1
|
van den Belt S, Zhao H, Alachiotis N. Scalable CNN-based classification of selective sweeps using derived allele frequencies. Bioinformatics 2024; 40:ii29-ii36. [PMID: 39230693 PMCID: PMC11373383 DOI: 10.1093/bioinformatics/btae385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2024] Open
Abstract
MOTIVATION Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding factors, such as severe population bottlenecks and old migration. By virtue of machine learning, and specifically convolutional neural networks (CNNs), new accurate classification models that are robust to confounding factors have been recently proposed. However, such methods are more computationally expensive than summary-statistic-based ones, yielding them impractical for processing large-scale genomic data. Moreover, SNP data are frequently preprocessed to improve classification accuracy, further exacerbating the long analysis times. RESULTS To this end, we propose a 1D CNN-based model, dubbed FAST-NN, that does not require any preprocessing while using only derived allele frequencies instead of summary statistics or raw SNP data, thereby yielding a sample-size-invariant, scalable solution. We evaluated several data fusion approaches to account for the variance of the density of genetic diversity across genomic regions (a selective sweep signature), and performed an extensive neural architecture search based on a state-of-the-art reference network architecture (SweepNet). The resulting model, FAST-NN, outperforms the reference architecture by up to 12% inference accuracy over all challenging evolutionary scenarios with confounding factors that were evaluated. Moreover, FAST-NN is between 30× and 259× faster on a single CPU core, and between 2.0× and 6.2× faster on a GPU, when processing sample sizes between 128 and 1000 samples. Our work paves the way for the practical use of CNNs in large-scale selective sweep detection. AVAILABILITY AND IMPLEMENTATION https://github.com/SjoerdvandenBelt/FAST-NN.
Collapse
Affiliation(s)
- Sjoerd van den Belt
- Department of Computer Science, Faculty of EEMCS, University of Twente, 7522NB Enschede, The Netherlands
| | - Hanqing Zhao
- Department of Computer Science, Faculty of EEMCS, University of Twente, 7522NB Enschede, The Netherlands
| | - Nikolaos Alachiotis
- Department of Computer Science, Faculty of EEMCS, University of Twente, 7522NB Enschede, The Netherlands
| |
Collapse
|
2
|
Takayama J, Makino S, Funayama T, Ueki M, Narita A, Murakami K, Orui M, Ishikuro M, Obara T, Kuriyama S, Yamamoto M, Tamiya G. A fine-scale genetic map of the Japanese population. Clin Genet 2024; 106:284-292. [PMID: 38719617 DOI: 10.1111/cge.14536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 08/13/2024]
Abstract
Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.
Collapse
Affiliation(s)
- Jun Takayama
- Department of AI and Innovative Medicine, Tohoku University School of Medicine, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Satoshi Makino
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Takamitsu Funayama
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Masao Ueki
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Akira Narita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
| | - Masatsugu Orui
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Mami Ishikuro
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Taku Obara
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Shinichi Kuriyama
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Department of AI and Innovative Medicine, Tohoku University School of Medicine, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| |
Collapse
|
3
|
Ohadi M, Arabfard M, Khamse S, Alizadeh S, Vafadar S, Bayat H, Tajeddin N, Maddi AMA, Delbari A, Khorram Khorshid HR. Novel crossover and recombination hotspots massively spread across primate genomes. Biol Direct 2024; 19:70. [PMID: 39169390 PMCID: PMC11340189 DOI: 10.1186/s13062-024-00508-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Accepted: 07/29/2024] [Indexed: 08/23/2024] Open
Abstract
BACKGROUND The recombination landscape and subsequent natural selection have vast consequences forevolution and speciation. However, most of the crossover and recombination hotspots are yet to be discovered. We previously reported the relevance of C and G trinucleotide two-repeat units (CG-TTUs) in crossovers and recombination. METHODS On a genome-wide scale, here we mapped all combinations of A and T trinucleotide two-repeat units (AT-TTUs) in human, consisting of AATAAT, ATAATA, ATTATT, TTATTA, TATTAT, and TAATAA. We also compared a number of the colonies formed by the AT-TTUs (distance between consecutive AT-TTUs < 500 bp) in several other primates and mouse. RESULTS We found that the majority of the AT-TTUs (> 96%) resided in approximately 1.4 million colonies, spread throughout the human genome. In comparison to the CG-TTU colonies, the AT-TTU colonies were significantly more abundant and larger in size. Pure units and overlapping units of the pure units were readily detectable in the same colonies, signifying that the units were the sites of unequal crossover. We discovered dynamic sharedness of several of the colonies across the primate species studied, which mainly reached maximum complexity and size in human. CONCLUSIONS We report novel crossover and recombination hotspots of the finest molecular resolution, massively spread and shared across the genomes of human and several other primates. With respect to crossovers and recombination, these genomes are far more dynamic than previously envisioned.
Collapse
Affiliation(s)
- Mina Ohadi
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
| | - Masoud Arabfard
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
| | - Safoura Khamse
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Samira Alizadeh
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Sara Vafadar
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hadi Bayat
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
- Biochemical Neuroendocrinology, Montreal Clinical and Research Institute (IRCM, affiliated to the McGill University, Montreal, QC, H2W 1R7, Canada
| | - Nahid Tajeddin
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
- Department of Biology, Central Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Ali M A Maddi
- Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
| | - Ahmad Delbari
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Hamid R Khorram Khorshid
- Personalized Medicine and Genometabolomics Research Center, Hope Generation Foundation, Tehran, Iran
| |
Collapse
|
4
|
Li L, Comi TJ, Bierman RF, Akey JM. Recurrent gene flow between Neanderthals and modern humans over the past 200,000 years. Science 2024; 385:eadi1768. [PMID: 38991054 DOI: 10.1126/science.adi1768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 05/14/2024] [Indexed: 07/13/2024]
Abstract
Although it is well known that the ancestors of modern humans and Neanderthals admixed, the effects of gene flow on the Neanderthal genome are not well understood. We develop methods to estimate the amount of human-introgressed sequences in Neanderthals and apply it to whole-genome sequence data from 2000 modern humans and three Neanderthals. We estimate that Neanderthals have 2.5 to 3.7% human ancestry, and we leverage human-introgressed sequences in Neanderthals to revise estimates of Neanderthal ancestry in modern humans, show that Neanderthal population sizes were significantly smaller than previously estimated, and identify two distinct waves of modern human gene flow into Neanderthals. Our data provide insights into the genetic legacy of recurrent gene flow between modern humans and Neanderthals.
Collapse
Affiliation(s)
- Liming Li
- Department of Medical Genetics and Developmental Biology, School of Medicine, The Key Laboratory of Developmental Genes and Human Diseases, Ministry of Education, Southeast University, Nanjing 210009, China
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Troy J Comi
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Rob F Bierman
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| | - Joshua M Akey
- The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08540, USA
| |
Collapse
|
5
|
Dutheil JY. On the estimation of genome-average recombination rates. Genetics 2024; 227:iyae051. [PMID: 38565705 PMCID: PMC11232287 DOI: 10.1093/genetics/iyae051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 04/04/2024] Open
Abstract
The rate at which recombination events occur in a population is an indicator of its effective population size and the organism's reproduction mode. It determines the extent of linkage disequilibrium along the genome and, thereby, the efficacy of both purifying and positive selection. The population recombination rate can be inferred using models of genome evolution in populations. Classic methods based on the patterns of linkage disequilibrium provide the most accurate estimates, providing large sample sizes are used and the demography of the population is properly accounted for. Here, the capacity of approaches based on the sequentially Markov coalescent (SMC) to infer the genome-average recombination rate from as little as a single diploid genome is examined. SMC approaches provide highly accurate estimates even in the presence of changing population sizes, providing that (1) within genome heterogeneity is accounted for and (2) classic maximum-likelihood optimization algorithms are employed to fit the model. SMC-based estimates proved sensitive to gene conversion, leading to an overestimation of the recombination rate if conversion events are frequent. Conversely, methods based on the correlation of heterozygosity succeed in disentangling the rate of crossing over from that of gene conversion events, but only when the population size is constant and the recombination landscape homogeneous. These results call for a convergence of these two methods to obtain accurate and comparable estimates of recombination rates between populations.
Collapse
Affiliation(s)
- Julien Y Dutheil
- Max Planck Institute for Evolutionary Biology, August-Thienemann-Str. 2, Plön 24306, Germany
| |
Collapse
|
6
|
Joseph J, Prentout D, Laverré A, Tricou T, Duret L. High prevalence of PRDM9-independent recombination hotspots in placental mammals. Proc Natl Acad Sci U S A 2024; 121:e2401973121. [PMID: 38809707 PMCID: PMC11161765 DOI: 10.1073/pnas.2401973121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 04/26/2024] [Indexed: 05/31/2024] Open
Abstract
In many mammals, recombination events are concentrated in hotspots directed by a sequence-specific DNA-binding protein named PRDM9. Intriguingly, PRDM9 has been lost several times in vertebrates, and notably among mammals, it has been pseudogenized in the ancestor of canids. In the absence of PRDM9, recombination hotspots tend to occur in promoter-like features such as CpG islands. It has thus been proposed that one role of PRDM9 could be to direct recombination away from PRDM9-independent hotspots. However, the ability of PRDM9 to direct recombination hotspots has been assessed in only a handful of species, and a clear picture of how much recombination occurs outside of PRDM9-directed hotspots in mammals is still lacking. In this study, we derived an estimator of past recombination activity based on signatures of GC-biased gene conversion in substitution patterns. We quantified recombination activity in PRDM9-independent hotspots in 52 species of boreoeutherian mammals. We observe a wide range of recombination rates at these loci: several species (such as mice, humans, some felids, or cetaceans) show a deficit of recombination, while a majority of mammals display a clear peak of recombination. Our results demonstrate that PRDM9-directed and PRDM9-independent hotspots can coexist in mammals and that their coexistence appears to be the rule rather than the exception. Additionally, we show that the location of PRDM9-independent hotspots is relatively more stable than that of PRDM9-directed hotspots, but that PRDM9-independent hotspots nevertheless evolve slowly in concert with DNA hypomethylation.
Collapse
Affiliation(s)
- Julien Joseph
- Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, CNRS, UMR 5558, Villeurbanne69100, France
| | - Djivan Prentout
- Department of Biological Sciences, Columbia University, New York, NY10027
| | - Alexandre Laverré
- Department of Ecology and Evolution, University of Lausanne, LausanneCH-1015, Switzerland
- Swiss Institute of Bioinformatics, LausanneCH-1015, Switzerland
| | - Théo Tricou
- Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, CNRS, UMR 5558, Villeurbanne69100, France
| | - Laurent Duret
- Laboratoire de Biométrie et Biologie Evolutive, Université Lyon 1, CNRS, UMR 5558, Villeurbanne69100, France
| |
Collapse
|
7
|
Chen Z, Zhou M, Sun Y, Tang X, Zhang Z, Huang L. Exploration of Genome-Wide Recombination Rate Variation Patterns at Different Scales in Pigs. Animals (Basel) 2024; 14:1345. [PMID: 38731349 PMCID: PMC11083071 DOI: 10.3390/ani14091345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 04/27/2024] [Accepted: 04/28/2024] [Indexed: 05/13/2024] Open
Abstract
Meiotic recombination is a prevalent process in eukaryotic sexual reproduction organisms that plays key roles in genetic diversity, breed selection, and species evolution. However, the recombination events differ across breeds and even within breeds. In this study, we initially computed large-scale population recombination rates of both sexes using approximately 52 K SNP genotypes in a total of 3279 pigs from four different Chinese and Western breeds. We then constructed a high-resolution historical recombination map using approximately 16 million SNPs from a sample of unrelated individuals. Comparative analysis of porcine recombination events from different breeds and at different resolutions revealed the following observations: Firstly, the 1Mb-scale pig recombination maps of the same sex are moderately conserved among different breeds, with the similarity of recombination events between Western pigs and Chinese indigenous pigs being lower than within their respective groups. Secondly, we identified 3861 recombination hotspots in the genome and observed medium- to high-level correlation between historical recombination rates (0.542~0.683) and estimates of meiotic recombination rates. Third, we observed that recombination hotspots are significantly far from the transcription start sites of pig genes, and the silico-predicted PRDM9 zinc finger domain DNA recognition motif is significantly enriched in the regions of recombination hotspots compared to recombination coldspots, highlighting the potential role of PRDM9 in regulating recombination hotspots in pigs. Our study analyzed the variation patterns of the pig recombination map at broad and fine scales, providing a valuable reference for genomic selection breeding and laying a crucial foundation for further understanding the molecular mechanisms of pig genome recombination.
Collapse
Affiliation(s)
| | | | | | | | - Zhiyan Zhang
- National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Jiangxi Agricultural University, Nanchang 330045, China
| | | |
Collapse
|
8
|
Liu X, Koyama S, Tomizuka K, Takata S, Ishikawa Y, Ito S, Kosugi S, Suzuki K, Hikino K, Koido M, Koike Y, Horikoshi M, Gakuhari T, Ikegawa S, Matsuda K, Momozawa Y, Ito K, Kamatani Y, Terao C. Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing. SCIENCE ADVANCES 2024; 10:eadi8419. [PMID: 38630824 PMCID: PMC11023554 DOI: 10.1126/sciadv.adi8419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.
Collapse
Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, College of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
| | - Kochi Matsuda
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| |
Collapse
|
9
|
Lyulina AS, Liu Z, Good BH. Linkage equilibrium between rare mutations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.28.587282. [PMID: 38617331 PMCID: PMC11014483 DOI: 10.1101/2024.03.28.587282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Recombination breaks down genetic linkage by reshuffling existing variants onto new genetic backgrounds. These dynamics are traditionally quantified by examining the correlations between alleles, and how they decay as a function of the recombination rate. However, the magnitudes of these correlations are strongly influenced by other evolutionary forces like natural selection and genetic drift, making it difficult to tease out the effects of recombination. Here we introduce a theoretical framework for analyzing an alternative family of statistics that measure the homoplasy produced by recombination. We derive analytical expressions that predict how these statistics depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles. We find that the degree of homoplasy can strongly depend on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how these scaling properties can be used to isolate the effects of recombination, and discuss their implications for the rates of horizontal gene transfer in bacteria.
Collapse
Affiliation(s)
- Anastasia S Lyulina
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Zhiru Liu
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Benjamin H Good
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub - San Francisco, San Francisco, CA 94158, USA
| |
Collapse
|
10
|
Aw AJ, Spence JP, Song YS. A SIMPLE AND FLEXIBLE TEST OF SAMPLE EXCHANGEABILITY WITH APPLICATIONS TO STATISTICAL GENOMICS. Ann Appl Stat 2024; 18:858-881. [PMID: 38784669 PMCID: PMC11115382 DOI: 10.1214/23-aoas1817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
In scientific studies involving analyses of multivariate data, basic but important questions often arise for the researcher: Is the sample exchangeable, meaning that the joint distribution of the sample is invariant to the ordering of the units? Are the features independent of one another, or perhaps the features can be grouped so that the groups are mutually independent? In statistical genomics, these considerations are fundamental to downstream tasks such as demographic inference and the construction of polygenic risk scores. We propose a non-parametric approach, which we call the V test, to address these two questions, namely, a test of sample exchangeability given dependency structure of features, and a test of feature independence given sample exchangeability. Our test is conceptually simple, yet fast and flexible. It controls the Type I error across realistic scenarios, and handles data of arbitrary dimensions by leveraging large-sample asymptotics. Through extensive simulations and a comparison against unsupervised tests of stratification based on random matrix theory, we find that our test compares favorably in various scenarios of interest. We apply the test to data from the 1000 Genomes Project, demonstrating how it can be employed to assess exchangeability of the genetic sample, or find optimal linkage disequilibrium (LD) splits for downstream analysis. For exchangeability assessment, we find that removing rare variants can substantially increase the p -value of the test statistic. For optimal LD splitting, the V test reports different optimal splits than previous approaches not relying on hypothesis testing. Software for our methods is available in R (CRAN: flintyR) and Python (PyPI: flintyPy).
Collapse
Affiliation(s)
- Alan J Aw
- Department of Statistics, University of California, Berkeley
| | | | - Yun S Song
- Department of Statistics and Computer Science Division, University of California, Berkeley
| |
Collapse
|
11
|
Jiang Z, Zang W, Ericson PGP, Song G, Wu S, Feng S, Drovetski SV, Liu G, Zhang D, Saitoh T, Alström P, Edwards SV, Lei F, Qu Y. Gene flow and an anomaly zone complicate phylogenomic inference in a rapidly radiated avian family (Prunellidae). BMC Biol 2024; 22:49. [PMID: 38413944 PMCID: PMC10900574 DOI: 10.1186/s12915-024-01848-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 02/15/2024] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Resolving the phylogeny of rapidly radiating lineages presents a challenge when building the Tree of Life. An Old World avian family Prunellidae (Accentors) comprises twelve species that rapidly diversified at the Pliocene-Pleistocene boundary. RESULTS Here we investigate the phylogenetic relationships of all species of Prunellidae using a chromosome-level de novo assembly of Prunella strophiata and 36 high-coverage resequenced genomes. We use homologous alignments of thousands of exonic and intronic loci to build the coalescent and concatenated phylogenies and recover four different species trees. Topology tests show a large degree of gene tree-species tree discordance but only 40-54% of intronic gene trees and 36-75% of exonic genic trees can be explained by incomplete lineage sorting and gene tree estimation errors. Estimated branch lengths for three successive internal branches in the inferred species trees suggest the existence of an empirical anomaly zone. The most common topology recovered for species in this anomaly zone was not similar to any coalescent or concatenated inference phylogenies, suggesting presence of anomalous gene trees. However, this interpretation is complicated by the presence of gene flow because extensive introgression was detected among these species. When exploring tree topology distributions, introgression, and regional variation in recombination rate, we find that many autosomal regions contain signatures of introgression and thus may mislead phylogenetic inference. Conversely, the phylogenetic signal is concentrated to regions with low-recombination rate, such as the Z chromosome, which are also more resistant to interspecific introgression. CONCLUSIONS Collectively, our results suggest that phylogenomic inference should consider the underlying genomic architecture to maximize the consistency of phylogenomic signal.
Collapse
Affiliation(s)
- Zhiyong Jiang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Wenqing Zang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Per G P Ericson
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, Stockholm, SE-104 05, Sweden
| | - Gang Song
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Shaoyuan Wu
- Jiangsu International Joint Center of Genomics, Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, School of Life Sciences, Jiangsu Normal University, Xuzhou, 221116, Jiangsu, China
| | - Shaohong Feng
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiashan, 314102, China
| | - Sergei V Drovetski
- National Museum of Natural History, Smithsonian Institution, Washington, DC, 20004, USA
- Present address: U.S. Geological Survey, Eastern Ecological Science Center at Patuxent Research Refuge, Laurel, MD, 20708, USA
| | - Gang Liu
- Chinese Academy of Forestry, Institute of Ecological Conservation and Restoration, Beijing, 100091, China
| | - Dezhi Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Takema Saitoh
- Yamashina Institute for Ornithology, Abiko, Chiba, Japan
| | - Per Alström
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Animal Ecology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18 D, 752 36, Uppsala, Sweden
| | - Scott V Edwards
- Museum of Comparative Zoology and Department of Organismic & Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, MA, 02138, USA
| | - Fumin Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yanhua Qu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, PO Box 50007, Stockholm, SE-104 05, Sweden.
| |
Collapse
|
12
|
Hoge C, de Manuel M, Mahgoub M, Okami N, Fuller Z, Banerjee S, Baker Z, McNulty M, Andolfatto P, Macfarlan TS, Schumer M, Tzika AC, Przeworski M. Patterns of recombination in snakes reveal a tug-of-war between PRDM9 and promoter-like features. Science 2024; 383:eadj7026. [PMID: 38386752 DOI: 10.1126/science.adj7026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 01/04/2024] [Indexed: 02/24/2024]
Abstract
In some mammals, notably humans, recombination occurs almost exclusively where the protein PRDM9 binds, whereas in vertebrates lacking an intact PRDM9, such as birds and canids, recombination rates are elevated near promoter-like features. To determine whether PRDM9 directs recombination in nonmammalian vertebrates, we focused on an exemplar species with a single, intact PRDM9 ortholog, the corn snake (Pantherophis guttatus). Analyzing historical recombination rates along the genome and crossovers in pedigrees, we found evidence that PRDM9 specifies the location of recombination events, but we also detected a separable effect of promoter-like features. These findings reveal that the uses of PRDM9 and promoter-like features need not be mutually exclusive and instead reflect a tug-of-war that is more even in some species than others.
Collapse
Affiliation(s)
- Carla Hoge
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Marc de Manuel
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Mohamed Mahgoub
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Naima Okami
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Zachary Fuller
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Shreya Banerjee
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Zachary Baker
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Morgan McNulty
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Peter Andolfatto
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Todd S Macfarlan
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Molly Schumer
- Department of Biology, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Athanasia C Tzika
- Laboratory of Artificial & Natural Evolution (LANE), Department of Genetics & Evolution, University of Geneva, Geneva, Switzerland
| | - Molly Przeworski
- Department of Biological Sciences, Columbia University, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| |
Collapse
|
13
|
Ariad D, Madjunkova S, Madjunkov M, Chen S, Abramov R, Librach C, McCoy RC. Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos. Genome Res 2024; 34:70-84. [PMID: 38071472 PMCID: PMC10903951 DOI: 10.1101/gr.278168.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 11/21/2023] [Indexed: 12/19/2023]
Abstract
Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes rely either on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or on direct detection of crossovers in gametes or multigeneration pedigrees, which limits data set scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, and the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations show our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ∼150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared with disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.
Collapse
Affiliation(s)
- Daniel Ariad
- Department of Biology, Johns Hopkins University, Baltimore, Maryland 21218, USA;
| | - Svetlana Madjunkova
- CReATe Fertility Centre, Toronto, Ontario M5G 1N8, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | | | - Siwei Chen
- CReATe Fertility Centre, Toronto, Ontario M5G 1N8, Canada
| | - Rina Abramov
- CReATe Fertility Centre, Toronto, Ontario M5G 1N8, Canada
| | - Clifford Librach
- CReATe Fertility Centre, Toronto, Ontario M5G 1N8, Canada
- Department of Obstetrics and Gynecology, University of Toronto, Toronto, Ontario M5G 1E2, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, Maryland 21218, USA;
| |
Collapse
|
14
|
Bascón-Cardozo K, Bours A, Manthey G, Durieux G, Dutheil JY, Pruisscher P, Odenthal-Hesse L, Liedvogel M. Fine-Scale Map Reveals Highly Variable Recombination Rates Associated with Genomic Features in the Eurasian Blackcap. Genome Biol Evol 2024; 16:evad233. [PMID: 38198800 PMCID: PMC10781513 DOI: 10.1093/gbe/evad233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2023] [Indexed: 01/12/2024] Open
Abstract
Recombination is responsible for breaking up haplotypes, influencing genetic variability, and the efficacy of selection. Bird genomes lack the protein PR domain-containing protein 9, a key determinant of recombination dynamics in most metazoans. Historical recombination maps in birds show an apparent stasis in positioning recombination events. This highly conserved recombination pattern over long timescales may constrain the evolution of recombination in birds. At the same time, extensive variation in recombination rate is observed across the genome and between different species of birds. Here, we characterize the fine-scale historical recombination map of an iconic migratory songbird, the Eurasian blackcap (Sylvia atricapilla), using a linkage disequilibrium-based approach that accounts for population demography. Our results reveal variable recombination rates among and within chromosomes, which associate positively with nucleotide diversity and GC content and negatively with chromosome size. Recombination rates increased significantly at regulatory regions but not necessarily at gene bodies. CpG islands are associated strongly with recombination rates, though their specific position and local DNA methylation patterns likely influence this relationship. The association with retrotransposons varied according to specific family and location. Our results also provide evidence of heterogeneous intrachromosomal conservation of recombination maps between the blackcap and its closest sister taxon, the garden warbler. These findings highlight the considerable variability of recombination rates at different scales and the role of specific genomic features in shaping this variation. This study opens the possibility of further investigating the impact of recombination on specific population-genomic features.
Collapse
Affiliation(s)
- Karen Bascón-Cardozo
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Andrea Bours
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Georg Manthey
- Institute of Avian Research “Vogelwarte Helgoland”, Wilhelmshaven 26386, Germany
| | - Gillian Durieux
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Julien Y Dutheil
- Department for Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Peter Pruisscher
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
- Department of Zoology, Stockholm University, Stockholm SE-106 91, Sweden
| | - Linda Odenthal-Hesse
- Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Miriam Liedvogel
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
- Institute of Avian Research “Vogelwarte Helgoland”, Wilhelmshaven 26386, Germany
- Department of Biology and Environmental Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg 26129, Germany
| |
Collapse
|
15
|
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] [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
|
16
|
Dinh BL, Tang E, Taparra K, Nakatsuka N, Chen F, Chiang CWK. Recombination map tailored to Native Hawaiians may improve robustness of genomic scans for positive selection. Hum Genet 2024; 143:85-99. [PMID: 38157018 PMCID: PMC10794367 DOI: 10.1007/s00439-023-02625-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 11/25/2023] [Indexed: 01/03/2024]
Abstract
Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map) and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score|> 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.
Collapse
Affiliation(s)
- Bryan L Dinh
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Echo Tang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Kekoa Taparra
- Department of Radiation Oncology, Stanford University, Palo Alto, CA, USA
| | | | - Fei Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Charleston W K Chiang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| |
Collapse
|
17
|
Ariad D, Madjunkova S, Madjunkov M, Chen S, Abramov R, Librach C, McCoy RC. Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.543910. [PMID: 37333422 PMCID: PMC10274764 DOI: 10.1101/2023.06.07.543910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes either rely on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or direct detection of crossovers in gametes or multi-generation pedigrees, which limits dataset scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, as well as the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations demonstrate our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ~150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared to disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.
Collapse
Affiliation(s)
- Daniel Ariad
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Svetlana Madjunkova
- CReATe Fertility Centre, Toronto, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | | | - Siwei Chen
- CReATe Fertility Centre, Toronto, Canada
| | | | - Clifford Librach
- CReATe Fertility Centre, Toronto, Canada
- Department of Obstetrics and Gynecology, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Department of Physiology, University of Toronto, Toronto, Canada
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| |
Collapse
|
18
|
Spence JP, Zeng T, Mostafavi H, Pritchard JK. Scaling the discrete-time Wright-Fisher model to biobank-scale datasets. Genetics 2023; 225:iyad168. [PMID: 37724741 PMCID: PMC10627256 DOI: 10.1093/genetics/iyad168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 06/01/2023] [Accepted: 09/08/2023] [Indexed: 09/21/2023] Open
Abstract
The discrete-time Wright-Fisher (DTWF) model and its diffusion limit are central to population genetics. These models can describe the forward-in-time evolution of allele frequencies in a population resulting from genetic drift, mutation, and selection. Computing likelihoods under the diffusion process is feasible, but the diffusion approximation breaks down for large samples or in the presence of strong selection. Existing methods for computing likelihoods under the DTWF model do not scale to current exome sequencing sample sizes in the hundreds of thousands. Here, we present a scalable algorithm that approximates the DTWF model with provably bounded error. Our approach relies on two key observations about the DTWF model. The first is that transition probabilities under the model are approximately sparse. The second is that transition distributions for similar starting allele frequencies are extremely close as distributions. Together, these observations enable approximate matrix-vector multiplication in linear (as opposed to the usual quadratic) time. We prove similar properties for Hypergeometric distributions, enabling fast computation of likelihoods for subsamples of the population. We show theoretically and in practice that this approximation is highly accurate and can scale to population sizes in the tens of millions, paving the way for rigorous biobank-scale inference. Finally, we use our results to estimate the impact of larger samples on estimating selection coefficients for loss-of-function variants. We find that increasing sample sizes beyond existing large exome sequencing cohorts will provide essentially no additional information except for genes with the most extreme fitness effects.
Collapse
Affiliation(s)
- Jeffrey P Spence
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Tony Zeng
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | | | - Jonathan K Pritchard
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| |
Collapse
|
19
|
Baker Z, Przeworski M, Sella G. Down the Penrose stairs, or how selection for fewer recombination hotspots maintains their existence. eLife 2023; 12:e83769. [PMID: 37830496 DOI: 10.7554/elife.83769] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 10/12/2023] [Indexed: 10/14/2023] Open
Abstract
In many species, meiotic recombination events tend to occur in narrow intervals of the genome, known as hotspots. In humans and mice, double strand break (DSB) hotspot locations are determined by the DNA-binding specificity of the zinc finger array of the PRDM9 protein, which is rapidly evolving at residues in contact with DNA. Previous models explained this rapid evolution in terms of the need to restore PRDM9 binding sites lost to gene conversion over time, under the assumption that more PRDM9 binding always leads to more DSBs. This assumption, however, does not align with current evidence. Recent experimental work indicates that PRDM9 binding on both homologs facilitates DSB repair, and that the absence of sufficient symmetric binding disrupts meiosis. We therefore consider an alternative hypothesis: that rapid PRDM9 evolution is driven by the need to restore symmetric binding because of its role in coupling DSB formation and efficient repair. To this end, we model the evolution of PRDM9 from first principles: from its binding dynamics to the population genetic processes that govern the evolution of the zinc finger array and its binding sites. We show that the loss of a small number of strong binding sites leads to the use of a greater number of weaker ones, resulting in a sharp reduction in symmetric binding and favoring new PRDM9 alleles that restore the use of a smaller set of strong binding sites. This decrease, in turn, drives rapid PRDM9 evolutionary turnover. Our results therefore suggest that the advantage of new PRDM9 alleles is in limiting the number of binding sites used effectively, rather than in increasing net PRDM9 binding. By extension, our model suggests that the evolutionary advantage of hotspots may have been to increase the efficiency of DSB repair and/or homolog pairing.
Collapse
Affiliation(s)
- Zachary Baker
- Department of Systems Biology, Columbia University, New York, United States
- Department of Biological Sciences, Columbia University, New York, United States
| | - Molly Przeworski
- Department of Systems Biology, Columbia University, New York, United States
- Department of Biological Sciences, Columbia University, New York, United States
- Program for Mathematical Genomics, Columbia University, New York, United States
| | - Guy Sella
- Department of Biological Sciences, Columbia University, New York, United States
- Program for Mathematical Genomics, Columbia University, New York, United States
| |
Collapse
|
20
|
Pivirotto AM, Platt A, Patel R, Kumar S, Hey J. Analyses of allele age and fitness impact reveal human beneficial alleles to be older than neutral controls. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561569. [PMID: 37873438 PMCID: PMC10592680 DOI: 10.1101/2023.10.09.561569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A classic population genetic prediction is that alleles experiencing directional selection should swiftly traverse allele frequency space, leaving detectable reductions in genetic variation in linked regions. However, despite this expectation, identifying clear footprints of beneficial allele passage has proven to be surprisingly challenging. We addressed the basic premise underlying this expectation by estimating the ages of large numbers of beneficial and deleterious alleles in a human population genomic data set. Deleterious alleles were found to be young, on average, given their allele frequency. However, beneficial alleles were older on average than non-coding, non-regulatory alleles of the same frequency. This finding is not consistent with directional selection and instead indicates some type of balancing selection. Among derived beneficial alleles, those fixed in the population show higher local recombination rates than those still segregating, consistent with a model in which new beneficial alleles experience an initial period of balancing selection due to linkage disequilibrium with deleterious recessive alleles. Alleles that ultimately fix following a period of balancing selection will leave a modest 'soft' sweep impact on the local variation, consistent with the overall paucity of species-wide 'hard' sweeps in human genomes.
Collapse
Affiliation(s)
| | - Alexander Platt
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- University of Pennsylvania, Department of Genetics, Philadelphia PA 19104, USA
| | - Ravi Patel
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- Institute for Genomics and Evolutionary Medicine, Temple University, PA 19122, USA
| | - Sudhir Kumar
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- Institute for Genomics and Evolutionary Medicine, Temple University, PA 19122, USA
| | - Jody Hey
- Temple University, Department of Biology, Philadelphia PA 19122, USA
| |
Collapse
|
21
|
Liu X, Matsunami M, Horikoshi M, Ito S, Ishikawa Y, Suzuki K, Momozawa Y, Niida S, Kimura R, Ozaki K, Maeda S, Imamura M, Terao C. Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations. Mol Biol Evol 2023; 40:msad231. [PMID: 37903429 PMCID: PMC10615566 DOI: 10.1093/molbev/msad231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 09/20/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023] Open
Abstract
Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.
Collapse
Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Masatoshi Matsunami
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| |
Collapse
|
22
|
Nait Saada J, Tsangalidou Z, Stricker M, Palamara PF. Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks. Mol Biol Evol 2023; 40:msad211. [PMID: 37738175 PMCID: PMC10581698 DOI: 10.1093/molbev/msad211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 09/11/2023] [Accepted: 09/18/2023] [Indexed: 09/24/2023] Open
Abstract
Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which uses a convolutional neural network to predict pairwise TMRCAs and allele ages from sequencing or SNP array data. CoalNN is trained through simulation and can be adapted to varying parameters, such as demographic history, using transfer learning. Across several simulated scenarios, CoalNN matched or outperformed the accuracy of model-based approaches for pairwise TMRCA and allele age prediction. We applied CoalNN to settings for which model-based approaches are under-developed and performed analyses to gain insights into the set of features it uses to perform TMRCA prediction. We next used CoalNN to analyze 2,504 samples from 26 populations in the 1,000 Genome Project data set, inferring the age of ∼80 million variants. We observed substantial variation across populations and for variants predicted to be pathogenic, reflecting heterogeneous demographic histories and the action of negative selection. We used CoalNN's predicted allele ages to construct genome-wide annotations capturing the signature of past negative selection. We performed LD-score regression analysis of heritability using summary association statistics from 63 independent complex traits and diseases (average N=314k), observing increased annotation-specific effects on heritability compared to a previous allele age annotation. These results highlight the effectiveness of using likelihood-free, simulation-trained models to infer properties of gene genealogies in large genomic data sets.
Collapse
Affiliation(s)
| | | | | | - Pier Francesco Palamara
- Department of Statistics, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| |
Collapse
|
23
|
Heraghty SD, Jackson JM, Lozier JD. Whole genome analyses reveal weak signatures of population structure and environmentally associated local adaptation in an important North American pollinator, the bumble bee Bombus vosnesenskii. Mol Ecol 2023; 32:5479-5497. [PMID: 37702957 DOI: 10.1111/mec.17125] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 08/21/2023] [Accepted: 08/24/2023] [Indexed: 09/14/2023]
Abstract
Studies of species that experience environmental heterogeneity across their distributions have become an important tool for understanding mechanisms of adaptation and predicting responses to climate change. We examine population structure, demographic history and environmentally associated genomic variation in Bombus vosnesenskii, a common bumble bee in the western USA, using whole genome resequencing of populations distributed across a broad range of latitudes and elevations. We find that B. vosnesenskii exhibits minimal population structure and weak isolation by distance, confirming results from previous studies using other molecular marker types. Similarly, demographic analyses with Sequentially Markovian Coalescent models suggest that minimal population structure may have persisted since the last interglacial period, with genomes from different parts of the species range showing similar historical effective population size trajectories and relatively small fluctuations through time. Redundancy analysis revealed a small amount of genomic variation explained by bioclimatic variables. Environmental association analysis with latent factor mixed modelling (LFMM2) identified few outlier loci that were sparsely distributed throughout the genome and although a few putative signatures of selective sweeps were identified, none encompassed particularly large numbers of loci. Some outlier loci were in genes with known regulatory relationships, suggesting the possibility of weak selection, although compared with other species examined with similar approaches, evidence for extensive local adaptation signatures in the genome was relatively weak. Overall, results indicate B. vosnesenskii is an example of a generalist with a high degree of flexibility in its environmental requirements that may ultimately benefit the species under periods of climate change.
Collapse
Affiliation(s)
- Sam D Heraghty
- Department of Biological Sciences, The University of Alabama, Tuscaloosa, Alabama, USA
| | - Jason M Jackson
- Department of Biological Sciences, The University of Alabama, Tuscaloosa, Alabama, USA
| | - Jeffrey D Lozier
- Department of Biological Sciences, The University of Alabama, Tuscaloosa, Alabama, USA
| |
Collapse
|
24
|
Li Z, Liu X, Wang C, Li Z, Jiang B, Zhang R, Tong L, Qu Y, He S, Chen H, Mao Y, Li Q, Pook T, Wu Y, Zan Y, Zhang H, Li L, Wen K, Chen Y. The pig pangenome provides insights into the roles of coding structural variations in genetic diversity and adaptation. Genome Res 2023; 33:1833-1847. [PMID: 37914227 PMCID: PMC10691484 DOI: 10.1101/gr.277638.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 09/12/2023] [Indexed: 11/03/2023]
Abstract
Structural variations have emerged as an important driving force for genome evolution and phenotypic variation in various organisms, yet their contributions to genetic diversity and adaptation in domesticated animals remain largely unknown. Here we constructed a pangenome based on 250 sequenced individuals from 32 pig breeds in Eurasia and systematically characterized coding sequence presence/absence variations (PAVs) within pigs. We identified 308.3-Mb nonreference sequences and 3438 novel genes absent from the current reference genome. Gene PAV analysis showed that 16.8% of the genes in the pangene catalog undergo PAV. A number of newly identified dispensable genes showed close associations with adaptation. For instance, several novel swine leukocyte antigen (SLA) genes discovered in nonreference sequences potentially participate in immune responses to productive and respiratory syndrome virus (PRRSV) infection. We delineated previously unidentified features of the pig mobilome that contained 490,480 transposable element insertion polymorphisms (TIPs) resulting from recent mobilization of 970 TE families, and investigated their population dynamics along with influences on population differentiation and gene expression. In addition, several candidate adaptive TE insertions were detected to be co-opted into genes responsible for responses to hypoxia, skeletal development, regulation of heart contraction, and neuronal cell development, likely contributing to local adaptation of Tibetan wild boars. These findings enhance our understanding on hidden layers of the genetic diversity in pigs and provide novel insights into the role of SVs in the evolutionary adaptation of mammals.
Collapse
Affiliation(s)
- Zhengcao Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China;
| | - Xiaohong Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Chen Wang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Zhenyang Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Bo Jiang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Ruifeng Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Lu Tong
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Youping Qu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Sheng He
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Haifan Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Yafei Mao
- Bio-X Institutes, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Qingnan Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Torsten Pook
- Animal Breeding and Genomics, Wageningen University & Research, Wageningen 6700 AH, The Netherlands
| | - Yu Wu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Yanjun Zan
- Key Laboratory of Tobacco Improvement and Biotechnology, Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao 266000, China
| | - Hui Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Lu Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Keying Wen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Yaosheng Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China;
| |
Collapse
|
25
|
Bours A, Pruisscher P, Bascón-Cardozo K, Odenthal-Hesse L, Liedvogel M. The blackcap (Sylvia atricapilla) genome reveals a recent accumulation of LTR retrotransposons. Sci Rep 2023; 13:16471. [PMID: 37777595 PMCID: PMC10542752 DOI: 10.1038/s41598-023-43090-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 09/19/2023] [Indexed: 10/02/2023] Open
Abstract
Transposable elements (TEs) are mobile genetic elements that can move around the genome, and as such are a source of genomic variability. Based on their characteristics we can annotate TEs within the host genome and classify them into specific TE types and families. The increasing number of available high-quality genome references in recent years provides an excellent resource that will enhance the understanding of the role of recently active TEs on genetic variation and phenotypic evolution. Here we showcase the use of a high-quality TE annotation to understand the distinct effect of recent and ancient TE insertions on the evolution of genomic variation, within our study species the Eurasian blackcap (Sylvia atricapilla). We investigate how these distinct TE categories are distributed along the genome and evaluate how their coverage across the genome is correlated with four genomic features: recombination rate, gene coverage, CpG island coverage and GC content. We found within the recent TE insertions an accumulation of LTRs previously not seen in birds. While the coverage of recent TE insertions was negatively correlated with both GC content and recombination rate, the correlation with recombination rate disappeared and turned positive for GC content when considering ancient TE insertions.
Collapse
Affiliation(s)
- Andrea Bours
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, 24306, Plön, Germany.
| | - Peter Pruisscher
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, 24306, Plön, Germany
- Department of Evolutionary Biology, Evolutionary Biology Centre (EBC), Uppsala University, Uppsala, Sweden
| | - Karen Bascón-Cardozo
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, 24306, Plön, Germany
| | - Linda Odenthal-Hesse
- Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, 24306, Plön, Germany
| | - Miriam Liedvogel
- MPRG Behavioural Genomics, Max Planck Institute for Evolutionary Biology, 24306, Plön, Germany.
- Institute of Avian Research "Vogelwarte Helgoland", 26386, Wilhelmshaven, Germany.
| |
Collapse
|
26
|
Dinh BL, Tang E, Taparra K, Nakatsuka N, Chen F, Chiang CWK. Recombination map tailored to Native Hawaiians improves robustness of genomic scans for positive selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.12.548735. [PMID: 37503129 PMCID: PMC10370006 DOI: 10.1101/2023.07.12.548735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map), and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score| > 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.
Collapse
Affiliation(s)
- Bryan L Dinh
- Department of Quantitative and Computational Biology, University of Southern California
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Echo Tang
- Department of Quantitative and Computational Biology, University of Southern California
| | - Kekoa Taparra
- Department of Radiation Oncology, Stanford University, Palo Alto, California
| | | | - Fei Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - Charleston W K Chiang
- Department of Quantitative and Computational Biology, University of Southern California
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| |
Collapse
|
27
|
He H, Yang H, Foo R, Chan W, Zhu F, Liu Y, Zhou X, Ma L, Wang LF, Zhai W. Population genomic analysis reveals distinct demographics and recent adaptation in the black flying fox (Pteropus alecto). J Genet Genomics 2023; 50:554-562. [PMID: 37182682 DOI: 10.1016/j.jgg.2023.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/03/2023] [Accepted: 05/03/2023] [Indexed: 05/16/2023]
Abstract
As the only mammalian group capable of powered flight, bats have many unique biological traits. Previous comparative genomic studies in bats have focused on long-term evolution. However, the micro-evolutionary processes driving recent evolution are largely under-explored. Using resequencing data from 50 black flying foxes (Pteropus alecto), one of the model species for bats, we find that black flying fox has much higher genetic diversity and lower levels of linkage disequilibrium than most of the mammalian species. Demographic inference reveals strong population fluctuations (>100 fold) coinciding with multiple historical events including the last glacial change and Toba super eruption, suggesting that the black flying fox is a very resilient species with strong recovery abilities. While long-term adaptation in the black flying fox is enriched in metabolic genes, recent adaptation in the black flying fox has a unique landscape where recently selected genes are not strongly enriched in any functional category. The demographic history and mode of adaptation suggest that black flying fox might be a well-adapted species with strong evolutionary resilience. Taken together, this study unravels a vibrant landscape of recent evolution for the black flying fox and sheds light on several unique evolutionary processes for bats comparing to other mammalian groups.
Collapse
Affiliation(s)
- Haopeng He
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hechuan Yang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Randy Foo
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Singhealth Duke-NUS Global Health Institute, Singapore 169857, Singapore
| | - Wharton Chan
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Singhealth Duke-NUS Global Health Institute, Singapore 169857, Singapore
| | - Feng Zhu
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Singhealth Duke-NUS Global Health Institute, Singapore 169857, Singapore
| | - Yunsong Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xuming Zhou
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Liang Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Lin-Fa Wang
- Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; Singhealth Duke-NUS Global Health Institute, Singapore 169857, Singapore.
| | - Weiwei Zhai
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.
| |
Collapse
|
28
|
Hoge C, de Manuel M, Mahgoub M, Okami N, Fuller Z, Banerjee S, Baker Z, McNulty M, Andolfatto P, Macfarlan TS, Schumer M, Tzika AC, Przeworski M. Patterns of recombination in snakes reveal a tug of war between PRDM9 and promoter-like features. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.11.548536. [PMID: 37502971 PMCID: PMC10369914 DOI: 10.1101/2023.07.11.548536] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
In vertebrates, there are two known mechanisms by which meiotic recombination is directed to the genome: in humans, mice, and other mammals, recombination occurs almost exclusively where the protein PRDM9 binds, while in species lacking an intact PRDM9, such as birds and canids, recombination rates are elevated near promoter-like features. To test if PRDM9 also directs recombination in non-mammalian vertebrates, we focused on an exemplar species, the corn snake (Pantherophis guttatus). Unlike birds, this species possesses a single, intact PRDM9 ortholog. By inferring historical recombination rates along the genome from patterns of linkage disequilibrium and identifying crossovers in pedigrees, we found that PRDM9 specifies the location of recombination events outside of mammals. However, we also detected an independent effect of promoter-like features on recombination, which is more pronounced on macro- than microchromosomes. Thus, our findings reveal that the uses of PRDM9 and promoter-like features are not mutually-exclusive, and instead reflect a tug of war, which varies in strength along the genome and is more lopsided in some species than others.
Collapse
Affiliation(s)
- Carla Hoge
- Dept. of Biological Sciences, Columbia University
| | | | - Mohamed Mahgoub
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health
| | - Naima Okami
- Dept. of Biological Sciences, Columbia University
| | | | | | | | | | | | - Todd S Macfarlan
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health
| | - Molly Schumer
- Dept. of Biology, Stanford University
- Howard Hughes Medical Institute, Stanford, CA
| | - Athanasia C Tzika
- Laboratory of Artificial & Natural Evolution (LANE), Department of Genetics & Evolution, University of Geneva
| | - Molly Przeworski
- Dept. of Biological Sciences, Columbia University
- Howard Hughes Medical Institute, Stanford, CA
| |
Collapse
|
29
|
Naseri A, Yue W, Zhang S, Zhi D. Fast inference of genetic recombination rates in biobank scale data. Genome Res 2023; 33:1015-1022. [PMID: 37349109 PMCID: PMC10538484 DOI: 10.1101/gr.277676.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 06/09/2023] [Indexed: 06/24/2023]
Abstract
Although rates of recombination events across the genome (genetic maps) are fundamental to genetic research, the majority of current studies only use one standard map. There is evidence suggesting population differences in genetic maps, and thus estimating population-specific maps, are of interest. Although the recent availability of biobank-scale data offers such opportunities, current methods are not efficient at leveraging very large sample sizes. The most accurate methods are still linkage disequilibrium (LD)-based methods that are only tractable for a few hundred samples. In this work, we propose a fast and memory-efficient method for estimating genetic maps from population genotyping data. Our method, FastRecomb, leverages the efficient positional Burrows-Wheeler transform (PBWT) data structure for counting IBD segment boundaries as potential recombination events. We used PBWT blocks to avoid redundant counting of pairwise matches. Moreover, we used a panel-smoothing technique to reduce the noise from errors and recent mutations. Using simulation, we found that FastRecomb achieves state-of-the-art performance at 10-kb resolution, in terms of correlation coefficients between the estimated map and the ground truth. This is mainly because FastRecomb can effectively take advantage of large panels comprising more than hundreds of thousands of haplotypes. At the same time, other methods lack the efficiency to handle such data. We believe further refinement of FastRecomb would deliver more accurate genetic maps for the genetics community.
Collapse
Affiliation(s)
- Ardalan Naseri
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas 77030, USA
| | - William Yue
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas 77030, USA
| | - Shaojie Zhang
- Department of Computer Science, University of Central Florida, Orlando, Florida 32816, USA
| | - Degui Zhi
- McWilliams School of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas 77030, USA;
| |
Collapse
|
30
|
Wang N, Cao S, Liu Z, Xiao H, Hu J, Xu X, Chen P, Ma Z, Ye J, Chai L, Guo W, Larkin RM, Xu Q, Morrell PL, Zhou Y, Deng X. Genomic conservation of crop wild relatives: A case study of citrus. PLoS Genet 2023; 19:e1010811. [PMID: 37339133 DOI: 10.1371/journal.pgen.1010811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 06/01/2023] [Indexed: 06/22/2023] Open
Abstract
Conservation of crop wild relatives is critical for plant breeding and food security. The lack of clarity on the genetic factors that lead to endangered status or extinction create difficulties when attempting to develop concrete recommendations for conserving a citrus wild relative: the wild relatives of crops. Here, we evaluate the conservation of wild kumquat (Fortunella hindsii) using genomic, geographical, environmental, and phenotypic data, and forward simulations. Genome resequencing data from 73 accessions from the Fortunella genus were combined to investigate population structure, demography, inbreeding, introgression, and genetic load. Population structure was correlated with reproductive type (i.e., sexual and apomictic) and with a significant differentiation within the sexually reproducing population. The effective population size for one of the sexually reproducing subpopulations has recently declined to ~1,000, resulting in high levels of inbreeding. In particular, we found that 58% of the ecological niche overlapped between wild and cultivated populations and that there was extensive introgression into wild samples from cultivated populations. Interestingly, the introgression pattern and accumulation of genetic load may be influenced by the type of reproduction. In wild apomictic samples, the introgressed regions were primarily heterozygous, and genome-wide deleterious variants were hidden in the heterozygous state. In contrast, wild sexually reproducing samples carried a higher recessive deleterious burden. Furthermore, we also found that sexually reproducing samples were self-incompatible, which prevented the reduction of genetic diversity by selfing. Our population genomic analyses provide specific recommendations for distinct reproductive types and monitoring during conservation. This study highlights the genomic landscape of a wild relative of citrus and provides recommendations for the conservation of crop wild relatives.
Collapse
Affiliation(s)
- Nan Wang
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Shuo Cao
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhongjie Liu
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Hua Xiao
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Jianbing Hu
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
| | - Xiaodong Xu
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Peng Chen
- Institute of Horticultural Research, Hunan Academy of Agricultural Sciences, Changsha, China
| | - Zhiyao Ma
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Junli Ye
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
| | - Lijun Chai
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
| | - Wenwu Guo
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Robert M Larkin
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Qiang Xu
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Peter L Morrell
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Yongfeng Zhou
- State Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- State Key Laboratory of Tropical Crop Breeding, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Xiuxin Deng
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| |
Collapse
|
31
|
Colbran LL, Ramos-Almodovar FC, Mathieson I. A gene-level test for directional selection on gene expression. Genetics 2023; 224:iyad060. [PMID: 37036411 PMCID: PMC10213495 DOI: 10.1093/genetics/iyad060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 01/11/2023] [Accepted: 03/31/2023] [Indexed: 04/11/2023] Open
Abstract
Most variants identified in human genome-wide association studies and scans for selection are noncoding. Interpretation of their effects and the way in which they contribute to phenotypic variation and adaptation in human populations is therefore limited by our understanding of gene regulation and the difficulty of confidently linking noncoding variants to genes. To overcome this, we developed a gene-wise test for population-specific selection based on combinations of regulatory variants. Specifically, we use the QX statistic to test for polygenic selection on cis-regulatory variants based on whether the variance across populations in the predicted expression of a particular gene is higher than expected under neutrality. We then applied this approach to human data, testing for selection on 17,388 protein-coding genes in 26 populations from the Thousand Genomes Project. We identified 45 genes with significant evidence (FDR<0.1) for selection, including FADS1, KHK, SULT1A2, ITGAM, and several genes in the HLA region. We further confirm that these signals correspond to plausible population-level differences in predicted expression. While the small number of significant genes (0.2%) is consistent with most cis-regulatory variation evolving under genetic drift or stabilizing selection, it remains possible that there are effects not captured in this study. Our gene-level QX score is independent of standard genomic tests for selection, and may therefore be useful in combination with traditional selection scans to specifically identify selection on regulatory variation. Overall, our results demonstrate the utility of combining population-level genomic data with functional data to understand the evolution of gene expression.
Collapse
Affiliation(s)
- Laura L Colbran
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | | |
Collapse
|
32
|
Spence JP, Zeng T, Mostafavi H, Pritchard JK. Scaling the Discrete-time Wright Fisher model to biobank-scale datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.19.541517. [PMID: 37293115 PMCID: PMC10245735 DOI: 10.1101/2023.05.19.541517] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The Discrete-Time Wright Fisher (DTWF) model and its large population diffusion limit are central to population genetics. These models describe the forward-in-time evolution of the frequency of an allele in a population and can include the fundamental forces of genetic drift, mutation, and selection. Computing like-lihoods under the diffusion process is feasible, but the diffusion approximation breaks down for large sample sizes or in the presence of strong selection. Unfortunately, existing methods for computing likelihoods under the DTWF model do not scale to current exome sequencing sample sizes in the hundreds of thousands. Here we present an algorithm that approximates the DTWF model with provably bounded error and runs in time linear in the size of the population. Our approach relies on two key observations about Binomial distributions. The first is that Binomial distributions are approximately sparse. The second is that Binomial distributions with similar success probabilities are extremely close as distributions, allowing us to approximate the DTWF Markov transition matrix as a very low rank matrix. Together, these observations enable matrix-vector multiplication in linear (as opposed to the usual quadratic) time. We prove similar properties for Hypergeometric distributions, enabling fast computation of likelihoods for subsamples of the population. We show theoretically and in practice that this approximation is highly accurate and can scale to population sizes in the billions, paving the way for rigorous biobank-scale population genetic inference. Finally, we use our results to estimate how increasing sample sizes will improve the estimation of selection coefficients acting on loss-of-function variants. We find that increasing sample sizes beyond existing large exome sequencing cohorts will provide essentially no additional information except for genes with the most extreme fitness effects.
Collapse
Affiliation(s)
| | - Tony Zeng
- Department of Genetics, Stanford University
| | | | - Jonathan K. Pritchard
- Department of Genetics, Stanford University
- Department of Biology, Stanford University
| |
Collapse
|
33
|
Palahí I Torres A, Höök L, Näsvall K, Shipilina D, Wiklund C, Vila R, Pruisscher P, Backström N. The fine-scale recombination rate variation and associations with genomic features in a butterfly. Genome Res 2023; 33:810-823. [PMID: 37308293 PMCID: PMC10317125 DOI: 10.1101/gr.277414.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 05/03/2023] [Indexed: 06/14/2023]
Abstract
Recombination is a key molecular mechanism that has profound implications on both micro- and macroevolutionary processes. However, the determinants of recombination rate variation in holocentric organisms are poorly understood, in particular in Lepidoptera (moths and butterflies). The wood white butterfly (Leptidea sinapis) shows considerable intraspecific variation in chromosome numbers and is a suitable system for studying regional recombination rate variation and its potential molecular underpinnings. Here, we developed a large whole-genome resequencing data set from a population of wood whites to obtain high-resolution recombination maps using linkage disequilibrium information. The analyses revealed that larger chromosomes had a bimodal recombination landscape, potentially caused by interference between simultaneous chiasmata. The recombination rate was significantly lower in subtelomeric regions, with exceptions associated with segregating chromosome rearrangements, showing that fissions and fusions can have considerable effects on the recombination landscape. There was no association between the inferred recombination rate and base composition, supporting a limited influence of GC-biased gene conversion in butterflies. We found significant but variable associations between the recombination rate and the density of different classes of transposable elements, most notably a significant enrichment of short interspersed nucleotide elements in genomic regions with higher recombination rate. Finally, the analyses unveiled significant enrichment of genes involved in farnesyltranstransferase activity in recombination coldspots, potentially indicating that expression of transferases can inhibit formation of chiasmata during meiotic division. Our results provide novel information about recombination rate variation in holocentric organisms and have particular implications for forthcoming research in population genetics, molecular/genome evolution, and speciation.
Collapse
Affiliation(s)
- Aleix Palahí I Torres
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, SE-752 36 Uppsala, Sweden;
| | - Lars Höök
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, SE-752 36 Uppsala, Sweden
| | - Karin Näsvall
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, SE-752 36 Uppsala, Sweden
| | - Daria Shipilina
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, SE-752 36 Uppsala, Sweden
| | - Christer Wiklund
- Department of Zoology: Division of Ecology, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Roger Vila
- Butterfly Diversity and Evolution Lab, Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
| | - Peter Pruisscher
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, SE-752 36 Uppsala, Sweden
| | - Niclas Backström
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, SE-752 36 Uppsala, Sweden
| |
Collapse
|
34
|
Fan S, Spence JP, Feng Y, Hansen MEB, Terhorst J, Beltrame MH, Ranciaro A, Hirbo J, Beggs W, Thomas N, Nyambo T, Mpoloka SW, Mokone GG, Njamnshi A, Folkunang C, Meskel DW, Belay G, Song YS, Tishkoff SA. Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation. Cell 2023; 186:923-939.e14. [PMID: 36868214 PMCID: PMC10568978 DOI: 10.1016/j.cell.2023.01.042] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 10/16/2022] [Accepted: 01/30/2023] [Indexed: 03/05/2023]
Abstract
We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.
Collapse
Affiliation(s)
- Shaohua Fan
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jeffrey P Spence
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Yuanqing Feng
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew E B Hansen
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jonathan Terhorst
- Department of Statistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marcia H Beltrame
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alessia Ranciaro
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jibril Hirbo
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William Beggs
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Neil Thomas
- Computer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Thomas Nyambo
- Department of Biochemistry, Kampala International University in Tanzania, P.O. Box 9790, Dar es Salaam, Tanzania
| | - Sununguko Wata Mpoloka
- Department of Biological Sciences, Faculty of Science, University of Botswana Gaborone, Private Bag UB 0022, Gaborone, Botswana
| | - Gaonyadiwe George Mokone
- Department of Biomedical Sciences, Faculty of Medicine, University of Botswana Gaborone, Private Bag UB 0022, Gaborone, Botswana
| | - Alfred Njamnshi
- Department of Neurology, Central Hospital Yaoundé; Brain Research Africa Initiative (BRAIN), Neuroscience Lab, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, P.O. Box 337, Yaoundé, Cameroon
| | - Charles Folkunang
- Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, P.O. Box 337, Yaoundé, Cameroon
| | - Dawit Wolde Meskel
- Department of Microbial Cellular and Molecular Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
| | - Gurja Belay
- Department of Microbial Cellular and Molecular Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
| | - Yun S Song
- Computer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Sarah A Tishkoff
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
| |
Collapse
|
35
|
Duchen D, Vergara C, Thio CL, Kundu P, Chatterjee N, Thomas DL, Wojcik GL, Duggal P. Pathogen exposure misclassification can bias association signals in GWAS of infectious diseases when using population-based common control subjects. Am J Hum Genet 2023; 110:336-348. [PMID: 36649706 PMCID: PMC9943744 DOI: 10.1016/j.ajhg.2022.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 12/20/2022] [Indexed: 01/18/2023] Open
Abstract
Genome-wide association studies (GWASs) have been performed to identify host genetic factors for a range of phenotypes, including for infectious diseases. The use of population-based common control subjects from biobanks and extensive consortia is a valuable resource to increase sample sizes in the identification of associated loci with minimal additional expense. Non-differential misclassification of the outcome has been reported when the control subjects are not well characterized, which often attenuates the true effect size. However, for infectious diseases the comparison of affected subjects to population-based common control subjects regardless of pathogen exposure can also result in selection bias. Through simulated comparisons of pathogen-exposed cases and population-based common control subjects, we demonstrate that not accounting for pathogen exposure can result in biased effect estimates and spurious genome-wide significant signals. Further, the observed association can be distorted depending upon strength of the association between a locus and pathogen exposure and the prevalence of pathogen exposure. We also used a real data example from the hepatitis C virus (HCV) genetic consortium comparing HCV spontaneous clearance to persistent infection with both well-characterized control subjects and population-based common control subjects from the UK Biobank. We find biased effect estimates for known HCV clearance-associated loci and potentially spurious HCV clearance associations. These findings suggest that the choice of control subjects is especially important for infectious diseases or outcomes that are conditional upon environmental exposures.
Collapse
Affiliation(s)
- Dylan Duchen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Candelaria Vergara
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Chloe L Thio
- Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Prosenjit Kundu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - David L Thomas
- Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Priya Duggal
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
| |
Collapse
|
36
|
Naseri A, Yue W, Zhang S, Zhi D. FastRecomb: Fast inference of genetic recombination rates in biobank scale data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.09.523304. [PMID: 36712114 PMCID: PMC9882036 DOI: 10.1101/2023.01.09.523304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
While rates of recombination events across the genome (genetic maps) are fundamental to genetic research, the majority of current studies only use one standard map. There is evidence suggesting population differences in genetic maps, and thus estimating population-specific maps are of interest. While the recent availability of biobank-scale data offers such opportunities, current methods are not efficient at leveraging very large sample sizes. The most accurate methods are still linkage-disequilibrium (LD)-based methods that are only tractable for a few hundred samples. In this work, we propose a fast and memory-efficient method for estimating genetic maps from population genotyping data. Our method, FastRecomb, leverages the efficient positional Burrows-Wheeler transform (PBWT) data structure for counting IBD segment boundaries as potential recombination events. We used PBWT blocks to avoid redundant counting of pairwise matches. Moreover, we used a panel smoothing technique to reduce the noise from errors and recent mutations. Using simulation, we found that FastRecomb achieves state-of-the-art performance at 10k resolution, in terms of correlation coefficients between the estimated map and the ground truth. This is mainly due to the fact that FastRecomb can effectively take advantage of large panels comprising more than hundreds of thousands of haplotypes. At the same time, other methods lack the efficiency to handle such data. We believe further refinement of FastRecomb would deliver more accurate genetic maps for the genetics community.
Collapse
Affiliation(s)
- Ardalan Naseri
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston TX 77030, USA
| | - William Yue
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston TX 77030, USA
| | - Shaojie Zhang
- Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA
| | - Degui Zhi
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston TX 77030, USA
| |
Collapse
|
37
|
Zhang X, Kim B, Singh A, Sankararaman S, Durvasula A, Lohmueller KE. MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations. Mol Biol Evol 2023; 40:msad001. [PMID: 36617238 PMCID: PMC9887621 DOI: 10.1093/molbev/msad001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 12/25/2022] [Accepted: 12/28/2022] [Indexed: 01/09/2023] Open
Abstract
Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for introgressed genomic regions. Although widely used, approaches intersecting outliers are vulnerable to a high false-negative rate as the power of different methods varies, especially for complex introgression events. Moreover, population genetic processes unrelated to AI, such as background selection or heterosis, may create similar genomic signals to AI, compromising the reliability of methods that rely on neutral null distributions. In recent years, machine learning (ML) methods have been increasingly applied to population genetic questions. Here, we present a ML-based method called MaLAdapt for identifying AI loci from genome-wide sequencing data. Using an Extra-Trees Classifier algorithm, our method combines information from a large number of biologically meaningful summary statistics to capture a powerful composite signature of AI across the genome. In contrast to existing methods, MaLAdapt is especially well-powered to detect AI with mild beneficial effects, including selection on standing archaic variation, and is robust to non-AI selective sweeps, heterosis from deleterious mutations, and demographic misspecification. Furthermore, MaLAdapt outperforms existing methods for detecting AI based on the analysis of simulated data and the validation of empirical signals through visual inspection of haplotype patterns. We apply MaLAdapt to the 1000 Genomes Project human genomic data and discover novel AI candidate regions in non-African populations, including genes that are enriched in functionally important biological pathways regulating metabolism and immune responses.
Collapse
Affiliation(s)
- Xinjun Zhang
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA
| | - Bernard Kim
- Department of Biology, Stanford University, Palo Alto, CA
| | - Armaan Singh
- Department of Computer Science, UCLA, Los Angeles, CA
| | - Sriram Sankararaman
- Department of Computer Science, UCLA, Los Angeles, CA
- Department of Computational Medicine, UCLA, Los Angeles, CA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA
| | - Arun Durvasula
- Department of Genetics, Harvard Medical School, Boston, MA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA
| |
Collapse
|
38
|
Wooldridge LK, Dumont BL. Rapid Evolution of the Fine-scale Recombination Landscape in Wild House Mouse (Mus musculus) Populations. Mol Biol Evol 2022; 40:6889355. [PMID: 36508360 PMCID: PMC9825251 DOI: 10.1093/molbev/msac267] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 11/23/2022] [Accepted: 11/30/2022] [Indexed: 12/14/2022] Open
Abstract
Meiotic recombination is an important evolutionary force and an essential meiotic process. In many species, recombination events concentrate into hotspots defined by the site-specific binding of PRMD9. Rapid evolution of Prdm9's zinc finger DNA-binding array leads to remarkably abrupt shifts in the genomic distribution of hotspots between species, but the question of how Prdm9 allelic variation shapes the landscape of recombination between populations remains less well understood. Wild house mice (Mus musculus) harbor exceptional Prdm9 diversity, with >150 alleles identified to date, and pose a particularly powerful system for addressing this open question. We employed a coalescent-based approach to construct broad- and fine-scale sex-averaged recombination maps from contemporary patterns of linkage disequilibrium in nine geographically isolated wild house mouse populations, including multiple populations from each of three subspecies. Comparing maps between wild mouse populations and subspecies reveals several themes. First, we report weak fine- and broad-scale recombination map conservation across subspecies and populations, with genetic divergence offering no clear prediction for recombination map divergence. Second, most hotspots are unique to one population, an outcome consistent with minimal sharing of Prdm9 alleles between surveyed populations. Finally, by contrasting aggregate hotspot activity on the X versus autosomes, we uncover evidence for population-specific differences in the degree and direction of sex dimorphism for recombination. Overall, our findings illuminate the variability of both the broad- and fine-scale recombination landscape in M. musculus and underscore the functional impact of Prdm9 allelic variation in wild mouse populations.
Collapse
|
39
|
Bergman J, Schierup MH. Evolutionary dynamics of pseudoautosomal region 1 in humans and great apes. Genome Biol 2022; 23:215. [PMID: 36253794 PMCID: PMC9575207 DOI: 10.1186/s13059-022-02784-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 09/30/2022] [Indexed: 12/03/2022] Open
Abstract
Background The pseudoautosomal region 1 (PAR1) is a 2.7 Mb telomeric region of human sex chromosomes. PAR1 has a crucial role in ensuring proper segregation of sex chromosomes during male meiosis, exposing it to extreme recombination and mutation processes. We investigate PAR1 evolution using population genomic datasets of extant humans, eight populations of great apes, and two archaic human genome sequences. Results We find that PAR1 is fast evolving and closer to evolutionary nucleotide equilibrium than autosomal telomeres. We detect a difference between substitution patterns and extant diversity in PAR1, mainly driven by the conflict between strong mutation and recombination-associated fixation bias at CpG sites. We detect excess C-to-G mutations in PAR1 of all great apes, specific to the mutagenic effect of male recombination. Despite recent evidence for Y chromosome introgression from humans into Neanderthals, we find that the Neanderthal PAR1 retained similarity to the Denisovan sequence. We find differences between substitution spectra of these archaics suggesting rapid evolution of PAR1 in recent hominin history. Frequency analysis of alleles segregating in females and males provided no evidence for recent sexual antagonism in this region. We study repeat content and double-strand break hotspot regions in PAR1 and find that they may play roles in ensuring the obligate X-Y recombination event during male meiosis. Conclusions Our study provides an unprecedented quantification of population genetic forces governing PAR1 biology across extant and extinct hominids. PAR1 evolutionary dynamics are predominantly governed by recombination processes with a strong impact on mutation patterns across all species. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-022-02784-x.
Collapse
Affiliation(s)
- Juraj Bergman
- Bioinformatics Research Centre, Aarhus University, DK-8000, Aarhus C, Denmark.
| | | |
Collapse
|
40
|
Lyu R, Tsui V, Crismani W, Liu R, Shim H, McCarthy D. sgcocaller and comapr: personalised haplotype assembly and comparative crossover map analysis using single-gamete sequencing data. Nucleic Acids Res 2022; 50:e118. [PMID: 36107768 PMCID: PMC9723612 DOI: 10.1093/nar/gkac764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 08/17/2022] [Accepted: 09/06/2022] [Indexed: 12/24/2022] Open
Abstract
Profiling gametes of an individual enables the construction of personalised haplotypes and meiotic crossover landscapes, now achievable at larger scale than ever through the availability of high-throughput single-cell sequencing technologies. However, high-throughput single-gamete data commonly have low depth of coverage per gamete, which challenges existing gamete-based haplotype phasing methods. In addition, haplotyping a large number of single gametes from high-throughput single-cell DNA sequencing data and constructing meiotic crossover profiles using existing methods requires intensive processing. Here, we introduce efficient software tools for the essential tasks of generating personalised haplotypes and calling crossovers in gametes from single-gamete DNA sequencing data (sgcocaller), and constructing, visualising, and comparing individualised crossover landscapes from single gametes (comapr). With additional data pre-possessing, the tools can also be applied to bulk-sequenced samples. We demonstrate that sgcocaller is able to generate impeccable phasing results for high-coverage datasets, on which it is more accurate and stable than existing methods, and also performs well on low-coverage single-gamete sequencing datasets for which current methods fail. Our tools achieve highly accurate results with user-friendly installation, comprehensive documentation, efficient computation times and minimal memory usage.
Collapse
Affiliation(s)
- Ruqian Lyu
- Bioinformatics and Cellular Genomics, St Vincent’s Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia,Melbourne Integrative Genomics/School of Mathematics and Statistics, Faculty of Science, The University of Melbourne, Building 184, Royal Parade, Parkville, Victoria 3010, Australia
| | - Vanessa Tsui
- DNA Repair and Recombination Laboratory, St Vincent’s Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia,The Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Wayne Crismani
- DNA Repair and Recombination Laboratory, St Vincent’s Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia,The Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Ruijie Liu
- Bioinformatics and Cellular Genomics, St Vincent’s Institute of Medical Research, 9 Princes Street, Fitzroy, Victoria 3065, Australia
| | | | - Davis J McCarthy
- To whom correspondence should be addressed. Tel: +61 3 9231 2480; Fax: +61 3 9416 2676;
| |
Collapse
|
41
|
Samuk K, Noor MAF. Gene flow biases population genetic inference of recombination rate. G3 GENES|GENOMES|GENETICS 2022; 12:6698695. [PMID: 36103705 PMCID: PMC9635666 DOI: 10.1093/g3journal/jkac236] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 08/30/2022] [Indexed: 11/21/2022]
Abstract
Accurate estimates of the rate of recombination are key to understanding a host of evolutionary processes as well as the evolution of the recombination rate itself. Model-based population genetic methods that infer recombination rates from patterns of linkage disequilibrium in the genome have become a popular method to estimate rates of recombination. However, these linkage disequilibrium-based methods make a variety of simplifying assumptions about the populations of interest that are often not met in natural populations. One such assumption is the absence of gene flow from other populations. Here, we use forward-time population genetic simulations of isolation-with-migration scenarios to explore how gene flow affects the accuracy of linkage disequilibrium-based estimators of recombination rate. We find that moderate levels of gene flow can result in either the overestimation or underestimation of recombination rates by up to 20–50% depending on the timing of divergence. We also find that these biases can affect the detection of interpopulation differences in recombination rate, causing both false positives and false negatives depending on the scenario. We discuss future possibilities for mitigating these biases and recommend that investigators exercise caution and confirm that their study populations meet assumptions before deploying these methods.
Collapse
Affiliation(s)
- Kieran Samuk
- Department of Biology, Duke University , Durham, NC 27708, USA
- Department of Evolution, Ecology, and Organismal Biology, The University of California, Riverside ,Riverside, CA 92521, USA
| | | |
Collapse
|
42
|
Setter D, Ebdon S, Jackson B, Lohse K. Estimating the rates of crossover and gene conversion from individual genomes. Genetics 2022; 222:iyac100. [PMID: 35771626 PMCID: PMC9434185 DOI: 10.1093/genetics/iyac100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 06/01/2022] [Indexed: 11/14/2022] Open
Abstract
Recombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the 2 processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We present heRho, a simple composite likelihood scheme for coestimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at 2 loci. We apply heRho to simulations and data from the house mouse Mus musculus castaneus, a well-studied model. Our analyses show (1) that the rates of crossover and gene conversion can be accurately coestimated at the level of individual chromosomes and (2) that previous estimates of the population scaled rate of recombination ρ=4Ner under a pure crossover model are likely biased.
Collapse
Affiliation(s)
- Derek Setter
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Sam Ebdon
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Ben Jackson
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Konrad Lohse
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| |
Collapse
|
43
|
van Eeden G, Uren C, Pless E, Mastoras M, van der Spuy GD, Tromp G, Henn BM, Möller M. The recombination landscape of the Khoe-San likely represents the upper limits of recombination divergence in humans. Genome Biol 2022; 23:172. [PMID: 35945619 PMCID: PMC9361568 DOI: 10.1186/s13059-022-02744-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 08/01/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Recombination maps are important resources for epidemiological and evolutionary analyses; however, there are currently no recombination maps representing any African population outside of those with West African ancestry. We infer the demographic history for the Nama, an indigenous Khoe-San population of southern Africa, and derive a novel, population-specific recombination map from the whole genome sequencing of 54 Nama individuals. We hypothesise that there are no publicly available recombination maps representative of the Nama, considering the deep population divergence and subsequent isolation of the Khoe-San from other African groups. RESULTS We show that the recombination landscape of the Nama does not cluster with any continental groups with publicly available representative recombination maps. Finally, we use selection scans as an example of how fine-scale differences between the Nama recombination map and the combined Phase II HapMap recombination map can impact the outcome of selection scans. CONCLUSIONS Fine-scale differences in recombination can meaningfully alter the results of a selection scan. The recombination map we infer likely represents an upper bound on the extent of divergence we expect to see for a recombination map in humans and would be of interest to any researcher that wants to test the sensitivity of population genetic or GWAS analysis to recombination map input.
Collapse
Affiliation(s)
- Gerald van Eeden
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Caitlin Uren
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, 7602 South Africa
| | - Evlyn Pless
- Department of Anthropology, Center for Population Biology and the Genome Center, University of California (UC) Davis, Davis, CA USA
| | - Mira Mastoras
- Department of Anthropology, Center for Population Biology and the Genome Center, University of California (UC) Davis, Davis, CA USA
| | - Gian D. van der Spuy
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, 7602 South Africa
- SAMRC-SHIP South African Tuberculosis Bioinformatics Initiative (SATBBI), Center for Bioinformatics and Computational Biology, Cape Town, South Africa
| | - Gerard Tromp
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, 7602 South Africa
- SAMRC-SHIP South African Tuberculosis Bioinformatics Initiative (SATBBI), Center for Bioinformatics and Computational Biology, Cape Town, South Africa
| | - Brenna M. Henn
- Department of Anthropology, Center for Population Biology and the Genome Center, University of California (UC) Davis, Davis, CA USA
| | - Marlo Möller
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
- Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, 7602 South Africa
| |
Collapse
|
44
|
Booker TR, Payseur BA, Tigano A. Background selection under evolving recombination rates. Proc Biol Sci 2022; 289:20220782. [PMID: 35730151 PMCID: PMC9233929 DOI: 10.1098/rspb.2022.0782] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Background selection (BGS), the effect that purifying selection exerts on sites linked to deleterious alleles, is expected to be ubiquitous across eukaryotic genomes. The effects of BGS reflect the interplay of the rates and fitness effects of deleterious mutations with recombination. A fundamental assumption of BGS models is that recombination rates are invariant over time. However, in some lineages, recombination rates evolve rapidly, violating this central assumption. Here, we investigate how recombination rate evolution affects genetic variation under BGS. We show that recombination rate evolution modifies the effects of BGS in a manner similar to a localized change in the effective population size, potentially leading to underestimation or overestimation of the genome-wide effects of selection. Furthermore, we find evidence that recombination rate evolution in the ancestors of modern house mice may have impacted inferences of the genome-wide effects of selection in that species.
Collapse
Affiliation(s)
- Tom R. Booker
- Department of Zoology, University of British Columbia, Vancouver Campus, Vancouver, BC, Canada
| | - Bret A. Payseur
- Laboratory of Genetics, University of Wisconsin - Madison, Madison, WI, USA
| | - Anna Tigano
- Department of Biology, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada
| |
Collapse
|
45
|
Schreiber M, Gao Y, Koch N, Fuchs J, Heckmann S, Himmelbach A, Börner A, Özkan H, Maurer A, Stein N, Mascher M, Dreissig S. Recombination landscape divergence between populations is marked by larger low-recombining regions in domesticated rye. Mol Biol Evol 2022; 39:msac131. [PMID: 35687854 PMCID: PMC9218680 DOI: 10.1093/molbev/msac131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 06/03/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
The genomic landscape of recombination plays an essential role in evolution. Patterns of recombination are highly variable along chromosomes, between sexes, individuals, populations, and species. In many eukaryotes, recombination rates are elevated in sub-telomeric regions and drastically reduced near centromeres, resulting in large low-recombining (LR) regions. The processes of recombination are influenced by genetic factors, such as different alleles of genes involved in meiosis and chromatin structure, as well as external environmental stimuli like temperature and overall stress. In this work, we focused on the genomic landscapes of recombination in a collection of 916 rye (Secale cereale) individuals. By analysing population structure among individuals of different domestication status and geographic origin, we detected high levels of admixture, reflecting the reproductive biology of a self-incompatible, wind-pollinating grass species. We then analysed patterns of recombination in overlapping subpopulations, which revealed substantial variation in the physical size of LR regions, with a tendency for larger LR regions in domesticated subpopulations. Genome-wide association scans (GWAS) for LR region size revealed a major quantitative-trait-locus (QTL) at which, among 18 annotated genes, an ortholog of histone H4 acetyltransferase ESA1 was located. Rye individuals belonging to domesticated subpopulations showed increased synaptonemal complex length, but no difference in crossover frequency, indicating that only the recombination landscape is different. Furthermore, the genomic region harbouring rye ScESA1 showed moderate patterns of selection in domesticated subpopulations, suggesting that larger LR regions were indirectly selected for during domestication to achieve more homogeneous populations for agricultural use.
Collapse
Affiliation(s)
- Mona Schreiber
- Department of Biology, University of Marburg, 35037 Marburg, Germany
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
| | - Yixuan Gao
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Natalie Koch
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Joerg Fuchs
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
| | - Stefan Heckmann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
| | - Andreas Börner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
| | - Hakan Özkan
- Faculty of Agriculture, Department of Field Crops, University of Cukurova, 01330 Adana, Turkey
| | - Andreas Maurer
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Seeland, OT Gatersleben, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
| | - Steven Dreissig
- Institute of Agricultural and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, 06120 Halle (Saale), Germany
| |
Collapse
|
46
|
Soni V, Vos M, Eyre-Walker A. A new test suggests hundreds of amino acid polymorphisms in humans are subject to balancing selection. PLoS Biol 2022; 20:e3001645. [PMID: 35653351 PMCID: PMC9162324 DOI: 10.1371/journal.pbio.3001645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 04/25/2022] [Indexed: 11/18/2022] Open
Abstract
The role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here, we introduce a new test, based on the McDonald–Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and provide some evidence that hundreds of nonsynonymous polymorphisms are subject to balancing selection.
Collapse
Affiliation(s)
- Vivak Soni
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
| | - Michiel Vos
- European Centre for Environment and Human Health, University of Exeter Medical School, Environment and Sustainability Institute, Penryn, United Kingdom
| | - Adam Eyre-Walker
- School of Life Sciences, University of Sussex, Brighton, United Kingdom
- * E-mail:
| |
Collapse
|
47
|
Li Y, Chen S, Rapakoulia T, Kuwahara H, Yip KY, Gao X. Deep learning identifies and quantifies recombination hotspot determinants. Bioinformatics 2022; 38:2683-2691. [PMID: 35561158 PMCID: PMC9113300 DOI: 10.1093/bioinformatics/btac234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 03/08/2022] [Accepted: 04/08/2022] [Indexed: 11/30/2022] Open
Abstract
MOTIVATION Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species. RESULTS RHSNet can significantly outperform other sequence-based methods on multiple datasets across different species, sexes and studies. In addition to being able to identify hotspot regions and the well-known determinants accurately, more importantly, RHSNet can quantify the determinants that contribute significantly to the recombination hotspot formation in the relation between PRDM9 binding motif, histone modification and GC content. Further cross-sex, cross-population and cross-species studies suggest that the proposed method has the generalization power and potential to identify and quantify the evolutionary determinant motifs. AVAILABILITY AND IMPLEMENTATION https://github.com/frankchen121212/RHSNet. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Yu Li
- To whom correspondence should be addressed. or
| | | | | | - Hiroyuki Kuwahara
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia
- KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia
| | - Kevin Y Yip
- Department of Computer Science and Engineering (CSE), The Chinese University of Hong Kong (CUHK), 999077, Hong Kong SAR, China
| | - Xin Gao
- To whom correspondence should be addressed. or
| |
Collapse
|
48
|
Li J, Llorente B, Liti G, Yue JX. RecombineX: A generalized computational framework for automatic high-throughput gamete genotyping and tetrad-based recombination analysis. PLoS Genet 2022; 18:e1010047. [PMID: 35533184 PMCID: PMC9119626 DOI: 10.1371/journal.pgen.1010047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 05/19/2022] [Accepted: 04/14/2022] [Indexed: 01/09/2023] Open
Abstract
Meiotic recombination is an essential biological process that ensures faithful chromosome segregation and promotes parental allele shuffling. Tetrad analysis is a powerful approach to quantify the genetic makeups and recombination landscapes of meiotic products. Here we present RecombineX (https://github.com/yjx1217/RecombineX), a generalized computational framework that automates the full workflow of marker identification, gamete genotyping, and tetrad-based recombination profiling based on any organism or genetic background with batch processing capability. Aside from conventional reference-based analysis, RecombineX can also perform analysis based on parental genome assemblies, which facilitates analyzing meiotic recombination landscapes in their native genomic contexts. Additional features such as copy number variation profiling and missing genotype inference further enhance downstream analysis. RecombineX also includes a dedicate module for simulating the genomes and reads of recombinant tetrads, which enables fine-tuned simulation-based hypothesis testing. This simulation module revealed the power and accuracy of RecombineX even when analyzing tetrads with very low sequencing depths (e.g., 1-2X). Tetrad sequencing data from the budding yeast Saccharomyces cerevisiae and green alga Chlamydomonas reinhardtii were further used to demonstrate the accuracy and robustness of RecombineX for organisms with both small and large genomes, manifesting RecombineX as an all-around one stop solution for future tetrad analysis. Interestingly, our re-analysis of the budding yeast tetrad sequencing data with RecombineX and Oxford Nanopore sequencing revealed two unusual structural rearrangement events that were not noticed before, which exemplify the occasional genome instability triggered by meiosis.
Collapse
Affiliation(s)
- Jing Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- Université Côte d’Azur, CNRS, INSERM, IRCAN, Nice, France
| | - Bertrand Llorente
- Aix-Marseille Université, CNRS, INSERM, CRCM, Institut Paoli-Calmettes, Marseille, France
| | - Gianni Liti
- Université Côte d’Azur, CNRS, INSERM, IRCAN, Nice, France
- * E-mail: (GL); (JXY)
| | - Jia-Xing Yue
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
- Université Côte d’Azur, CNRS, INSERM, IRCAN, Nice, France
- * E-mail: (GL); (JXY)
| |
Collapse
|
49
|
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: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [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
| |
Collapse
|
50
|
Otto M, Zheng Y, Wiehe T. Recombination, selection and the evolution of tandem gene arrays. Genetics 2022; 221:6572811. [PMID: 35460227 PMCID: PMC9252282 DOI: 10.1093/genetics/iyac052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 03/17/2022] [Indexed: 11/16/2022] Open
Abstract
Multigene families—immunity genes or sensory receptors, for instance—are often subject to diversifying selection. Allelic diversity may be favored not only through balancing or frequency-dependent selection at individual loci but also by associating different alleles in multicopy gene families. Using a combination of analytical calculations and simulations, we explored a population genetic model of epistatic selection and unequal recombination, where a trade-off exists between the benefit of allelic diversity and the cost of copy abundance. Starting from the neutral case, where we showed that gene copy number is Gamma distributed at equilibrium, we derived also the mean and shape of the limiting distribution under selection. Considering a more general model, which includes variable population size and population substructure, we explored by simulations mean fitness and some summary statistics of the copy number distribution. We determined the relative effects of selection, recombination, and demographic parameters in maintaining allelic diversity and shaping the mean fitness of a population. One way to control the variance of copy number is by lowering the rate of unequal recombination. Indeed, when encoding recombination by a rate modifier locus, we observe exactly this prediction. Finally, we analyzed the empirical copy number distribution of 3 genes in human and estimated recombination and selection parameters of our model.
Collapse
Affiliation(s)
- Moritz Otto
- Institut für Genetik, Universität zu Köln, Zülpicher Straße 47a, 50674 Köln, Germany
| | - Yichen Zheng
- Institut für Genetik, Universität zu Köln, Zülpicher Straße 47a, 50674 Köln, Germany
| | - Thomas Wiehe
- Institut für Genetik, Universität zu Köln, Zülpicher Straße 47a, 50674 Köln, Germany
| |
Collapse
|