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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

Cannabis use, depression and self-harm: phenotypic and genetic relationships

Background and AimsThe use of cannabis has previously been linked to both depression and self-harm, however the role of genetics in this relationship are unclear. We aimed to examine the phenotypic and genetic relationships between these traits. DesignGenetic and cross-sectional phenotypic data collected through UK Biobank, together with consortia genome-wide association study summary statistics. These data were used to assess the phenotypic and genetic relationship between cannabis use, depression and self harm. SettingUK, with additional international consortia data ParticipantsN=126,291 British adults aged between 40 and 70 years, recruited into UK Biobank MeasurementsGenome-wide genetic data, phenotypic data on lifetime history of cannabis use, depression and self-harm. FindingsIn UK Biobank, cannabis use is associated with increased likelihood of depression (OR=1.64, 95% CI=1.59-1.70, p=1.19x10-213) and self-harm (OR=2.85, 95% CI=2.69-3.01, p=3.46x10-304). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Additionally, significant genetic correlations are seen between cannabis use and depression using consortia summary statistics (rg=0.289, SE=0.036, p=1.45x10-15). Polygenic risk scores for cannabis use and depression both explain a small but significant proportion of variance in cannabis use, depression and self harm within a UK Biobank target sample. However, two-sample Mendelian randomisation analyses were not significant. ConclusionsCannabis use is both phenotypically and genetically associated with depression and self harm. Future work dissecting the causal mechanism linking these traits may have implications for cannabis users.

genetics↗

bioRxiv2019

Genetic basis of plasticity for forage quality traits in response to water deficit in a diverse germplasm panel of alfalfa

Plant phenotypic plasticity is the ability of plants to express different phenotypes in response to environmental variations. Genetic bases by which phenotypic plasticity affects plant adaptation to environmental change remain largely unknown. In the present study, we characterized 26 forage quality traits in a panel of alfalfa 198 accessions in a field trial under water deficit gradient. The regression analysis revealed that the values of fiber-related traits decreased, while those among energy-related traits increased, as water deficit increased. Genetic loci for forage quality traits were investigated by Genome-wide association studies (GWAS) under different levels of water deficit. Genetic loci associated with forage quality traits were identified and compared. Similar regions were found between energy-related traits when grand means were used for GWAS. Most of the associated markers were identified under water deficit, suggesting genetic mechanisms for forage quality traits were differ between well-watered and water stressed plants. Although GWAS on forage quality have been reported, we are the first to address the genetic factors for forage quality traits under water deficit in autotetraploid alfalfa. The information gained from the present study will be useful for the genetic improvement of alfalfa with enhanced drought/salt tolerance while maintaining forage quality.

genetics↗

bioRxiv2019

Genetic analysis identifies molecular systems and biological pathways associated with household income

Socio-economic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. Previous genome-wide association studies (GWAS) using household income as a marker of SEP have shown that common genetic variants account for 11% of its variation. Here, in a sample of 286,301 participants from UK Biobank, we identified 30 independent genome-wide significant loci, 29 novel, that are associated with household income. Using a recently-developed method to meta-analyze data that leverages power from genetically-correlated traits, we identified an additional 120 income-associated loci. These loci showed clear evidence of functional enrichment, with transcriptional differences identified across multiple cortical tissues, in addition to links with GABAergic and serotonergic neurotransmission. We identified neurogenesis and the components of the synapse as candidate biological systems that are linked with income. By combining our GWAS on income with data from eQTL studies and chromatin interactions, 24 genes were prioritized for follow up, 18 of which were previously associated with cognitive ability. Using Mendelian Randomization, we identified cognitive ability as one of the causal, partly-heritable phenotypes that bridges the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. Significant differences between genetic correlations indicated that, the genetic variants associated with income are related to better mental health than those linked to educational attainment (another commonly-used marker of SEP). Finally, we were able to predict 2.5% of income differences using genetic data alone in an independent sample. These results are important for understanding the observed socioeconomic inequalities in Great Britain today.

genetics↗

bioRxiv2019

Genetic structure is stronger across human-impacted habitats than among islands in the coral Porites lobata

We examined genetic structure in the lobe coral Porites lobata among pairs of highly variable and high-stress nearshore sites and adjacent less variable and less impacted offshore sites on the islands of Oahu and Maui, Hawai i. Using an analysis of molecular variance framework, we tested whether populations were more structured by geographic distance or environmental extremes. The genetic patterns we observed followed isolation by environment, where nearshore and adjacent offshore populations showed significant genetic structure at both locations (AMOVA FST = 0.04 [~] 0.19, P < 0.001), but no significant isolation by distance between islands. In contrast, a third site with a less impacted nearshore site showed no significant structure. Strikingly, corals from the two impacted nearshore sites on different islands over 100km apart with similar environmentally stressful conditions were genetically closer (FST[~] 0, P = 0.733) than those within a single location less than 2 km apart (FST= 0.041[~]0.079, P < 0.01). Our results suggest that ecological boundaries appear to play a strong role in forming genetic structure in the coastal environment, and that genetic divergence in the absence of geographical barriers to gene flow may be explained by disruptive selection across contrasting habitats.

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bioRxiv2019

Genomic analyses underpin the feasibility of concomitant genetic improvement of milk yield and mastitis resistance in dairy sheep

Milk yield is the most important dairy sheep trait and constitutes the key genetic improvement goal via selective breeding. Mastitis is one of the most prevalent diseases, significantly impacting on animal welfare, milk yield and quality, while incurring substantial costs. Our objectives were to determine the feasibility of a concomitant genetic improvement programme for enhanced milk production and resistance to mastitis. Individual records for milk yield and four mastitis-related traits were collected monthly throughout lactation for 609 ewes of the Chios breed. All ewes were genotyped with a mastitis specific custom-made 960 single nucleotide polymorphism array. We performed genomic association studies, (co)variance component estimation and pathway enrichment analysis, and characterised gene expression levels and the extent of allelic expression imbalance. Presence of heritable variation for milk yield was confirmed. There was no significant genetic correlation between milk yield and mastitis. Environmental factors appeared to favour both milk production and udder health. Four Quantitative Trait Loci (QTLs) affecting milk yield were detected on chromosomes 2, 12, 16 and 19, in locations distinct from those previously identified to affect mastitis resistance. Pathways, networks and functional gene clusters for milk yield were identified. Seven genes (DNAJA1, DNAJC10, FGF10, GHR, HMGCS1, LYPLA1, OXCT1) located within the QTL regions were highly expressed in both the mammary gland and milk transcriptome, suggesting involvement in milk synthesis and production. Furthermore, the expression of four genes (DNAJC10, FGF10, OXCT1, EMB) was enriched in immune tissues implying a favourable pleiotropic effect or likely role in milk production during udder infection. In conclusion, the absence of genetic antagonism between milk yield and mastitis resistance suggests that simultaneous genetic improvement of both traits be achievable. The detection of milk yield QTLs with the mastitis array underpins the latters utility as a breeding tool for the genetic enhancement of both traits.

genetics↗

bioRxiv2019

Changes in gene expression shift and switch genetic interactions

An important goal in disease genetics and evolutionary biology is to understand how mutations combine to alter phenotypes and fitness. Non-additive interactions between mutations occur extensively and change across conditions, cell types, and species, making genetic prediction a difficult challenge. To understand the reasons for this, we reduced the problem to a minimal system where we combined mutations in a single protein performing a single function (a transcriptional repressor inhibiting a target gene). Even in this minimal system, a change in gene expression altered both the strength and type of genetic interactions. These seemingly complicated changes could, however, be predicted by a mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype. We show that similar changes will be observed for many genes. These results provide fundamental insights into genotype-phenotype maps and illustrate how changes in genetic interactions can be predicted using hierarchical mechanistic models.\n\nOne sentence SummaryDeep mutagenesis of the lambda repressor reveals that changes in gene expression will alter the strength and direction of genetic interactions between mutations in many genes.\n\nHighlightsO_LIDeep mutagenesis of the lambda repressor at two expression levels reveals extensive changes in mutational effects and genetic interactions\nC_LIO_LIGenetic interactions can switch from positive (suppressive) to negative (enhancing) as the expression of a gene changes\nC_LIO_LIA mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype accurately predicts changes in mutational effects and interactions\nC_LIO_LIChanges in expression will alter mutational effects and interactions for many genes\nC_LIO_LIFor some genes, perfect mechanistic models will never be able to predict how mutations of known effect combine without measurements of intermediate phenotypes\nC_LI

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bioRxiv2019

Insight into the genetic aetiology of retinal detachment by combining small clinical and large population-based datasets

Idiopathic retinal detachment is a serious common condition, but genetic studies to date have been hampered by the small size of the assembled cohorts. Genetic correlations between retinal detachment and high myopia or cataract operation were high, respectively 0.46 (SE=0.08) and 0.44 (SE=0.07), in the UK Biobank dataset and in line with known epidemiological associations. Meta-analysis of genome-wide association studies using UK Biobank retinal detachment cases (N=3977) and two cohorts, each comprising [~]1000 rhegmatogenous retinal detachment patients, uncovered 11 genome-wide significant association signals, near or within ZC3H11B, BMP3, COL22A1, DLG5, PLCE1, EFEMP2, TYR, FAT3, TRIM29, COL2A1 and LOXL1. Replication in the 23andMe dataset, where retinal detachment is self-reported by participants, firmly establishes association at six loci FAT3, COL22A1, TYR, BMP3, ZC3H11B and PLCE1. The former two seem to particularly impact on retinal detachment, the latter three shed light on shared aetiologies with cataract, myopia and glaucoma.\n\nAuthor SummaryRetinal detachments are common conditions that may lead to permanent severe sight reduction or blindness; they are a major cause of emergency eye surgery. The most common type of retinal detachment follows a break in the retina and is thought to be in part genetically determined but little is known about the contributing individual genetic risk variants. The condition prevalence increases with age and with common eye conditions such as myopia, cataract or glaucoma. We showed that the retinal detachment cases derived from self-report or hospitalisation records in the large UK Biobank dataset show very similar characteristics to samples of carefully clinically evaluated retinal detachment with break cases and therefore could be used to perform genetic analysis of the condition. Association studies require large sample of cases and by pooling Biobank and clinical cases, this study identifies 11 novel significant associations, six of which were further replicated in an independent population-based dataset (23andMe). Two of the replicated findings seem to specifically underline retinal detachment risk while three others highlight shared genetic risk with myopia, cataract and/or glaucoma, paving the way to better understanding of these conditions and of their overlap.

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bioRxiv2019

Genetic evaluation modeling of the Tunisian dairy cattle: assessment of the test-day model (TDM) and lactation model (L305) in accordance to the flock size

Genetic evaluation in dairy cattle has been commonly carried following the lactation model (L305) and the test-day model (TDM), the purpose of this study was to test the adjustment and the accuracy of these main models in relation to the size of the Tunisian dairy flocks while assessing the effect of genealogical data availability on both approaches. Data were obtained from the Tunisian official milk recording system and cows were classified in accordance to the flock sizes into eight groups. Genetic parameters and breeding values were estimated per size group for 305-days (L305) and daily milk yields (TDM) through two animal models and by using 3 pedigrees of different quality. Contemporary groups were defined as herd*calving year for L305 and as herd*control year for TDM. Genetic evaluation approaches were compared by connecting the different obtained results. Fixed factors were observed to be differently significant per group of flock size explaining a specific variance of the average milk yield and that small flocks are mostly affected by environmental factors. Using TDM and an equilibrated pedigree file, genetic parameters were higher, breeding values were fairly compared leading to a more objective ranking of the cows and a better illustration of genetic variabilities between the flock groups. Low genetic variability and significant contribution of unfavorable environmental conditions were observed within the Tunisian dairy flocks.

genetics↗

bioRxiv2019

Shared genetic background between children and adults with attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention, impulsivity and hyperactivity that persist into adulthood in the majority of the diagnosed children. Despite several risk factors during childhood predicting the persistence of ADHD symptoms into adulthood, the genetic architecture underlying the trajectory of ADHD over time is still unclear. We set out to study the contribution of common genetic variants to the risk for ADHD across the lifespan by conducting meta-analyses of genome-wide association studies on persistent ADHD in adults and ADHD in childhood separately and comparing the genetic background between them in a total sample of 17,149 cases and 32,411 controls. Our results show nine new independent loci and support a shared contribution of common genetic variants to ADHD in children and adults. No subgroup heterogeneity was observed among children, while this group consists of future remitting and persistent individuals. We report similar patterns of genetic correlation of ADHD with other ADHD-related datasets and different traits and disorders among adults, children and when combining both groups. These findings confirm that persistent ADHD in adults is a neurodevelopmental disorder and extend the existing hypothesis of a shared genetic architecture underlying ADHD and different traits to a lifespan perspective.

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bioRxiv2019

Genetic Architecture of Chilling Tolerance in Sorghum Dissected with a Nested Association Mapping Population

Dissecting the genetic architecture of stress tolerance in crops is critical to understand and improve adaptation. In temperate climates, early planting of chilling-tolerant varieties could provide longer growing seasons and drought escape, but chilling tolerance (<15{degrees}) is generally lacking in tropical-origin crops. Here we developed a nested association mapping (NAM) population to dissect the genetic architecture of early-season chilling tolerance in the tropical-origin cereal sorghum (Sorghum bicolor [L.] Moench). The NAM resource, developed from reference line BTx623 and three chilling-tolerant Chinese lines, is comprised of 771 recombinant inbred lines genotyped by sequencing at 43,320 single nucleotide polymorphisms. We phenotyped the NAM population for emergence, seedling vigor, and agronomic traits (>75,000 data points from [~]16,000 plots) in multi-environment field trials in Kansas under natural chilling stress (sown 30-45 days early) and normal growing conditions. Joint linkage mapping with early-planted field phenotypes revealed an oligogenic architecture, with 5-10 chilling tolerance loci explaining 20-41% of variation. Surprisingly, several of the major chilling tolerance loci co-localize precisely with the classical grain tannin (Tan1 and Tan2) and dwarfing genes (Dw1 and Dw3) that were under strong directional selection in the US during the 20th century. These findings suggest that chilling sensitivity was inadvertently selected due to coinheritance with desired nontannin and dwarfing alleles. The characterization of genetic architecture with NAM reveals why past chilling tolerance breeding was stymied and provides a path for genomics-enabled breeding of chilling tolerance.\n\nArticle SummaryChilling sensitivity limits productivity of tropical-origin crops in temperate climates, and remains poorly understood at a genetic level. We developed a nested association mapping resource in sorghum, a tropical-origin cereal, to understand the genetic architecture of chilling tolerance. Linkage mapping of growth traits from early-planted field trials revealed several major chilling tolerance loci, including some colocalized with genes that were selected in the origin of US grain sorghum. These findings suggest chilling sensitivity was inadvertently selected during 20th century breeding, but can be bypassed using a better understanding of the underlying genetic architecture.\n\nDisclaimerMention of a trademark, warranty, proprietary product, or vendor does not constitute a guarantee by the USDA and does not imply approval or recommendation of the product to the exclusion of others that may be suitable. USDA is an equal opportunity provider and employer.

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bioRxiv2019

Why are education, socioeconomic position and intelligence genetically correlated?

Genetic associations and correlations are perceived as confirmation that genotype influences one or more phenotypes respectively. However, genetic correlations can arise from non-biological or indirect mechanisms including population stratification, dynastic effects, and assortative mating. In this paper, we outline these mechanisms and demonstrate available tools and analytic methods that can be used to assess their presence in estimates of genetic correlations and genetic associations. Using educational attainment and parental socioeconomic position data as an exemplar, we demonstrate that both heritability and genetic correlation estimates may be inflated by these indirect mechanisms. The results highlight the limitations of between-individual estimates obtained from samples of unrelated individuals and the potential value of family-based studies. Use of the highlighted tools in combination with within-sibling or mother-father-offspring trio data may offer researchers greater opportunity to explore the underlying mechanisms behind genetic associations and correlations and identify the underlying causes of estimate inflation.

genetics↗

bioRxiv2019

Development of a Genomic DNA Reference Material Panel for Thalassemia Genetic Testing

Thalassemia is one of the most common autosomal recessive inherited diseases worldwide, and it is also highly prevalent and variable in Southern China. Various types of genetic testing technologies have been developed for diagnosis and screening of thalassemia. Characterized genomic DNA reference materials are necessary for assay development, validation, proficiency testing and quality assurance. However, there is no publicly available reference materials for thalassemia genetic testing as yet. To address the need for these materials, the National Institutes for Food and Drug Control and the China National Gene Bank established 31 new cell lines with 2 wild genotypes and 29 distinct genotypes of thalassemia which account for approximately 90% thalassemia carriers in China. The genomic DNA of 31 cell lines were characterized by four clinical genetic testing laboratories using different genetic testing methods and technology platforms. The genotyping results were concordant among four laboratories. In addition, the results of stability test demonstrated that the genotypes of these DNA samples were not influenced by preanalytical conditions such as long-term exposure to high temperature(37{square}) environment and repeated freeze-thawing. In conclusion, we developed the first national panel of 31 genomic DNA reference materials which are renewable and publicly available for the quality assurance of various genetic testing methods and will facilitate research and development in thalassemia genetic testing.

genetics↗

bioRxiv2019

Mozambican genetic variation provides new insights into the Bantu expansion

The Bantu expansion, which started in West Central Africa around 5,000 BP, constitutes a major migratory movement involving the joint spread of peoples and languages across sub-Saharan Africa. Despite the rich linguistic and archaeological evidence available, the genetic relationships between different Bantu-speaking populations and the migratory routes they followed during various phases of the expansion remain poorly understood. Here, we analyze the genetic profiles of southwestern and southeastern Bantu-speaking peoples located at the edges of the Bantu expansion by generating genome-wide data for 200 individuals from 12 Mozambican and 3 Angolan populations using [~]1.9 million autosomal single nucleotide polymorphisms. Incorporating a wide range of available genetic data, our analyses confirm previous results favoring a \"late split\" between West and East Bantu speakers, following a joint passage through the rainforest. In addition, we find that Bantu speakers from eastern Africa display genetic substructure, with Mozambican populations forming a gradient of relatedness along a North-South cline stretching from the coastal border between Kenya and Tanzania to South Africa. This gradient is further associated with a southward increase in genetic homogeneity, and involved minimum admixture with resident populations. Together, our results provide the first genetic evidence in support of a rapid North-South dispersal of Bantu peoples along the Indian Ocean Coast, as inferred from the distribution and antiquity of Early Iron Age assemblages associated with the Kwale archaeological tradition.

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bioRxiv2019

Genome-wide analysis reveals genetic diversity, linkage disequilibrium, and selection for milk traits in Chinese buffalo breeds

Water buffalo holds the tremendous potential of milk and meat that widespread throughout central and southern China. However, characterization of the population genetics of Chinese buffalo is poorly understood. Using Axiom(R) buffalo genotyping array, we performed the genetic diversity, linkage disequilibrium (LD) pattern and signature of selection in the 176 Chinese buffaloes from thirteen breeds. A total of 35,547 SNPs passed quality control and were used for further analyses. Population genetic analysis revealed a clear separation between the swamp and river types. Ten Chinese indigenous breeds clustered into the swamp group, Murrah and Nili-Ravi breeds were the river group, and the crossbred breed was closer to the river group. Genetic diversity analysis showed that the swamp group had a lower average expected heterozygosities compared to the river group. LD decay distance was much shorter in the swamp group compared with the river group with [Formula] value of approximately 50 Kb. Analysis of runs of homozygosity indicated that extensive remote and recent inbreeding activity was respectively found within swamp and river groups. Moreover, a total of 12 genomic regions under selection were detected between river and swamp groups. Further, 12 QTL regions were found associated with buffalo milk production traits. Some candidate genes within these QTLs were predicted to be involved in the cell structure and function, suggesting that these genes might play vital roles in the buffalo milk performance. Our data contribute to our understanding of the characterization of population genetics in Chinese buffaloes, which in turn may be utilized in buffalo breeding programs.\n\nAuthor SummaryIdentifying the causal genes or markers associated with important economic traits in livestock is critical to increasing the production level on the species. However, current understanding of the genetic basis for milk production traits in buffalo is limited. Here, we confirmed the divergent evolution, distinct population structure, and LD extent among Chinese buffalo breeds. We also identified 12 QTL regions associated with milk production traits in buffaloes using the selective sweeps and haplotype analysis. Further, a total of 7 genes involved in the cell structure and function were predicted within the identified QTLs. These findings suggested that these genes can serve as the candidate genes associated with buffalo milk production, which hold a vital role in the milk trait improvement of dairy buffalo industry.

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bioRxiv2019

Negative selection on complex traits limits genetic risk prediction accuracy between populations

Accurate genetic risk prediction is a key goal for medical genetics and great progress has been made toward identifying individuals with extreme risk across several traits and diseases (Collins and Varmus, 2015). However, many of these studies are done in predominantly European populations (Bustamante et al., 2011; Popejoy and Fullerton, 2016). Although GWAS effect sizes correlate across ancestries (Wojcik et al., 2019), risk scores show substantial reductions in accuracy when applied to non-European populations (Kim et al., 2018; Martin et al., 2019; Scutari et al., 2016). We use simulations to show that human demographic history and negative selection on complex traits result in population specific genetic architectures. For traits under moderate negative selection, ~50% of the heritability can be accounted for by variants in Europe that are absent from Africa. We show that this directly leads to poor performance in risk prediction when using variants discovered in Europe to predict risk in African populations, especially in the tails of the risk distribution. To evaluate the impact of this effect in genomic data, we built a Bayesian model to stratify heritability between European-specific and shared variants and applied it to 43 traits and diseases in the UK Biobank. Across these phenotypes, we find ~50% of the heritability comes from European-specific variants, setting an upper bound on the accuracy of genetic risk prediction in non-European populations using effect sizes discovered in European populations. We conclude that genetic association studies need to include more diverse populations to enable to utility of genetic risk prediction in all populations.

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bioRxiv2019

Unraveling the genetic structure of the coconut scale insect pest (Aspidiotus rigidus Reyne) outbreak populations in the Philippines

The Philippines suffered from a devastating outbreak of the coconut scale insect pest, Aspidiotus rigidus Reyne inflicting significant economic losses to the countrys coconut industry. Despite the massive outbreak, little is known about the population and dispersal history of this invasive pest in the Philippines. Here, we examined the genetic diversity, structure and demographic history of A. rigidus sampled from localities with reported outbreaks from 2014 to 2017. We analyzed the genetic structure of seven A. rigidus outbreak populations using mitochondrial COI and nuclear EF-1 markers. Both markers and all methods of population genetic structure analyses indicate clear differentiation among the A. rigidus populations separating the northern (i.e., Luzon provinces) from the southern (i.e., Basilan and Zamboanga Peninsula) regions of the Philippines. Very low or no genetic differentiation was observed within and amongst the populations per geographic region indicating two unrelated outbreak events of the pest originating from two genetically uniform populations isolated in each respective region. Historical data supports the resurgence of an established A. rigidus population in the south which could have been driven by sudden climatic changes or human-induced habitat imbalance. Given no historical information, we disregard the possible resurgence from the northern population and infer that the outbreak could have resulted from a recent introduction of a non-native A. rigidus in the region. Our study provides valuable information on the genetic differentiation of the two A. rigidus groups that would be useful for developing and implementing biological control strategies against this pest in the Philippines.

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bioRxiv2019

Regulatory kinase genetic interaction profiles differ between environmental conditions and cellular states

Cell growth and quiescence in eukaryotic cells is controlled by an evolutionarily conserved network of signaling pathways. Signal transduction networks operate to modulate a wide range of cellular processes and physiological properties when cells exit proliferative growth and initiate a quiescent state. How signaling networks function to respond to diverse signals that result in cell cycle exit and establishment of a quiescent state is poorly understood. Here, we studied the function of signaling pathways in quiescent cells using global genetic interaction mapping in the model eukaryotic cell, Saccharomyces cerevisiae (budding yeast). We performed pooled analysis of genotypes using molecular barcode sequencing to test the role of [~]3,900 gene deletion mutants and [~]11,700 pairwise interactions between all non-essential genes and the protein kinases TOR1, RIM15, PHO85 in three different nutrient-restricted conditions in both proliferative and quiescent cells. We detect nearly five-fold more genetic interactions in quiescent cells compared to proliferative cells. We find that both individual gene effects and genetic interaction profiles vary depending on the specific pro-quiescence signal. The master regulator of quiescence, RIM15 shows distinct genetic interaction profiles in response to different starvation signals. However, vacuole-related functions show consistent genetic interactions with RIM15 in response to different starvation signals suggesting that RIM15 integrates diverse signals to maintain protein homeostasis in quiescent cells. Our study expands genome-wide genetic interaction profiling to additional conditions, and phenotypes, highlighting the conditional dependence of epistasis.

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bioRxiv2019

Genetic \"General Intelligence,\" Objectively Determined and Measured

It has been known for 115 years that, in humans, diverse cognitive traits are positively intercorrelated; this forms the basis for the general factor of intelligence (g). We directly test for a genetic basis for g using data from seven different cognitive tests (N = 11,263 to N = 331,679) and genome-wide autosomal single nucleotide polymorphisms. A genetic g factor accounts for 58.4% (SE = 4.8%) of the genetic variance in the cognitive traits, with trait-specific genetic factors accounting for the remaining 41.6%. We distill genetic loci broadly relevant for many cognitive traits (g) from loci associated with only individual cognitive traits. These results elucidate the etiological basis for a long-known yet poorly-understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive traits.

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