@article{21841, abstract = {The long-standing notion that genotypes map to phenotypes through simple one gene–one trait relationships continues to shape both research in the life sciences and public understanding, with implications for policy and funding priorities. Yet this paradigm is increasingly recognized as inadequate for explaining continuous phenotypic variation and the complex genetic architectures of the genotype–phenotype map. Modern genetics emerged from the early 20th-century synthesis of Mendelian and biometric schools of heredity, with R.A. Fisher demonstrating early on how multiple discrete loci could collectively produce continuous variation. Despite this fundamental insight, Mendelism—with its focus on single genes and standardized genetic backgrounds—became the dominant framework, shaping current genetics research and molecular biology as well as science education. The advent of large-scale genomic data has revealed yet again the limitations of this reductionist approach. Evidence from quantitative genetics now shows that most phenotypes arise from complex networks of many interdependent genes and their dynamic responses to environmental perturbations. Here we trace the historical roots of how Mendelian classical genetics departed from the biometric school to create the current predominant paradigm in genetics, despite fundamentally unresolved issues. Moving on from this one-sided paradigm will require systematic development of integrative, evolutionarily grounded experimental approaches that better capture the multigenic and context-dependent nature of inheritance. Achieving such an extended perspective will require methodological innovation, including advances in large-scale (e.g. automated) phenotyping. Dedicated research programs will be necessary to advance a new era of genetic research into the complex mechanisms underlying phenotypic variation.}, author = {Tautz, Diethard and Pallares, Luisa F and Andersson, Leif and Barghi, Neda and Barton, Nicholas H and Bay, Rachael and Chan, Yingguang Frank and Hancock, Angela and Kaiser, Tobias S and Koenig, Daniel and Kontarakis, Zacharias and Liedvogel, Miriam and de Meaux, Juliette and Nordborg, Magnus and Palmer, Abraham A and Purugganan, Michael and Schlötterer, Christian and Schmid, Karl and Stainier, Didier Y R and Weigel, Detlef and Wolf, Jochen B W and Ebert, Dieter and Gibson, Greg}, issn = {1943-2631}, journal = {Genetics}, keywords = {classic genetics, quantitative genetics, genotype–phenotype map}, number = {4}, publisher = {Oxford University Press}, title = {{Beyond Mendel: A call to revisit the genotype–phenotype map through new experimental paradigms}}, doi = {10.1093/genetics/iyag024}, volume = {232}, year = {2026}, } @article{20848, abstract = {Genetic variation that influences complex disease susceptibility is introduced into the population by mutation and removed by natural selection and genetic drift. This mutation–selection–drift balance (MSDB) shapes the prevalence of a disease and its genetic architecture. To date, however, MSDB has been modeled only for monogenic (Mendelian) diseases. Here, we develop an MSDB model for complex disease susceptibility: we assume that genotype relates to disease risk according to the canonical liability threshold model and that the selection on variants affecting risk stems from the fitness cost of the disease. We focus on diseases that are highly polygenic, entail a substantial fitness cost, and are neither extremely common in the population nor exceedingly rare. The comparison of model predictions with genome-wide association studies and other observations in humans indicates that common genetic variation affecting complex disease susceptibility is little affected by directional selection and instead shaped by pleiotropic stabilizing selection on other traits. In turn, directional selection may exert a more substantial effect on rare, large-effect variants. Our results also suggest that current estimates of disease heritability are likely biased. The model thus provides a better understanding of the evolutionary processes that shape the architecture and prevalence of complex diseases.}, author = {Berg, Jeremy J. and Li, Xinyi and Riall, Kellen and Hayward, Laura and Sella, Guy}, issn = {1943-2631}, journal = {Genetics}, number = {4}, publisher = {Oxford University Press}, title = {{Mutation–selection–drift balance models of complex diseases}}, doi = {10.1093/genetics/iyaf220}, volume = {231}, year = {2025}, } @article{18936, abstract = {A major obstacle to predictive understanding of evolution stems from the complexity of biological systems, which prevents detailed characterization of key evolutionary properties. Here, we highlight some of the major sources of complexity that arise when relating molecular mechanisms to their evolutionary consequences and ask whether accounting for every mechanistic detail is important to accurately predict evolutionary outcomes. To do this, we developed a mechanistic model of a bacterial promoter regulated by 2 proteins, allowing us to connect any promoter genotype to 6 phenotypes that capture the dynamics of gene expression following an environmental switch. Accounting for the mechanisms that govern how this system works enabled us to provide an in-depth picture of how regulated bacterial promoters might evolve. More importantly, we used the model to explore which factors that contribute to the complexity of this system are essential for understanding its evolution, and which can be simplified without information loss. We found that several key evolutionary properties—the distribution of phenotypic and fitness effects of mutations, the evolutionary trajectories during selection for regulation—can be accurately captured without accounting for all, or even most, parameters of the system. Our findings point to the need for a mechanistic approach to studying evolution, as it enables tackling biological complexity and in doing so improves the ability to predict evolutionary outcomes.}, author = {Grah, Rok and Guet, Calin C and Tkačik, Gašper and Lagator, Mato}, issn = {1943-2631}, journal = {Genetics}, number = {2}, publisher = {Oxford University Press}, title = {{Linking molecular mechanisms to their evolutionary consequences: a primer}}, doi = {10.1093/genetics/iyae191}, volume = {229}, year = {2025}, } @article{14452, abstract = {The classical infinitesimal model is a simple and robust model for the inheritance of quantitative traits. In this model, a quantitative trait is expressed as the sum of a genetic and an environmental component, and the genetic component of offspring traits within a family follows a normal distribution around the average of the parents’ trait values, and has a variance that is independent of the parental traits. In previous work, we showed that when trait values are determined by the sum of a large number of additive Mendelian factors, each of small effect, one can justify the infinitesimal model as a limit of Mendelian inheritance. In this paper, we show that this result extends to include dominance. We define the model in terms of classical quantities of quantitative genetics, before justifying it as a limit of Mendelian inheritance as the number, M, of underlying loci tends to infinity. As in the additive case, the multivariate normal distribution of trait values across the pedigree can be expressed in terms of variance components in an ancestral population and probabilities of identity by descent determined by the pedigree. Now, with just first-order dominance effects, we require two-, three-, and four-way identities. We also show that, even if we condition on parental trait values, the “shared” and “residual” components of trait values within each family will be asymptotically normally distributed as the number of loci tends to infinity, with an error of order 1/M−−√⁠. We illustrate our results with some numerical examples.}, author = {Barton, Nicholas H and Etheridge, Alison M. and Véber, Amandine}, issn = {1943-2631}, journal = {Genetics}, number = {2}, publisher = {Oxford University Press}, title = {{The infinitesimal model with dominance}}, doi = {10.1093/genetics/iyad133}, volume = {225}, year = {2023}, } @article{11411, abstract = {Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but few have examined the demographic processes driving these patterns. In this study, we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of the self-incompatible plant Antirrhinum majus. Excess variance in heterozygosity between individuals is due to identity disequilibrium, which reflects the variance in inbreeding between individuals; it is measured by the statistic g2. We calculated g2 together with FST and pairwise relatedness (Fij) using 91 SNPs in 22,353 individuals collected over 11 years. We find that pairwise Fij declines rapidly over short spatial scales, and the excess variance in heterozygosity between individuals reflects significant variation in inbreeding. Additionally, we detect an excess of individuals with around half the average heterozygosity, indicating either selfing or matings between close relatives. We use 2 types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g2. Second, we simulate a 1,000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity.}, author = {Surendranadh, Parvathy and Arathoon, Louise S and Baskett, Carina and Field, David and Pickup, Melinda and Barton, Nicholas H}, issn = {1943-2631}, journal = {Genetics}, number = {3}, publisher = {Oxford University Press}, title = {{Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus}}, doi = {10.1093/genetics/iyac083}, volume = {221}, year = {2022}, } @article{7400, abstract = {Suppressed recombination allows divergence between homologous sex chromosomes and the functionality of their genes. Here, we reveal patterns of the earliest stages of sex-chromosome evolution in the diploid dioecious herb Mercurialis annua on the basis of cytological analysis, de novo genome assembly and annotation, genetic mapping, exome resequencing of natural populations, and transcriptome analysis. The genome assembly contained 34,105 expressed genes, of which 10,076 were assigned to linkage groups. Genetic mapping and exome resequencing of individuals across the species range both identified the largest linkage group, LG1, as the sex chromosome. Although the sex chromosomes of M. annua are karyotypically homomorphic, we estimate that about one-third of the Y chromosome, containing 568 transcripts and spanning 22.3 cM in the corresponding female map, has ceased recombining. Nevertheless, we found limited evidence for Y-chromosome degeneration in terms of gene loss and pseudogenization, and most X- and Y-linked genes appear to have diverged in the period subsequent to speciation between M. annua and its sister species M. huetii, which shares the same sex-determining region. Taken together, our results suggest that the M. annua Y chromosome has at least two evolutionary strata: a small old stratum shared with M. huetii, and a more recent larger stratum that is probably unique to M. annua and that stopped recombining ∼1 MYA. Patterns of gene expression within the nonrecombining region are consistent with the idea that sexually antagonistic selection may have played a role in favoring suppressed recombination.}, author = {Veltsos, Paris and Ridout, Kate E. and Toups, Melissa A and González-Martínez, Santiago C. and Muyle, Aline and Emery, Olivier and Rastas, Pasi and Hudzieczek, Vojtech and Hobza, Roman and Vyskot, Boris and Marais, Gabriel A. B. and Filatov, Dmitry A. and Pannell, John R.}, issn = {1943-2631}, journal = {Genetics}, number = {3}, pages = {815--835}, publisher = {Genetics Society of America}, title = {{Early sex-chromosome evolution in the diploid dioecious plant Mercurialis annua}}, doi = {10.1534/genetics.119.302045}, volume = {212}, year = {2019}, } @article{4251, abstract = {In finite populations subject to selection, genetic drift generates negative linkage disequilibrium, on average, even if selection acts independently (i.e. multiplicatively) upon all loci. Negative disequilibrium reduces the variance in fitness and hence, by FISHER's Fundamental Theorem (1930), slows the rate of increase in mean fitness. Modifiers that increase recombination eliminate the negative disequilibria that impede selection and consequently increase in frequency by 'hitch-hiking'. In addition, recombinant progeny are more fit on average than non-recombinant progeny when there is negative linkage disequilibrium and loci interact multiplicatively. For both these reasons, stochastic fluctuations in linkage disequilibrium in finite populations favor the evolution of increased rates of recombination, even in the absence of epistatic interactions among loci and even when disequilibrium is initially absent. The method developed within this paper quantifies the strength of selection on a modifier allele that increases recombination due to stochastically generated linkage disequilibria. The analysis indicates that, in a population subject to multiplicative selection, genetic associations generated by drift do select for increased recombination, a result that is confirmed by Monte Carlo simulations. Selection for a modifier that increases recombination is highest when linkage among all loci is tight, when beneficial alleles rise from low to high frequency, and when the population size is small.}, author = {Barton, Nicholas H and Otto, Sarah}, issn = {1943-2631}, journal = {Genetics}, number = {4}, pages = {2353 -- 2370}, publisher = {Genetics Society of America}, title = {{Evolution of recombination due to random drift}}, doi = {10.1534/genetics.104.032821}, volume = {169}, year = {2005}, } @article{3151, abstract = {Biosynthesis of most peptide hormones and neuropeptides requires proteolytic excision of the active peptide from inactive proprotein precursors, an activity carried out by subtilisin-like proprotein convertases (SPCs) in constitutive or regulated secretory pathways. The Drosophila amontillado (amon) gene encodes a homolog of the mammalian PC2 protein, an SPC that functions in the regulated secretory pathway in neuroendocrine tissues. We have identified amon mutants by isolating ethylmethanesulfonate (EMS)-induced lethal and visible mutations that define two complementation groups in the amon interval at 97D1 of the third chromosome. DNA sequencing identified the amon complementation group and the DNA sequence change for each of the nine amon alleles isolated. amon mutants display partial embryonic lethality, are defective in larval growth, and arrest during the first to second instar larval molt. Mutant larvae can be rescued by heat-shock-induced expression of the amon protein. Rescued larvae arrest at the subsequent larval molt, suggesting that amon is also required for the second to third instar larval molt. Our data indicate that the amon proprotein convertase is required during embryogenesis and larval development in Drosophila and support the hypothesis that AMON acts to proteolytically process peptide hormones that regulate hatching, larval growth, and larval ecdysis.}, author = {Rayburn, Lowell and Gooding, Holly and Choksi, Semil and Maloney, Dhea and Kidd, Ambrose and Siekhaus, Daria E and Bender, Michael}, issn = {1943-2631}, journal = {Genetics}, number = {1}, pages = {227 -- 237}, publisher = {Oxford Academic}, title = {{Amontillado, the Drosophila homolog of the prohormone processing protease PC2, is required during embryogenesis and early larval development}}, doi = {10.1093/genetics/163.1.227}, volume = {163}, year = {2003}, }