Interactions between chromosomal and nonchromosomal elements reveal missing heritability

Genomic and transcriptomic analyses reveal polygenic architecture for ecologically important traits in aspen (Populus tremuloides Michx.)

Intraspecific genetic variation in foundation species such as aspen (Populus tremuloides Michx.) shapes their impact on forest structure and function. Identifying genes underlying ecologically important traits is key to understanding that impact. Previous studies, using single-locus genome-wide association (GWA) analyses to identify candidate genes, have identified fewer genes than anticipated for highly heritable quantitative traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this "missing heritability" phenomenon. Our research characterized the genetic architecture of 30 ecologically important traits using a common garden of aspen through genomic and transcriptomic analyses. A multilocus association model revealed that most traits displayed a highly polygenic architecture, with most variation explained by loci with small effects (likely below the detection levels of single-locus GWA methods). Consistent with a polygenic architecture, our single-locus GWA analyses found only 38 significant SNPs in 22 genes across 15 traits. Next, we used differential expression analysis on a subset of aspen genets with divergent concentrations of salicinoid phenolic glycosides (key defense traits). This complementary method to traditional GWA discovered 1243 differentially expressed genes for a polygenic trait. Soft clustering analysis revealed three gene clusters (241 candidate genes) involved in secondary metabolite biosynthesis and regulation. Our work reveals that ecologically important traits governing higher-order community- and ecosystem-level attributes of a foundation forest tree species have complex underlying genetic structures and will require methods beyond traditional GWA analyses to unravel.

RNA viruses, M satellites, chromosomal killer genes, and killer/nonkiller phenotypes in the 100-genomes S. cerevisiae strains

We characterized previously identified RNA viruses (L-A, L-BC, 20S, and 23S), L-A-dependent M satellites (M1, M2, M28, and Mlus), and M satellite-dependent killer phenotypes in the Saccharomyces cerevisiae 100-genomes genetic resource population. L-BC was present in all strains, albeit in 2 distinct levels, L-BChi and L-BClo; the L-BC level is associated with the L-BC genotype. L-BChi, L-A, 20S, 23S, M1, M2, and Mlus (M28 was absent) were in fewer strains than the similarly inherited 2µ plasmid. Novel L-A-dependent phenotypes were identified. Ten M+ strains exhibited M satellite-dependent killing (K+) of at least 1 of the naturally M0 and cured M0 derivatives of the 100-genomes strains; in these M0 strains, sensitivities to K1+, K2+, and K28+ strains varied. Finally, to complement our M satellite-encoded killer toxin analysis, we assembled the chromosomal KHS1 and KHR1 killer genes and used naturally M0 and cured M0 derivatives of the 100-genomes strains to assess and characterize the chromosomal killer phenotypes.

Novel viruses of the family Partitiviridae discovered in Saccharomyces cerevisiae

It has been 49 years since the last discovery of a new virus family in the model yeast Saccharomyces cerevisiae. A large-scale screen to determine the diversity of double-stranded RNA (dsRNA) viruses in S. cerevisiae has identified multiple novel viruses from the family Partitiviridae that have been previously shown to infect plants, fungi, protozoans, and insects. Most S. cerevisiae partitiviruses (ScPVs) are associated with strains of yeasts isolated from coffee and cacao beans. The presence of partitiviruses was confirmed by sequencing the viral dsRNAs and purifying and visualizing isometric, non-enveloped viral particles. ScPVs have a typical bipartite genome encoding an RNA-dependent RNA polymerase (RdRP) and a coat protein (CP). Phylogenetic analysis of ScPVs identified three species of ScPV, which are most closely related to viruses of the genus Cryspovirus from the mammalian pathogenic protozoan Cryptosporidium parvum. Molecular modeling of the ScPV RdRP revealed a conserved tertiary structure and catalytic site organization when compared to the RdRPs of the Picornaviridae. The ScPV CP is the smallest so far identified in the Partitiviridae and has structural homology with the CP of other partitiviruses but likely lacks a protrusion domain that is a conspicuous feature of other partitivirus particles. ScPVs were stably maintained during laboratory growth and were successfully transferred to haploid progeny after sporulation, which provides future opportunities to study partitivirus-host interactions using the powerful genetic tools available for the model organism S. cerevisiae.

The prevalence of killer yeasts and double-stranded RNAs in the budding yeast Saccharomyces cerevisiae

Killer toxins are antifungal proteins produced by many species of "killer" yeasts, including the brewer's and baker's yeast Saccharomyces cerevisiae. Screening 1270 strains of S. cerevisiae for killer toxin production found that 50% are killer yeasts, with a higher prevalence of yeasts isolated from human clinical samples and winemaking processes. Since many killer toxins are encoded by satellite double-stranded RNAs (dsRNAs) associated with mycoviruses, S. cerevisiae strains were also assayed for the presence of dsRNAs. This screen identified that 51% of strains contained dsRNAs from the mycovirus families Totiviridae and Partitiviridae, as well as satellite dsRNAs. Killer toxin production was correlated with the presence of satellite dsRNAs but not mycoviruses. However, in most killer yeasts, whole genome analysis identified the killer toxin gene KHS1 as significantly associated with killer toxin production. Most killer yeasts had unique spectrums of antifungal activities compared to canonical killer toxins, and sequence analysis identified mutations that altered their antifungal activities. The prevalence of mycoviruses and killer toxins in S. cerevisiae is important because of their known impact on yeast fitness, with implications for academic research and industrial application of this yeast species.

Association of ScV-LA Virus with Host Protein Metabolism Determined by Proteomics Analysis and Cognate RNA Sequencing

Saccharomyces yeasts are highly dispersed in the environment and microbiota of higher organisms. The yeast killing phenotype, encoded by the viral system, was discovered to be a significant property for host survival. Minor alterations in transcription patterns underpin the reciprocal relationship between LA and M viruses and their hosts, suggesting the fine-tuning of the transcriptional landscape. To uncover the principal targets of both viruses, we performed proteomics analysis of virus-enriched subsets of host proteins in virus type-specific manner. The essential pathways of protein metabolism-from biosynthesis and folding to degradation-were found substantially enriched in virus-linked subsets. The fractionation of viruses allowed separation of virus-linked host RNAs, investigated by high-content RNA sequencing. Ribosomal RNA was found to be inherently associated with LA-lus virus, along with other RNAs essential for ribosome biogenesis. This study provides a unique portrayal of yeast virions through the characterization of the associated proteome and cognate RNAs, and offers a background for understanding ScV-LA viral infection persistency.

Loss-of-function mutation survey revealed that genes with background-dependent fitness are rare and functionally related in yeast

In different individuals, the same mutation can lead to different phenotypes due to genetic background effects. This is commonly observed in various systems, including many human diseases. While isolated examples of such background effects have been observed, a systematic view across a large number of individuals is still lacking. Here, we surveyed genetic background effects associated with gene loss-of-function mutations across a population of natural isolates of the yeast Saccharomyces cerevisiae. We found that ∼15% of genes can display a background-dependent fitness change. Genes related to mitochondrial functions are significantly overrepresented, and showed reversed patterns of fitness gain or loss with genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport, suggesting a potential functional rewiring.

In natural populations, the same mutation can lead to different phenotypic outcomes due to the genetic variation that exists among individuals. Such genetic background effects are commonly observed, including in the context of many human diseases. However, systematic characterization of these effects at the species level is still lacking to date. Here, we sought to comprehensively survey background-dependent traits associated with gene loss-of-function (LoF) mutations in 39 natural isolates of Saccharomyces cerevisiae using a transposon saturation strategy. By analyzing the modeled fitness variability of a total of 4,469 genes, we found that 15% of them, when impacted by a LoF mutation, exhibited a significant gain- or loss-of-fitness phenotype in certain natural isolates compared with the reference strain S288C. Out of these 632 genes with predicted background-dependent fitness effects, around 2/3 impact multiple backgrounds with a gradient of predicted fitness change while 1/3 are specific to a single genetic background. Genes related to mitochondrial function are significantly overrepresented in the set of genes showing a continuous variation and display a potential functional rewiring with other genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport. Such rewiring effects are likely modulated by both the genetic background and the environment. While background-specific cases are rare and span diverse cellular processes, they can be functionally related at the individual level. All genes with background-dependent fitness effects tend to have an intermediate connectivity in the global genetic interaction network and have shown relaxed selection pressure at the population level, highlighting their potential evolutionary characteristics.

Adaptive Response of Saccharomyces Hosts to Totiviridae L-A dsRNA Viruses Is Achieved through Intrinsically Balanced Action of Targeted Transcription Factors

Totiviridae L-A virus is a widespread yeast dsRNA virus. The persistence of the L-A virus alone appears to be symptomless, but the concomitant presence of a satellite M virus provides a killer trait for the host cell. The presence of L-A dsRNA is common in laboratory, industrial, and wild yeasts, but little is known about the impact of the L-A virus on the host’s gene expression. In this work, based on high-throughput RNA sequencing data analysis, the impact of the L-A virus on whole-genome expression in three different Saccharomyces paradoxus and S. cerevisiae host strains was analyzed. In the presence of the L-A virus, moderate alterations in gene expression were detected, with the least impact on respiration-deficient cells. Remarkably, the transcriptional adaptation of essential genes was limited to genes involved in ribosome biogenesis. Transcriptional responses to L-A maintenance were, nevertheless, similar to those induced upon stress or nutrient availability. Based on these data, we further dissected yeast transcriptional regulators that, in turn, modulate the cellular L-A dsRNA levels. Our findings point to totivirus-driven fine-tuning of the transcriptional landscape in yeasts and uncover signaling pathways employed by dsRNA viruses to establish the stable, yet allegedly profitless, viral infection of fungi.

The complex role of genetic background in shaping the effects of spontaneous and induced mutations

Spontaneous and induced mutations frequently show different phenotypic effects across genetically distinct individuals. It is generally appreciated that these background effects mainly result from genetic interactions between the mutations and segregating loci. However, the architectures and molecular bases of these genetic interactions are not well understood. Recent work in a number of model organisms has tried to advance knowledge of background effects both by using large‐scale screens to find mutations that exhibit this phenomenon and by identifying the specific loci that are involved. Here, we review this body of research, emphasizing in particular the insights it provides into both the prevalence of background effects across different mutations and the mechanisms that cause these background effects.

A large fraction of mutations show different effects in distinct individuals.

These background effects are mainly caused by epistasis with segregating loci.

Mapping studies show a diversity of genetic architectures can be involved.

Genetically complex changes in gene expression are often, but not always, causative.

Déjà vu All Over Again: A Unitary Biological Mechanism for Intelligence Is (Probably) Untenable

Nearly a century ago, Spearman proposed that “specific factors can be regarded as the ‘nuts and bolts’ of cognitive performance…, while the general factor is the mental energy available to power the specific engines”. Geary (2018; 2019) takes Spearman’s analogy of “mental energy” quite literally and doubles-down on the notion by proposing that a unitary energy source, the mitochondria, explains variations in both cognitive function and health-related outcomes. This idea is reminiscent of many earlier attempts to describe a low-level biological determinant of general intelligence. While Geary does an admirable job developing an innovative theory with specific and testable predictions, this new theory suffers many of the shortcomings of previous attempts at similar goals. We argue that Geary’s theory is generally implausible, and does not map well onto known psychological and genetic properties of intelligence or its relationship to health and fitness. While Geary’s theory serves as an elegant model of “what could be”, it is less successful as a description of “what is”.

Global Genetic Networks and the Genotype-to-Phenotype Relationship

Genetic interactions identify combinations of genetic variants that impinge on phenotype. With whole-genome sequence information available for thousands of individuals within a species, a major outstanding issue concerns the interpretation of allelic combinations of genes underlying inherited traits. In this Review, we discuss how large-scale analyses in model systems have illuminated the general principles and phenotypic impact of genetic interactions. We focus on studies in budding yeast, including the mapping of a global genetic network. We emphasize how information gained from work in yeast translates to other systems, and how a global genetic network not only annotates gene function but also provides new insights into the genotype-to-phenotype relationship.

Complex modifier landscape underlying genetic background effects

Genetic background impacts the phenotypic outcome of a mutation in different individuals; however, the underlying molecular mechanisms are often unclear. We characterized genes exhibiting conditional essentiality when mutated in two genetically distinct yeast strains. Hybrid crosses and whole-genome sequencing revealed that conditional essentiality can be associated with nonchromosomal elements or a single-modifier locus, but most involve a complex set of modifier loci. Detailed analysis of the cysteine biosynthesis pathway showed that independent, rare, single-gene modifiers, related to both up- and downstream pathway functions, can arise in multiple allelic forms from separate lineages. For several genes, we also resolved complex sets of modifying loci underlying conditional essentiality, revealing specific genetic interactions that drive an individual strain’s background effect.

The phenotypic consequence of a given mutation can be influenced by the genetic background. For example, conditional gene essentiality occurs when the loss of function of a gene causes lethality in one genetic background but not another. Between two individual Saccharomyces cerevisiae strains, S288c and Σ1278b, ∼1% of yeast genes were previously identified as “conditional essential.” Here, in addition to confirming that some conditional essential genes are modified by a nonchromosomal element, we show that most cases involve a complex set of genomic modifiers. From tetrad analysis of S288C/Σ1278b hybrid strains and whole-genome sequencing of viable hybrid spore progeny, we identified complex sets of multiple genomic regions underlying conditional essentiality. For a smaller subset of genes, including CYS3 and CYS4, each of which encodes components of the cysteine biosynthesis pathway, we observed a segregation pattern consistent with a single modifier associated with conditional essentiality. In natural yeast isolates, we found that the CYS3/CYS4 conditional essentiality can be caused by variation in two independent modifiers, MET1 and OPT1, each with roles associated with cellular cysteine physiology. Interestingly, the OPT1 allelic variation appears to have arisen independently from separate lineages, with rare allele frequencies below 0.5%. Thus, while conditional gene essentiality is usually driven by genetic interactions associated with complex modifier architectures, our analysis also highlights the role of functionally related, genetically independent, and rare variants.

Identification of Specific Nuclear Genetic Loci and Genes That Interact With the Mitochondrial Genome and Contribute to Fecundity in Caenorhabditis elegans

Previous studies have found that fecundity is a multigenic trait regulated, in part, by mitochondrial-nuclear (mit-n) genetic interactions. However, the identification of specific nuclear genetic loci or genes interacting with the mitochondrial genome and contributing to the quantitative trait fecundity is an unsolved issue. Here, a panel of recombinant inbred advanced intercrossed lines (RIAILs), established from a cross between the N2 and CB4856 strains of C. elegans, were used to characterize the underlying genetic basis of mit-n genetic interactions related to fecundity. Sixty-seven single nucleotide polymorphisms (SNPs) were identified by association mapping to be linked with fecundity among 115 SNPs linked to mitotype. This indicated significant epistatic effects between nuclear and mitochondria genetics on fecundity. In addition, two specific nuclear genetic loci interacting with the mitochondrial genome and contributing to fecundity were identified. A significant reduction in fecundity was observed in the RIAILs that carried CB4856 mitochondria and a N2 genotype at locus 1 or a CB4856 genotype at locus 2 relative to the wild-type strains. Then, a hybrid strain (CNC10) was established, which was bred as homoplasmic for the CB4856 mtDNA genome and N2 genotype at locus 1 in the CB4856 nuclear background. The mean fecundity of CNC10 was half the fecundity of the control strain. Several functional characteristics of the mitochondria in CNC10 were also influenced by mit-n interactions. Overall, experimental evidence was presented that specific nuclear genetic loci or genes have interactions with the mitochondrial genome and are associated with fecundity. In total, 18 genes were identified using integrative approaches to have interactions with the mitochondrial genome and to contribute to fecundity.

Mitochondrial Genome Variation Affects Multiple Respiration and Nonrespiration Phenotypes in Saccharomyces cerevisiae

Mitochondrial genome variation and its effects on phenotypes have been widely analyzed in higher eukaryotes but less so in the model eukaryote Saccharomyces cerevisiae Here, we describe mitochondrial genome variation in 96 diverse S. cerevisiae strains and assess associations between mitochondrial genotype and phenotypes as well as nuclear-mitochondrial epistasis. We associate sensitivity to the ATP synthase inhibitor oligomycin with SNPs in the mitochondrially encoded ATP6 gene. We describe the use of iso-nuclear F1 pairs, the mitochondrial genome equivalent of reciprocal hemizygosity analysis, to identify and analyze mitochondrial genotype-dependent phenotypes. Using iso-nuclear F1 pairs, we analyze the oligomycin phenotype-ATP6 association and find extensive nuclear-mitochondrial epistasis. Similarly, in iso-nuclear F1 pairs, we identify many additional mitochondrial genotype-dependent respiration phenotypes, for which there was no association in the 96 strains, and again find extensive nuclear-mitochondrial epistasis that likely contributes to the lack of association in the 96 strains. Finally, in iso-nuclear F1 pairs, we identify novel mitochondrial genotype-dependent nonrespiration phenotypes: resistance to cycloheximide, ketoconazole, and copper. We discuss potential mechanisms and the implications of mitochondrial genotype and of nuclear-mitochondrial epistasis effects on respiratory and nonrespiratory quantitative traits.

Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression

The phenotypic consequences of a given mutation can vary across individuals. This so-called background effect is widely observed, from mutant fitness of loss-of-function variants in model organisms to variable disease penetrance and expressivity in humans; however, the underlying genetic basis often remains unclear. Taking insights gained from recent large-scale surveys of genetic interaction and suppression analyses in yeast, we propose that the genetic network context for a given mutation may shape its propensity of exhibiting background-dependent phenotypes. We argue that further efforts in systematically mapping the genetic interaction networks beyond yeast will provide not only key insights into the functional properties of genes, but also a better understanding of the background effects and the (un)predictability of traits in a broader context.

Sources of Fungal Genetic Variation and Associating It with Phenotypic Diversity

The first eukaryotic genome to be sequenced was fungal, and there continue to be more sequenced genomes in the kingdom Fungi than in any other eukaryotic kingdom. Comparison of these genomes reveals many sources of genetic variation, from single nucleotide polymorphisms to horizontal gene transfer and on to changes in the arrangement and number of chromosomes, not to mention endofungal bacteria and viruses. Population genomics shows that all sources generate variation all the time and implicate natural selection as the force maintaining genome stability. Variation in wild populations is a rich resource for associating genetic variation with phenotypic variation, whether through quantitative trait locus mapping, genome-wide association studies, or reverse ecology. Subjects of studies associating genetic and phenotypic variation include model fungi, e.g., Saccharomyces and Neurospora, but pioneering studies have also been made with fungi pathogenic to plants, e.g., Pyricularia (= Magnaporthe), Zymoseptoria, and Fusarium, and to humans, e.g., Coccidioides, Cryptococcus, and Candida.

The frenemies within: viruses, retrotransposons and plasmids that naturally infect Saccharomyces yeasts

Viruses are a major focus of current research efforts because of their detrimental impact on humanity and their ubiquity within the environment. Bacteriophages have long been used to study host-virus interactions within microbes, but it is often forgotten that the single-celled eukaryote Saccharomyces cerevisiae and related species are infected with double-stranded RNA viruses, single-stranded RNA viruses, LTR-retrotransposons and double-stranded DNA plasmids. These intracellular nucleic acid elements have some similarities to higher eukaryotic viruses, i.e. yeast retrotransposons have an analogous lifecycle to retroviruses, the particle structure of yeast totiviruses resembles the capsid of reoviruses and segregation of yeast plasmids is analogous to segregation strategies used by viral episomes. The powerful experimental tools available to study the genetics, cell biology and evolution of S. cerevisiae are well suited to further our understanding of how cellular processes are hijacked by eukaryotic viruses, retrotransposons and plasmids. This article has been written to briefly introduce viruses, retrotransposons and plasmids that infect Saccharomyces yeasts, emphasize some important cellular proteins and machineries with which they interact, and suggest the evolutionary consequences of these interactions. Copyright © 2017 John Wiley & Sons, Ltd.

Relationships and Evolution of Double-Stranded RNA Totiviruses of Yeasts Inferred from Analysis of L-A-2 and L-BC Variants in Wine Yeast Strain Populations

Saccharomyces cerevisiae killer strains secrete a protein toxin active on nonkiller strains of the same (or other) yeast species. Different killer toxins, K1, K2, K28, and Klus, have been described. Each toxin is encoded by a medium-size (1.5- to 2.3-kb) M double-stranded RNA (dsRNA) located in the cytoplasm. M dsRNAs require L-A helper virus for maintenance. L-A belongs to the Totiviridae family, and its dsRNA genome of 4.6 kb codes for the major capsid protein Gag and a minor Gag-Pol protein, which form the virions that separately encapsidate L-A or the M satellites. Different L-A variants exist in nature; on average, 24% of their nucleotides are different. Previously, we reported that L-A-lus was specifically associated with Mlus, suggesting coevolution, and proposed a role of the toxin-encoding M dsRNAs in the appearance of new L-A variants. Here we confirm this by analyzing the helper virus in K2 killer wine strains, which we named L-A-2. L-A-2 is required for M2 maintenance, and neither L-A nor L-A-lus shows helper activity for M2 in the same genetic background. This requirement is overcome when coat proteins are provided in large amounts by a vector or in ski mutants. The genome of another totivirus, L-BC, frequently accompanying L-A in the same cells shows a lower degree of variation than does L-A (about 10% of nucleotides are different). Although L-BC has no helper activity for M dsRNAs, distinct L-BC variants are associated with a particular killer strain. The so-called L-BC-lus (in Klus strains) and L-BC-2 (in K2 strains) are analyzed.

IMPORTANCE

Killer strains of S. cerevisiae secrete protein toxins that kill nonkiller yeasts. The "killer phenomenon" depends on two dsRNA viruses: L-A and M. M encodes the toxin, and L-A, the helper virus, provides the capsids for both viruses. Different killer toxins exist: K1, K2, K28, and Klus, encoded on different M viruses. Our data indicate that each M dsRNA depends on a specific helper virus; these helper viruses have nucleotide sequences that may be as much as 26% different, suggesting coevolution. In wine environments, K2 and Klus strains frequently coexist. We have previously characterized the association of Mlus and L-A-lus. Here we sequence and characterize L-A-2, the helper virus of M2, establishing the helper virus requirements of M2, which had not been completely elucidated. We also report the existence of two specific L-BC totiviruses in Klus and K2 strains with about 10% of their nucleotides different, suggesting different evolutionary histories from those of L-A viruses.

Traditional and novel tools to probe the mitochondrial metabolism in health and disease

Mitochondrial metabolism links energy production to other essential cellular processes such as signaling, cellular differentiation, and apoptosis. In addition to producing adenosine triphosphate (ATP) as an energy source, mitochondria are responsible for the synthesis of a myriad of important metabolites and cofactors such as tetrahydrofolate, α-ketoacids, steroids, aminolevulinic acid, biotin, lipoic acid, acetyl-CoA, iron-sulfur clusters, heme, and ubiquinone. Furthermore, mitochondria and their metabolism have been implicated in aging and several human diseases, including inherited mitochondrial disorders, cardiac dysfunction, heart failure, neurodegenerative diseases, diabetes, and cancer. Therefore, there is great interest in understanding mitochondrial metabolism and the complex relationship it has with other cellular processes. A large number of studies on mitochondrial metabolism have been conducted in the last 50 years, taking a broad range of approaches. In this review, we summarize and discuss the most commonly used tools that have been used to study different aspects of the metabolism of mitochondria: ranging from dyes that monitor changes in the mitochondrial membrane potential and pharmacological tools to study respiration or ATP synthesis, to more modern tools such as genetically encoded biosensors and trans-omic approaches enabled by recent advances in mass spectrometry, computation, and other technologies. These tools have allowed the large number of studies that have shaped our current understanding of mitochondrial metabolism. WIREs Syst Biol Med 2017, 9:e1373. doi: 10.1002/wsbm.1373 For further resources related to this article, please visit the WIREs website.

Genome-wide association study reveals putative regulators of bioenergy traits in Populus deltoides

Genome-wide association studies (GWAS) have been used extensively to dissect the genetic regulation of complex traits in plants. These studies have focused largely on the analysis of common genetic variants despite the abundance of rare polymorphisms in several species, and their potential role in trait variation. Here, we conducted the first GWAS in Populus deltoides, a genetically diverse keystone forest species in North America and an important short rotation woody crop for the bioenergy industry. We searched for associations between eight growth and wood composition traits, and common and low-frequency single-nucleotide polymorphisms detected by targeted resequencing of 18 153 genes in a population of 391 unrelated individuals. To increase power to detect associations with low-frequency variants, multiple-marker association tests were used in combination with single-marker association tests. Significant associations were discovered for all phenotypes and are indicative that low-frequency polymorphisms contribute to phenotypic variance of several bioenergy traits. Our results suggest that both common and low-frequency variants need to be considered for a comprehensive understanding of the genetic regulation of complex traits, particularly in species that carry large numbers of rare polymorphisms. These polymorphisms may be critical for the development of specialized plant feedstocks for bioenergy.

Nature or Nurture? Heritability in the Classroom

Understanding evolution is a necessary component of undergraduate education in biology, and evolution is difficult to explain without studying the heritability of traits. However, in most classes, heritability is presented with only a handful of graphs showing typical morphological traits, for example, beak size in finches and height in humans. The active-inquiry exercise outlined in the following pages allows instructors to engage students in this formerly dry subject by bringing their own data as the basis for estimates of heritability. Students are challenged to come up with their own hypotheses regarding how and to what extent their traits are inherited from their parents and then gather, analyze data, and make inferences with help from the instructor. The exercise is simple in concept and execution but uncovers many new avenues of inquiry for students, including potential biases in their estimates of heritability and misconceptions that they may have had about the extent of inference that can be made from their heritability estimates. The active-inquiry format of the exercise prioritizes curiosity and discussion, leading to a much deeper understanding of heritability and the scientific method.

The Microcosm within: An interview with William B. Miller, Jr., on the Extended Hologenome theory of evolution

There is a singular unifying reality underlying every biologic interaction on our planet. In immunology, that which does not kill you makes you different.

-William B. Miller, Jr.

We are experiencing a revolution in our understanding of inner space on a par with our exponentially increasing understanding of outer space. In biology, we are learning that the genetic and epigenetic complexity within organisms is far deeper than suspected. This is a key theme in William B. Miller Jr.'s book, The Microcosm Within: Evolution and Extinction in the Hologenome.

We are learning also that a focus on the human genome alone is misleading when it comes to who we really are as biological entities, and in terms of how we and other creatures have evolved. Rather than being defined by the human genome alone, we are instead defined by the “hologenome,” the sum of the human genome and the far larger genetic endowment of the microbiome and symbiotic communities that reside within and around us.

Miller is a medical doctor previously in private practice in Pennsylvania and Phoenix, Arizona. This book is his first foray into evolutionary theory. His book could have been titled “The Origin of Variation” because this is his primary focus. He accepts that natural selection plays a role in evolution, but he demotes this mechanism to a less important role than the Modern Synthesis suggests. His main gripe, however, concerns random variation. He argues that random variation is unable to explain the origin and evolution of biological forms that we see in the world around us and in the historical record. Miller suggests that, rather than random variation as the engine of novelty, there is a creative impulse at the heart of cellular life, and even at the level of the genetic aggregate, that generates novelty on a regular basis. I probe this assertion in the interview below. He also highlights the strong role of “exogenous genetic assault” in variation and in his immunological model of evolution.

A population study of killer viruses reveals different evolutionary histories of two closely related Saccharomyces sensu stricto yeasts

Microbes have evolved ways of interference competition to gain advantage over their ecological competitors. The use of secreted killer toxins by yeast cells through acquiring double-stranded RNA viruses is one such prominent example. Although the killer behaviour has been well studied in laboratory yeast strains, our knowledge regarding how killer viruses are spread and maintained in nature and how yeast cells co-evolve with viruses remains limited. We investigated these issues using a panel of 81 yeast populations belonging to three Saccharomyces sensu stricto species isolated from diverse ecological niches and geographic locations. We found that killer strains are rare among all three species. In contrast, killer toxin resistance is widespread in Saccharomyces paradoxus populations, but not in Saccharomyces cerevisiae or Saccharomyces eubayanus populations. Genetic analyses revealed that toxin resistance in S. paradoxus is often caused by dominant alleles that have independently evolved in different populations. Molecular typing identified one M28 and two types of M1 killer viruses in those killer strains. We further showed that killer viruses of the same type could lead to distinct killer phenotypes under different host backgrounds, suggesting co-evolution between the viruses and hosts in different populations. Taken together, our data suggest that killer viruses vary in their evolutionary histories even within closely related yeast species.

Unisexual versus bisexual mating in Cryptococcus neoformans: Consequences and biological impacts

Cryptococcus neoformans is an opportunistic human fungal pathogen and can undergo both bisexual and unisexual mating. Despite the fact that one mating type is dispensable for unisexual mating, the two sexual cycles share surprisingly similar features. Both mating cycles are affected by similar environmental factors and regulated by the same pheromone response pathway. Recombination takes place during unisexual reproduction in a fashion similar to bisexual reproduction and can both admix pre-existing genetic diversity and also generate diversity de novo just like bisexual reproduction. These common features may allow the unisexual life cycle to provide phenotypic and genotypic plasticity for the natural Cryptococcus population, which is predominantly α mating type, and to avoid Muller's ratchet. The morphological transition from yeast to hyphal growth during both bisexual and unisexual mating may provide increased opportunities for outcrossing and the ability to forage for nutrients at a distance. The unisexual life cycle is a key evolutionary factor for Cryptococcus as a highly successful global fungal pathogen.

Model selection emphasises the importance of non-chromosomal information in genetic studies

Ever since the case of the missing heritability was highlighted some years ago, scientists have been investigating various possible explanations for the issue. However, none of these explanations include non-chromosomal genetic information. Here we describe explicitly how chromosomal and non-chromosomal modifiers collectively influence the heritability of a trait, in this case, the growth rate of yeast. Our results show that the non-chromosomal contribution can be large, adding another dimension to the estimation of heritability. We also discovered, combining the strength of LASSO with model selection, that the interaction of chromosomal and non-chromosomal information is essential in describing phenotypes.

Higher-order genetic interactions and their contribution to complex traits

The contribution of genetic interactions involving three or more loci to complex traits is poorly understood. These higher-order genetic interactions (HGIs) are difficult to detect in genetic mapping studies, therefore, few examples of them have been described. However, the lack of data on HGIs should not be misconstrued as proof that this class of genetic effect is unimportant. To the contrary, evidence from model organisms suggests that HGIs frequently influence genetic studies and contribute to many complex traits. Here, we review the growing literature on HGIs and discuss the future of research on this topic.