Biology subjects

Gopalakrishnan, S.

Publications and source records attributed to Gopalakrishnan, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Disrupted Cholesterol Biosynthesis and Hair Follicle Stem Cell Impairment in the Onset of Alopecia

BackgroundHair follicle cycle and the functioning of stem cells in alopecia are influenced by the suppression of cholesterol synthesis and the accumulation of sterol intermediates. ObjectiveThis investigation aims to elucidate the regulatory function of disrupted cholesterol homeostasis in the functioning of hair follicle stem cells (HFSCs) and the cycling of hair follicles. Additionally, it seeks to provide an understanding of the fate of stem cells in primary cicatricial alopecia (PCA). MethodsTo evaluate the influence of cholesterol on the functionality of hair follicles, a study was conducted to analyse gene expression and pathways associated with hair follicle stem cell markers in scalp samples affected by PCA (LPP, FFA, CCCA, DC, DF, TF). To assess the influence of disrupted cholesterol homeostasis on HFSCs, we conducted experiments involving the administration of 7-dehydrocholesterol (7DHC) and BM15766 (Pharmacological inhibitor of cholesterol biosynthesis), to Human Hair Follicle Outer Root Sheath Cells (HORSCs), as well as C57BL/6 mice, and hair follicle organoid cultures. The study utilised reverse transcription polymerase chain reaction (RT-PCR) to assess gene expression, while immunofluorescence was employed to analyse protein expression. The tracking of stem cell fate was accomplished through the utilisation of a BrdU pulse-chase experiment, while the verification of apoptotic consequences was established by utilising the TUNEL assay. A statistical analysis was conducted to assess the statistical significance of the data. ResultsThere was a notable decrease in the expression of HFSC marker genes among patients afflicted with PCA. In vitro data further confirmed the cholesterol inhibition and sterol intermediate accumulation in stem cells, leading to stem cell characteristics disruption. The experimental group of mice exposed to 7DHC and BM15766 also exhibited a notable inability to initiate hair regrowth. Consequently, this deficiency in hair regrowth resulted in the activation of apoptosis, specifically in the stem cells. Additionally, our confirmatory analysis, which was performed utilising organoid culture, consistently yielded comparable results. The results as mentioned above emphasise the significant importance of cholesterol production in preserving the integrity and functionality of HFSCs, hence providing novel insights into the progression of alopecia. ConclusionIndividuals with aberrant cholesterol production, particularly those afflicted with PCA, experience a persistent impairment in hair regrowth due to the irreversible destruction of their hair follicles. The observed phenomenon is hypothesised to be attributed to the loss of hair follicle stem cells. Our study presents additional findings that elucidate the previously unknown involvement of sterol intermediates in regulating hair follicle cycling and stem cell function in PCA. The regulation of cholesterol production and the buildup of sterol intermediates have an impact on the hair follicle cycle and the role of stem cells in alopecia.

cell biology↗

bioRxiv2023

Multi-omic characterization of antibody-producing CHO cell lines elucidates metabolic reprogramming and nutrient uptake bottlenecks

Characterizing the phenotypic diversity and metabolic capabilities of industrially relevant manufacturing cell lines is critical to bioprocess optimization and cell line development. Metabolic capabilities of the production hosts limit nutrient and resource channeling into desired cellular processes and can have a profound impact on productivity but cannot be directly inferred from measured data such as spent media concentrations or transcriptomics. Here, we present an integrated multi-omic characterization approach combining exo-metabolomics, transcriptomics, and genome-scale metabolic network analysis and apply it to three antibody-producing Chinese Hamster Ovary cell lines to reprogramming features associated with high-producer clones and metabolic bottlenecks limiting product production in an industrial bioprocess. Analysis of individual datatypes revealed a decreased nitrogenous byproduct secretion in high-producing clones and the topological changes in peripheral metabolic pathway expression associated with phase shifts. An integrated omics analysis in the context of the genome-scale metabolic model elucidated the differences in central metabolism and identified amino acid utilization bottlenecks limiting cell growth and antibody production that were not evident from exo-metabolomics or transcriptomics alone. Thus, we demonstrate the utility of a multi-omics characterization in providing an in-depth understanding of cellular metabolism, which is critical to efforts in cell engineering and bioprocess optimization.

systems biology↗

bioRxiv2023

COSMIC-dFBA: A novel multi-scale hybrid framework for bioprocess modeling

Metabolism governs cell performance in biomanufacturing, as it fuels growth and productivity. However, even in well-controlled culture systems, metabolism is dynamic, with shifting objectives and resources, thus limiting the predictive capability of mechanistic models for process design and optimization. Here, we present Cellular Objectives and State Modulation In bioreaCtors (COSMIC)-dFBA, a hybrid multi-scale modeling paradigm that accurately predicts cell density, antibody titer, and bioreactor metabolite concentration profiles. Using machine-learning, COSMIC-dFBA decomposes the instantaneous metabolite uptake and secretion rates in a bioreactor into weighted contributions from each cell state (growth or antibody-producing state) and integrates these with a genome-scale metabolic model. A major strength of COSMIC-dFBA is that it can be parameterized with only metabolite concentrations from spent media, although constraining the metabolic model with other omics data can further improve its capabilities. Using COSMIC-dFBA, we can predict the final cell density and antibody titer to within 10% of the measured data, and compared to a standard dFBA model, we found the framework showed a 90% and 72% improvement in cell density and antibody titer prediction, respectively. Thus, we demonstrate our hybrid modeling framework effectively captures cellular metabolism and expands the applicability of dFBA to model the dynamic conditions in a bioreactor.

systems biology↗

bioRxiv2023

Synergistic Fusion of Graph and Transformer Features for Enhanced Molecular Property Prediction

Molecular property prediction is a critical task in computational drug discovery. While recent advances in Graph Neural Networks (GNNs) and Transformers have shown to be effective and promising, they face the following limitations: Transformer self-attention does not explicitly consider the underlying molecule structure while GNN feature representation alone is not sufficient to capture granular and hidden interactions and characteristics that distinguish similar molecules. To address these limitations, we propose SYN-FUSION, a novel approach that synergistically combines pre-trained features from GNNs and Transformers. This approach provides a comprehensive molecular representation, capturing both the global molecule structure and the individual atom characteristics. Experimental results on MoleculeNet benchmarks demonstrate superior performance, surpassing previous models in 5 out of 7 classification datasets and 4 out of 6 regression datasets. The performance of SYN-FUSION has been compared with other Graph-Transformer models that have been jointly trained using a combination of transformer and graph features, and it is found that our approach is on par with those models in terms of performance. Extensive analysis of the learned fusion model across aspects such as loss, latent space, and weight distribution further validates the effectiveness of SYN-FUSION. Finally, an ablation study unequivocally demonstrates that the synergy achieved by SYN-FUSION surpasses the performance of its individual model components and their ensemble, offering a substantial improvement in predicting molecular properties. CCS CONCEPTS*Applied computing [->]Molecular sequence analysis; Bioinformatics; * Computing methodologies[->] Artificial intelligence; Transfer learning; Neural networks.

bioinformatics↗

bioRxiv2023

A genomic exploration of the possible de-extirpation of the Zanzibar leopard

The recently extirpated Zanzibar leopard was the only known African leopard (Panthera pardus spp.) population restricted exclusively to a major island habitat. Although its demise was driven through habitat change and conflict with humans, given its role as a keystone species for the Zanzibar Archipelago, its potential reintroduction might offer a means for helping preserve the natural biodiversity of its former habitat. Whether this is feasible, however, would be contingent on both whether closely related source populations can be identified on mainland Africa, and whether the Zanzibar form exhibited any special adaptations that might need to be considered when choosing such a source. In light of these questions, we genomically profiled two of the six known historic specimens, to explore whether they represent a realistic candidate for de-extirpation through reintroduction. Our analyses indicate that despite its geographic separation, the Zanzibar leopard shared a close genetic relationship with mainland East African individuals. Furthermore, although its uniqueness as an island population was emphasised by genomic signatures of high inbreeding and increased mutation load, the latter similar to the level of the critically endangered Amur leopard (P. p. orientalis), we find no evidence of positive selection unique to Zanzibar. We therefore conclude that should attempts to restore leopards to Zanzibar be planned, then mainland East African leopards would provide a suitable gene pool, whether using genetic engineering or conventional rewilding approaches.

evolutionary biology↗

bioRxiv2023

Redefining rock doves, Columba livia, using historical whole genome sequences

The domestic pigeons exceptional phenotypic diversity was key in developing Darwins Theory of Evolution and establishing the concept of artificial selection in domestic species. However, unlike its domestic counterpart, its wild progenitor, the rock dove Columba livia, has received considerably less attention. Therefore, questions regarding their domestication, evolution, taxonomy, and conservation status remain unresolved. We generated whole-genome sequencing data from 65 historical rock dove samples representing all currently recognised subspecies and spanning the species original geographic distribution. Our dataset includes three specimens from Darwins collection and the type specimens of five different taxa. We characterised rock doves population structure, genomic diversity and gene-flow patterns. We show the West African subspecies C. l. gymnocyclus is basal to rock doves and domestic pigeons. Our results show gene-flow signals between the rock doves sister species C. rupestris and all rock doves except the West African populations. Our results led us to propose an evolutionary model for the rock dove considering the Pleistocene refugia theory. We propose that todays rock dove genetic diversity and introgression patterns derive from a history of allopatric cycles and dispersion waves during the Quaternary glacial and interglacial periods. To explore the rock dove domestication history, we combined our new dataset with available genomes from domestic pigeons. Our results point to at least one domestication event in the Levant region that gave rise to all domestic breeds analysed in this study. Finally, we propose a species-level taxonomic arrangement to reflect the evolutionary history of the West African rock dove populations.

evolutionary biology↗

bioRxiv2023

Conservation implications of elucidating the Korean wolf taxonomic ambiguity through whole-genome sequencing

The taxonomic status of the now likely extirpated Korean Peninsula wolf has been extensively debated, with some arguing it represents an independent wolf lineage, Canis coreanus. To investigate the Korean wolf genetic affiliations and their taxonomic implications, we sequenced and analysed the genomes of a historical Korean wolf dated to the beginning of the 20th century, and a captive wolf originally located at the Pyongyang Central Zoo. Our results indicated that the Korean wolf bears similar genetic ancestry to other regional East Asian populations, therefore suggesting it is not a distinct taxonomic lineage. We identified regional patterns of wolf population structure and admixture in East Asia with potential conservation consequences in the Korean Peninsula and on a regional scale. We find the Korean wolf has similar diversity and inbreeding to other East Asian wolves. Finally, we show that, in contrast to the historical sample, the captive wolf is more genetically similar to wolves from the Tibetan Plateau, hence, Korean wolf conservation programs might not benefit from the inclusion of this specimen.

evolutionary biology↗

bioRxiv2022

Guidelines for extracting biologically relevant context-specific metabolic models using gene expression data

Genome-scale metabolic models comprehensively describe an organisms metabolism and can be tailored using omics data to model condition-specific physiology. The quality of context-specific models is impacted by (i) choice of algorithm and parameters and (ii) alternate context-specific models that equally explain the -omics data. Here we quantify the influence of alternate optima on microbial and mammalian model extraction using GIMME, iMAT, MBA, and mCADRE. We find that metabolic tasks defining an organisms phenotype must be explicitly and quantitatively protected. The scope of alternate models is strongly influenced by algorithm choice and the topological properties of the parent genome-scale model with fatty acid metabolism and intracellular metabolite transport contributing much to alternate solutions in all models. mCADRE extracted the most reproducible context-specific models and models generated using MBA had the most alternate solutions. There were fewer qualitatively different solutions generated by GIMME in E. coli, but these increased substantially in the mammalian models. Screening ensembles using a receiver operating characteristic plot identified the best-performing models. A comprehensive evaluation of models extracted using combinations of extraction methods and expression thresholds revealed that GIMME generated the best-performing models in E. coli, whereas mCADRE is better suited for complex mammalian models. These findings suggest guidelines for benchmarking -omics integration algorithms and motivate the development of a systematic workflow to enumerate alternate models and extract biologically relevant context-specific models.

systems biology↗

bioRxiv2022

Genomic differentiation among European perch in the western Baltic Sea reflects colonization history and local adaptation

Environmental variation across the distribution of wild species can lead to local adaptations. The Baltic Sea was formed when the Fenno-Scandian ice sheet retreated around 12 thousand years ago, creating a new brackish water habitat colonised by both marine and freshwater fish species. The European perch (Perca fluviatilis) is a predatory freshwater fish with a large geographical distribution across Eurasia, where it inhabits a wide range of environmental niches. In the Baltic Sea region it has even developed a specialised brackish water phenotype that can tolerate environmental salinity levels, which are lethal to the ancestral freshwater phenotype. However, very little is known about the colonisation history and underlying genomic mechanisms facilitating the colonisation and adaptation of perch to the Baltic Sea. Here, we use Genotyping-By-Sequencing data from six freshwater and six brackish water localities to disclose the evolutionary relationship between the freshwater and brackish water phenotype. Our results show that the brackish water perch phenotype occurs in multiple distinct genetic clusters. We find that gene flow between brackish water phenotypes with full access to the sea likely led to lower levels of differentiation and higher diversity than in freshwater phenotypes. Selection analyses suggest that genomic adaptation played a role in the colonisation of the Baltic Sea and that the top three regions under selection harbour salinity tolerance genes. We also find a link between the historic salinity of the Baltic Sea and the demographic history of the brackish water phenotypes and go on to discuss the implications of our findings for management of brackish water perch in the western Baltic sea. HighlightsO_LIGBS data from 12 perch populations, six with brackish and six with freshwater origin C_LIO_LIColonisation history and differentiated gene flow shaped the current population structure C_LIO_LIThe brackish water ecotype was found in all three major genetic clades C_LIO_LITop three regions under selection harboured salinity tolerance genes C_LIO_LISalinity influenced Ne during the formation of the Baltic Sea C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/516742v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@29e5dforg.highwire.dtl.DTLVardef@b2b35borg.highwire.dtl.DTLVardef@1d3457org.highwire.dtl.DTLVardef@1574e46_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2022

HaploCart: Human mtDNA Haplogroup Classification Using a Pangenomic Reference Graph

Current mitochondrial DNA (mtDNA) haplogroup classification tools map reads to a single reference genome and perform inference based on the detected mutations to this reference. This approach biases haplogroup assignments towards the reference and prohibits accurate calculations of the uncertainty in assignment. We present HaploCart, an mtDNA haplogroup classifier which uses VGs pangenomic reference graph framework together with principles of Bayesian inference. We demonstrate that our approach significantly outperforms available tools by being more robust to lower coverage or incomplete consensus sequences and producing phylogenetically-aware confidence scores that are unbiased towards any haplogroup. HaploCart is available both as a command-line tool and through a user-friendly web interface. The program written in C++ accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments along with confidence estimates. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment. HaploCart is available as a command-line tool at https://github.com/grenaud/vgan and as a web server at https://services.healthtech.dtu.dk/service. php?HaploCart.

bioinformatics↗

bioRxiv2022

Ancient DNA Reveals China as a Historical Genetic Melting Pot in Tiger Evolution

The contrast between the tigers (Panthera tigris) 2-3 My age and extant tigers coalescence approximately 110,000 years ago suggests an ancient demographic bottleneck. Here we collected over 60 extinct specimens across mainland Asia and generated whole genome sequences from a 10,600-year-old Russian Far East (RFE) specimen (RUSA21, 8{xi} coverage), 14 South China tigers (0.1-12{xi}), three Caspian tigers (4-8{xi}), plus 17 new mitogenomes. RUSA21 clustered within modern Northeast Asian phylogroups and partially derived from an extinct Late Pleistocene lineage. While some 8,000-10,000-year-old RFE mitogenomes are basal to all tigers, one 2,000-year-old specimen resembles present Amur tigers. The Caspian tiger likely dispersed from an ancestral Northeast Asian population and experienced gene flow from southern Bengal tigers. Lastly, genome-wide monophyly supported the South China tiger as a distinct subspecies, albeit with mitochondrial paraphyly, hence resolving its longstanding taxonomic controversy. The distribution of mitochondrial haplogroups corroborated by biogeographical modeling suggested Southwest China was a Late Pleistocene refugium for a relic basal lineage. As suitable habitat returned, Eastern China became a genetic melting pot to foster divergent lineages to merge into South China tigers and other subsequent northern subspecies to develop. Genomic information retrieved from ancient tigers hence sheds light on the species full evolutionary history leading to nine modern subspecies and resolves the natural history of surviving tigers.

evolutionary biology↗

bioRxiv2022

Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

The human leukocyte antigen (HLA) system is a group of genes coding for proteins that are central to the adaptive immune system and identifying the specific HLA allele combination of a patient is relevant in organ donation, risk assessment of autoimmune and infectious diseases and cancer immunotherapy. However, due to the high genetic polymorphism in this region, HLA typing requires specialized methods. We investigated the performance of five next-generation-sequencing (NGS) based HLA typing tools with a non-restricted license namely HLA*LA, Optitype, HISAT-genotype, Kourami and STC-Seq. This evaluation was done for the five HLA loci, HLA-A, -B, -C, -DRB1 and -DQB1 using whole-exome sequencing (WES) samples from 829 individuals. The robustness of the tools to lower coverage was evaluated by subsampling and HLA typing 230 WES samples at coverages ranging from 1X to 100X. The typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions, which specifically focus on the peptide binding region. On average, across the five HLA genes, HLA*LA was found to have the highest typing accuracy. For the individual genes, HLA-A, -B and -C, Optitypes typing accuracy was highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools robustness to lower coverage data varied widely and further depended on the specific HLA locus. For all class I loci, Optitype had a typing accuracy above 95% (according to the modification of the amino acids in the functionally relevant portion of the protein) at 50X, but increasing the depth of coverage beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA genes as well as HLA*LAs typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which often is based on lower quality sequencing data. Interestingly, we found that Optitypes typing accuracy is not notably impaired by short read length or by DNA damage, which is typical of aDNA, as long as the depth of coverage is sufficiently high.

bioinformatics↗

bioRxiv2022

The type 1 diabetes gene TYK2 regulates β-cell development and its responses to interferon-α

Type 1 diabetes (T1D) is an autoimmune disease that results in the destruction of insulin producing pancreatic {beta}-cells. One of the genes associated with T1D is TYK2, which encodes a Janus kinase with critical roles in type-I interferon (IFN) mediated intracellular signaling. To study the role of TYK2 in human pancreatic {beta}-cell development and response to IFN, we generated TYK2 knockout human iPSCs and directed them into the pancreatic endocrine lineage. Here we show that loss of TYK2 compromised the emergence of endocrine precursors by regulating KRAS expression while mature stem cell-islets (SC-islets) function was not affected. In the maturing SC-islets, the loss or inhibition of TYK2 prevented IFN-induced antigen processing and presentation, including MHC Class I expression in pancreatic endocrine and progenitor cells. Furthermore, in a CD8+ cytotoxic T-cell co-culture model, the survival of {beta}-cells was enhanced by a selective TYK2 inhibitor. These results identify an unsuspected role for TYK2 on {beta}-cell development and support TYK2 inhibition in adult {beta}-cells as a potent therapeutic target to halt T1D progression.

molecular biology↗

bioRxiv2022

Uncovering the hologenomic basis of an extraordinary plant invasion

While invasive species are a key driver of the global biodiversity crisis, the drivers of invasiveness remain debated. To investigate the genomic basis of invasiveness in plants, we use the invasive weed Ambrosia artemisiifolia, introduced to Europe in the late 19th century, resequencing 655 ragweed genomes, including 308 herbarium specimens collected up to 190 years ago. In introduced European populations, we report selection signatures in defense genes and lower prevalence of particular plant pathogens in the invasive range. Together with temporal changes in population structure associated with introgression from closely related Ambrosia species, escape from microbial enemies likely favoured the plants remarkable success as an invasive species. One-Sentence SummaryThe invasive success of European ragweed was facilitated by release from enemy microbes and inter-species hybridization.

genomics↗

bioRxiv2022

Genomes of the extinct Sicilian wolf reveal a complex history of isolation and admixture with ancient dogs

The Sicilian wolf represented the only population of wolves living on a Mediterranean island until the first half of the twentieth century (1930s-1960s) 1-7. Previous studies hypothesised that they remained isolated from mainland wolves from the end of the Last Glacial Maximum (LGM) 8,9, until human persecutions led them to extinction 1-7. There are only seven known Sicilian wolf specimens from the 19th and 20th century preserved in museums in Italy and recent morphometric analyses assigned them to the new subspecies Canis lupus cristaldii 10. To better understand the origins of the Sicilian wolf, and its relationship to other wolf populations, we sequenced four whole genomes (3.8x-11.6x) and five mitogenomes. We investigated the relationship between Sicilian wolves and other modern breeds to identify potential admixture. Furthermore, considering that the last land-bridge between Sicily and Italy disappeared after the LGM 11, around 17 kya, we explored the possibility that the Sicilian wolf retained ancestry from ancient wolf and dog lineages. Additionally, we explored whether the long-term isolation might have affected the genomic diversity, inbreeding levels and genetic load of the Sicilian wolf. Our findings show that the Sicilian wolves shared most ancestry with the modern Italian wolf population but are better modelled as admixed with European dog breeds, and shared traces of Eneolithic and Bronze age European dogs. We also find signatures of severe inbreeding and low genomic diversity at population and individual levels due to long-term isolation and drift, suggesting also low effective population size.

genomics↗

bioRxiv2021

Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits. Significance statementUnderstanding the genetic basis of important phenotypes is a central goal of genetics. However, the highly polygenic architectures of complex traits inferred by large-scale genome-wide association studies (GWAS) in humans stand in contrast to the results of quantitative trait locus (QTL) mapping studies in model organisms. Here, we use a barcoding approach to conduct QTL mapping in budding yeast at a scale two orders of magnitude larger than the previous state of the art. The resulting increase in power reveals the polygenic nature of complex traits in yeast, and offers insight into widespread patterns of pleiotropy and epistasis. Our data and analysis methods offer opportunities for future work in systems biology, and have implications for large-scale GWAS in human populations.

genetics↗

bioRxiv2021

Evidence of long-term purging of mutation load in killer whale genomes

Genomes of high latitude killer whales harbour signatures of post-glacial founding and expansion. Here, we investigate whether reduced efficacy of selection increased mutation load in founder populations, or whether recessive deleterious mutations exposed to selection in homozygous genotypes were purged. Comparing the accumulation of synonymous and non-synonymous mutations across pairs of globally sampled genomes reveals that the most significant outliers are high latitude North Atlantic genomes, which have accumulated significantly fewer non-synonymous mutations than all other populations. Comparisons with the genome of a 7.5-Kyr-old North Atlantic killer whale, inferred to be closely related to the population directly ancestral to present-day Icelandic and Norwegian populations, calibrates the timing of the action of selection on non-synonymous mutations predominantly to the mid-late Holocene. Non-synonymous mutations purged in modern Norwegian killer whale genomes are found as globally shared standing variation in heterozygote genotypes more often than expected, suggesting overdominance. Taken together, our findings are consistent with purging of recessive non-synonymous mutations exposed to selection in founder-associated homozygous genotypes.

evolutionary biology↗

bioRxiv2021

Genomic analyses of the extinct Sardinian dhole (Cynotherium sardous) reaveal its evolutionary history

The Sardinian dhole (Cynotherium sardous)1 was an iconic and unique canid species of canid that was endemic of Sardinia and Corsica until it became extinct at the end of the Late Pleistocene2-5. Given its peculiar dental morphology, small body size and high level of endemism, several canids have been proposed as possible ancestors of the Sardinian dhole, including the Asian dhole and African hunting dog ancestor 3,6-9. Morphometric analyses3,6,8-12 have failed to clarify the evolutionary relationship with other canids. We sequenced the genome of a ca 21,100 year old Sardinian dhole in order to understand its genomic history and clarify its phylogenetic position. We found it represents a separate taxon from all other living canids from Eurasia, Africa and North America, and that the Sardinian and Asian dhole lineages diverged ca 885 ka. We additionally detected historical gene flow between the Sardinian and Asian dhole lineages, that ended approximately 500-300 ka, when the landbridge between Sardinia and mainland Italy was broken, severing their population connectivity. Our sample showed low genome-wide diversity compared to other extant canids - probably a result of the long-term isolation - that could have contributed to the subsequent extinction of the Sardinian dhole.

genomics↗