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Dingoes are wild canids living in Australia, originating from domestic dogs. They have lived isolated from both the wild and the domestic ancestor, making them a unique model for studying feralization. Here, we sequence the genomes of 10 dingoes and 2 New Guinea Singing Dogs. Phylogenetic and demographic analyses show that dingoes originate from dogs in southern East Asia, which migrated via Island Southeast Asia to reach Australia around 8300 years ago, and subsequently diverged into a genetically distinct population. Selection analysis identifies 50 positively selected genes enriched in digestion and metabolism, indicating a diet change during feralization of dingoes. Thirteen of these genes have shifted allele frequencies compared to dogs but not compared to wolves. Functional assays show that an A-to-G mutation in ARHGEF7 decreases the endogenous expression, suggesting behavioral adaptations related to the transitions in environment. Our results indicate that the feralization of the dingo induced positive selection on genomic regions correlated to neurodevelopment, metabolism and reproduction, in adaptation to a wild environment. Dingoes evolved in isolation from both their domesticated and wild ancestors. Here, the authors investigate the genomic basis of the feralization of dingoes and trace their origin to domestic dogs that migrated to Australia approximately 8300 years ago.

AbstractAdmixture resulting from natural dispersal processes can potentially generate novel phenotypic variation that may facilitate persistence in changing environments or result in the loss of population-specific adaptations. Yet, under the US Endangered Species Act, policy is limited for management of individuals whose ancestry includes a protected taxon; therefore, they are generally not protected under the Act. This issue is exemplified by the recently re-established grey wolves of the Pacific Northwest states of Washington and Oregon, USA. This population was likely founded by two phenotypically and genetically distinct wolf ecotypes: Northern Rocky Mountain (NRM) forest and coastal rainforest. The latter is considered potentially threatened in southeast Alaska and thus the source of migrants may affect plans for their protection. To assess the genetic source of the re-established population, we sequenced a ~ 300 bp portion of the mitochondrial control region and ~ 5 Mbp of the nuclear genome. Genetic analysis revealed that the Washington wolves share ancestry with both wolf ecotypes, whereas the Oregon population shares ancestry with NRM forest wolves only. Using ecological niche modelling, we found that the Pacific Northwest states contain environments suitable for each ecotype, with wolf packs established in both environmental types. Continued migration from coastal rainforest and NRM forest source populations may increase the genetic diversity of the Pacific Northwest population. However, this admixed population challenges traditional management regimes given that admixture occurs between an adaptively distinct ecotype and a more abundant reintroduced interior form. Our results emphasize the need for a more precise US policy to address the general problem of admixture in the management of endangered species, subspecies, and distinct population segments.

Genetic introgression not only provides material for adaptive evolution but also confounds our understanding of evolutionary history. This is particularly true for canids, a species complex in which genome sequencing and analysis has revealed a complex history of admixture and introgression. Here, we sequence 19 new whole genomes from high-altitude Tibetan and Himalayan wolves and dogs and combine these into a larger data set of 166 whole canid genomes. Using these data, we explore the evolutionary history and adaptation of these and other canid lineages. We find that Tibetan and Himalayan wolves are closely related to each other, and that ∼39% of their nuclear genome is derived from an as-yet-unrecognized wolf-like lineage that is deeply diverged from living Holarctic wolves and dogs. The EPAS1 haplotype, which is present at high frequencies in Tibetan dog breeds and wolves and confers an adaptive advantage to animals living at high altitudes, was probably derived from this ancient lineage. Our study underscores the complexity of canid evolution and demonstrates how admixture and introgression can shape the evolutionary trajectories of species.

The Tibetan grey wolf (Canis lupus chanco) occupies habitats on the Qinghai-Tibet Plateau, a high altitude (>3000 m) environment where low oxygen tension exerts unique selection pressure on individuals to adapt to hypoxic conditions. To identify genes involved in hypoxia adaptation, we generated complete genome sequences of nine Chinese wolves from high and low altitude populations at an average coverage of 25× coverage. We found that, beginning about 55,000 years ago, the highland Tibetan grey wolf suffered a more substantial population decline than lowland wolves. Positively selected hypoxia-related genes in highland wolves are enriched in the HIF signaling pathway (P = 1.57E-6), ATP binding (P = 5.62E-5), and response to an oxygen-containing compound (P≤5.30E-4). Of these positively selected hypoxia-related genes, three genes (EPAS1, ANGPT1, and RYR2) had at least one specific fixed non-synonymous SNP in highland wolves based on the nine genome data. Our re-sequencing studies on a large panel of individuals showed a frequency difference greater than 58% between highland and lowland wolves for these specific fixed non-synonymous SNPs and a high degree of LD surrounding the three genes, which imply strong selection. Past studies have shown that EPAS1 and ANGPT1 are important in the response to hypoxic stress, and RYR2 is involved in heart function. These three genes also exhibited significant signals of natural selection in high altitude human populations, which suggest similar evolutionary constraints on natural selection in wolves and humans of the Qinghai-Tibet Plateau.

Abstract Ethiopian wolves, a canid species endemic to the Ethiopian Highlands, have been steadily declining in numbers for decades. Currently, out of 35 extant species, it is now one of the world's most endangered canids. Most conservation efforts have focused on preventing disease, monitoring movements and behavior, and assessing the geographic ranges of sub-populations. Here, we add an essential layer by determining the Ethiopian wolf's demographic and evolutionary history using high-coverage (∼40×) whole-genome sequencing from 10 Ethiopian wolves from the Bale Mountains. We observe exceptionally low diversity and enrichment of weakly deleterious variants in the Ethiopian wolves in comparison with two North American gray wolf populations and four dog breeds. These patterns are consequences of long-term small population size, rather than recent inbreeding. We infer the demographic history of the Ethiopian wolf and find it to be concordant with historic records and previous genetic analyses, suggesting Ethiopian wolves experienced a series of both ancient and recent bottlenecks, resulting in a census population size of fewer than 500 individuals and an estimated effective population size of approximately 100 individuals. Additionally, long-term small population size may have limited the accumulation of strongly deleterious recessive mutations. Finally, as the Ethiopian wolves have inhabited high-altitude areas for thousands of years, we searched for evidence of high-altitude adaptation, finding evidence of positive selection at a transcription factor in a hypoxia-response pathway [CREB-binding protein (CREBBP)]. Our findings are pertinent to continuing conservation efforts and understanding how demography influences the persistence of deleterious variation in small populations.

The Tibetan Mastiff (TM), a native of the Tibetan Plateau, has quickly adapted to the extreme highland environment. Recently, the impact of positive selection on the TM genome was studied and potential hypoxia-adaptive genes were identified. However, the origin of the adaptive variants remains unknown. In this study, we investigated the signature of genetic introgression in the adaptation of TMs with dog and wolf genomic data from different altitudes in close geographic proximity. On a genome-wide scale, the TM was much more closely related to other dogs than wolves. However, using the ‘ABBA/BABA’ test, we identified genomic regions from the TM that possibly introgressed from Tibetan gray wolf. Several of the regions, including the EPAS1 and HBB loci, also showed the dominant signature of selective sweeps in the TM genome. We validated the introgression of the two loci by excluding the possibility of convergent evolution and ancestral polymorphisms and examined the haplotypes of all available canid genomes. The estimated time of introgression based on a non-coding region of the EPAS1 locus mostly overlapped with the Paleolithic era. Our results demonstrated that the introgression of hypoxia adaptive genes in wolves from the highland played an important role for dogs living in hypoxic environments, which indicated that domestic animals could acquire local adaptation quickly by secondary contact with their wild relatives.

With the assistance of their human companions, dogs have dispersed into new environments during the expansion of human civilization. Tibetan Mastiff (TM), a native of the Tibetan Plateau, was derived from the domesticated Chinese native dog and, like Tibetans, has adapted to the extreme environment of high altitude. Here, we genotyped genome-wide single-nucleotide polymorphisms (SNPs) from 32 TMs and compared them with SNPs from 20 Chinese native dogs and 14 gray wolves (Canis lupus). We identified 16 genes with signals of positive selection in the TM, with 12 of these candidate genes associated with functions that have roles in adaptation to high-altitude adaptation, such as EPAS1, SIRT7, PLXNA4, and MAFG that have roles in responses to hypoxia. This study provides important information on the genetic diversity of the TM and potential mechanisms for adaptation to hypoxia.

Background The wolf ( Canis lupus ) is one of the most widely distributed terrestrial mammals, because it is well adapted to various ecological niches and their corresponding pathogen environments. Immunological competence is a crucial factor involved in adapting to a changing environment and fighting pathogen infection in animals. In this study, the peripheral blood transcriptome of wolves was generated via RNA-seq to advance understanding of the wolf immunome, with a special focus on the major histocompatibility complex class I (MHC I) and toll-like receptor (TLR) gene families, which are involved in pathogen recognition and defense. Results The blood transcriptomic libraries of eight wolves originating from Tibet and Inner Mongolia were sequenced, and approximately 383 million reads were generated. Using a genome-guided assembly strategy, we obtained 123,851 unigenes, with a mean length of 845 bp and an N50 length of 1121 bp. On the basis of BLAST searches against the NCBI non-redundant protein database (Nr), a total of 36,192 (29.22%) unigenes were annotated. For functional classification, 24,663 unigenes were assigned to 13,016 Gene Ontology (GO) terms belonging to 51 sub-categories of the three main GO categories. Additionally, 7682 unigenes were classified into 6 Kyoto Encyclopedia of Genes and Genomes (KEGG) categories, in which the most represented functional sub-categories were signal transduction and the immune system, and 16,238 unigenes were functionally classified into 25 Eukaryotic Orthologous Groups (KOG) categories. We observed an overall higher ω ( d N / d S ) value at antigen-binding sites (ABSs) than at non-ABS regions as well as clear evidence of intergenic/intragenic recombination events at wolf MHC I loci. Additionally, our analysis revealed that carnivorous TLRs were dominated by purifying selection, with mean ω values at each TLR locus ranging from 0.173 to 0.527. However, we also found significant instances of positive selection that acted on several codons in pathogen recognition domains and were linked to species-specific differences in pathogen recognition. Conclusions This study represents the first attempt to characterize the blood transcriptome of the wolf and to highlight the value of investigating the immune system. Balancing selection and recombination have contributed to the historical evolution of wolf MHC I genes. Moreover, TLRs in carnivores have undergone adaptive evolution against the background of purifying selection, and a high level of adaptive evolution was detected in the wolf TLR system.

In this study, we introduce the pied kingfisher optimizer (PKO), a novel swarm-based meta-heuristic algorithm that draws inspiration from the distinctive hunting behavior and symbiotic relationships observed in pied kingfishers in the natural world. The PKO algorithm is structured around three distinct phases: perching/hovering for prey (exploration/diversification), diving for prey (exploitation/intensification), and fostering symbiotic relations. These behavioral aspects are translated into mathematical models capable of effectively addressing a wide array of optimization challenges across diverse search spaces. The algorithm’s performance is rigorously evaluated across thirty-nine test functions, which encompass various unimodal, multimodal, composite, and hybrid ones. Additionally, eight real-world engineering optimization problems, including both constrained and unconstrained scenarios, are considered in the assessment. To gauge PKO’s efficacy, it is subjected to a comparative analysis against 3 categories of rival optimizers. The 1st category comprises well-established and widely-cited optimizers such as particle swarm optimization and genetic algorithm. The 2nd category encompasses recently published algorithms, including Harris Hawks optimization, Whale optimization algorithm, sine cosine algorithm, Grey Wolf optimizer, gravitational search algorithm, and moth-flame optimization. The 3rd category includes advanced algorithms, such as covariance matrix adaptation evolution strategy and Ensemble Sinusoidal Differential Covariance Matrix Adaptation with Euclidean Neighborhood (LSHADE-cnEpSin). The comparative analysis employs various performance metrics, including the Friedman mean rank and the Wilcoxon rank-sum test, to reveal PKO’s effectiveness and efficiency. The overall results highlight PKO’s exceptional ability to tackle intricate optimization problems characterized by challenging search spaces. PKO demonstrates superior exploration and exploitation tendencies while effectively avoiding local optima. The source code for the PKO algorithm is publicly accessible at  https://www.mathworks.com/matlabcentral/fileexchange/160043-pied-kingfisher-optimizer-pko .