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Kekäläinen J. Genetic incompatibility of the reproductive partners: an evolutionary perspective on infertility. Hum Reprod 2021; 36:3028-3035. [PMID: 34580729 PMCID: PMC8600657 DOI: 10.1093/humrep/deab221] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/22/2021] [Indexed: 12/18/2022] Open
Abstract
In natural fertilisation, the female reproductive tract allows only a strictly selected sperm subpopulation to proceed in the vicinity of an unfertilised oocyte. Female-mediated sperm selection (also known as cryptic female choice (CFC)) is far from a random process, which frequently biases paternity towards particular males over others. Earlier studies have shown that CFC is a ubiquitous phenomenon in the animal kingdom and often promotes assortative fertilisation between genetically compatible mates. Here, I demonstrate that CFC for genetic compatibility likely also occurs in humans and is mediated by a complex network of interacting male and female genes. I also show that the relative contribution of genetic compatibility (i.e. the male-female interaction effect) to reproductive success is generally high and frequently outweighs the effects of individual males and females. Together, these facts indicate that, along with male- and female-dependent pathological factors, reproductive failure can also result from gamete-level incompatibility of the reproductive partners. Therefore, I argue that a deeper understanding of these evolutionary mechanisms of sperm selection can pave the way towards a more inclusive view of infertility and open novel possibilities for the development of more personalised infertility diagnostics and treatments.
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Affiliation(s)
- Jukka Kekäläinen
- Department of Environmental and Biological Sciences, University of Eastern Finland, Joensuu, Finland
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Abstract
Throughout human history, large-scale migrations have facilitated the formation of populations with ancestry from multiple previously separated populations. This process leads to subsequent shuffling of genetic ancestry through recombination, producing variation in ancestry between populations, among individuals in a population, and along the genome within an individual. Recent methodological and empirical developments have elucidated the genomic signatures of this admixture process, bringing previously understudied admixed populations to the forefront of population and medical genetics. Under this theme, we present a collection of recent PLOS Genetics publications that exemplify recent progress in human genetic admixture studies, and we discuss potential areas for future work.
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Affiliation(s)
- Katharine L. Korunes
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina, United States of America
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina, United States of America
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Ni X, Zhou M, Wang H, He KY, Broeckel U, Hanis C, Kardia S, Redline S, Cooper RS, Tang H, Zhu X. Detecting fitness epistasis in recently admixed populations with genome-wide data. BMC Genomics 2020; 21:476. [PMID: 32652930 PMCID: PMC7353720 DOI: 10.1186/s12864-020-06874-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 06/30/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population. RESULTS We developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value< 8.11 × 10- 7) on chromosomes 1 and 10. The ancestral correlations were not explained by population admixture. Historical African-European crossover events are reduced between pairs of epistatic regions. We observed multiple pairs of co-expressed genes shared by the two regions on each chromosome, including ADAR being co-expressed with IFI44 in almost all tissues and DARC being co-expressed with VCAM1, S1PR1 and ELTD1 in multiple tissues in the Genotype-Tissue Expression (GTEx) data. Moreover, the co-expressed gene pairs are associated with the same diseases/traits in the GWAS Catalog, such as white blood cell count, blood pressure, lung function, inflammatory bowel disease and educational attainment. CONCLUSIONS Our analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.
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Affiliation(s)
- Xumin Ni
- Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing, 100044, China
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Mengshi Zhou
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Uli Broeckel
- Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Craig Hanis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Sharon Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Richard S Cooper
- Department of Public Health Science, Loyola University Medical Center, Maywood, IL, USA
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.
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Abstract
Local ancestry, defined as the genetic ancestry at a genomic location of an admixed individual, is widely used as a genetic marker in genetic association and evolutionary genetics studies. Many methods have been developed to infer the local ancestries in a set of unrelated individuals, a few of them have been extended to small nuclear families, but none can be applied to large (e.g. three-generation) pedigrees. In this study, we developed a method, FamANC, that can improve the accuracy of local ancestry inference in large pedigrees by: (1) using an existing algorithm to infer local ancestries for all individuals in a family, assuming (contrary to fact) they are unrelated, and (2) improving its accuracy by correcting inference errors using pedigree structure. Applied on African-American pedigrees from the Cleveland Family Study, FamANC was able to correct all identified Mendelian errors and most of double crossovers.
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Hart MW, Stover DA, Guerra V, Mozaffari SV, Ober C, Mugal CF, Kaj I. Positive selection on human gamete-recognition genes. PeerJ 2018; 6:e4259. [PMID: 29340252 PMCID: PMC5767332 DOI: 10.7717/peerj.4259] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Accepted: 12/21/2017] [Indexed: 01/29/2023] Open
Abstract
Coevolution of genes that encode interacting proteins expressed on the surfaces of sperm and eggs can lead to variation in reproductive compatibility between mates and reproductive isolation between members of different species. Previous studies in mice and other mammals have focused in particular on evidence for positive or diversifying selection that shapes the evolution of genes that encode sperm-binding proteins expressed in the egg coat or zona pellucida (ZP). By fitting phylogenetic models of codon evolution to data from the 1000 Genomes Project, we identified candidate sites evolving under diversifying selection in the human genes ZP3 and ZP2. We also identified one candidate site under positive selection in C4BPA, which encodes a repetitive protein similar to the mouse protein ZP3R that is expressed in the sperm head and binds to the ZP at fertilization. Results from several additional analyses that applied population genetic models to the same data were consistent with the hypothesis of selection on those candidate sites leading to coevolution of sperm- and egg-expressed genes. By contrast, we found no candidate sites under selection in a fourth gene (ZP1) that encodes an egg coat structural protein not directly involved in sperm binding. Finally, we found that two of the candidate sites (in C4BPA and ZP2) were correlated with variation in family size and birth rate among Hutterite couples, and those two candidate sites were also in linkage disequilibrium in the same Hutterite study population. All of these lines of evidence are consistent with predictions from a previously proposed hypothesis of balancing selection on epistatic interactions between C4BPA and ZP3 at fertilization that lead to the evolution of co-adapted allele pairs. Such patterns also suggest specific molecular traits that may be associated with both natural reproductive variation and clinical infertility.
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Affiliation(s)
- Michael W Hart
- Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Daryn A Stover
- School of Mathematical and Natural Sciences, Arizona State University Colleges at Lake Havasu City, Lake Havasu City, AZ, USA
| | - Vanessa Guerra
- Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Sahar V Mozaffari
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Carina F Mugal
- Department of Ecology and Genetics, Uppsala University, Uppsala, Sweden
| | - Ingemar Kaj
- Department of Mathematics, Uppsala University, Uppsala, Sweden
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Graur D. An Upper Limit on the Functional Fraction of the Human Genome. Genome Biol Evol 2017; 9:1880-1885. [PMID: 28854598 PMCID: PMC5570035 DOI: 10.1093/gbe/evx121] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/06/2017] [Indexed: 12/13/2022] Open
Abstract
For the human population to maintain a constant size from generation to generation, an increase in fertility must compensate for the reduction in the mean fitness of the population caused, among others, by deleterious mutations. The required increase in fertility due to this mutational load depends on the number of sites in the genome that are functional, the mutation rate, and the fraction of deleterious mutations among all mutations in functional regions. These dependencies and the fact that there exists a maximum tolerable replacement level fertility can be used to put an upper limit on the fraction of the human genome that can be functional. Mutational load considerations lead to the conclusion that the functional fraction within the human genome cannot exceed 15%.
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Affiliation(s)
- Dan Graur
- Department of Biology and Biochemistry, University of Houston, TX
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