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The aim of this systematic review is to determine whether Deep Learning (DL) algorithms can provide a clinically feasible alternative to classic algorithms for synthetic Computer Tomography (sCT). The following categories are presented in this study: (Formula presented.) MR-based treatment planning and synthetic CT generation techniques. (Formula presented.) Generation of synthetic CT images based on Cone Beam CT images. (Formula presented.) Low-dose CT to High-dose CT generation. (Formula presented.) Attenuation correction for PET images. To perform appropriate database searches, we reviewed journal articles published between January 2018 and June 2023. Current methodology, study strategies, and results with relevant clinical applications were analyzed as we outlined the state-of-the-art of deep learning based approaches to inter-modality and intra-modality image synthesis. This was accomplished by contrasting the provided methodologies with traditional research approaches. The key contributions of each category were highlighted, specific challenges were identified, and accomplishments were summarized. As a final step, the statistics of all the cited works from various aspects were analyzed, which revealed that DL-based sCTs have achieved considerable popularity, while also showing the potential of this technology. In order to assess the clinical readiness of the presented methods, we examined the current status of DL-based sCT generation.

The aim of this systematic review is to determine whether Deep Learning (DL) algorithms can provide a clinically feasible alternative to classic algorithms for synthetic Computer Tomography (sCT). The following categories are presented in this study: (Formula presented.) MR-based treatment planning and synthetic CT generation techniques. (Formula presented.) Generation of synthetic CT images based on Cone Beam CT images. (Formula presented.) Low-dose CT to High-dose CT generation. (Formula presented.) Attenuation correction for PET images. To perform appropriate database searches, we reviewed journal articles published between January 2018 and June 2023. Current methodology, study strategies, and results with relevant clinical applications were analyzed as we outlined the state-of-the-art of deep learning based approaches to inter-modality and intra-modality image synthesis. This was accomplished by contrasting the provided methodologies with traditional research approaches. The key contributions of each category were highlighted, specific challenges were identified, and accomplishments were summarized. As a final step, the statistics of all the cited works from various aspects were analyzed, which revealed that DL-based sCTs have achieved considerable popularity, while also showing the potential of this technology. In order to assess the clinical readiness of the presented methods, we examined the current status of DL-based sCT generation.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier., gene flow, Scandinavian genetic structure, Viking, migration period, human population genomics

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been "liberated"from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1-0.53) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition.

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been “liberated” from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1–0.5×) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition.

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, a probabilistic mtDNA haplogroup classifier which uses a 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 C++ program accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments of the samples along with the level of confidence in the assignments. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment.

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been "liberated"from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1-0.53) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition.

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been “liberated” from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1–0.5×) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition.

Environmental variation across the range 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 perch variant that can tolerate environmental salinity levels, which are lethal to freshwater perch. However, very little is known about the underlying 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 freshwater and brackish water perch. Our results show that the brackish water perch occurs in multiple distinct genetic clusters. We find that gene flow between brackish water perch with full access to the sea likely led to lower levels of differentiation and higher diversity than in freshwater perch. 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 complete by discussing the implications of our findings for management of brackish water perch in the western Baltic sea.

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's genetic affiliations and taxonomic status, we sequenced and analysed the genomes of a Korean wolf dated to the beginning of the 20th century, and a captive wolf originally from 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 that the Korean wolf has similar genomic diversity and inbreeding to other East Asian wolves. Finally, we show that, in contrast to the historical sample, the captive wolf is genetically more similar to wolves from the Tibetan Plateau; hence, Korean wolf conservation programmes might not benefit from the inclusion of this specimen.

The Sicilian wolf remained isolated in Sicily from the end of the Pleistocene until its extermination in the 1930s–1960s. Given its long-term isolation on the island and distinctive morphology, the genetic origin of the Sicilian wolf remains debated. We sequenced four nuclear genomes and five mitogenomes from the seven existing museum specimens to investigate the Sicilian wolf ancestry, relationships with extant and extinct wolves and dogs, and diversity. Our results show that the Sicilian wolf is most closely related to the Italian wolf but carries ancestry from a lineage related to European Eneolithic and Bronze Age dogs. The average nucleotide diversity of the Sicilian wolf was half of the Italian wolf, with 37–50% of its genome contained in runs of homozygosity. Overall, we show that, by the time it went extinct, the Sicilian wolf had high inbreeding and low-genetic diversity, consistent with a population in an insular environment.

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, a probabilistic mtDNA haplogroup classifier which uses a 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 C++ program accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments of the samples along with the level of confidence in the assignments. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment.

Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

Motivation Machine learning (ML) methods are motivated by the need to automate information extraction from large datasets in order to support human users in data-driven tasks. This is an attractive approach for integrative joint analysis of vast amounts of omics data produced in next generation sequencing and other -omics assays. A systematic assessment of the current literature can help to identify key trends and potential gaps in methodology and applications. We surveyed the literature on ML multi-omic data integration and quantitatively explored the goals, techniques and data involved in this field. We were particularly interested in examining how researchers use ML to deal with the volume and complexity of these datasets.Results Our main finding is that the methods used are those that address the challenges of datasets with few samples and many features. Dimensionality reduction methods are used to reduce the feature count alongside models that can also appropriately handle relatively few samples. Popular techniques include autoencoders, random forests and support vector machines. We also found that the field is heavily influenced by the use of The Cancer Genome Atlas dataset, which is accessible and contains many diverse experiments.Availability and implementationAll data and processing scripts are available at this GitLab repository: or in Zenodo: .Supplementary informationare available at Bioinformatics online.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

Motivation Machine learning (ML) methods are motivated by the need to automate information extraction from large datasets in order to support human users in data-driven tasks. This is an attractive approach for integrative joint analysis of vast amounts of omics data produced in next generation sequencing and other -omics assays. A systematic assessment of the current literature can help to identify key trends and potential gaps in methodology and applications. We surveyed the literature on ML multi-omic data integration and quantitatively explored the goals, techniques and data involved in this field. We were particularly interested in examining how researchers use ML to deal with the volume and complexity of these datasets.Results Our main finding is that the methods used are those that address the challenges of datasets with few samples and many features. Dimensionality reduction methods are used to reduce the feature count alongside models that can also appropriately handle relatively few samples. Popular techniques include autoencoders, random forests and support vector machines. We also found that the field is heavily influenced by the use of The Cancer Genome Atlas dataset, which is accessible and contains many diverse experiments.Availability and implementationAll data and processing scripts are available at this GitLab repository: or in Zenodo: .Supplementary informationare available at Bioinformatics online.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

Ancestral Coast Salish societies in the Pacific Northwest kept long-haired “woolly dogs” that were bred and cared for over millennia. However, the dog wool–weaving tradition declined during the 19th century, and the population was lost. In this study, we analyzed genomic and isotopic data from a preserved woolly dog pelt from “Mutton,” collected in 1859. Mutton is the only known example of an Indigenous North American dog with dominant precolonial ancestry postdating the onset of settler colonialism. We identified candidate genetic variants potentially linked with their distinct woolly phenotype. We integrated these data with interviews from Coast Salish Elders, Knowledge Keepers, and weavers about shared traditional knowledge and memories surrounding woolly dogs, their importance within Coast Salish societies, and how colonial policies led directly to their disappearance.

The domestic pigeon’s exceptional phenotypic diversity was key in developing Darwin’s Theory of Evolution and establishing the concept of artificial selection. However, unlike its domestic counterpart, its wild progenitor, the rock dove Columba livia has received considerably less attention. Therefore, questions regarding its domestication, evolution, taxonomy, and conservation status remain unresolved. We generated whole-genome sequencing data from 65 historical rock doves that represent all currently recognized subspecies and span the species’ original geographic distribution. Our dataset includes 3 specimens from Darwin’s collection, and the type specimens of 5 different taxa. We characterized their population structure, genomic diversity, and gene-flow patterns. Our results show the West African subspecies C. l. gymnocyclus is basal to rock doves and domestic pigeons, and suggests gene-flow between the rock dove’s sister species C. rupestris, and the ancestor of rock doves after its split from West African populations. These genomes allowed us to propose a model for the evolution of the rock dove in light of the refugia theory. We propose that 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 1 domestication event in the Levant 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.

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been “liberated” from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1–0.5×) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition.

Environmental variation across the range 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 perch variant that can tolerate environmental salinity levels, which are lethal to freshwater perch. However, very little is known about the underlying 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 freshwater and brackish water perch. Our results show that the brackish water perch occurs in multiple distinct genetic clusters. We find that gene flow between brackish water perch with full access to the sea likely led to lower levels of differentiation and higher diversity than in freshwater perch. 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 complete by discussing the implications of our findings for management of brackish water perch in the western Baltic sea.

The tiger (Panthera tigris) is a charismatic megafauna species that originated and diversified in Asia and probably experienced population contraction and expansion during the Pleistocene, resulting in low genetic diversity of modern tigers. However, little is known about patterns of genomic diversity in ancient populations. Here we generated whole-genome sequences from ancient or historical (100–10,000 yr old) specimens collected across mainland Asia, including a 10,600-yr-old Russian Far East specimen (RUSA21, 8× coverage) plus six ancient mitogenomes, 14 South China tigers (0.1–12×) and three Caspian tigers (4–8×). Admixture analysis showed that RUSA21 clustered within modern Northeast Asian phylogroups and partially derived from an extinct Late Pleistocene lineage. While some of the 8,000–10,000-yr-old Russian Far East mitogenomes are basal to all tigers, one 2,000-yr-old specimen resembles present Amur tigers. Phylogenomic analyses suggested that the Caspian tiger probably 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 modelling suggested that Southwest China was a Late Pleistocene refugium for a relic basal lineage. As suitable habitat returned, admixture between divergent lineages of South China tigers took place in Eastern China, promoting the evolution of other northern subspecies. Altogether, our analysis of ancient genomes sheds light on the evolutionary history of tigers and supports the existence of nine modern subspecies.

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's genetic affiliations and taxonomic status, we sequenced and analysed the genomes of a Korean wolf dated to the beginning of the 20th century, and a captive wolf originally from 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 that the Korean wolf has similar genomic diversity and inbreeding to other East Asian wolves. Finally, we show that, in contrast to the historical sample, the captive wolf is genetically more similar to wolves from the Tibetan Plateau; hence, Korean wolf conservation programmes might not benefit from the inclusion of this specimen.

The Sicilian wolf remained isolated in Sicily from the end of the Pleistocene until its extermination in the 1930s–1960s. Given its long-term isolation on the island and distinctive morphology, the genetic origin of the Sicilian wolf remains debated. We sequenced four nuclear genomes and five mitogenomes from the seven existing museum specimens to investigate the Sicilian wolf ancestry, relationships with extant and extinct wolves and dogs, and diversity. Our results show that the Sicilian wolf is most closely related to the Italian wolf but carries ancestry from a lineage related to European Eneolithic and Bronze Age dogs. The average nucleotide diversity of the Sicilian wolf was half of the Italian wolf, with 37–50% of its genome contained in runs of homozygosity. Overall, we show that, by the time it went extinct, the Sicilian wolf had high inbreeding and low-genetic diversity, consistent with a population in an insular environment.

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, a probabilistic mtDNA haplogroup classifier which uses a 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 C++ program accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments of the samples along with the level of confidence in the assignments. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment.

The domestic pigeon’s exceptional phenotypic diversity was key in developing Darwin’s Theory of Evolution and establishing the concept of artificial selection. However, unlike its domestic counterpart, its wild progenitor, the rock dove Columba livia has received considerably less attention. Therefore, questions regarding its domestication, evolution, taxonomy, and conservation status remain unresolved. We generated whole-genome sequencing data from 65 historical rock doves that represent all currently recognized subspecies and span the species’ original geographic distribution. Our dataset includes 3 specimens from Darwin’s collection, and the type specimens of 5 different taxa. We characterized their population structure, genomic diversity, and gene-flow patterns. Our results show the West African subspecies C. l. gymnocyclus is basal to rock doves and domestic pigeons, and suggests gene-flow between the rock dove’s sister species C. rupestris, and the ancestor of rock doves after its split from West African populations. These genomes allowed us to propose a model for the evolution of the rock dove in light of the refugia theory. We propose that 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 1 domestication event in the Levant 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.

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1-8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000-30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located.

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000–30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located.

Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.

Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.

Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants have been introduced to regions outside their native ranges both intentionally and accidentally by European voyagers and early colonists making transoceanic journeys; however, records are scarce to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to investigate how patterns of genomic diversity are distributed among populations of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique genotype groups showing very little sign of admixture and low degree of outcrossing among them. We show that genotype groups are latitudinally restricted, and that more than one successful genotype colonized and spread into the introduced ranges. With the exception of New Zealand, only one genotype group is present in the Southern Hemisphere. Three of the most prevalent genotypes present in the native Eurasian range gave rise to introduced populations in the Americas, Africa, Australia, and New Zealand, which could lend support to the hypothesis that P. major was unknowlingly dispersed by early European colonists. Dispersal of multiple successful genotypes is a likely reason for success. Genomic signatures and phylogeographic methods can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species, contributing to our understanding of the role of genomic variation for successful establishment of introduced taxa.

The grey wolf (Canis lupus) was the first species to give rise to a domestic population, and they remained widespread throughout the last Ice Age when many other large mammal species went extinct. Little is known, however, about the history and possible extinction of past wolf populations or when and where the wolf progenitors of the present-day dog lineage (Canis familiaris) lived1-8. Here we analysed 72 ancient wolf genomes spanning the last 100,000 years from Europe, Siberia and North America. We found that wolf populations were highly connected throughout the Late Pleistocene, with levels of differentiation an order of magnitude lower than they are today. This population connectivity allowed us to detect natural selection across the time series, including rapid fixation of mutations in the gene IFT88 40,000-30,000 years ago. We show that dogs are overall more closely related to ancient wolves from eastern Eurasia than to those from western Eurasia, suggesting a domestication process in the east. However, we also found that dogs in the Near East and Africa derive up to half of their ancestry from a distinct population related to modern southwest Eurasian wolves, reflecting either an independent domestication process or admixture from local wolves. None of the analysed ancient wolf genomes is a direct match for either of these dog ancestries, meaning that the exact progenitor populations remain to be located.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

We investigate the global frequency selection of two-dimensional vortex shedding in the flat plate wake. The analysis is based on the mean-flow velocity profiles obtained from experimental measurements carried out for two values of Reynolds number, 1850 and 3350, which are based on the plate thickness and the free-stream velocity. Two different trailing edge geometries of the flat plate are considered in this study: blunt and circular. By performing local spatiotemporal analyses on the measured mean-flow velocity profiles, we estimate the global shedding frequency of the flow. This is in excellent agreement with the shedding frequency measured experimentally. To complement the study, we carry out a low-dimensional modeling based on the proper orthogonal decomposition (POD) of the flow fields which is novel for flat plate wakes. We observe that a model based on only two POD modes produces an accurate estimate of the global shedding frequency. Our results also highlight the role of the interaction strength between the mean flow and the higher harmonics thereby experimentally supporting the theoretical criterion outlined in Sipp and Lebedev [J. Fluid Mech. 593, 333 (2007)10.1017/S0022112007008907]., SCOPUS: ar.j, DecretOANoAutActif, info:eu-repo/semantics/published

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.

Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial 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 depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype’s typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools’ robustness to lower DOC 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 HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA’s typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype’s typing accuracy is not notably impaired by short read length or by DNA damage, which is typi, Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial 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 depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype's typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools' robustness to lower DOC 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 HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA's typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype's typing accuracy is not notably impaired by short read length or by DNA damage, which is t

Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial 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 depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype’s typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools’ robustness to lower DOC 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 HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA’s typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype’s typing accuracy is not notably impaired by short read length or by DNA damage, which is typi, Identifying the specific human leukocyte antigen (HLA) allele combination of an individual is crucial 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 depth of coverage (DOC) was evaluated by subsampling and HLA typing 230 WES samples at DOC ranging from 1X to 100X. The HLA typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions (P group and pseudo-sequence), which specifically focus on the peptide binding region. On average, across the five HLA loci examined, HLA*LA was found to have the highest typing accuracy. For the individual loci, HLA-A, -B and -C, Optitype's typing accuracy was the highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools' robustness to lower DOC 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 HLA molecule) at 50X, but increasing the DOC beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA loci as well as HLA*LA's typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which is often based on sequencing data with lower quality and DOC. Interestingly, we found that Optitype's typing accuracy is not notably impaired by short read length or by DNA damage, which is t