072462 DOI: 10.1371/journal.pgen.1010677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 04/04/2023] [Accepted: 02/22/2023] [Indexed: 03/25/2023] Open
Abstract
The standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.
Collapse
Affiliation(s)
- Fabian Freund
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany
- Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Elise Kerdoncuff
- Department of Genetics, University of California, Berkeley, California, United States of America
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
| | | | - Marguerite Lapierre
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
| | | | - Jeffrey D Jensen
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Luca Ferretti
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Amaury Lambert
- Institut de Biologie de l'ENS (IBENS), École Normale Supérieure, Paris, France
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
| | - Timothy B Sackton
- Éco-anthropologie, Muséum National d'Histoire Naturelle, Université Paris-Cité, Paris, France
| | - Guillaume Achaz
- Informatics Group, Harvard University, Cambridge, Massachusetts, United States of America
- SMILE group, Center for Interdisciplinary Research in Biology (CIRB), Collège de France, Paris, France
| |
Collapse
|
17
|
Ghafoor S, Santos J, Versoza CJ, Jensen JD, Pfeifer SP. The Impact of Sample Size and Population History on Observed Mutational Spectra: A Case Study in Human and Chimpanzee Populations. Genome Biol Evol 2023; 15:7039701. [PMID: 36790107 PMCID: PMC9989333 DOI: 10.1093/gbe/evad019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 01/20/2023] [Accepted: 02/08/2023] [Indexed: 02/16/2023] Open
Abstract
Recent studies have highlighted variation in the mutational spectra among human populations as well as closely related hominoids-yet little remains known about the genetic and nongenetic factors driving these rate changes across the genome. Pinpointing the root causes of these differences is an important endeavor that requires careful comparative analyses of population-specific mutational landscapes at both broad and fine genomic scales. However, several factors can confound such analyses. Although previous studies have shown that technical artifacts, such as sequencing errors and batch effects, can contribute to observed mutational shifts, other potentially confounding parameters have received less attention thus far. Using population genetic simulations of human and chimpanzee populations as an illustrative example, we here show that the sample size required for robust inference of mutational spectra depends on the population-specific demographic history. As a consequence, the power to detect rate changes is high in certain hominoid populations while, for others, currently available sample sizes preclude analyses at fine genomic scales.
Collapse
Affiliation(s)
- Suhail Ghafoor
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - João Santos
- School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Cyril J Versoza
- School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Susanne P Pfeifer
- School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
18
|
Jensen JD. Population genetic concerns related to the interpretation of empirical outliers and the neglect of common evolutionary processes. Heredity (Edinb) 2023; 130:109-110. [PMID: 36829044 PMCID: PMC9981695 DOI: 10.1038/s41437-022-00575-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/27/2022] [Accepted: 10/28/2022] [Indexed: 02/26/2023] Open
Affiliation(s)
- Jeffrey D Jensen
- School of Life Science, Arizona State University, Tempe, AZ, USA.
| |
Collapse
|
19
|
Abstract
It has recently been proposed that lower mutation rates in gene bodies compared with upstream and downstream sequences in Arabidopsis thaliana are the result of an "adaptive" modification of the rate of beneficial and deleterious mutations in these functional regions. This claim was based both on analyses of mutation accumulation lines and on population genomics data. Here, we show that several questionable assumptions were used in the population genomics analyses. In particular, we demonstrate that the difference between gene bodies and less selectively constrained sequences in the magnitude of Tajima's D can in principle be explained by the presence of sites subject to purifying selection and does not require lower mutation rates in regions experiencing selective constraints.
Collapse
Affiliation(s)
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, 85281 AZ
| |
Collapse
|
20
|
Hager ER, Harringmeyer OS, Wooldridge TB, Theingi S, Gable JT, McFadden S, Neugeboren B, Turner KM, Jensen JD, Hoekstra HE. A chromosomal inversion contributes to divergence in multiple traits between deer mouse ecotypes. Science 2022; 377:399-405. [PMID: 35862520 DOI: 10.1126/science.abg0718] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
How locally adapted ecotypes are established and maintained within a species is a long-standing question in evolutionary biology. Using forest and prairie ecotypes of deer mice (Peromyscus maniculatus), we characterized the genetic basis of variation in two defining traits-tail length and coat color-and discovered a 41-megabase chromosomal inversion linked to both. The inversion frequency is 90% in the dark, long-tailed forest ecotype; decreases across a habitat transition; and is absent from the light, short-tailed prairie ecotype. We implicate divergent selection in maintaining the inversion at frequencies observed in the wild, despite high levels of gene flow, and explore fitness benefits that arise from suppressed recombination within the inversion. We uncover a key role for a large, previously uncharacterized inversion in the evolution and maintenance of classic mammalian ecotypes.
Collapse
Affiliation(s)
- Emily R Hager
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Olivia S Harringmeyer
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - T Brock Wooldridge
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Shunn Theingi
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Jacob T Gable
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Sade McFadden
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Beverly Neugeboren
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Kyle M Turner
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Hopi E Hoekstra
- Department of Molecular and Cellular Biology, Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, and Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| |
Collapse
|
21
|
Abstract
We discuss the genetic, demographic, and selective forces that are likely to be at play in restricting observed levels of DNA sequence variation in natural populations to a much smaller range of values than would be expected from the distribution of census population sizes alone-Lewontin's Paradox. While several processes that have previously been strongly emphasized must be involved, including the effects of direct selection and genetic hitchhiking, it seems unlikely that they are sufficient to explain this observation without contributions from other factors. We highlight a potentially important role for the less-appreciated contribution of population size change; specifically, the likelihood that many species and populations may be quite far from reaching the relatively high equilibrium diversity values that would be expected given their current census sizes.
Collapse
Affiliation(s)
- Brian Charlesworth
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
22
|
Charlesworth B, Jensen JD. Some complexities in interpreting apparent effects of hitchhiking: A commentary on Gompert et al. (2022). Mol Ecol 2022; 31:4440-4443. [PMID: 35778972 DOI: 10.1111/mec.16573] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 12/25/2022]
Abstract
We write to address recent claims by regarding the potentially important and underappreciated phenomena of "indirect selection," the observation that neutral regions may be affected by natural selection. We argue both that this phenomenon-generally known as genetic hitchhiking-is neither new nor poorly studied, and that the patterns described by the authors have multiple alternative explanations.
Collapse
Affiliation(s)
- Brian Charlesworth
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| |
Collapse
|
23
|
Johri P, Eyre-Walker A, Gutenkunst RN, Lohmueller KE, Jensen JD. On the prospect of achieving accurate joint estimation of selection with population history. Genome Biol Evol 2022; 14:6604401. [PMID: 35675379 PMCID: PMC9254643 DOI: 10.1093/gbe/evac088] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/02/2022] [Indexed: 11/15/2022] Open
Abstract
As both natural selection and population history can affect genome-wide patterns of variation, disentangling the contributions of each has remained as a major challenge in population genetics. We here discuss historical and recent progress towards this goal—highlighting theoretical and computational challenges that remain to be addressed, as well as inherent difficulties in dealing with model complexity and model violations—and offer thoughts on potentially fruitful next steps.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | | | - Ryan N Gutenkunst
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA.,Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
24
|
Johri P, Aquadro CF, Beaumont M, Charlesworth B, Excoffier L, Eyre-Walker A, Keightley PD, Lynch M, McVean G, Payseur BA, Pfeifer SP, Stephan W, Jensen JD. Recommendations for improving statistical inference in population genomics. PLoS Biol 2022; 20:e3001669. [PMID: 35639797 PMCID: PMC9154105 DOI: 10.1371/journal.pbio.3001669] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Charles F. Aquadro
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America
| | - Mark Beaumont
- School of Biological Sciences, University of Bristol, Bristol, United Kingdom
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne, Switzerland
| | - Adam Eyre-Walker
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
| | - Peter D. Keightley
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael Lynch
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | - Gil McVean
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Bret A. Payseur
- Laboratory of Genetics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Susanne P. Pfeifer
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | | | - Jeffrey D. Jensen
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- * E-mail:
| |
Collapse
|
25
|
Sabin S, Morales-Arce AY, Pfeifer SP, Jensen JD. The impact of frequently neglected model violations on bacterial recombination rate estimation: a case study in Mycobacterium canettii and Mycobacterium tuberculosis. G3 (Bethesda) 2022; 12:jkac055. [PMID: 35253851 PMCID: PMC9073693 DOI: 10.1093/g3journal/jkac055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 02/28/2022] [Indexed: 12/04/2022]
Abstract
Mycobacterium canettii is a causative agent of tuberculosis in humans, along with the members of the Mycobacterium tuberculosis complex. Frequently used as an outgroup to the M. tuberculosis complex in phylogenetic analyses, M. canettii is thought to offer the best proxy for the progenitor species that gave rise to the complex. Here, we leverage whole-genome sequencing data and biologically relevant population genomic models to compare the evolutionary dynamics driving variation in the recombining M. canettii with that in the nonrecombining M. tuberculosis complex, and discuss differences in observed genomic diversity in the light of expected levels of Hill-Robertson interference. In doing so, we highlight the methodological challenges of estimating recombination rates through traditional population genetic approaches using sequences called from populations of microorganisms and evaluate the likely mis-inference that arises owing to a neglect of common model violations including purifying selection, background selection, progeny skew, and population size change. In addition, we compare performance when full within-host polymorphism data are utilized, versus the more common approach of basing analyses on within-host consensus sequences.
Collapse
Affiliation(s)
- Susanna Sabin
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Ana Y Morales-Arce
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Susanne P Pfeifer
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
| | - Jeffrey D Jensen
- Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA
| |
Collapse
|
26
|
Morales-Arce AY, Johri P, Jensen JD. Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies. Heredity (Edinb) 2022; 128:79-87. [PMID: 34987185 PMCID: PMC8728706 DOI: 10.1038/s41437-021-00493-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 11/19/2022] Open
Abstract
We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.
Collapse
Affiliation(s)
- Ana Y. Morales-Arce
- grid.215654.10000 0001 2151 2636Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ USA
| | - Parul Johri
- grid.215654.10000 0001 2151 2636Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ USA
| | - Jeffrey D. Jensen
- grid.215654.10000 0001 2151 2636Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ USA
| |
Collapse
|
27
|
Abstract
The ability to accurately identify and quantify genetic signatures associated with soft selective sweeps based on patterns of nucleotide variation has remained controversial. We here provide counter viewpoints to recent publications in PLOS Genetics that have argued not only for the statistical identifiability of soft selective sweeps, but also for their pervasive evolutionary role in both Drosophila and HIV populations. We present evidence that these claims owe to a lack of consideration of competing evolutionary models, unjustified interpretations of empirical outliers, as well as to new definitions of the processes themselves. Our results highlight the dangers of fitting evolutionary models based on hypothesized and episodic processes without properly first considering common processes and, more generally, of the tendency in certain research areas to view pervasive positive selection as a foregone conclusion.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| | | | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
| |
Collapse
|
28
|
Abstract
Patterns of variation and evolution at a given site in a genome can be strongly influenced by the effects of selection at genetically linked sites. In particular, the recombination rates of genomic regions correlate with their amount of within-population genetic variability, the degree to which the frequency distributions of DNA sequence variants differ from their neutral expectations, and the levels of adaptation of their functional components. We review the major population genetic processes that are thought to lead to these patterns, focusing on their effects on patterns of variability: selective sweeps, background selection, associative overdominance, and Hill–Robertson interference among deleterious mutations. We emphasize the difficulties in distinguishing among the footprints of these processes and disentangling them from the effects of purely demographic factors such as population size changes. We also discuss how interactions between selective and demographic processes can significantly affect patterns of variability within genomes.
Collapse
Affiliation(s)
- Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, United Kingdom
| | - Jeffrey D. Jensen
- School of Life Sciences, Arizona State University, Tempe, Arizona 85281, USA
| |
Collapse
|
29
|
Johri P, Charlesworth B, Howell EK, Lynch M, Jensen JD. Revisiting the Notion of Deleterious Sweeps. Genetics 2021; 219:6298596. [PMID: 34125884 PMCID: PMC9101445 DOI: 10.1093/genetics/iyab094] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 06/08/2021] [Indexed: 11/14/2022] Open
Abstract
It has previously been shown that, conditional on its fixation, the time to fixation of a semi-dominant deleterious autosomal mutation in a randomly mating population is the same as that of an advantageous mutation. This result implies that deleterious mutations could generate selective sweep-like effects. Although their fixation probabilities greatly differ, the much larger input of deleterious relative to beneficial mutations suggests that this phenomenon could be important. We here examine how the fixation of mildly deleterious mutations affects levels and patterns of polymorphism at linked sites - both in the presence and absence of interference amongst deleterious mutations - and how this class of sites may contribute to divergence between-populations and species. We find that, while deleterious fixations are unlikely to represent a significant proportion of outliers in polymorphism-based genomic scans within populations, minor shifts in the frequencies of deleterious mutations can influence the proportions of private variants and the value of FST after a recent population split. As sites subject to deleterious mutations are necessarily found in functional genomic regions, interpretations in terms of recurrent positive selection may require reconsideration.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Emma K Howell
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Michael Lynch
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States.,Center for Mechanisms of Evolution, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, United States
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| |
Collapse
|
30
|
Wang HY, Valencia SM, Pfeifer SP, Jensen JD, Kowalik TF, Permar SR. Common Polymorphisms in the Glycoproteins of Human Cytomegalovirus and Associated Strain-Specific Immunity. Viruses 2021; 13:v13061106. [PMID: 34207868 PMCID: PMC8227702 DOI: 10.3390/v13061106] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/04/2021] [Accepted: 06/07/2021] [Indexed: 12/18/2022] Open
Abstract
Human cytomegalovirus (HCMV), one of the most prevalent viruses across the globe, is a common cause of morbidity and mortality for immunocompromised individuals. Recent clinical observations have demonstrated that mixed strain infections are common and may lead to more severe disease progression. This clinical observation illustrates the complexity of the HCMV genome and emphasizes the importance of taking a population-level view of genotypic evolution. Here we review frequently sampled polymorphisms in the glycoproteins of HCMV, comparing the variable regions, and summarizing their corresponding geographic distributions observed to date. The related strain-specific immunity, including neutralization activity and antigen-specific cellular immunity, is also discussed. Given that these glycoproteins are common targets for vaccine design and anti-viral therapies, this observed genetic variation represents an important resource for future efforts to combat HCMV infections.
Collapse
Affiliation(s)
- Hsuan-Yuan Wang
- Department of Pediatrics, Weill Cornell Medicine, New York, NY 10065, USA;
- Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC 27710, USA;
| | - Sarah M. Valencia
- Duke Human Vaccine Institute, Duke University Medical Center, Durham, NC 27710, USA;
| | - Susanne P. Pfeifer
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; (S.P.P.); (J.D.J.)
| | - Jeffrey D. Jensen
- Center for Evolution & Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA; (S.P.P.); (J.D.J.)
| | - Timothy F. Kowalik
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA 01655, USA;
| | - Sallie R. Permar
- Department of Pediatrics, Weill Cornell Medicine, New York, NY 10065, USA;
- Correspondence: ; Tel.: +1-212-746-4111
| |
Collapse
|
31
|
Clemente F, Unterländer M, Dolgova O, Amorim CEG, Coroado-Santos F, Neuenschwander S, Ganiatsou E, Cruz Dávalos DI, Anchieri L, Michaud F, Winkelbach L, Blöcher J, Arizmendi Cárdenas YO, Sousa da Mota B, Kalliga E, Souleles A, Kontopoulos I, Karamitrou-Mentessidi G, Philaniotou O, Sampson A, Theodorou D, Tsipopoulou M, Akamatis I, Halstead P, Kotsakis K, Urem-Kotsou D, Panagiotopoulos D, Ziota C, Triantaphyllou S, Delaneau O, Jensen JD, Moreno-Mayar JV, Burger J, Sousa VC, Lao O, Malaspinas AS, Papageorgopoulou C. The genomic history of the Aegean palatial civilizations. Cell 2021; 184:2565-2586.e21. [PMID: 33930288 PMCID: PMC8127963 DOI: 10.1016/j.cell.2021.03.039] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 09/17/2020] [Accepted: 03/18/2021] [Indexed: 12/30/2022]
Abstract
The Cycladic, the Minoan, and the Helladic (Mycenaean) cultures define the Bronze Age (BA) of Greece. Urbanism, complex social structures, craft and agricultural specialization, and the earliest forms of writing characterize this iconic period. We sequenced six Early to Middle BA whole genomes, along with 11 mitochondrial genomes, sampled from the three BA cultures of the Aegean Sea. The Early BA (EBA) genomes are homogeneous and derive most of their ancestry from Neolithic Aegeans, contrary to earlier hypotheses that the Neolithic-EBA cultural transition was due to massive population turnover. EBA Aegeans were shaped by relatively small-scale migration from East of the Aegean, as evidenced by the Caucasus-related ancestry also detected in Anatolians. In contrast, Middle BA (MBA) individuals of northern Greece differ from EBA populations in showing ∼50% Pontic-Caspian Steppe-related ancestry, dated at ca. 2,600-2,000 BCE. Such gene flow events during the MBA contributed toward shaping present-day Greek genomes.
Collapse
Affiliation(s)
- Florian Clemente
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Martina Unterländer
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece; Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Olga Dolgova
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028 Barcelona, Spain
| | - Carlos Eduardo G Amorim
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Francisco Coroado-Santos
- CE3C, Centre for Ecology, Evolution and Environmental Changes, Faculty of Sciences of the University of Lisbon, 1749-016 Lisbon, Portugal
| | - Samuel Neuenschwander
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Vital-IT, Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Elissavet Ganiatsou
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Diana I Cruz Dávalos
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Lucas Anchieri
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Frédéric Michaud
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Laura Winkelbach
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Jens Blöcher
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Yami Ommar Arizmendi Cárdenas
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Bárbara Sousa da Mota
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Eleni Kalliga
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Angelos Souleles
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Ioannis Kontopoulos
- Center for GeoGenetics, GLOBE Institute, University of Copenhagen, 1350 Copenhagen, Denmark
| | | | - Olga Philaniotou
- Ephor Emerita of Antiquities, Hellenic Ministry of Culture and Sports, 10682 Athens, Greece
| | - Adamantios Sampson
- Department of Mediterranean Studies, University of the Aegean, 85132 Rhodes, Greece
| | - Dimitra Theodorou
- Ephorate of Antiquities of Kozani, Hellenic Ministry of Culture and Sports, 50004 Kozani, Greece
| | - Metaxia Tsipopoulou
- Ephor Emerita of Antiquities, Hellenic Ministry of Culture and Sports, 10682 Athens, Greece
| | - Ioannis Akamatis
- Department of History and Archaeology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Paul Halstead
- Department of Archaeology, University of Sheffield, Minalloy House, 10-16 Regent St., Sheffield S1 3NJ, UK
| | - Kostas Kotsakis
- Department of History and Archaeology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Dushka Urem-Kotsou
- Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece
| | - Diamantis Panagiotopoulos
- Institute of Classical Archaeology, University of Heidelberg, Marstallhof 4, 69117 Heidelberg, Germany
| | - Christina Ziota
- Ephorate of Antiquities of Florina, Hellenic Ministry of Culture and Sports, 53100 Florina, Greece
| | - Sevasti Triantaphyllou
- Department of History and Archaeology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Olivier Delaneau
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - J Víctor Moreno-Mayar
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; Center for GeoGenetics, GLOBE Institute, University of Copenhagen, 1350 Copenhagen, Denmark; National Institute of Genomic Medicine (INMEGEN), 14610 Mexico City, Mexico
| | - Joachim Burger
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution, Johannes Gutenberg University of Mainz, 55099 Mainz, Germany
| | - Vitor C Sousa
- CE3C, Centre for Ecology, Evolution and Environmental Changes, Faculty of Sciences of the University of Lisbon, 1749-016 Lisbon, Portugal
| | - Oscar Lao
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Anna-Sapfo Malaspinas
- Department of Computational Biology, University of Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
| | - Christina Papageorgopoulou
- Laboratory of Physical Anthropology, Department of History and Ethnology, Democritus University of Thrace, 69100 Komotini, Greece.
| |
Collapse
|
32
|
Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD. The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects. Mol Biol Evol 2021; 38:2986-3003. [PMID: 33591322 PMCID: PMC8233493 DOI: 10.1093/molbev/msab050] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Kellen Riall
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Hannes Becher
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
33
|
Johri P, Riall K, Becher H, Excoffier L, Charlesworth B, Jensen JD. The impact of purifying and background selection on the inference of population history: problems and prospects. bioRxiv 2021. [PMID: 33501439 PMCID: PMC7836109 DOI: 10.1101/2020.04.28.066365] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Kellen Riall
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| | - Hannes Becher
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Laurent Excoffier
- Institute of Ecology and Evolution, University of Berne, Berne 3012, Switzerland.,Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA
| |
Collapse
|
34
|
Jensen JD, Stikeleather RA, Kowalik TF, Lynch M. Imposed mutational meltdown as an antiviral strategy. Evolution 2020; 74:2549-2559. [PMID: 33047822 PMCID: PMC7993354 DOI: 10.1111/evo.14107] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 09/30/2020] [Accepted: 10/10/2020] [Indexed: 12/25/2022]
Abstract
Following widespread infections of the most recent coronavirus known to infect humans, SARS‐CoV‐2, attention has turned to potential therapeutic options. With no drug or vaccine yet approved, one focal point of research is to evaluate the potential value of repurposing existing antiviral treatments, with the logical strategy being to identify at least a short‐term intervention to prevent within‐patient progression, while long‐term vaccine strategies unfold. Here, we offer an evolutionary/population‐genetic perspective on one approach that may overwhelm the capacity for pathogen defense (i.e., adaptation) – induced mutational meltdown – providing an overview of key concepts, review of previous theoretical and experimental work of relevance, and guidance for future research. Applied with appropriate care, including target specificity, induced mutational meltdown may provide a general, rapidly implemented approach for the within‐patient eradication of a wide range of pathogens or other undesirable microorganisms.
Collapse
Affiliation(s)
- Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, Arizona, 85281.,Center for Evolution & Medicine, Arizona State University, Tempe, Arizona, 85281
| | - Ryan A Stikeleather
- Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, Arizona, 85281
| | - Timothy F Kowalik
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts, 01655
| | - Michael Lynch
- School of Life Sciences, Arizona State University, Tempe, Arizona, 85281.,Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, Arizona, 85281
| |
Collapse
|
35
|
Morales-Arce AY, Sabin SJ, Stone AC, Jensen JD. The population genomics of within-host Mycobacterium tuberculosis. Heredity (Edinb) 2020; 126:1-9. [PMID: 33060846 DOI: 10.1038/s41437-020-00377-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 10/02/2020] [Accepted: 10/03/2020] [Indexed: 11/09/2022] Open
Abstract
Recent progress in genomic sequencing from patient samples has allowed for the first detailed insight into the within-host genetic diversity of Mycobacterium tuberculosis (M.TB), revealing remarkably low levels of variation. While this has often been attributed to low mutation rates, other factors have been described, including resistance evolution (i.e., selective sweeps), widespread purifying and background selection, and, more recently, progeny skew. Here we review recent findings pertaining to the processes governing the evolutionary dynamics of M.TB, discuss their implications for improving our understanding of this important human pathogen, and make recommendations for future work. Significantly, this emerging evolutionary framework involving the joint estimation of demographic, selective, and reproductive processes is forming a new paradigm for the study of within-host pathogen evolution that will be widely applicable across organisms.
Collapse
Affiliation(s)
- Ana Y Morales-Arce
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.
| | - Susanna J Sabin
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Anne C Stone
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.,School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA
| | - Jeffrey D Jensen
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA. .,School of Life Sciences, Arizona State University, Tempe, AZ, USA.
| |
Collapse
|
36
|
Jones MR, Mills LS, Jensen JD, Good JM. The Origin and Spread of Locally Adaptive Seasonal Camouflage in Snowshoe Hares. Am Nat 2020; 196:316-332. [DOI: 10.1086/710022] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
|
37
|
Abstract
First inspired by the seminal work of Lewontin and Krakauer (1973. Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74(1):175-195.) and Maynard Smith and Haigh (1974. The hitch-hiking effect of a favourable gene. Genet Res. 23(1):23-35.), genomic scans for positive selection remain a widely utilized tool in modern population genomic analysis. Yet, the relative frequency and genomic impact of selective sweeps have remained a contentious point in the field for decades, largely owing to an inability to accurately identify their presence and quantify their effects-with current methodologies generally being characterized by low true-positive rates and/or high false-positive rates under many realistic demographic models. Most of these approaches are based on Wright-Fisher assumptions and the Kingman coalescent and generally rely on detecting outlier regions which do not conform to these neutral expectations. However, previous theoretical results have demonstrated that selective sweeps are well characterized by an alternative class of model known as the multiple-merger coalescent. Taken together, this suggests the possibility of not simply identifying regions which reject the Kingman, but rather explicitly testing the relative fit of a genomic window to the multiple-merger coalescent. We describe the advantages of such an approach, which owe to the branching structure differentiating selective and neutral models, and demonstrate improved power under certain demographic scenarios relative to a commonly used approach. However, regions of the demographic parameter space continue to exist in which neither this approach nor existing methodologies have sufficient power to detect selective sweeps.
Collapse
|
38
|
Jones MR, Mills LS, Jensen JD, Good JM. Convergent evolution of seasonal camouflage in response to reduced snow cover across the snowshoe hare range*. Evolution 2020; 74:2033-2045. [DOI: 10.1111/evo.13976] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 03/26/2020] [Accepted: 04/02/2020] [Indexed: 12/14/2022]
Affiliation(s)
- Matthew R. Jones
- Division of Biological Sciences University of Montana Missoula Montana 59812
| | - L. Scott Mills
- Wildlife Biology Program University of Montana Missoula Montana 59812
- Office of Research and Creative Scholarship University of Montana Missoula Montana 59812
| | - Jeffrey D. Jensen
- School of Life Sciences Arizona State University Tempe Arizona 85281
| | - Jeffrey M. Good
- Division of Biological Sciences University of Montana Missoula Montana 59812
- Wildlife Biology Program University of Montana Missoula Montana 59812
| |
Collapse
|
39
|
Johri P, Charlesworth B, Jensen JD. Toward an Evolutionarily Appropriate Null Model: Jointly Inferring Demography and Purifying Selection. Genetics 2020; 215:173-192. [PMID: 32152045 PMCID: PMC7198275 DOI: 10.1534/genetics.119.303002] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/05/2020] [Indexed: 01/27/2023] Open
Abstract
The question of the relative evolutionary roles of adaptive and nonadaptive processes has been a central debate in population genetics for nearly a century. While advances have been made in the theoretical development of the underlying models, and statistical methods for estimating their parameters from large-scale genomic data, a framework for an appropriate null model remains elusive. A model incorporating evolutionary processes known to be in constant operation, genetic drift (as modulated by the demographic history of the population) and purifying selection, is lacking. Without such a null model, the role of adaptive processes in shaping within- and between-population variation may not be accurately assessed. Here, we investigate how population size changes and the strength of purifying selection affect patterns of variation at "neutral" sites near functional genomic components. We propose a novel statistical framework for jointly inferring the contribution of the relevant selective and demographic parameters. By means of extensive performance analyses, we quantify the utility of the approach, identify the most important statistics for parameter estimation, and compare the results with existing methods. Finally, we reanalyze genome-wide population-level data from a Zambian population of Drosophila melanogaster, and find that it has experienced a much slower rate of population growth than was inferred when the effects of purifying selection were neglected. Our approach represents an appropriate null model, against which the effects of positive selection can be assessed.
Collapse
Affiliation(s)
- Parul Johri
- School of Life Sciences, Arizona State University, Tempe, Arizona 85287
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, EH9 3FL, United Kingdom
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, Arizona 85287
| |
Collapse
|
40
|
Morales-Arce AY, Harris RB, Stone AC, Jensen JD. Evaluating the contributions of purifying selection and progeny-skew in dictating within-host Mycobacterium tuberculosis evolution. Evolution 2020; 74:992-1001. [PMID: 32233086 DOI: 10.1111/evo.13954] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 03/08/2020] [Indexed: 12/28/2022]
Abstract
The within-host evolutionary dynamics of tuberculosis (TB) remain unclear, and underlying biological characteristics render standard population genetic approaches based upon the Wright-Fisher model largely inappropriate. In addition, the compact genome combined with an absence of recombination is expected to result in strong purifying selection effects. Thus, it is imperative to establish a biologically relevant evolutionary framework incorporating these factors in order to enable an accurate study of this important human pathogen. Further, such a model is critical for inferring fundamental evolutionary parameters related to patient treatment, including mutation rates and the severity of infection bottlenecks. We here implement such a model and infer the underlying evolutionary parameters governing within-patient evolutionary dynamics. Results demonstrate that the progeny skew associated with the clonal nature of TB severely reduces genetic diversity and that the neglect of this parameter in previous studies has led to significant mis-inference of mutation rates. As such, our results suggest an underlying de novo mutation rate that is considerably faster than previously inferred, and a progeny distribution differing significantly from Wright-Fisher assumptions. This inference represents a more appropriate evolutionary null model, against which the periodic effects of positive selection, associated with drug-resistance for example, may be better assessed.
Collapse
Affiliation(s)
- Ana Y Morales-Arce
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
| | - Rebecca B Harris
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA
| | - Anne C Stone
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA.,School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona, USA
| | - Jeffrey D Jensen
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, USA.,School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| |
Collapse
|
41
|
Jensen JD, Lynch M. Considering mutational meltdown as a potential SARS-CoV-2 treatment strategy. Heredity (Edinb) 2020; 124:619-620. [PMID: 32251365 PMCID: PMC7133120 DOI: 10.1038/s41437-020-0314-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 01/30/2023] Open
Affiliation(s)
- Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, USA.
| | - Michael Lynch
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| |
Collapse
|
42
|
Abstract
As one of the most commonly utilized organisms in the study of local adaptation, an accurate characterization of the demographic history of Drosophila melanogaster remains as an important research question. This owes both to the inherent interest in characterizing the population history of this model organism, as well as to the well-established importance of an accurate null demographic model for increasing power and decreasing false positive rates in genomic scans for positive selection. Although considerable attention has been afforded to this issue in non-African populations, less is known about the demographic history of African populations, including from the ancestral range of the species. While qualitative predictions and hypotheses have previously been forwarded, we here present a quantitative model fitting of the population history characterizing both the ancestral Zambian population range as well as the subsequently colonized west African populations, which themselves served as the source of multiple non-African colonization events. We here report the split time of the West African population at 72 kya, a date corresponding to human migration into this region as well as a period of climatic changes in the African continent. Furthermore, we have estimated population sizes at this split time. These parameter estimates thus represent an important null model for future investigations in to African and non-African D. melanogaster populations alike.
Collapse
Affiliation(s)
- Adamandia Kapopoulou
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Susanne P Pfeifer
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, Arizona
| | - Jeffrey D Jensen
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, Arizona
| | - Stefan Laurent
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Department of Comparative Development and Genetics, Max Planck Institute for Plant Breeding Research, Cologne, Germany
| |
Collapse
|
43
|
Pfeifer SP, Laurent S, Sousa VC, Linnen CR, Foll M, Excoffier L, Hoekstra HE, Jensen JD. The Evolutionary History of Nebraska Deer Mice: Local Adaptation in the Face of Strong Gene Flow. Mol Biol Evol 2019; 35:792-806. [PMID: 29346646 PMCID: PMC5905656 DOI: 10.1093/molbev/msy004] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The interplay of gene flow, genetic drift, and local selective pressure is a dynamic process that has been well studied from a theoretical perspective over the last century. Wright and Haldane laid the foundation for expectations under an island-continent model, demonstrating that an island-specific beneficial allele may be maintained locally if the selection coefficient is larger than the rate of migration of the ancestral allele from the continent. Subsequent extensions of this model have provided considerably more insight. Yet, connecting theoretical results with empirical data has proven challenging, owing to a lack of information on the relationship between genotype, phenotype, and fitness. Here, we examine the demographic and selective history of deer mice in and around the Nebraska Sand Hills, a system in which variation at the Agouti locus affects cryptic coloration that in turn affects the survival of mice in their local habitat. We first genotyped 250 individuals from 11 sites along a transect spanning the Sand Hills at 660,000 single nucleotide polymorphisms across the genome. Using these genomic data, we found that deer mice first colonized the Sand Hills following the last glacial period. Subsequent high rates of gene flow have served to homogenize the majority of the genome between populations on and off the Sand Hills, with the exception of the Agouti pigmentation locus. Furthermore, mutations at this locus are strongly associated with the pigment traits that are strongly correlated with local soil coloration and thus responsible for cryptic coloration.
Collapse
Affiliation(s)
- Susanne P Pfeifer
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ
| | - Stefan Laurent
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Vitor C Sousa
- Institute of Ecology & Evolution, University of Berne, Berne, Switzerland.,Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | | | - Matthieu Foll
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Laurent Excoffier
- Institute of Ecology & Evolution, University of Berne, Berne, Switzerland
| | - Hopi E Hoekstra
- Department of Organismic & Evolutionary Biology and Molecular & Cellular Biology, Museum of Comparative Zoology, Howard Hughes Medical Institute, Harvard University, Cambridge, MA
| | - Jeffrey D Jensen
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ
| |
Collapse
|
44
|
Barrett RDH, Laurent S, Mallarino R, Pfeifer SP, Xu CCY, Foll M, Wakamatsu K, Duke-Cohan JS, Jensen JD, Hoekstra HE. Linking a mutation to survival in wild mice. Science 2019; 363:499-504. [DOI: 10.1126/science.aav3824] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 12/06/2018] [Indexed: 12/19/2022]
Abstract
Adaptive evolution in new or changing environments can be difficult to predict because the functional connections between genotype, phenotype, and fitness are complex. Here, we make these explicit connections by combining field and laboratory experiments in wild mice. We first directly estimate natural selection on pigmentation traits and an underlying pigment locus, Agouti, by using experimental enclosures of mice on different soil colors. Next, we show how a mutation in Agouti associated with survival causes lighter coat color through changes in its protein binding properties. Together, our findings demonstrate how a sequence variant alters phenotype and then reveal the ensuing ecological consequences that drive changes in population allele frequency, thereby illuminating the process of evolution by natural selection.
Collapse
|
45
|
Jensen JD, Payseur BA, Stephan W, Aquadro CF, Lynch M, Charlesworth D, Charlesworth B. The importance of the Neutral Theory in 1968 and 50 years on: A response to Kern and Hahn 2018. Evolution 2019; 73:111-114. [PMID: 30460993 PMCID: PMC6496948 DOI: 10.1111/evo.13650] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 11/09/2018] [Indexed: 01/31/2023]
Abstract
A recent article reassessing the Neutral Theory of Molecular Evolution claims that it is no longer as important as is widely believed. The authors argue that "the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality." Claiming that "the neutral theory has been overwhelmingly rejected," they propose instead that natural selection is the major force shaping both between-species divergence and within-species variation. Although this is probably a minority view, it is important to evaluate such claims carefully in the context of current knowledge, as inaccuracies can sometimes morph into an accepted narrative for those not familiar with the underlying science. We here critically examine and ultimately reject Kern and Hahn's arguments and assessment, and instead propose that it is now abundantly clear that the foundational ideas presented five decades ago by Kimura and Ohta are indeed correct.
Collapse
Affiliation(s)
| | - Bret A. Payseur
- Laboratory of Genetics, University of Wisconsin-Madison,
Madison, Wisconsin
| | - Wolfgang Stephan
- Leibniz-Institute for Evolution and Biodiversity Science,
Berlin, Germany
| | - Charles F. Aquadro
- Department of Molecular Biology & Genetics, Cornell
University, Ithaca, New York
| | - Michael Lynch
- Center for Mechanisms of Evolution, Arizona State
University, Tempe, Arizona
| | - Deborah Charlesworth
- Institute of Evolutionary Biology, School of Biological
Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological
Sciences, University of Edinburgh, Edinburgh, United Kingdom
| |
Collapse
|
46
|
Harris RB, Sackman A, Jensen JD. On the unfounded enthusiasm for soft selective sweeps II: Examining recent evidence from humans, flies, and viruses. PLoS Genet 2018; 14:e1007859. [PMID: 30592709 PMCID: PMC6336318 DOI: 10.1371/journal.pgen.1007859] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2018] [Revised: 01/17/2019] [Accepted: 11/28/2018] [Indexed: 12/13/2022] Open
Abstract
Since the initial description of the genomic patterns expected under models of positive selection acting on standing genetic variation and on multiple beneficial mutations—so-called soft selective sweeps—researchers have sought to identify these patterns in natural population data. Indeed, over the past two years, large-scale data analyses have argued that soft sweeps are pervasive across organisms of very different effective population size and mutation rate—humans, Drosophila, and HIV. Yet, others have evaluated the relevance of these models to natural populations, as well as the identifiability of the models relative to other known population-level processes, arguing that soft sweeps are likely to be rare. Here, we look to reconcile these opposing results by carefully evaluating three recent studies and their underlying methodologies. Using population genetic theory, as well as extensive simulation, we find that all three examples are prone to extremely high false-positive rates, incorrectly identifying soft sweeps under both hard sweep and neutral models. Furthermore, we demonstrate that well-fit demographic histories combined with rare hard sweeps serve as the more parsimonious explanation. These findings represent a necessary response to the growing tendency of invoking parameter-heavy, assumption-laden models of pervasive positive selection, and neglecting best practices regarding the construction of proper demographic null models. A long-standing debate in evolutionary biology revolves around the role of selective vs. stochastic processes in driving molecular evolution and shaping genetic variation. With the advent of genomics, genome-wide polymorphism data have been utilized to characterize these processes, with a major interest in describing the fraction of genomic variation shaped by positive selection. These genomic scans were initially focused around a hard sweep model, in which selection acts upon rare, newly arising beneficial mutations. Recent years have seen the description of sweeps occurring from both standing and rapidly recurring beneficial mutations, collectively known as soft sweeps. However, common to both hard and soft sweeps is the difficulty in distinguishing these effects from neutral demographic patterns, and disentangling these processes has remained an important field of study within population genetics. Despite this, there is a recent and troubling tendency to neglect these demographic considerations, and to naively fit sweep models to genomic data. Recent realizations of such efforts have resulted in the claim that soft sweeps play a dominant role in shaping genomic variation and in driving adaptation across diverse branches of the tree of life. Here, we reanalyze these findings and demonstrate that a more careful consideration of neutral processes results in highly differing conclusions.
Collapse
Affiliation(s)
- Rebecca B. Harris
- School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
| | - Andrew Sackman
- School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
| | - Jeffrey D. Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
- * E-mail:
| |
Collapse
|
47
|
Avnir Y, Prachanronarong KL, Zhang Z, Hou S, Peterson EC, Sui J, Zayed H, Kurella VB, McGuire AT, Stamatatos L, Hilbert BJ, Bohn MF, Kowalik TF, Jensen JD, Finberg RW, Wang JP, Goodall M, Jefferis R, Zhu Q, Kurt Yilmaz N, Schiffer CA, Marasco WA. Structural Determination of the Broadly Reactive Anti-IGHV1-69 Anti-idiotypic Antibody G6 and Its Idiotope. Cell Rep 2018; 21:3243-3255. [PMID: 29241550 PMCID: PMC7185437 DOI: 10.1016/j.celrep.2017.11.056] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Revised: 11/04/2017] [Accepted: 11/15/2017] [Indexed: 12/17/2022] Open
Abstract
The heavy chain IGHV1-69 germline gene exhibits a high level of polymorphism and shows biased use in protective antibody (Ab) responses to infections and vaccines. It is also highly expressed in several B cell malignancies and autoimmune diseases. G6 is an anti-idiotypic monoclonal Ab that selectively binds to IGHV1-69 heavy chain germline gene 51p1 alleles that have been implicated in these Ab responses and disease processes. Here, we determine the co-crystal structure of humanized G6 (hG6.3) in complex with anti-influenza hemagglutinin stem-directed broadly neutralizing Ab D80. The core of the hG6.3 idiotope is a continuous string of CDR-H2 residues starting with M53 and ending with N58. G6 binding studies demonstrate the remarkable breadth of binding to 51p1 IGHV1-69 Abs with diverse CDR-H3, light chain, and antigen binding specificities. These studies detail the broad expression of the G6 cross-reactive idiotype (CRI) that further define its potential role in precision medicine. G6 binds to a subset of IGHV1-69 germline-based anti-influenza Abs The structure of humanized G6 with a IGHV1-69 anti-influenza Ab is reported Various binding assays further define the G6 cross-reactive binding idiotope The core binding idiotope of G6 is deduced
Collapse
Affiliation(s)
- Yuval Avnir
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kristina L Prachanronarong
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Zhen Zhang
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Shurong Hou
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Eric C Peterson
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jianhua Sui
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Hatem Zayed
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Vinodh B Kurella
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Andrew T McGuire
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Leonidas Stamatatos
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Brendan J Hilbert
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Markus-Frederik Bohn
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Timothy F Kowalik
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
| | - Robert W Finberg
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Jennifer P Wang
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Margaret Goodall
- Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Roy Jefferis
- Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Quan Zhu
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Nese Kurt Yilmaz
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA.
| | - Celia A Schiffer
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA.
| | - Wayne A Marasco
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
48
|
Jones MR, Mills LS, Alves PC, Callahan CM, Alves JM, Lafferty DJR, Jiggins FM, Jensen JD, Melo-Ferreira J, Good JM. Adaptive introgression underlies polymorphic seasonal camouflage in snowshoe hares. Science 2018; 360:1355-1358. [DOI: 10.1126/science.aar5273] [Citation(s) in RCA: 182] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 05/01/2018] [Indexed: 12/14/2022]
Abstract
Snowshoe hares (Lepus americanus) maintain seasonal camouflage by molting to a white winter coat, but some hares remain brown during the winter in regions with low snow cover. We show that cis-regulatory variation controlling seasonal expression of the Agouti gene underlies this adaptive winter camouflage polymorphism. Genetic variation at Agouti clustered by winter coat color across multiple hare and jackrabbit species, revealing a history of recurrent interspecific gene flow. Brown winter coats in snowshoe hares likely originated from an introgressed black-tailed jackrabbit allele that has swept to high frequency in mild winter environments. These discoveries show that introgression of genetic variants that underlie key ecological traits can seed past and ongoing adaptation to rapidly changing environments.
Collapse
|
49
|
Canale AS, Venev SV, Whitfield TW, Caffrey DR, Marasco WA, Schiffer CA, Kowalik TF, Jensen JD, Finberg RW, Zeldovich KB, Wang JP, Bolon DNA. Synonymous Mutations at the Beginning of the Influenza A Virus Hemagglutinin Gene Impact Experimental Fitness. J Mol Biol 2018; 430:1098-1115. [PMID: 29466705 DOI: 10.1016/j.jmb.2018.02.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 01/19/2018] [Accepted: 02/05/2018] [Indexed: 01/15/2023]
Abstract
The fitness effects of synonymous mutations can provide insights into biological and evolutionary mechanisms. We analyzed the experimental fitness effects of all single-nucleotide mutations, including synonymous substitutions, at the beginning of the influenza A virus hemagglutinin (HA) gene. Many synonymous substitutions were deleterious both in bulk competition and for individually isolated clones. Investigating protein and RNA levels of a subset of individually expressed HA variants revealed that multiple biochemical properties contribute to the observed experimental fitness effects. Our results indicate that a structural element in the HA segment viral RNA may influence fitness. Examination of naturally evolved sequences in human hosts indicates a preference for the unfolded state of this structural element compared to that found in swine hosts. Our overall results reveal that synonymous mutations may have greater fitness consequences than indicated by simple models of sequence conservation, and we discuss the implications of this finding for commonly used evolutionary tests and analyses.
Collapse
Affiliation(s)
- Aneth S Canale
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Sergey V Venev
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Troy W Whitfield
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655, USA; Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Daniel R Caffrey
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Wayne A Marasco
- Department of Cancer Immunology & Virology, Dana-Farber Cancer Institute, Harvard Medical School, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Celia A Schiffer
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Timothy F Kowalik
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ. 85281, USA
| | - Robert W Finberg
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Konstantin B Zeldovich
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Jennifer P Wang
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA.
| | - Daniel N A Bolon
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01655, USA.
| |
Collapse
|
50
|
Sackman AM, Pfeifer SP, Kowalik TF, Jensen JD. On the Demographic and Selective Forces Shaping Patterns of Human Cytomegalovirus Variation within Hosts. Pathogens 2018; 7:pathogens7010016. [PMID: 29382090 PMCID: PMC5874742 DOI: 10.3390/pathogens7010016] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 01/23/2018] [Accepted: 01/25/2018] [Indexed: 02/08/2023] Open
Abstract
Human cytomegalovirus (HCMV) is a member of the β -herpesvirus subfamily within Herpesviridae that is nearly ubiquitous in human populations, and infection generally results only in mild symptoms. However, symptoms can be severe in immunonaive individuals, and transplacental congenital infection of HCMV can result in serious neurological sequelae. Recent work has revealed much about the demographic and selective forces shaping the evolution of congenitally transmitted HCMV both on the level of hosts and within host compartments, providing insight into the dynamics of congenital infection, reinfection, and evolution of HCMV with important implications for the development of effective treatments and vaccines.
Collapse
Affiliation(s)
- Andrew M Sackman
- School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA.
| | - Susanne P Pfeifer
- School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA.
| | - Timothy F Kowalik
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA 01655, USA.
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ 85281, USA.
| |
Collapse
|