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bioRxiv2022

The broad shell colour variation in common cockle (Cerastoderma edule) from Northeast Atlantic relies on a major QTL revealed by GWAS using a new high-density genetic map

Shell colour pattern shows broad diversity in molluscs, and both genetic and environmental factors seem to interact to some extent on the final phenotype. Despite information on the genetic component and pathways involved in shell construction and colour has increased in the last decade, more data are needed particularly to understand colour variation and its putative role on adaptation. The European common cockle (Cerastoderma edule) is a valuable species from ecological and commercial perspectives with important variation in colour pattern, but this diversity has never been characterized and the underlying genetic architecture is unknown. In this study, we constructed a high-density genetic map, as an essential tool for genomic screening in common cockle, that was applied to ascertain the genetic basis of colour pattern variation in the species. The consensus map, including 13,874 2b-RAD SNPs, was constituted by the 19 linkage groups (LGs) corresponding to the n = 19 chromosomes of its karyotype and spanned 1,073 cM (730 markers per LG; inter-marker distance of 0.13 cM). Five full-sib families showing segregation for several colour-associated traits were used to perform a GWAS analysis. A major QTL on chromosome 13 explained most of the variation for shell colour patterns. Mining on this genomic region revealed the presence of several candidate genes enriched on Gene Ontology terms such as anatomical structure development, ion transport, membrane transport and cell periphery, closely related to shell architecture, including six chitin-related, one ependymin, several ion binding and transporters, and others related to transit across the cell membrane. Interestingly, this major QTL overlaps with a genomic region previously reported associated with divergent selection in the distribution range of the species, suggesting a putative role on local adaptation.

genomics↗

bioRxiv2022

Larger cerebral cortex is genetically correlated with greater frontal area and dorsal thickness

Human cortical expansion has occurred non-uniformly across the brain. We assessed the genetic architecture of cortical global expansion and regionalization by comparing two sets of genome-wide association studies of 24 cortical regions with and without adjustment for global measures (i.e. total surface area, mean cortical thickness) using a genetically-informed parcellation in 32,488 adults. We found 393 and 756 significant loci with and without adjusting for globals, respectively, among which 8% and 45% loci were associated with more than one region. Results from analyses without adjustment for globals recounted loci associated with global measures. Genetic factors that contribute to total surface area of the cortex particularly expand anterior/frontal regions, whereas those contributing to thicker cortex predominantly increase dorsal/frontal-parietal thickness. Interactome-based analyses revealed significant overlap of global and regional genetic modules, enriched for neurodevelopmental and immune system pathways. Consideration of global measures is important in understanding the genetic variants underlying cortical morphology.

neuroscience↗

bioRxiv2022

Genetic structure and differentiation of the endemic Bolle's Laurel Pigeon (Columba bollii) in the Canary Islands

Island archipelagos are global biodiversity hotspots since they often foster high concentrations of diverse lineages and endemic species. Here, we examine the population genetics of the endemic Bolles Laurel Pigeon Columba bollii, a frugivorous bird inhabiting subtropical laurel forests. We genotyped ten microsatellite loci using DNA obtained from moulted tail feathers collected at eight sampling sites on the four western islands of the Canarian archipelago. Analyses including F-statistics, Bayesian clustering approaches, isolation by distance tests and population graph topologies, were used to infer the genetic diversity and the population differentiation within and among insular populations. Additionally, we evaluated the effect of null alleles on data analysis. Low genetic diversity was found in all populations of Bolles Laurel Pigeon, with no significant differences in diversity among them. However, significant genetic differentiation was detected among all populations, with pigeons from La Palma and El Hierro exhibiting the closest affinity. Bayesian clustering supported population separation between islands, and also detected fine-scale structure within the Tenerife and La Gomera populations. Present-day pigeon movements appear to occur between islands, however, this has not been sufficient to remove the signature of genetic divergence among the populations of Bolles Laurel Pigeon, which was moderately linked to geographical distance. According to metapopulation structure, this study suggests that the evolutionary history of C. bollii is closely related to the geological past of these oceanic islands and the distribution range of its habitat, the laurel forest. Finally, conservation implications for the species are discussed.

evolutionary biology↗

bioRxiv2022

Polygenic Transcriptome Risk Scores Can Translate Genetic Results Between Species

Genome-wide association studies (GWAS) have implicated specific alleles and genes as risk factors for numerous complex traits. However, translating GWAS results into biologically and therapeutically meaningful discoveries remains extremely challenging. Most GWAS results identify noncoding regions of the genome, suggesting that differences in gene regulation are the major driver of trait variability. To better integrate GWAS results with gene regulatory polymorphisms, we previously developed PrediXcan (also known as "transcriptome-wide association studies" or TWAS), which maps SNPs to predicted gene expression using GWAS data. In this study, we developed RatXcan, a framework that extends this methodology to outbred heterogeneous stock (HS) rats. RatXcan accounts for the close familial relationships among HS rats by modeling the relatedness with a random effect that encodes the genetic relatedness. RatXcan also corrects for polygenic-driven inflation because of the equivalence between a relatedness random effect and the infinitesimal polygenic model. To develop RatXcan, we trained transcript predictors for 8,934 genes using reference genotype and expression data from five rat brain regions. We found that the cis genetic architecture of gene expression in both rats and humans was sparse and similar across brain tissues. We tested the association between predicted expression in rats and two example traits (body length and BMI) using phenotype and genotype data from 5,401 densely genotyped HS rats and identified a significant enrichment between the genes associated with rat and human body length and BMI. Thus, RatXcan represents a valuable tool for identifying the relationship between gene expression and phenotypes across species and paves the way to explore shared biological mechanisms of complex traits. Author SummaryUnderstanding how genetic variation affects phenotypic variation is critical to leveraging the wealth of genetic studies to make biologically and therapeutically useful discoveries. Since most of the genetic loci associated with complex diseases are regulatory in nature--meaning that they do not alter protein coding but rather subtly affect gene expression--transcriptome-wide association studies have been developed. However, these apply only to human data where large samples of unrelated individuals are available. For animal models, relatedness is much higher, causing higher false-positive rates. We propose a computationally efficient method to address this problem and find shared biology between humans and rats. Taken together, our development paves the way to further explore shared biological mechanisms of complex traits across species.

genomics↗

bioRxiv2022

The phers R package: using phenotype risk scores based on electronic health records to study Mendelian disease and rare genetic variants

Electronic health record (EHR) data linked to DNA biobanks are a valuable resource for understanding the phenotypic effects of human genetic variation. We previously developed the phenotype risk score (PheRS) as an approach to quantify the extent to which a patients clinical features resemble a given Mendelian disease. Using PheRS, we have uncovered novel associations between Mendelian diseaselike phenotypes and rare genetic variants, and identified patients who may have undiagnosed Mendelian disease. Although the PheRS approach is conceptually simple, it involves multiple mapping steps and was previously only available as custom scripts, limiting the approachs usability. Thus, we developed the phers R package, a complete and user-friendly set of functions and maps for performing a PheRS-based analysis on linked clinical and genetic data. The package includes up-to-date maps between EHR-based phenotypes (i.e., ICD codes and phecodes), human phenotype ontology (HPO) terms, and Mendelian diseases. Starting with occurrences of ICD codes, the package enables the user to calculate phenotype risk scores, validate the scores using case-control analyses, and perform genetic association analyses. By increasing PheRSs transparency and usability, the phers R package will help improve our understanding of the relationships between rare genetic variants and clinically meaningful human phenotypes. AvailabilityThe phers R package is free and open-source, and available on CRAN and at https://phers.hugheylab.org. Contactjakejhughey@gmail.com Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Genetic exchange in Leishmania is facilitated by IgM natural antibodies

Host factors mediating Leishmania genetic exchange are not well defined. Here, we demonstrate that IgM antibodies, but not IgG or IgA, facilitate parasite genetic hybridization in vitro and in vivo. IgM induces the gradual and transient formation of a structured parasite clump in a process essential for L. major and L. tropica hybridization in vitro. Parasite hybrids and 3-nucleated parasites were observed inside this structure, named the Leishmania mating clump. IgM was also required for or significantly increased Leishmania hybrid formation in vivo. At minimum, we observed a 12-fold increase in the proportion of hybrids recovered from sand flies provided a second blood meal containing IgM compared to controls. Notably, genetic backcross events in sand flies were only observed in the presence of IgM, and were reproducibly recovered, reinforcing the relevance of IgM for Leishmania genetic exchange in vivo. The in vitro and in vivo Leishmania crosses from these studies resulted in full genome hybrids. Leishmania co-option of a host antibody to facilitate mating in the insect vector establishes a new paradigm of parasite-host-vector coevolution that promotes parasite diversity and fitness through genetic exchange.

microbiology↗

bioRxiv2022

Genetic transformation and cell division delay in competent Staphylococcus aureus

Natural competence for genetic transformation, considered as one of the three main mechanisms leading to horizontal gene transfer in bacteria, is able to promote evolution, through genomic plasticity, and foster antibiotic resistance and virulence factors spreading. Conserved machineries and actors required to perform genetic transformation have been shown to accumulate at different cellular localizations depending on the model organism considered. Here, we show in the human pathogen Staphylococcus aureus that DNA binding, uptake and recombination are spatially and temporally coordinated to ensure S. aureus genetic transformation. We also reveal that localization of genetic transformation proteins is dynamic and preferentially occurs in the vicinity of the division septum. We finally propose that S. aureus competent cells would initiate and then block cell division to ensure the success of genetic transformation before the final constriction of the cytokinetic ring.

microbiology↗

bioRxiv2022

Genetic score omics regression and multi-trait meta-analysis detect widespread cis-regulatory effects shaping bovine complex traits

To complete the genome-to-phenome map, transcriptome-wide association studies (TWAS) are performed to correlate genetically predicted gene expression with observed phenotypic measurements. However, the relatively small training population assayed with gene expression could limit the accuracy of TWAS. We propose Genetic Score Omics Regression (GSOR) correlating observed gene expression with genetically predicted phenotype, i.e., genetic score. The score, calculated using variants near genes with assayed expression, provides a powerful association test between cis-effects on gene expression and the trait. In simulated and real data, GSOR outperforms TWAS in detecting causal/informative genes. Applying GSOR to transcriptomes of 16 tissue (N[~]5000) and 37 traits in [~]120,000 cattle, multi-trait meta-analyses of omics-associations (MTAO) found that, on average, each significant gene expression and splicing mediates cis-genetic effects on 8[~]10 traits. Supported by Mendelian Randomisation, MTAO prioritised genes/splicing show increased evolutionary constraints. Many newly discovered genes/splicing regions underlie previously thought single-gene loci to influence multiple traits.

genomics↗

bioRxiv2022

Intergenerational effects from spatial and genetic environment predict early-life social network structure

Early independence is a crucial stage in the ontogeny of social environments, but it is often challenging to study in the wild. Genetics may structure groups if young animals associate with familiar kin, but association opportunities also develop as a by-product of environmental processes such as spatial resource distribution. The contribution of these alternate factors in initial opportunities for bonding outside direct relatives is difficult to pick apart, despite its importance in shaping later life. However, species where genetics and spatial structure are less closely coupled (for example, via extra-pair mating) provide a natural opportunity to disentangle these effects. We addressed this gap by investigating the contribution of relatedness versus spatiotemporal synchrony (natal nest-box location and fledge timing) to early-life social structure in newly-independent young hihi (Notiomystis cincta). We also investigated the contribution of inbreeding in both juveniles and their parents, to individual-level sociality, as this genetic factor has had limited focus in studies of social structure. Using a long-term genetic pedigree, detailed breeding records, and social network data collected across three cohorts, we found that juvenile social associations were predicted by natal nest-box location, irrespective of relatedness between juveniles. Therefore, the physical environment can create initial opportunities for associations to develop once young animals disperse from natal sites. Furthermore, juvenile sociability was predicted by their fathers (but not mothers) inbreeding, highlighting how genetics may have indirect and intergenerational effects on social behaviour. Overall, social structure in wild animals can emerge early in life if the natal environment determines association opportunities. These patterns may even be pre-determined across generations if breeding and settlement decisions made by parents affect the physical and social environments experienced by their offspring. Ultimately, our study highlights how influences on early life social structure may have important consequences for population dynamics and evolutionary potential.

animal behavior and cognition↗

bioRxiv2022

An investigation of the sex-specific genetic architecture of fitness in Drosophila melanogaster

In dioecious populations, the sexes employ divergent reproductive strategies to maximize fitness and, as a result, genetic variants can affect fitness differently in males and females. Moreover, recent studies have highlighted an important role of the mating environment in shaping the strength and direction of sex-specific selection. Here, we measure adult fitness for each sex of 357 lines from the Drosophila Synthetic Population Resource (DSPR) in two different mating environments. We analyze the data using three different approaches to gain insight into the sex-specific genetic architecture for fitness: classical quantitative genetics, genomic associations, and a mutational burden approach. The quantitative genetics analysis finds that, on average segregating genetic variation in this population has concordant fitness effects both across the sexes and across mating environments. We do not find specific genomic regions with strong associations with either sexually antagonistic (SA) or sexually concordant (SC) fitness effects, yet there is modest evidence of an excess of genomic regions with weak associations, both with SA and SC fitness effects. Our examination of mutational burden indicates stronger selection against indels and loss-of-function variants in females than males.

evolutionary biology↗

bioRxiv2022

Using computational simulations to quantify genetic load and predict extinction risk

Small and isolated wildlife populations face numerous threats to extinction, among which is the deterioration of fitness due to an accumulation of deleterious genetic variation. Genomic tools are increasingly used to quantify the impacts of deleterious variation in small populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of individual mutations. Computational simulations of deleterious genetic variation offer an alternative and complementary tool that can help overcome these limitations, though such approaches have yet to be widely employed. In this Perspective, we aim to encourage conservation genomics researchers to adopt greater use of computational simulations to aid in quantifying and predicting the threat that deleterious genetic variation poses to extinction. We first provide an overview of the components of a simulation of deleterious genetic variation, describing the key parameters involved in such models. Next, we clarify several misconceptions about an essential simulation parameter, the distribution of fitness effects (DFE) of new mutations, and review recent debates over what the most appropriate DFE parameters are. We conclude by comparing modern simulation tools to those that have long been employed in population viability analysis, weighing the pros and cons of a genomics-informed simulation approach, and discussing key areas for future research. Our aim is that this Perspective will facilitate broader use of computational simulations in conservation genomics, enabling a deeper understanding of the threat that deleterious genetic variation poses to biodiversity.

evolutionary biology↗

bioRxiv2022

Analysis of a genetic region affecting mouse body weight

Genetic factors affect an individuals risk of developing obesity, but in most cases each genetic variant has a small effect. Discovery of genes that regulate obesity may provide clues about its underlying biological processes and point to new ways the disease can be treated. Pre-clinical animal models facilitate genetic discovery in obesity because environmental factors can be better controlled compared to the human population. We studied inbred mouse strains to identify novel genes affecting obesity and glucose metabolism. BTBR T+ Itpr3tf/J (BTBR) mice are fatter and more glucose intolerant than C57BL/6J (B6) mice. Prior genetic studies of these strains identified an obesity locus on chromosome 2. Using congenic mice, we found that obesity was affected by a ~316 kb region, with only two known genes, pyruvate dehydrogenase kinase 1 (Pdk1) and integrin alpha 6 (Itga6). Both genes had mutations affecting their amino acid sequence and reducing mRNA levels. Both genes have known functions that could modulate obesity, lipid metabolism, insulin secretion and/or glucose homeostasis. We hypothesized that genetic variation in or near Pdk1 or Itga6 causing reduced Pdk1 and Itga6 expression would promote obesity and impaired glucose tolerance. We used knockout mice lacking Pdk1 or Itga6 fed an obesigenic diet to test this hypothesis. Under the conditions we studied, we were unable to detect an individual contribution of either Pdk1 or Itga6 to body weight. However, we identified a previously unknown role for Pdk1 in cardiac lipid metabolism providing the basis for future investigations in that area.

physiology↗

bioRxiv2022

Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency

Preclinical models of neurodevelopmental disorders typically use single inbred strains which fail to capture human genetic and symptom heterogeneity that is common clinically. We tested if systematically modeling human genetic diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. Trait disruptions mimicked those seen in human populations, including high penetrance of macrocephaly and disrupted behavior, but with robust strain and sex differences. For every trait, some strains exhibited a range of large effect size disruptions, sometimes in opposite directions, and remarkably others expressed resilience. Thus, systematically introducing genetic diversity into mouse models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies and improved treatments. One-Sentence SummaryAutism trait heterogeneity due to a syndromic gene mutation is recapitulated in mice by incorporating genetic diversity.

neuroscience↗

bioRxiv2022

Effect of beneficial sweeps and background selection on genetic diversity in changing environments

Neutral theory predicts that the genetic diversity within a population is proportional to the census population size. In contrast, observed genetic diversity for various species is much lower than theoretical prediction (Lewontins paradox). The selective sweeps and background selection, reduce the genetic variation at the linked neutral sites and have been studied considering the environment to be selectively constant. However, in a natural population, the selective environment varies with time. Here, we investigate the impact of selective sweeps and background selection on neutral genetic diversity when the selection coefficient changes periodically over time. The reduction in genetic variation due to selective sweeps is known to depend on the conditional fixation time. Here, we find that the effect of changing environment on conditional mean fixation time is most substantial for the randomly mating population than the inbreeding population with arbitrary inbreeding coefficient. We also study the effect of background selection on neutral sites when the selection co-efficient of linked deleterious mutation change periodically in time. In the slowly changing environment, we find that neutral heterozygosity is significantly different, and the site frequency spectrum has a different shape than that in the static environment.

evolutionary biology↗

bioRxiv2022

Genetic control of RNA editing in Neurodegenerative disease

A-to-I RNA editing diversifies human transcriptome to confer its functional effects on the downstream genes or regulations, potentially involving in neurodegenerative pathogenesis. Its variabilities are attributed to multiple regulators, including the key factor of genetic variant. To comprehensively investigate the potentials of neurodegenerative disease-susceptibility variants from the view of A-to-I RNA editing, we analyzed matched genetic and transcriptomic data of 1,596 samples across nine brain tissues and whole blood from two large consortiums, Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) and Parkinsons Progression Markers Initiative (PPMI). The large-scale and genome-wide identification of 95,637 RNA editing quantitative trait loci revealed the preferred genetic effects on adjacent editing events. Furthermore, to explore the underlying mechanisms of the genetic controls of A-to-I RNA editing, several top RNA binding proteins were pointed out, such as EIF4A3, U2AF2, NOP58, FBL, NOP56, and DHX9, since their regulations on multiple RNA editing events probably interfered by these genetic variants. Moreover, these variants may also contribute to the variability of other molecular phenotypes associated with RNA editing, including the functions of four proteins, expressions of 148 genes, and splicing of 417 events. All the analyses results shown in NeuroEdQTL (https://relab.xidian.edu.cn/NeuroEdQTL/) constituted a unique resource for the understanding of neurodegenerative pathogenesis from genotypes to phenotypes related to A-to-I RNA editing.

bioinformatics↗

bioRxiv2022

Direct inference and control of genetic population structure from RNA sequencing data

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

bioinformatics↗

bioRxiv2022

Population level genetic memory of prior metabolic adaptation in E. coli

Bacteria must often survive following the exhaustion of their external growth resources. Fitting with this need, many bacterial species that cannot sporulate, can enter a state known as long term stationary phase (LTSP) in which they can persist for years within spent media. Several recent studies have revealed the dynamics of genetic adaptation of Escherichia coli under LTSP. Yet, the metabolic consequences of such genetic adaptation were not addressed. Here, we characterized the metabolic changes LTSP populations experience and link them to their genetic adaptation. We observed that during growth within fresh resources E. coli produces the short chain fatty acid butyrate, which wildtype E. coli cannot consume. Once resources are otherwise exhausted, E. coli adapts genetically to consume butyrate through the convergent, temporally precise emergence of mutation combinations within genes that regulate fatty acid metabolism. These mutations appear to negatively affect bacterial fitness when butyrate is not available, and hence rapidly decrease in frequency, once all butyrate is consumed. Yet despite this, E. coli populations show a remarkable capability of maintaining a population-level genetic memory of prior adaptation to consume butyrate. The maintenance of such a memory allows bacteria to rapidly re-adapt, at an ecological, rather than an evolutionary timeframe, to re-consume previously encountered metabolites.

evolutionary biology↗

bioRxiv2022

GRETA: an R package for mapping in silico genetic interaction and essentiality networks

SummaryMapping genetic interaction and essentiality networks in human cell lines have been used to identify vulnerabilities of cells carrying specific genetic alterations and to associate novel functions to genes, respectively. In vitro and in vivo genetic screens to decipher these networks are resource-intensive, limiting the throughput of samples that can be analyzed. In this application note, we provide an R package we call Genetic inteRaction and EssentialiTy mApper (GRETA). GRETA is an accessible tool for in silico genetic interaction screens and essentiality network analyses using publicly available data, requiring only basic R programming knowledge. Availability and implementationThe R package, GRETA, is licensed under GNU General Public License v3.0 and freely available at https://github.com/ytakemon/GRETA and https://doi.org/10.5281/zenodo.6940757, with documentation and tutorial. A Singularity container is also available at https://cloud.sylabs.io/library/ytakemon/greta/greta. Contactmmarra@bcgsc.ca Supplemental informationSupplemental materials are available at Bioinformatics online. Issue sectionSystems biology

bioinformatics↗