Highly complete long-read genomes reveal pangenomic variation underlying yeast phenotypic diversity.

Understanding the genetic causes of trait variation is a primary goal of genetic research. One way that individuals can vary genetically is through variable pangenomic genes: genes that are only present in some individuals in a population. The presence or absence of entire genes could have large effects on trait variation. However, variable pangenomic genes can be missed in standard genotyping workflows, owing to reliance on aligning short-read sequencing to reference genomes. A popular method for studying the genetic basis of trait variation is linkage mapping, which identifies quantitative trait loci (QTLs), regions of the genome that harbor causative genetic variants. Large-scale linkage mapping in the budding yeast Saccharomyces cerevisiae has found thousands of QTLs affecting myriad yeast phenotypes. To enable the resolution of QTLs caused by variable pangenomic genes, we used long-read sequencing to generate highly complete de novo genome assemblies of 16 diverse yeast isolates. With these assemblies, we resolved QTLs for growth on maltose, sucrose, raffinose, and oxidative stress to specific genes that are absent from the reference genome but present in the broader yeast population at appreciable frequency. Copies of genes also duplicate onto chromosomes where they are absent in the reference genome, and we found that these copies generate additional QTLs whose resolution requires pangenome characterization. Our findings show the need for highly complete genome assemblies to identify the genetic basis of trait variation.

Discovery of a rapidly evolving yeast defense factor, KTD1, against the secreted killer toxin K28.

Secreted protein toxins are widely used weapons in conflicts between organisms. Elucidating how organisms genetically adapt to defend themselves against these toxins is fundamental to understanding the coevolutionary dynamics of competing organisms. Within yeast communities, "killer" toxins are secreted to kill nearby sensitive yeast, providing a fitness advantage in competitive growth environments. Natural yeast isolates vary in their sensitivity to these toxins, but to date, no polymorphic genetic factors contributing to defense have been identified. We investigated the variation in resistance to the killer toxin K28 across diverse natural isolates of the Saccharomyces cerevisiae population. Using large-scale linkage mapping, we discovered a novel defense factor, which we named KTD1. We identified many KTD1 alleles, which provided different levels of K28 resistance. KTD1 is a member of the DUP240 gene family of unknown function, which is rapidly evolving in a region spanning its two encoded transmembrane helices. We found that this domain is critical to KTD1's protective ability. Our findings implicate KTD1 as a key polymorphic factor in the defense against K28 toxin.

Analysis of the genetic basis of height in large Jewish nuclear families.

Despite intensive study, most of the specific genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. Loci we identified in discovery families could explain an estimated lower bound of 6% of the variance in height in validation families. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population.

Systematic genetic characterization of the human PKR kinase domain highlights its functional malleability to escape a viral substrate mimic.

Evolutionary arms races can arise at the contact surfaces between host and viral proteins, producing dynamic spaces in which genetic variants are continually pursued. However, the sampling of genetic variation must be balanced with the need to maintain protein function. A striking case is given by protein kinase R (PKR), a member of the mammalian innate immune system. PKR detects viral replication within the host cell and halts protein synthesis to prevent viral replication by phosphorylating eIF2α, a component of the translation initiation machinery. PKR is targeted by many viral antagonists, including poxvirus pseudosubstrate antagonists that inhibit PKR by interacting with the same binding surface as eIF2α. Remarkably, PKR has several rapidly evolving residues at this interface, suggesting it is engaging in an evolutionary arms race, despite the surface's critical role in phosphorylating eIF2α. To systematically explore the evolutionary opportunities available at this dynamic interface, we generated and characterized a library of 426 SNP-accessible nonsynonymous variants of human PKR for their ability to escape inhibition by the model pseudosubstrate inhibitor K3 from vaccinia virus. We identified key sites in the PKR kinase domain that harbor K3-resistant variants, as well as critical sites where variation leads to loss of function. We find K3-resistant variants are readily available throughout the interface and are enriched at sites under positive selection. Moreover, variants beneficial against K3 were also beneficial against an enhanced variant of K3, indicating resilience to viral adaptation. Overall, we find that the eIF2α-binding surface of PKR is highly malleable, potentiating its evolutionary ability to combat viral inhibition.

Systematic characterization of the local evolutionary space available to human PKR and vaccinia virus K3.

The interfaces between host and viral proteins can be dynamic spaces in which genetic variants are continually pursued, giving rise to evolutionary arms races. One such scenario is found between the mammalian innate immunity protein PKR (protein kinase R) and the poxvirus antagonist K3. Once activated, PKR phosphorylates the natural substrate eIF2α, which halts protein synthesis within the cell and prevents viral replication. K3 acts as a pseudosubstrate antagonist against PKR by directly antagonizing this halt in protein synthesis, enabling poxviruses to replicate in the cell. Exploring the impact of genetic variants in both PKR and K3 is necessary not only to highlight residues of evolutionary constraint and opportunity but also to elucidate the mechanism by which human PKR is able to subvert a rapidly evolving viral antagonist. To systematically explore this dynamic interface, we have generated a combinatorial library of PKR and K3 missense variants to be co-expressed and characterized in a high-throughput yeast selection assay. This assay allows us to characterize hundreds of thousands of unique PKR-K3 genetic combinations in a single pooled experiment. Our results highlight specific missense variants available to PKR that subvert the K3 antagonist. We find that improved PKR variants are readily available at sites under positive selection, with limited opportunity at sites interfacing with K3 and eIF2α. Additionally, we find many variants that improve and disable K3 antagonism, suggesting a pliable interface. We reason that this approach can be leveraged to explore the evolutionary plasticity of many other host-virus interfaces.

Genome-wide base editor screen identifies regulators of protein abundance in yeast.

Proteins are key molecular players in a cell, and their abundance is extensively regulated not just at the level of gene expression but also post-transcriptionally. Here, we describe a genetic screen in yeast that enables systematic characterization of how protein abundance regulation is encoded in the genome. The screen combines a CRISPR/Cas9 base editor to introduce point mutations with fluorescent tagging of endogenous proteins to facilitate a flow-cytometric readout. We first benchmarked base editor performance in yeast with individual gRNAs as well as in positive and negative selection screens. We then examined the effects of 16,452 genetic perturbations on the abundance of eleven proteins representing a variety of cellular functions. We uncovered hundreds of regulatory relationships, including a novel link between the GAPDH isoenzymes Tdh1/2/3 and the Ras/PKA pathway. Many of the identified regulators are specific to one of the eleven proteins, but we also found genes that, upon perturbation, affected the abundance of most of the tested proteins. While the more specific regulators usually act transcriptionally, broad regulators often have roles in protein translation. Overall, our novel screening approach provides unprecedented insights into the components, scale and connectedness of the protein regulatory network.

Ancient balancing selection maintains incompatible versions of the galactose pathway in yeast.

Metabolic pathways differ across species but are expected to be similar within a species. We discovered two functional, incompatible versions of the galactose pathway in Saccharomyces cerevisiae We identified a three-locus genetic interaction for growth in galactose, and used precisely engineered alleles to show that it arises from variation in the galactose utilization genes GAL2, GAL1/10/7, and phosphoglucomutase (PGM1), and that the reference allele of PGM1 is incompatible with the alternative alleles of the other genes. Multiloci balancing selection has maintained the two incompatible versions of the pathway for millions of years. Strains with alternative alleles are found primarily in galactose-rich dairy environments, and they grow faster in galactose but slower in glucose, revealing a trade-off on which balancing selection may have acted.

Rare variants contribute disproportionately to quantitative trait variation in yeast.

How variants with different frequencies contribute to trait variation is a central question in genetics. We use a unique model system to disentangle the contributions of common and rare variants to quantitative traits. We generated ~14,000 progeny from crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) for 38 traits. We combined our results with sequencing data for 1011 yeast isolates to show that rare variants make a disproportionate contribution to trait variation. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, and that negative selection has shaped the relationship between variant frequency and effect size. We leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects.

Highly parallel genome variant engineering with CRISPR-Cas9.

Understanding the functional effects of DNA sequence variants is of critical importance for studies of basic biology, evolution, and medical genetics; however, measuring these effects in a high-throughput manner is a major challenge. One promising avenue is precise editing with the CRISPR-Cas9 system, which allows for generation of DNA double-strand breaks (DSBs) at genomic sites matching the targeting sequence of a guide RNA (gRNA). Recent studies have used CRISPR libraries to generate many frameshift mutations genome wide through faulty repair of CRISPR-directed breaks by nonhomologous end joining (NHEJ) 1 . Here, we developed a CRISPR-library-based approach for highly efficient and precise genome-wide variant engineering. We used our method to examine the functional consequences of premature-termination codons (PTCs) at different locations within all annotated essential genes in yeast. We found that most PTCs were highly deleterious unless they occurred close to the 3' end of the gene and did not affect an annotated protein domain. Unexpectedly, we discovered that some putatively essential genes are dispensable, whereas others have large dispensable regions. This approach can be used to profile the effects of large classes of variants in a high-throughput manner.

Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast.

Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion that most genetic variance in populations is additive. Here we describe networks of capacitating genetic interactions that contribute to quantitative trait variation in a large yeast intercross population. The additive variance explained by individual loci in a network is highly dependent on the allele frequencies of the interacting loci. Modeling of phenotypes for multilocus genotype classes in the epistatic networks is often improved by accounting for the interactions. We discuss the implications of these results for attempts to dissect genetic architectures and to predict individual phenotypes and long-term responses to selection.

CRISPR-directed mitotic recombination enables genetic mapping without crosses.

Linkage and association studies have mapped thousands of genomic regions that contribute to phenotypic variation, but narrowing these regions to the underlying causal genes and variants has proven much more challenging. Resolution of genetic mapping is limited by the recombination rate. We developed a method that uses CRISPR (clustered, regularly interspaced, short palindromic repeats) to build mapping panels with targeted recombination events. We tested the method by generating a panel with recombination events spaced along a yeast chromosome arm, mapping trait variation, and then targeting a high density of recombination events to the region of interest. Using this approach, we fine-mapped manganese sensitivity to a single polymorphism in the transporter Pmr1. Targeting recombination events to regions of interest allows us to rapidly and systematically identify causal variants underlying trait differences.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast.

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL-QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL-QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies.

Multiple inputs control sulfur-containing amino acid synthesis in Saccharomyces cerevisiae.

In Saccharomyces cerevisiae, transcription of the MET regulon, which encodes the proteins involved in the synthesis of the sulfur-containing amino acids methionine and cysteine, is repressed by the presence of either methionine or cysteine in the environment. This repression is accomplished by ubiquitination of the transcription factor Met4, which is carried out by the SCF(Met30) E3 ubiquitin ligase. Mutants defective in MET regulon repression reveal that loss of Cho2, which is required for the methylation of phosphatidylethanolamine to produce phosphatidylcholine, leads to induction of the MET regulon. This induction is due to reduced cysteine synthesis caused by the Cho2 defects, uncovering an important link between phospholipid synthesis and cysteine synthesis. Antimorphic mutants in S-adenosyl-methionine (SAM) synthetase genes also induce the MET regulon. This effect is due, at least in part, to SAM deficiency controlling the MET regulon independently of SAM's contribution to cysteine synthesis. Finally, the Met30 protein is found in two distinct forms whose relative abundance is controlled by the availability of sulfur-containing amino acids. This modification could be involved in the nutritional control of SCF(Met30) activity toward Met4.

Nutritional control of epigenetic processes in yeast and human cells.

The vitamin folate is required for methionine homeostasis in all organisms. In addition to its role in protein synthesis, methionine is the precursor to S-adenosyl-methionine (SAM), which is used in myriad cellular methylation reactions, including all histone methylation reactions. Here, we demonstrate that folate and methionine deficiency led to reduced methylation of lysine 4 of histone H3 (H3K4) in Saccharomyces cerevisiae. The effect of nutritional deficiency on H3K79 methylation was less pronounced, but was exacerbated in S. cerevisiae carrying a hypomorphic allele of Dot1, the enzyme responsible for H3K79 methylation. This result suggested a hierarchy of epigenetic modifications in terms of their susceptibility to nutritional limitations. Folate deficiency caused changes in gene transcription that mirrored the effect of complete loss of H3K4 methylation. Histone methylation was also found to respond to nutritional deficiency in the fission yeast Schizosaccharomyces pombe and in human cells in culture.