Substrate-specific effects of natural genetic variation on proteasome activity.

Protein degradation is an essential biological process that regulates protein abundance and removes misfolded and damaged proteins from cells. In eukaryotes, most protein degradation occurs through the stepwise actions of two functionally distinct entities, the ubiquitin system and the proteasome. Ubiquitin system enzymes attach ubiquitin to cellular proteins, targeting them for degradation. The proteasome then selectively binds and degrades ubiquitinated substrate proteins. Genetic variation in ubiquitin system genes creates heritable differences in the degradation of their substrates. However, the challenges of measuring the degradative activity of the proteasome independently of the ubiquitin system in large samples have limited our understanding of genetic influences on the proteasome. Here, using the yeast Saccharomyces cerevisiae, we built and characterized reporters that provide high-throughput, ubiquitin system-independent measurements of proteasome activity. Using single-cell measurements of proteasome activity from millions of genetically diverse yeast cells, we mapped 15 loci across the genome that influence proteasomal protein degradation. Twelve of these 15 loci exerted specific effects on the degradation of two distinct proteasome substrates, revealing a high degree of substrate-specificity in the genetics of proteasome activity. Using CRISPR-Cas9-based allelic engineering, we resolved a locus to a causal variant in the promoter of RPT6, a gene that encodes a subunit of the proteasome's 19S regulatory particle. The variant increases RPT6 expression, which we show results in increased proteasome activity. Our results reveal the complex genetic architecture of proteasome activity and suggest that genetic influences on the proteasome may be an important source of variation in the many cellular and organismal traits shaped by protein degradation.

Genes and compounds that increase type VII collagen expression as potential treatments for dystrophic epidermolysis bullosa.

Dystrophic epidermolysis bullosa (DEB) is a skin-blistering disease caused by mutations in COL7A1, which encodes type VII collagen (C7). There is no cure for DEB, but previous work has shown potential therapeutic benefit of increased production of even partially functional C7. Genome-wide screens using CRISPR-Cas9 have enabled the identification of genes involved in cancer development, drug resistance and other genetic diseases, suggesting that they could be used to identify drivers of C7 production. A keratinocyte C7 reporter cell line was created and used in a genome-wide CRISPR activation (CRISPRa) screen to identify genes and pathways that increase C7 expression. The CRISPRa screen results were used to develop a targeted drug screen to identify compounds that upregulate C7 expression. The C7_tdTomato cell line was validated as an effective reporter for detection of C7 upregulation. The CRISPRa screen identified DENND4B and TYROBP as top gene hits plus pathways related to calcium uptake and immune signalling in C7 regulation. The targeted drug screen identified several compounds that increase C7 expression in keratinocytes, of which kaempferol, a plant flavonoid, also significantly increased C7 mRNA and protein in DEB patient cells.

DNA variants affecting the expression of numerous genes in trans have diverse mechanisms of action and evolutionary histories.

DNA variants that alter gene expression contribute to variation in many phenotypic traits. In particular, trans-acting variants, which are often located on different chromosomes from the genes they affect, are an important source of heritable gene expression variation. However, our knowledge about the identity and mechanism of causal trans-acting variants remains limited. Here, we developed a fine-mapping strategy called CRISPR-Swap and dissected three expression quantitative trait locus (eQTL) hotspots known to alter the expression of numerous genes in trans in the yeast Saccharomyces cerevisiae. Causal variants were identified by engineering recombinant alleles and quantifying the effects of these alleles on the expression of a green fluorescent protein-tagged gene affected by the given locus in trans. We validated the effect of each variant on the expression of multiple genes by RNA-sequencing. The three variants differed in their molecular mechanism, the type of genes they reside in, and their distribution in natural populations. While a missense leucine-to-serine variant at position 63 in the transcription factor Oaf1 (L63S) was almost exclusively present in the reference laboratory strain, the two other variants were frequent among S. cerevisiae isolates. A causal missense variant in the glucose receptor Rgt2 (V539I) occurred at a poorly conserved amino acid residue and its effect was strongly dependent on the concentration of glucose in the culture medium. A noncoding variant in the conserved fatty acid regulated (FAR) element of the OLE1 promoter influenced the expression of the fatty acid desaturase Ole1 in cis and, by modulating the level of this essential enzyme, other genes in trans. The OAF1 and OLE1 variants showed a non-additive genetic interaction, and affected cellular lipid metabolism. These results demonstrate that the molecular basis of trans-regulatory variation is diverse, highlighting the challenges in predicting which natural genetic variants affect gene expression.

The role of regulatory variation in complex traits and disease.

We are in a phase of unprecedented progress in identifying genetic loci that cause variation in traits ranging from growth and fitness in simple organisms to disease in humans. However, a mechanistic understanding of how these loci influence traits is lacking for the majority of loci. Studies of the genetics of gene expression have emerged as a key tool for linking DNA sequence variation to phenotypes. Here, we review recent insights into the molecular nature of regulatory variants and describe their influence on the transcriptome and the proteome. We discuss conceptual advances from studies in model organisms and present examples of complete chains of causality that link individual polymorphisms to changes in gene expression, which in turn result in physiological changes and, ultimately, disease risk.

Genetics of single-cell protein abundance variation in large yeast populations.

Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or several genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL). Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power. Consequently, many eQTL are probably missed, especially those with smaller effects. Furthermore, most studies use messenger RNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics reported unexpected differences between eQTL and protein QTL (pQTL) for the same genes, but these studies have been even more limited in scope. Here we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyces cerevisiae. We measure single-cell protein abundance through the use of green fluorescent protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high versus low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci that we detected were clustered in 'hotspots' that influence multiple proteins, and some hotspots were found to influence more than half of the proteins that we examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.

Genetic mapping of MAPK-mediated complex traits Across S. cerevisiae.

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.

The evolution of gene expression levels in mammalian organs.

Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

Genetic influences on translation in yeast.

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.

The genomic architecture of population divergence between subspecies of the European rabbit.

The analysis of introgression of genomic regions between divergent populations provides an excellent opportunity to determine the genetic basis of reproductive isolation during the early stages of speciation. However, hybridization and subsequent gene flow must be relatively common in order to localize individual loci that resist introgression. In this study, we used next-generation sequencing to study genome-wide patterns of genetic differentiation between two hybridizing subspecies of rabbits (Oryctolagus cuniculus algirus and O. c. cuniculus) that are known to undergo high rates of gene exchange. Our primary objective was to identify specific genes or genomic regions that have resisted introgression and are likely to confer reproductive barriers in natural conditions. On the basis of 326,000 polymorphisms, we found low to moderate overall levels of differentiation between subspecies, and fewer than 200 genomic regions dispersed throughout the genome showing high differentiation consistent with a signature of reduced gene flow. Most differentiated regions were smaller than 200 Kb and contained very few genes. Remarkably, 30 regions were each found to contain a single gene, facilitating the identification of candidate genes underlying reproductive isolation. This gene-level resolution yielded several insights into the genetic basis and architecture of reproductive isolation in rabbits. Regions of high differentiation were enriched on the X-chromosome and near centromeres. Genes lying within differentiated regions were often associated with transcription and epigenetic activities, including chromatin organization, regulation of transcription, and DNA binding. Overall, our results from a naturally hybridizing system share important commonalities with hybrid incompatibility genes identified using laboratory crosses in mice and flies, highlighting general mechanisms underlying the maintenance of reproductive barriers.

A comparison of brain gene expression levels in domesticated and wild animals.

Domestication has led to similar changes in morphology and behavior in several animal species, raising the question whether similarities between different domestication events also exist at the molecular level. We used mRNA sequencing to analyze genome-wide gene expression patterns in brain frontal cortex in three pairs of domesticated and wild species (dogs and wolves, pigs and wild boars, and domesticated and wild rabbits). We compared the expression differences with those between domesticated guinea pigs and a distant wild relative (Cavia aperea) as well as between two lines of rats selected for tameness or aggression towards humans. There were few gene expression differences between domesticated and wild dogs, pigs, and rabbits (30-75 genes (less than 1%) of expressed genes were differentially expressed), while guinea pigs and C. aperea differed more strongly. Almost no overlap was found between the genes with differential expression in the different domestication events. In addition, joint analyses of all domesticated and wild samples provided only suggestive evidence for the existence of a small group of genes that changed their expression in a similar fashion in different domesticated species. The most extreme of these shared expression changes include up-regulation in domesticates of SOX6 and PROM1, two modulators of brain development. There was almost no overlap between gene expression in domesticated animals and the tame and aggressive rats. However, two of the genes with the strongest expression differences between the rats (DLL3 and DHDH) were located in a genomic region associated with tameness and aggression, suggesting a role in influencing tameness. In summary, the majority of brain gene expression changes in domesticated animals are specific to the given domestication event, suggesting that the causative variants of behavioral domestication traits may likewise be different.

Comparative population genomics of the ejaculate in humans and the great apes.

The rapid molecular evolution of reproductive genes is nearly ubiquitous across animals, yet the selective forces and functional targets underlying this divergence remain poorly understood. Humans and closely related species of great apes show strongly divergent mating systems, providing a powerful system to investigate the influence of sperm competition on the evolution of reproductive genes. This is complemented by detailed information on male reproductive biology and unparalleled genomic resources in humans. Here, we have used custom microarrays to capture and sequence 285 genes encoding proteins present in the ejaculate as well as 101 randomly selected control genes in 21 gorillas, 20 chimpanzees, 20 bonobos, and 20 humans. In total, we have generated >25× average genomic coverage per individual for over 1 million target base pairs. Our analyses indicate high levels of evolutionary constraint across much of the ejaculate combined with more rapid evolution of genes involved in immune defense and proteolysis. We do not find evidence for appreciably more positive selection along the lineage leading to bonobos and chimpanzees, although this would be predicted given more intense sperm competition in these species. Rather, the extent of positive and negative selection depended more on the effective population sizes of the species. Thus, general patterns of male reproductive protein evolution among apes and humans depend strongly on gene function but not on inferred differences in the intensity of sperm competition among extant species.

Assembly, stability, and dynamics of the infant gut microbiome are linked to bacterial strains and functions in mother's milk.

The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as the sole source of nutrition for the human infant, little is known about how variation in milk composition, and especially the milk microbiome, shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiome using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. We found that the microbial taxonomic overlap between milk and the infant gut was driven by bifidobacteria, in particular by B. longum. Infant stool samples dominated by B. longum also showed higher temporal stability compared to samples dominated by other species. We identified two instances of strain sharing between maternal milk and the infant gut, one involving a commensal (B. longum) and one a pathobiont (K. pneumoniae). In addition, strain sharing between unrelated infants was higher among infants born at the same hospital compared to infants born in different hospitals, suggesting a potential role of the hospital environment in shaping the infant gut microbiome composition. The infant gut microbiome at one month compared to six months of age was enriched in metabolic pathways associated with de-novo molecule biosynthesis, suggesting that early colonisers might be more versatile and metabolically independent compared to later colonizers. Lastly, we found a significant overlap in antimicrobial resistance genes carriage between the mother's milk and their infant's gut microbiome. Taken together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome.

Expression of carnitine palmitoyl-CoA transferase-1B is influenced by a cis-acting eQTL in two chicken lines selected for high and low body weight.

Carnitine palmitoyl-CoA transferase-1B is a mitochondrial enzyme in the fatty acid oxidation pathway. In a previous study, CPT1B was identified as differentially expressed in the hypothalamus of two lines of chickens established by long-term selection for high (HWS) or low (LWS) body weight. Mammals have three paralogs (CPT1a, b and c) while nonmammalian vertebrates only have two (CPT1A, B). CPT1A is expressed in liver and CPT1B in muscle. CPT1c is expressed in hypothalamus, where it regulates feeding and energy expenditure. We identified an intronic length polymorphism, fixed for different alleles in the two populations, and mapped the hitherto missing CPT1B locus in the chicken genome assembly, to the distal tip of chromosome 1p. Based on molecular phylogeny and gene synteny we suggest that chicken CPT1B is pro-orthologous of the mammalian CPT1c. Chicken CPT1B was differentially expressed in both muscle and hypothalamus but in opposite directions: higher levels in hypothalamus but lower levels in muscle in the HWS than in the LWS line. Using an advanced intercross population of the lines, we found CPT1B expression to be influenced by a cis-acting expression quantitative trait locus in muscle. The increased expression in hypothalamus and reduced expression in muscle is consistent with an increased food intake in the HWS line and at the same time reduced fatty acid oxidation in muscle yielding a net accumulation of energy intake and storage. The altered expression of CPT1B in hypothalamus and peripheral tissue is likely to be a mechanism contributing to the remarkable difference between lines.

Evidence for widespread positive and purifying selection across the European rabbit (Oryctolagus cuniculus) genome.

The nearly neutral theory of molecular evolution predicts that the efficacy of both positive and purifying selection is a function of the long-term effective population size (N(e)) of a species. Under this theory, the efficacy of natural selection should increase with N(e). Here, we tested this simple prediction by surveying ~1.5 to 1.8 Mb of protein coding sequence in the two subspecies of the European rabbit (Oryctolagus cuniculus algirus and O. c. cuniculus), a mammal species characterized by high levels of nucleotide diversity and N(e) estimates for each subspecies on the order of 1 × 10(6). When the segregation of slightly deleterious mutations and demographic effects were taken into account, we inferred that >60% of amino acid substitutions on the autosomes were driven to fixation by positive selection. Moreover, we inferred that a small fraction of new amino acid mutations (<4%) are effectively neutral (defined as 0 < N(e)s < 1) and that this fraction was negatively correlated with a gene's expression level. Consistent with models of recurrent adaptive evolution, we detected a negative correlation between levels of synonymous site polymorphism and the rate of protein evolution, although the correlation was weak and nonsignificant. No systematic X chromosome-autosome difference was found in the efficacy of selection. For example, the proportion of adaptive substitutions was significantly higher on the X chromosome compared with the autosomes in O. c. algirus but not in O. c. cuniculus. Our findings support widespread positive and purifying selection in rabbits and add to a growing list of examples suggesting that differences in N(e) among taxa play a substantial role in determining rates and patterns of protein evolution.

Trans-eQTL hotspots shape complex traits by modulating cellular states.

Regulatory genetic variation shapes gene expression, providing an important mechanism connecting DNA variation and complex traits. The causal relationships between gene expression and complex traits remain poorly understood. Here, we integrated transcriptomes and 46 genetically complex growth traits in a large cross between two strains of the yeast Saccharomyces cerevisiae. We discovered thousands of genetic correlations between gene expression and growth, suggesting functional connections. Local regulatory variation was a minor source of these genetic correlations. Instead, genetic correlations tended to arise from multiple independent trans-acting regulatory loci. Trans-acting hotspots that affect the expression of numerous genes accounted for particularly large fractions of genetic growth variation and of genetic correlations between gene expression and growth. Genes with genetic correlations were enriched for similar biological processes across traits, but with heterogeneous direction of effect. Our results reveal how trans-acting regulatory hotspots shape complex traits by altering cellular states.

Integration of 168,000 samples reveals global patterns of the human gut microbiome.

Understanding the factors that shape variation in the human microbiome is a major goal of research in biology. While other genomics fields have used large, pre-compiled compendia to extract systematic insights requiring otherwise impractical sample sizes, there has been no comparable resource for the 16S rRNA sequencing data commonly used to quantify microbiome composition. To help close this gap, we have assembled a set of 168,484 publicly available human gut microbiome samples, processed with a single pipeline and combined into the largest unified microbiome dataset to date. We use this resource, which is freely available at microbiomap.org, to shed light on global variation in the human gut microbiome. We find that Firmicutes, particularly Bacilli and Clostridia, are almost universally present in the human gut. At the same time, the relative abundance of the 65 most common microbial genera differ between at least two world regions. We also show that gut microbiomes in undersampled world regions, such as Central and Southern Asia, differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America. Moreover, humans in these overlooked regions likely harbor hundreds of taxa that have not yet been discovered due to this undersampling, highlighting the need for diversity in microbiome studies. We anticipate that this new compendium can serve the community and enable advanced applied and methodological research.

Human Cytomegalovirus in breast milk is associated with milk composition, the infant gut microbiome, and infant growth.

Human cytomegalovirus (CMV) is a highly prevalent herpesvirus that is often transmitted to the neonate via breast milk. Postnatal CMV transmission can have negative health consequences for preterm and immunocompromised infants, but any effects on healthy term infants are thought to be benign. Furthermore, the impact of CMV on the composition of the hundreds of bioactive factors in human milk has not been tested. Here, we utilize a cohort of exclusively breastfeeding full term mother-infant pairs to test for differences in the milk transcriptome and metabolome associated with CMV, and the impact of CMV in breast milk on the infant gut microbiome and infant growth. We find upregulation of the indoleamine 2,3- dioxygenase (IDO) tryptophan-to-kynurenine metabolic pathway in CMV+ milk samples, and that CMV+ milk is associated with decreased Bifidobacterium in the infant gut. Our data indicate a complex relationship between milk CMV, milk kynurenine, and infant growth; with kynurenine positively correlated, and CMV viral load negatively correlated, with infant weight-for-length at 1 month of age. These results suggest CMV transmission, CMV-related changes in milk composition, or both may be modulators of full term infant development.

Human milk variation is shaped by maternal genetics and impacts the infant gut microbiome.

Human milk is a complex mix of nutritional and bioactive components that provide complete nutrition for the infant. However, we lack a systematic knowledge of the factors shaping milk composition and how milk variation influences infant health. Here, we used multi-omic profiling to characterize interactions between maternal genetics, milk gene expression, milk composition, and the infant fecal microbiome in 242 exclusively breastfeeding mother-infant pairs. We identified 487 genetic loci associated with milk gene expression unique to the lactating mammary gland, including loci that impacted breast cancer risk and human milk oligosaccharide concentration. Integrative analyses uncovered connections between milk gene expression and infant gut microbiome, including an association between the expression of inflammation-related genes with IL-6 concentration in milk and the abundance of Bifidobacteria in the infant gut. Our results show how an improved understanding of the genetics and genomics of human milk connects lactation biology with maternal and infant health.

Altered immune response in mice deficient for the G protein-coupled receptor GPR34.

The X-chromosomal GPR34 gene encodes an orphan G(i) protein-coupled receptor that is highly conserved among vertebrates. To evaluate the physiological relevance of GPR34, we generated a GPR34-deficient mouse line. GPR34-deficient mice were vital, reproduced normally, and showed no gross abnormalities in anatomical, histological, laboratory chemistry, or behavioral investigations under standard housing. Because GPR34 is highly expressed in mononuclear cells of the immune system, mice were specifically tested for altered functions of these cell types. Following immunization with methylated BSA, the number of granulocytes and macrophages in spleens was significantly lower in GPR34-deficient mice as in wild-type mice. GPR34-deficient mice showed significantly increased paw swelling in the delayed type hypersensitivity test and higher pathogen burden in extrapulmonary tissues after pulmonary infection with Cryptococcus neoformans compared with wild-type mice. The findings in delayed type hypersensitivity and infection tests were accompanied by significantly different basal and stimulated TNF-α, GM-CSF, and IFN-γ levels in GPR34-deficient animals. Our data point toward a functional role of GPR34 in the cellular response to immunological challenges.

Multiple epistatic DNA variants in a single gene affect gene expression in trans.

DNA variants that alter gene expression in trans are important sources of phenotypic variation. Nevertheless, the identity of trans-acting variants remains poorly understood. Single causal variants in several genes have been reported to affect the expression of numerous distant genes in trans. Whether these simple molecular architectures are representative of trans-acting variation is unknown. Here, we studied the large RAS signaling regulator gene IRA2, which contains variants with extensive trans-acting effects on gene expression in the yeast Saccharomyces cerevisiae. We used systematic CRISPR-based genome engineering and a sensitive phenotyping strategy to dissect causal variants to the nucleotide level. In contrast to the simple molecular architectures known so far, IRA2 contained at least seven causal nonsynonymous variants. The effects of these variants were modulated by nonadditive, epistatic interactions. Two variants at the 5'-end affected gene expression and growth only when combined with a third variant that also had no effect in isolation. Our findings indicate that the molecular basis of trans-acting genetic variation may be considerably more complex than previously appreciated.