The genetics of the many forms of diversity

Abstract

The Genetics Society of America Medal honors an individual member of the Society for their contributions to the field of genetics at the midcareer level (up to 15 years since starting an independent position). The society established the GSA Medal in 1981 to recognize members who exemplify the ingenuity of the GSA membership through elegant and highly meaningful contributions to modern genetics. Joseph Schacherer is being recognized for his impactful contributions to the field through the study of population genomics in the model Saccharomyces cerevisiae and other less well-studied species, the genetic basis and architecture of complex traits, and mitochondrial genome evolution in yeast. This award also celebrates Schacherer's work leading the 1000 Yeast Genomes Project, which has provided a reference framework for studying genetic diversity and domestication, and efforts to train and support a diverse group of early career scientists.

My first steps in genetics

When I look back on my scientific trajectory, I realize that the same question has followed me for as long as I can remember. From an early age, I was fascinated by the remarkable diversity of life. No two individuals seemed exactly alike. Plants growing side by side exhibited subtle differences, animals of the same species displayed distinct appearances and behaviors, and human populations revealed an almost unlimited range of variation. At the time, these observations were simply a source of curiosity. Much later, I would discover that understanding the origins of biological diversity is among the central questions of genetics.

As an undergraduate student at the Louis Pasteur University in France, I became deeply interested in genetics. What attracted me was not only the discipline itself but also the way in which it emerged. I was fascinated by the fact that the founders of genetics uncovered fundamental biological principles without any of the tools we now take for granted. Mendel knew nothing about DNA. Morgan had never seen a genome sequence. Muller had no access to molecular biology. In those early days, a conceptual framework of inheritance was established by taking advantage of the diversity found in nature: peas that are yellow or green, fruit flies with red or white eyes, and many more. Through carefully designed experiments, rigorous observation and elegant reasoning, these pioneers inferred the principles of inheritance while being blind to its molecular nature. Their work convinced me that genetics occupied a special place in biology, with a level of conceptual clarity that few disciplines can match.

My encounter with yeast was, by comparison, almost accidental. Like many students, I joined a laboratory for practical training without a clear idea of what model organism I would eventually work on. The laboratory happened to study S. cerevisiae and what started as a research internship quickly turned into a lasting interest. Yeast possessed a unique combination of qualities. It offered the elegance of classical genetics, the power of molecular biology, and increasingly, the opportunities of genomics (Botstein and Fink 2011). Experiments that would take months or years in other organisms could be carried out in days. More importantly, yeast can provide a precise path to addressing one of the questions that fascinated me most: how genetic variation generates phenotypic diversity. At the time, I did not realize that this question would become the central theme of my scientific trajectory.

My doctoral work with Jacky de Montigny introduced me to this problem through the study of gene duplication, one of the major evolutionary forces generating biological novelty and phenotypic diversity. Using a genetic selection system, I investigated the molecular mechanisms underlying spontaneous gene duplication events in yeast. Our work revealed that new functional gene copies could arise through a retroposition mechanism involving Ty1 retrotransposons, providing experimental evidence for how genomic rearrangements can generate novel genetic architectures and restore cellular functions (Schacherer et al. 2004, 2005). Although focused on a specific molecular process, this project exposed me to a much broader idea: phenotypic diversity is ultimately rooted in the dynamic nature of genomes. Changes in gene content, structure, and regulation continuously create new opportunities for evolutionary innovation.

At the same time, I was fortunate to carry out my PhD in an environment that was deeply engaged in one of the most ambitious genomics efforts of its time. The Génolevures consortium, led by Bernard Dujon, Jean-Luc Souciet, Claude Gaillardin, sought to move beyond a single yeast genome and explore genomic diversity across the Saccharomycotina subphylum (Souciet et al. 2000; Dujon et al. 2004; Génolevures Consortium 2009). For a young student, it was impossible not to be influenced by the excitement generated by these large-scale comparative genomics initiatives. They revealed that genomes are not static entities but highly dynamic evolutionary landscapes shaped by duplications, losses, and chromosomal rearrangements (Dujon 2006). Looking back, the coexistence of these two perspectives—the mechanistic study of genome evolution in my own project and the emerging comparative genomics view provided by the Génolevures consortium—was formative. Together, they convinced me that understanding biological diversity requires understanding genome diversity, a conviction that has guided my research ever since.

Toward a more quantitative view of genetics

One important intellectual turning point of my career occurred during my postdoctoral years at Princeton University. I joined Leonid Kruglyak's group at the Lewis-Sigler Institute, an environment that fundamentally transformed the way I thought about genetics. Until then, my scientific training had largely focused on classical genetics and molecular mechanisms. It was there that I really discovered quantitative genetics.

The Lewis-Sigler Institute was an extraordinary place. Physicists, computational scientists, and biologists interacted. New ideas seemed to emerge naturally from conversations in hallways, offices, and seminars. It was impossible not to be influenced by such an environment. Equally important was the vibrant yeast community that surrounded the institute. The joint meetings between the Kruglyak and Botstein laboratories remain among my strongest scientific memories. Every week brought intense discussions, new hypotheses, and new ways of thinking about biological problems. David Botstein had an extraordinary ability to make every experiment seem exciting and every question seem important, whether or not they truly were. His intellectual energy was contagious and one could not leave those meetings without feeling inspired.

When I arrived at Princeton, high-throughput sequencing was still in its infancy and obtaining genome-wide variation across many individuals remained impossible. At the time, David Gresham was developing an innovative approach based on whole-genome tiling arrays to detect mutations and polymorphisms at nucleotide resolution (Gresham et al. 2006). The method provided a powerful alternative to sequencing and opened the door to population-scale studies of genetic variation. This approach made it possible to explore the natural diversity of S. cerevisiae at an unprecedented scale. I eagerly embraced this opportunity and led a survey of diverse natural and domesticated yeast isolates, which provided one of the first genome-wide views of population structure and genetic diversity in S. cerevisiae (Schacherer et al. 2007, 2009).

In fact, it was there that I first met many of the researchers who would later become long-term collaborators and friends. Matt Rockman, Erin Smith, Joshua Shapiro, Maitreya Dunham, Viktor Boer, David Hess, and many others contributed to a remarkably stimulating environment in which ideas circulated freely and collaborations emerged naturally. In retrospect, I realize that this period taught me something far more important than any analytical approach or specific technique. It taught me that science advances through discussion, exchange, and collaboration. The most exciting ideas rarely emerge in isolation but they grow through interactions with colleagues who challenge assumptions, share perspectives, and collectively push the field forward.

The making of the HaploTeam

The transition to independence was both exciting and challenging. Like many young principal investigators, I quickly discovered that establishing a research group required far more than developing scientific ideas. A substantial part of my time was devoted to teaching genetics, which I enjoyed, but balancing that with the demands of building a group often felt overwhelming. There were moments when I was not entirely sure how the group would survive its early years. What ultimately made the difference was the people who joined it. I was extraordinarily fortunate to be surrounded by talented, ambitious, and creative scientists who transformed a fragile beginning into a thriving research program.

Scientifically, different directions emerged almost immediately. A first direction grew out of the GB-3G consortium, a collaborative effort with the groups of Gilles Fischer, Bertrand Llorente, and Cécile Neuvéglise, aiming to combine comparative, functional, and population genomics to understand genome evolution (Friedrich et al. 2015; Sigwalt et al. 2016; Vakirlis et al. 2016). Working with Gilles was both stimulating and demanding. We argued frequently, challenged each other's assumptions, and continuously refined our ideas. Those discussions helped shape much of the group's early scientific identity.

At the same time, several research directions emerged in the group around a central question that had long guided my career: how genetic variation translates into phenotypic diversity. It would be impossible to recount all of them here, but one particularly influential line of research was developed with Jing Hou. She and I spent countless hours in front of a whiteboard discussing genetics, designing experiments, and debating interpretations. Together, we explored how effects of Mendelian variants are shaped by genetic backgrounds and how genetic incompatibilities contribute to reproductive isolation (Hou et al. 2014, 2015, 2016; Hou and Schacherer 2016). These studies revealed that even traits controlled by a single gene can display unexpected levels of complexity when examined across diverse natural populations (Hou et al. 2016). More broadly, they reinforced the idea that genotype–phenotype relationships cannot be fully understood without considering the genetic context in which variants operate. Jing is now a principal investigator at the CNRS studying genetic interactions, what she likes to call “network genetics”. We still argue regularly. Another foundational figure was Anne Friedrich, whose expertise in bioinformatics helped establish the analytical backbone of the group. Her contributions were essential for transforming large genomic datasets into biological insight.

These early studies mattered because they gave us confidence that we could tackle ambitious questions. More importantly, they reinforced a lesson that I had already begun to learn during my years at Princeton: science is fundamentally a collective endeavor. The best ideas emerge from discussion, disagreement, and collaboration. Over time, we began referring to ourselves as the “HaploTeam”. It would seem that the name comes from haplotypes—combinations of genetic variants inherited together. In fact, it became a metaphor for the group itself. Just as individual genetic variants reveal their significance through interactions with other variants, scientific discoveries emerge through the interactions among people. Each member brings different expertise, perspectives, and ideas, but it is their combination that creates something greater than the sum of its parts.

Discovering diversity at the species level

As sequencing technologies continued to evolve, our ambitions expanded as well. By then, it had become clear that understanding natural diversity required moving beyond individual strains and even beyond individual populations. We needed a species-wide view. Together with Gianni Liti, and with the crucial support of Patrick Wincker and the French sequencing center (Genoscope), we launched the 1002 Yeast Genomes Project (Peter et al. 2018). At the time, sequencing 1,000 genomes represented a formidable undertaking. In retrospect, it was only the beginning (Loegler et al. 2024).

The project transformed our understanding of S. cerevisiae evolution. The resulting collection of more than one thousand genomes revealed an unexpectedly complex population structure shaped by geography, ecology, domestication, hybridization, and genome plasticity. It provided strong evidence for an East Asian origin of the species and clarified the evolutionary relationships among both wild and domesticated lineages. The analyses also revealed that genome evolution operates through a remarkable diversity of mechanisms, including copy number variation, gene content variation, introgressions from related species, aneuploidies, and extensive loss-of-heterozygosity events. At the same time, the project established the first comprehensive framework for exploring genotype–phenotype relationships at the scale of an entire species, revealing the importance of rare variants and structural variation in shaping phenotypic diversity.

More than a catalog of genomes, the 1002 Yeast Genomes Project became a community resource. It provided a foundation for countless studies in evolution, population genomics, quantitative genetics, and functional genomics, while generating as many questions as it answered. This project marked a turning point. It reinforced the idea that understanding biological diversity requires looking beyond individual genes, pathways, or strains. Diversity itself had become the object of study, rather than simply an outcome.

From genetic diversity to function and beyond

However, describing diversity was never the final objective. The real challenge was to understand its consequences: what phenotypic effects do variants produce, which forms of genetic variation are most important, and how do thousands of variants combine to generate the diversity observed within a species?

These questions pushed the group toward what we refer to as functional population genomics. The goal was no longer simply to catalog variants but to understand how different forms of genetic variation contribute to phenotype. Over the years, we explored rare variants (Fournier et al. 2019; Tsouris et al. 2024), loss-of-function mutations (Caudal et al. 2022), gene expression (Caudal et al. 2024), protein abundance (Muenzner et al. 2024; Teyssonnière et al. 2024), accessory genome (Peter et al. 2018; Caudal et al. 2024; Loegler et al. 2025), and structural variation (Peter et al. 2018; O’Donnell et al. 2023; Tsouris et al. 2024; Loegler et al. 2025) at a population scale. What emerged was a view of genotype–phenotype relationships that was both richer and more complex than we had initially imagined.

One recurring observation was that the variants with the largest biological effects are often the hardest to detect (Fournier et al. 2019). Rare variants contribute disproportionately to phenotypic variation, and their low frequencies make them difficult to capture through conventional association approaches. At the same time, comparative analyses of transcriptomes and proteomes across natural populations revealed that the flow of information from genome to phenotype is far from linear (Teyssonnière et al. 2024). Gene expression and protein abundance are often controlled by partially distinct genetic architectures, indicating that important regulatory processes occur beyond transcription itself. We also discovered that the accessory genome—the fraction of genes that may be absent from the reference genome but present in other strains of the species—makes a substantial contribution to expression variation and phenotypic diversity (Caudal et al. 2024). Together, these findings highlighted a central lesson: understanding phenotypes requires considering the full spectrum of genetic variation.

More recently, long-read sequencing technologies have allowed us to move from population genomics toward pangenomics (Loegler et al. 2025). The realization that a species cannot be represented by a single genome is now unavoidable. Telomere-to-telomere assemblies have revealed extensive structural variation, accessory genes, and chromosome-scale differences that remained invisible when genomes were analyzed through a single reference framework. By integrating more than one thousand near-complete genomes into a species-wide pangenome, we showed that structural variants explain a substantial fraction of phenotypic variation and represent a major component of the missing link between genotype and phenotype. Rather than being exceptions, genome rearrangements, copy number changes, and nonreference sequences are fundamental components of natural diversity (O’Donnell et al. 2023; Loegler et al. 2025). The move from population genomics to pangenomics therefore represents more than a technological advance, it is a conceptual shift in how we think about biological variation and its consequences.

Why I still love genetics

Looking back, I realize that the most important lessons have come not only from science itself but also from the people who practice it. The yeast community occupies a special place in this regard. The publication of the first yeast genome, the development of community resources, the construction of mutant collections, the emergence of population genomics, and many of the projects that shaped my own trajectory were collective achievements. Science is about sharing. The yeast community understands this exceptionally well. Strains are shared, data are shared, ideas are shared, and so is enthusiasm. I have been fortunate to spend my scientific life in such an environment. Thirty years after the publication of the first eukaryotic genome, I remain fascinated by the same question that attracted me to biology: how does biological diversity arise? The technologies have evolved, the datasets have grown in scale, the questions have become more complex, but the mystery remains. We still do not have a complete answer. Fortunately, that is precisely what makes genetics so exciting.