SEARCH · bioRxiv Science

Results for “genetics”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,765 records · Page 98Linked to original sources

bioRxiv2022

The population-level impact of Enterococcus faecalis genetics on intestinal colonisation and extraintestinal infection

Enterococcus faecalis is a commensal pathogenic bacterium commonly found in the human gastrointestinal tract and a cause of opportunistic infections typically associated with multidrug resistance. The E. faecalis genetic changes associated with pathogenicity and extraintestinal infection, particularly through gut-to-bloodstream translocation, are poorly understood. Here, we investigate the E. faecalis genetic signatures associated with intestinal colonisation and extraintestinal infection and infection of hospitalised and non-hospitalised individuals using heritability estimation and a genome-wide association study (GWAS). We analysed 750 whole-genome sequences of faecal and bloodstream E. faecalis isolates from hospitalised patients and non-hospitalised individuals, respectively, predominantly in Europe. We found that E. faecalis infection of individuals depending on their hospitalisation status and extraintestinal infection are heritable traits and that [~]24% and [~]34% of their variation is explained by the considered genetic effects, respectively. Further, a GWAS using linear mixed models did not pinpoint any clear enrichment of individual genetic changes in isolates from different isolation sites and individuals with varying hospitalisation statuses, suggesting that these traits are highly polygenic. Altogether, our findings indicate that E. faecalis infection and extraintestinal infection are influenced by variation in genetic, host, and environmental factors, and ultimately the opportunistic pathogenic lifestyle of this versatile host generalist bacterium.

microbiology↗

bioRxiv2022

Chromosome-scale reference genome and RAD-based genetic map of yellow starthistle (Centaurea solstitialis) reveal putative structural variation and QTLs associated with invader traits

Invasive species offer outstanding opportunities to identify the genomic sources of variation that contribute to rapid adaptation, as well as the genetic mechanisms facilitating invasions. The Eurasian plant yellow starthistle (Centaurea solstitialis) is highly invasive in North and South American grasslands and known to have evolved increased growth and reproduction during invasion. Here we develop new genomic resources for C. solstitialis and map the genetic basis of invasiveness traits. We present a chromosome-scale (1N = 8) reference genome using PacBio CLR and Dovetail Omni-C technologies, and functional gene annotation using RNAseq. We find repeat structure typical of the family Asteraceae, with over 25% of gene content derived from ancestral whole genome duplications (paleologs). Using an F2 mapping population derived from a cross between native and invading parents, with a restriction site-associated DNA (RAD)-based genetic map, we validate the assembly and identify 13 QTL underpinning size traits that have evolved during invasion. We find evidence that large effect QTL may be associated with structural variants between native and invading genotypes, including a variant with an overdominant and pleiotropic effect on key invader traits. We also find evidence of significant paleolog enrichment under two QTL. Our results add to growing evidence of the importance of structural variants in evolution, and to understanding of the rapid evolution of invaders. Significance StatementInvasive species often evolve rapidly in new environments, potentially informing our understanding of the genomic basis of adaptation, but genomic studies of these non-model systems are limited. We provide a chromosome-scale reference genome, annotation, and genetic map for the invasive plant yellow starthistle, and we investigate the genetic basis of invader trait evolution in this system. We find regions of the genome with large effects on traits that differ between native and invading genotypes, and evidence suggesting genome structural variants and past genome duplications could play a role in rapid adaptation of invading populations. These genomic resources and evolutionary insights aid in our understanding of the sources of genomic variation for adaptation, and how their evolution facilitates invasion.

genomics↗

bioRxiv2022

Kinship and genetic variation in aquarium-spawned Acropora hyacinthus corals

Recent scientific advances in ex situ system design and operation make it possible to complete gametogenic cycles of broadcast spawning corals. Breeding corals in aquaria are critical advances for population management, particularly genetic rescue and assisted gene flow efforts. Genetic rescue projects for corals are already underway to bring threatened species into ex situ culture and propagation, thereby preserving standing genetic variation. However, while breeding corals is increasingly feasible, the consequences of the aquarium environment on the genetic and phenotypic composition of coral populations is not yet known. The aquarium environment may in itself be a selective pressure on corals, but it also presents relaxed selective pressure in other respects. In 2019 and 2020, gravid Acropora hyacinthus coral colonies were collected from Palauan reefs and shipped to the California Academy of Sciences (CAS) in San Francisco. In both years, gametes were batch-fertilized to produce larvae that were then settled and reared to recruits. As of April 2021, when they were sampled for sequencing, 23 corals produced at CAS in 2019 and 16 corals produced at CAS in 2020 had survived for two years and one year, respectively. We sequenced the full genomes of the 39 offspring corals and their 15 potential parents to a median 26x depth of coverage. We find clear differential parentage, with some parents producing the vast majority of offspring, while the majority of parents produced no surviving offspring. After scanning 12.9 million single nucleotide polymorphisms (SNPs), we found 887 SNPs that may be under selection in the aquarium environment, and we identified the genes and pathways these SNPs may affect. We present recommendations for preserving standing genetic variation in aquarium-bred corals based on the results of this pilot project.

evolutionary biology↗

bioRxiv2022

How density dependence, genetic erosion, and the extinction vortex impact evolutionary rescue

Following severe environmental change that reduces mean population fitness below replacement, populations must adapt to avoid eventual extinction, a process called evolutionary rescue. Models of evolutionary rescue demonstrate that initial size, genetic variation, and degree of maladaptation influence population fates. However, many models feature populations that grow without negative density dependence or with constant genetic diversity despite precipitous population decline, assumptions likely to be violated in conservation settings. We examined the simultaneous influences of density-dependent growth and erosion of genetic diversity on populations adapting to novel environmental change using stochastic, individual-based simulations. Density dependence decreased the probability of rescue and increased the probability of extinction, especially in large and initially well-adapted populations that previously have been predicted to be at low risk. Increased extinction occurred shortly following environmental change, as populations under density dependence experienced more rapid decline and reached smaller sizes. Populations that experienced evolutionary rescue lost genetic diversity through drift and adaptation, particularly under density dependence. Populations that declined to extinction entered an extinction vortex, where small size increased drift, loss of genetic diversity, and the fixation of maladaptive alleles, hindered adaptation, and kept populations at small densities where they were vulnerable to extinction via demographic stochasticity.

ecology↗

bioRxiv2022

Different genetic architectures of complex traits and their relevance to polygenic score performance

BackgroundDespite the many insights gleaned from GWAS, polygenic predictions of complex traits have had limited success, particularly when these predictions are applied to individuals of non-European descent. A deeper understanding of the genetic architecture of complex traits may inform why some traits are easier to predict than others. MethodsExamining 163 complex traits from the UK Biobank, we compared and contrasted three aspects of genetic architecture (SNP heritability, LD variability, and genomic inequality) with three aspects of polygenic score performance (prediction accuracy in the source population, portability across populations, and trait divergence across populations). Here, genomic inequality refers to how unequally the genetic variance of each trait is distributed across the top trait-associated SNPs, as quantified via a novel application of Gini coefficients. ResultsConsistent with reduced statistical power, polygenic predictions of binary traits performed worse than predictions of quantitative traits. Traits with low Gini coefficients (i.e., highly polygenic architectures) include hip circumference as well as systolic and diastolic blood pressure. Traits with large population-level differences in polygenic scores include skin pigmentation and hair color. Focusing on 96 quantitative traits, we found that highly heritable traits were easier to predict and had predictions that were more portable to other ancestries. Traits with highly divergent polygenic score distributions across populations were less likely to have portable predictions. Intriguingly, LD variability was largely uninformative regarding the portability of polygenic predictions. This suggests that factors other than the differential tagging of causal SNPs drive the reduction in polygenic score accuracy across populations. Subsequent analyses identified suites of traits with similar genetic architecture and polygenic score performance profiles. Importantly, lifestyle and psychological traits tended to have low heritability, as well as poor predictability and portability. ConclusionsNovel metrics capture different aspects of trait-specific genetic architectures and polygenic score performance. Our findings also caution against the application of polygenic scores to traits like general happiness, alcohol frequency, and average income, especially when polygenic scores are applied to individuals who have an ancestry that differs from the original source population.

genomics↗

bioRxiv2022

Assessing the impact of pedigree quality on the validity of quantitative genetic parameterestimates

Investigating the evolutionary dynamics of complex traits in nature requires the accurate assessment of their genetic architecture. Using a quantitative genetic (QG) modeling approach (e.g., animal model), relatedness information from a pedigree combined with phenotypic measurements can be used to infer the amount of additive genetic variance in traits. However, pedigree information from natural systems is not perfect and might contain errors or be of low quality. Published sensitivity analyses revealed a limited impact of expected error rates on parameter estimates. However, natural systems will differ in many respects (e.g., mating system, data availability, pedigree structure), thus it can be inappropriate to generalize outcomes from one system to another. French-Canadian (FC) genealogies are extensive and deep-rooted (up to 9 generations in this study) making them ideal to study how the quality and properties (e.g., errors, completeness) of pedigrees affect QG estimates. We conducted simulation analyses to infer the reliability of QG estimates using FC pedigrees and how it is impacted by genealogical errors and variation in pedigree structure. Broadly, results show that pedigree size and depth are important determinants of precision but not of accuracy. While the mean genealogical entropy (based on missing links) seems to be a good indicator of accuracy. Including a shared familial component into the simulations led to on average a 46% overestimation of the additive genetic variance. This has crucial implications for evolutionary studies aiming to estimate QG parameters given that many traits of interest, such as life history, exhibit important non-genetic sources of variation.

evolutionary biology↗

bioRxiv2022

The genetic structure within a single tree is determined by the behavior of the stem cells in the meristem

Genomic sequencing revealed that somatic mutations cause a genetic differentiation of the cells in a single tree. In this study, we consider a mathematical model for stem cell proliferation in the shoot apical meristem (abbrev. SAM), which results in genetic diversification between the cells differing in the distance along the shoot and the angle around a shoot axis. The assumptions are as follows. Stem cells in the SAM normally undergo asymmetric cell division and produce successor stem cells and differentiated cells. The differentiated cells proliferate and contribute to shoot elongation. Occasionally, a stem cell is replaced by a copy of an adjacent stem cell. We discuss the "coalescent length" between cells indicating their genetic difference with respect to neutral mutations. A mathematical analysis revealed the following. The genetic diversity of cells sampled at the same position along the shoot increases with the distance from the bottom of the shoot. Stem cells hold a larger variation if they are replaced only by the nearest neighbors than if they are replaced by any cells. The coalescent length between two cells increases not only with the difference in the position along the shoot but also in the angle around the shoot axis. The dynamics of stem cells at the SAM determine the genetic pattern of the entire shoot.

evolutionary biology↗

bioRxiv2022

A compendium of genetic regulatory effects across pig tissues

The Farm animal Genotype-Tissue Expression (FarmGTEx, https://www.farmgtex.org/) project has been established to develop a comprehensive public resource of genetic regulatory variants in domestic animal species, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biology discovery and exploitation in animal breeding and human biomedicine. Here we present results from the pilot phase of PigGTEx (http://piggtex.farmgtex.org/), where we processed 9,530 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs. We build a pig genotype imputation panel, characterize the transcriptional landscape across over 100 tissues, and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We study interactions between genotype and breed/cell type, evaluate tissue specificity of regulatory effects, and elucidate the molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying about 80% of the genetic associations for 207 pig complex phenotypes, and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, corroborating the importance of pigs as a human biomedical model.

genomics↗

bioRxiv2022

Short-term adaptation on tunable fitness landscapes from standing genetic variation in recombining populations

How does standing genetic variation affect polygenic adaptation in recombining populations? Despite a large body of work in quantitative genetics, epistatic and weak additive fitness effects among simultaneously segregating genetic variants are difficult to capture experimentally or to predict theoretically. In this study, we simulated adaptation on fitness landscapes with tunable ruggedness driven by standing genetic variation in recombining populations. We confirmed that recombination hinders the movement of a population through a rugged fitness landscape. When surveying the effect of epistasis on the fixation of alleles, we found that the combined effects of high ruggedness and high recombination probabilities lead to preferential fixation of alleles that had a high initial frequency. This indicates that positively epistatic alleles escape from being broken down by recombination when they start at high frequency. We further extract direct selection coefficients and pairwise epistasis along the adaptive path. When taking the final fixed genotype as the reference genetic background, we observe that, along the adaptive path, beneficial direct selection appears stronger and pairwise epistasis weaker than in the underlying fitness landscape. Quantitatively, the ratio of epistasis and direct selection is smaller along the adaptive path ({approx} 1) than expected. Thus, adaptation on a rugged fitness landscape may lead to spurious signals of direct selection generated through epistasis. Our study highlights how the interplay of epistasis and recombination constrains the adaptation of a diverse population to a new environment.

evolutionary biology↗

bioRxiv2022

A 3D genome atlas of genetic variants and their pathological effects

The spatial architecture of the genome can be categorized into distinct layers. Each layer plays a critical role in transcriptional regulation and/or genomic integrity. Alterations at any level of the 3D genome can lead to an unwanted cascade of molecular events, which may ultimately drive the manifestation of disease. However, a comprehensive atlas of the mutations and structural genetic defects that affect genome organization has yet to be compiled. Moreover, we lack a centralized resource for interpretating the pathological effects of such genetic mutations. Therefore, we curated from the literature all the pathological alterations from the chromosome level on down to single nucleotide polymorphisms (SNPs) in order to investigate these diverse genetic mutations. Using a two-phase scoring algorithm, 3DFunc, we scored the transcriptomic causality of all variants in the context of 3D genome architecture from 20 cancer and 15 normal tissues. Further, 3DFunc can identify pathological variant-gene pairs in non-oncological diseases. Finally, we constructed a web-based database, 3DGeOD (https://www.csuligroup.com/3DGeOD/home), to provide all the curated variants, genomic disruptions, as well as the scoring results derived from 3DFunc. In summary, our study constructed a 3D genome atlas of genetic variants and will serve as a valuable resource for mining the putative pathological effects of any genetic mutation.

bioinformatics↗

bioRxiv2022

Investigating the genetic diversity of H5 avian influenza in the UK 2020-2022

Since 2020, the UK and Europe, have experienced annual epizootics of high pathogenicity avian influenza virus (HPAIV). The first during autumn/winter 2020/21 involved the detected with six H5Nx subtypes although H5N8 HPAIV dominated in the UK. Whilst genetic assessment of the H5N8 HPAIVs within the UK demonstrated relative homogeneity, there was a background of other genotypes circulating at a lower degree with different neuraminidase and internal genes. Following a small number of summer detections of H5N1 in wild birds over the summer of 2021, autumn/winter 2021/22 saw another European H5 HPAIV epizootic, that has dwarfed the prior epizootic. This second epizootic was dominated almost exclusively by H5N1 HPAIV, although six distinct genotypes were defined. We have used genetic analysis to evaluate the emergence of different genotypes and proposed reassortment events that have been observed. The existing data suggests that the H5N1 circulating in Europe during late 2020, continued to circulate in wild birds throughout 2021, with minimal adaptation, but has then gone on to reassort with AIVs in the wild bird population. We have undertaken an in-depth genetic assessment of H5 HPAIVs detected in the UK, over the last two winter seasons and demonstrate the utility of in-depth genetic analyses in defining the diversity of H5 HPAIVs circulating in avian species, the potential for zoonotic risk and whether incidents of lateral spread can be defined over independent incursion of infection from wild birds. Key supporting data for mitigation activities. ImportanceHigh pathogenicity avian influenza virus (HPAIV) outbreaks devastate avian species across all sectors having both economic and ecological impacts through mortalities in poultry and wild birds, respectively. These viruses can also represent a significant zoonotic risk. Since 2020, the UK has experienced two successive outbreaks of H5 HPAIV. Whilst H5N8 HPAIV was predominant during the 2020/21 outbreak, other H5 subtypes were also detected. The following year there was a shift in subtype dominance to H5N1 HPAIV, but multiple H5N1 genotypes were detected. Through thorough utilisation of whole-genome sequencing, it was possible to track and characterise the genetic evolution of these H5 HPAIVs in UK poultry and wild birds. This has enabled us to assess the risk posed by these viruses at the poultry:wild bird and the avian:human interface and to investigate potential lateral spread between infected premises, a key factor in understanding threat to the commercial sector.

molecular biology↗

bioRxiv2022

Parallels and divergences in landscape genetic and metacommunity patterns in zooplankton inhabiting soda pans

Ecological processes maintaining landscape genetic variation and metacommunity structure in natural landscapes have traditionally been studied in isolation. Their integrated study may hold important information as to what extent the effect of major ecological processes are species-or landscape-specific, resulting in a more coherent picture on the spatial organization of biodiversity. Here, we explicitly compared the relative importance of spatial and environmental drivers of both cladoceran metacommunity structure as well as landscape genetic structure of its most widespread member, the water flea Daphnia magna, in soda pans of the Seewinkel region in Austria. This landscape of soda pans is characterized by strong environmental gradients and unidirectional wind acting as a key dispersal agent among these temporary habitats. Our study shows both parallels and divergences in the relative importance of local environmental sorting and spatial connectivity in determining landscape genetic versus metacommunity structure. The metacommunity is structured primarily by the environment, while in the D. magna metapopulation, the spatial signal is predominant. The much weaker environmental signal in Daphnia can be explained by the fact that the microsatellite markers are presumably neutral and was confirmed by a per-allele analysis. An important parallel between metacommunity and landscape genetic structure is the strong signal of the prevailing wind direction in determining the spatial pattern. This suggests that for both community assembly in cladocerans and population assembly in D. magna, wind plays an important role in determining connectivity among soda pans, thereby affecting dispersal and colonization rates, influencing both local species and genetic composition.

ecology↗

bioRxiv2023

The genetic architecture of the human skeletal form

The human skeletal form underlies our ability to walk on two legs, but unlike standing height, the genetic basis of limb lengths and skeletal proportions is less well understood. Here we applied a deep learning model to 31,221 whole body dual-energy X-ray absorptiometry (DXA) images from the UK Biobank (UKB) to extract 23 different image-derived phenotypes (IDPs) that include all long bone lengths as well as hip and shoulder width, which we analyzed while controlling for height. All skeletal proportions are highly heritable ([~]40-50%), and genome-wide association studies (GWAS) of these traits identified 179 independent loci, of which 102 loci were not associated with height. These loci are enriched in genes regulating skeletal development as well as associated with rare human skeletal diseases and abnormal mouse skeletal phenotypes. Genetic correlation and genomic structural equation modeling indicated that limb proportions exhibited strong genetic sharing but were genetically independent of width and torso proportions. Phenotypic and polygenic risk score analyses identified specific associations between osteoarthritis (OA) of the hip and knee, the leading causes of adult disability in the United States, and skeletal proportions of the corresponding regions. We also found genomic evidence of evolutionary change in arm-to-leg and hip-width proportions in humans consistent with striking anatomical changes in these skeletal proportions in the hominin fossil record. In contrast to cardiovascular, auto-immune, metabolic, and other categories of traits, loci associated with these skeletal proportions are significantly enriched in human accelerated regions (HARs), and regulatory elements of genes differentially expressed through development between humans and the great apes. Taken together, our work validates the use of deep learning models on DXA images to identify novel and specific genetic variants affecting the human skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis.

genomics↗

bioRxiv2023

Reliable genetic correlation estimation via multiple sample splitting and smoothing

In this paper, we aim to investigate the problem of estimating the genetic correlation between two traits. Instead of making assumptions about the distribution of effect sizes of the genetic factors, we propose the use of a high-dimensional linear model to relate a trait to genetic factors. To estimate the genetic correlation, we develop a generic strategy that combines the use of sparse penalization methods and multiple sample splitting approaches. The final estimate is determined by taking the median of the calculations, resulting in a smoothed and reliable estimate. Through simulations, we demonstrate that our proposed approach is reliable and accurate in comparison to naive plug-in methods. To further illustrate the advantages of our method, we apply it to a real-world example of a bacterial GWAS dataset, specifically to estimate the genetic correlation between antibiotic resistant traits in Streptococus pneumoniae. This application not only validates the effectiveness of our method but also highlights its potential in real-world applications.

bioinformatics↗

bioRxiv2023

FedDP: Secure Federated Learning for Disease Prediction with Imbalanced Genetic Data

It is challenging to share and aggregate biomedical data distributed among multiple institutions or computing resources due to various concerns including data privacy, security, and confidentiality. The federated Learning (FL) schema can effectively enable multiple institutions jointly perform machine learning by training a robust model with local data to satisfy the requirement of user privacy protection as well as data security. However, conventional FL methods are exposed to the risk of gradient leakage and cannot be directly applied to genetic data since they cannot address the unique challenges of data imbalance typically seen in genomics. To provide secure and efficient disease prediction based on genetic data distributed across multiple parties, we propose an FL framework enhanced with differential privacy (FedDP) on trained model parameters. In FedDP, local models can be trained among multiple local-hold genetic data with efficient secure and privacy-preserving techniques. The key idea of FedDP is to deploy differential privacy on compressed intermediate gradients that are computed and transmitted by optimizers from local parties. In addition, the unique weighted minmax loss in FedDP is able to address the difficulties of prediction for highly imbalanced genetic datasets. Our experiments on multiple genetic datasets demonstrate that FedDP provides a powerful tool to implement and evaluate various strategies in support of privacy preservation and model performance guarantee to overcome data imbalance.

bioinformatics↗

bioRxiv2023

Novel Pipeline for Large-Scale Comparative Population Genetics

As scientists continue to ask complex questions about biodiversity and deal with increasingly large amounts of data, there is a demand for new methods and computational developments to perform scientific analyses. Analytical pipelines and modules can provide a way to meet these demands and ensure reproducibility in scientific methods and analyses. The goal of this study was to create efficient, reproducible, reusable programming modules that are publicly available for future research. These modules were used to determine population genetic structure measures and compare these measures across species with different biological traits. The functionality of the modules is shown through a case study on Diptera (true fly) species from Canada and Greenland. We leveraged high-throughput DNA sequencing data from Northern areas, as it is a valuable resource and provides new opportunities to study the Arctic. Data were pulled from public databases (Barcode of Life Data System and Global Biodiversity Information Facility), as well as taxon-specific literature. The pipeline we developed in R includes fifteen modules, including modules to prepare and filter the data, calculate population genetic structure measures (e.g., FST), and run a multiple regression. These modules can be easily adapted and applied to a diverse set of animal groups, geographic regions, and biological traits. Best practices were followed for pipeline development, and the modules were designed and tested to work for datasets of different sizes by providing multiple different analyses and filtering options. Biological results were also obtained for Diptera species. Habitat and larval diet were both significantly related to population genetic structure. Evidence of isolation by distance and a relationship between population genetic structure and both latitude and longitude were also found. Overall, this study has created efficient, reusable bioinformatics modules, and provided insight into the factors affecting population genetic structure in Northern fly communities.

bioinformatics↗

bioRxiv2023

Genetic diversity of the eastern black rhinoceros (Diceros bicornis michaeli) in Tanzania; implications for future conservation

In the past decade, there has been a drastic decline in the number of Eastern Black rhinoceros (black rhinoceros) (Diceros bicornis michaeli), primarily because of poaching across their natural habitats, leaving few individuals in small, isolated populations that are vulnerable to demographic extinction, disease epidemics, genetic drift and inbreeding. However, genetic consequences of the demographic decline on the remaining populations have not been investigated. Using the mitochondrial control region, this study investigated how current levels of genetic diversity relate to historical patterns, quantified genetic differentiation between extant populations and assessed the impacts of previous translocations on genetic diversity across populations. A total of 74 individual eastern black rhinoceroses were sampled from five extant populations in Tanzania and one neighbouring cross-border population in the Maasai Mara in Kenya. Six maternal haplotypes were identified, with an overall haplotype diversity of h=0.7 but low overall nucleotide diversity within populations ({pi} = 0.017) compared to historical populations from Tanzania ({pi} = 0.021). There was extensive variation in haplotype distribution between populations, with more variation exists within (65.5 %) than among the populations (35.5%), which may indicate lack of migration between populations. Specifically, some geographically close populations with different histories of introductions didnt share any haplotypes, suggesting that gene flow is currently restricted. The haplotypes were distributed among three east African haplogroups (CV, CE and EA) that have been described in previous studies, suggesting that multiple lineages have been preserved despite loss of haplotypes. One of the haplotypes was highly divergent and matched sequences previously classified as a subspecies that has not been recognised in recent years (D. b. ladoensis). We recommend that current levels of diversity be maintained by allowing natural movements of rhinoceroses between the populations, with the possibility of introducing additional variations by translocation of individuals between sites.

evolutionary biology↗

bioRxiv2023

Hypothesis-free phenotype prediction within a genetics-first framework

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed rare, even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population1-3). Our understanding of how rare genetic variants influence disease and organism-level phenotypes has achieved limited progress, partly explained by the intrinsic difficulty in statistically evaluating the biological significance of rare events. Here we show that discoveries can instead be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible novel genetic causes for developmental disorders that have eluded other established methods and present novel molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

genomics↗