Toward 3D facial analysis for recognizing Mendelian causes of autism spectrum disorder.

Recognizing Mendelian causes is crucial in molecular diagnostics and counseling for patients with autism spectrum disorder (ASD). We explored facial dysmorphism and facial asymmetry in relation to genetic causes in ASD patients and studied the potential of objective facial phenotyping in discriminating between Mendelian and multifactorial ASD. In a cohort of 152 ASD patients, 3D facial images were used to calculate three metrics: a computational dysmorphism score, a computational asymmetry score, and an expert dysmorphism score. High scores for each of the three metrics were associated with Mendelian causes of ASD. The computational dysmorphism score showed a significant correlation with the average expert dysmorphism score. However, in some patients, different dysmorphism aspects were captured making the metrics potentially complementary. The computational dysmorphism and asymmetry scores both enhanced the individual expert dysmorphism scores in differentiating Mendelian from non-Mendelian cases. Furthermore, the computational asymmetry score enhanced the average expert opinion in predicting a Mendelian cause. By design, our study does not allow to draw conclusions on the actual point-of-care use of 3D facial analysis. Nevertheless, 3D morphometric analysis is promising for developing clinical dysmorphology applications in diagnostics and training.

Capturing the fusion of two ancestries and kinship structures in Merovingian Flanders.

The Merovingian period (5th to 8th cc AD) was a time of demographic, socioeconomic, cultural, and political realignment in Western Europe. Here, we report the whole-genome shotgun sequence data of 30 human skeletal remains from a coastal Late Merovingian site of Koksijde (675 to 750 AD), alongside 18 remains from two Early to Late Medieval sites in present-day Flanders, Belgium. We find two distinct ancestries, one shared with Early Medieval England and the Netherlands, while the other, minor component, reflecting likely continental Gaulish ancestry. Kinship analyses identified no large pedigrees characteristic to elite burials revealing instead a high modularity of distant relationships among individuals of the main ancestry group. In contrast, individuals with >90% Gaulish ancestry had no kinship links among sampled individuals. Evidence for population structure and major differences in the extent of Gaulish ancestry in the main group, including in a mother-daughter pair, suggests ongoing admixture in the community at the time of their burial. The isotopic and genetic evidence combined supports a model by which the burials, representing an established coastal nonelite community, had incorporated migrants from inland populations. The main group of burials at Koksijde shows an abundance of >5 cM long shared allelic intervals with the High Medieval site nearby, implying long-term continuity and suggesting that similarly to Britain, the Early Medieval ancestry shifts left a significant and long-lasting impact on the genetic makeup of the Flemish population. We find substantial allele frequency differences between the two ancestry groups in pigmentation and diet-associated variants, including those linked with lactase persistence, likely reflecting ancestry change rather than local adaptation.

MEMOR: A database of archeological human remains collections from Flanders, Belgium.

The aim of this article is to describe a newly created open access database of archeological human remains collections from Flanders, Belgium. The MEMOR database (www.memor.be) was created to provide an overview of the current practices of loans, reburial, and the research potential of human skeletons from archeological sites currently stored in Flanders. In addition, the project aimed to provide a legal and ethical framework for the handling of human remains and was created around stakeholder involvement from anthropologists, geneticists, contract archeologists, the local, regional and national government agencies, local and national government, universities, and representatives of the major religions. The project has resulted in the creation of a rich database with many collections available for study. The database was created using the open-source Arches data management platform that is freely available for organizations worldwide to configure in accordance with their individual needs and without restrictions on its use. Each collection is linked to information about the excavation and the site the remains originate from, its size and time period. In addition, a research potential tab reveals whether any analyses were performed, and whether excavation notes are available with the assemblage. The database currently contains 742 collections, ranging in size from 1 to over 1000 individuals. New collections will continue to be added when new assemblages are excavated and studied. The database can also be expanded to include human remains collections from other regions and other material categories, such as archaeozoological collections.

Whole Slide Imaging-Based Prediction of TP53 Mutations Identifies an Aggressive Disease Phenotype in Prostate Cancer.

In prostate cancer, there is an urgent need for objective prognostic biomarkers that identify the metastatic potential of a tumor at an early stage. While recent analyses indicated TP53 mutations as candidate biomarkers, molecular profiling in a clinical setting is complicated by tumor heterogeneity. Deep learning models that predict the spatial presence of TP53 mutations in whole slide images (WSI) offer the potential to mitigate this issue. To assess the potential of WSIs as proxies for spatially resolved profiling and as biomarkers for aggressive disease, we developed TiDo, a deep learning model that achieves state-of-the-art performance in predicting TP53 mutations from WSIs of primary prostate tumors. In an independent multifocal cohort, the model showed successful generalization at both the patient and lesion level. Analysis of model predictions revealed that false positive (FP) predictions could at least partially be explained by TP53 deletions, suggesting that some FP carry an alteration that leads to the same histological phenotype as TP53 mutations. Comparative expression and histologic cell type analyses identified a TP53-like cellular phenotype triggered by expression of pathways affecting stromal composition. Together, these findings indicate that WSI-based models might not be able to perfectly predict the spatial presence of individual TP53 mutations but they have the potential to elucidate the prognosis of a tumor by depicting a downstream phenotype associated with aggressive disease biomarkers. SIGNIFICANCE: Deep learning models predicting TP53 mutations from whole slide images of prostate cancer capture histologic phenotypes associated with stromal composition, lymph node metastasis, and biochemical recurrence, indicating their potential as in silico prognostic biomarkers. See related commentary by Bordeleau, p. 2809.

Genomic analyses of hair from Ludwig van Beethoven.

Ludwig van Beethoven (1770-1827) remains among the most influential and popular classical music composers. Health problems significantly impacted his career as a composer and pianist, including progressive hearing loss, recurring gastrointestinal complaints, and liver disease. In 1802, Beethoven requested that following his death, his disease be described and made public. Medical biographers have since proposed numerous hypotheses, including many substantially heritable conditions. Here we attempt a genomic analysis of Beethoven in order to elucidate potential underlying genetic and infectious causes of his illnesses. We incorporated improvements in ancient DNA methods into existing protocols for ancient hair samples, enabling the sequencing of high-coverage genomes from small quantities of historical hair. We analyzed eight independently sourced locks of hair attributed to Beethoven, five of which originated from a single European male. We deemed these matching samples to be almost certainly authentic and sequenced Beethoven's genome to 24-fold genomic coverage. Although we could not identify a genetic explanation for Beethoven's hearing disorder or gastrointestinal problems, we found that Beethoven had a genetic predisposition for liver disease. Metagenomic analyses revealed furthermore that Beethoven had a hepatitis B infection during at least the months prior to his death. Together with the genetic predisposition and his broadly accepted alcohol consumption, these present plausible explanations for Beethoven's severe liver disease, which culminated in his death. Unexpectedly, an analysis of Y chromosomes sequenced from five living members of the Van Beethoven patrilineage revealed the occurrence of an extra-pair paternity event in Ludwig van Beethoven's patrilineal ancestry.

Large-scale pedigree analysis highlights rapidly mutating Y-chromosomal short tandem repeats for differentiating patrilineal relatives and predicting their degrees of consanguinity.

Rapidly mutating Y-chromosomal short tandem repeats (RM Y-STRs) were suggested for differentiating patrilineally related men as relevant in forensic genetics, anthropological genetics, and genetic genealogy. Empirical data are available for closely related males, while differentiation rates for more distant relatives are scarce. Available RM Y-STR mutation rate estimates are typically based on father-son pair data, while pedigree-based studies for efficient analysis requiring less samples are rare. Here, we present a large-scale pedigree analysis in 9379 pairs of men separated by 1-34 meioses on 30 Y-STRs with increased mutation rates including all known RM Y-STRs (RMplex). For comparison, part of the samples were genotyped at 25 standard Y-STRs mostly with moderate mutation rates (Yfiler Plus). For 43 of the 49 Y-STRs analyzed, pedigree-based mutation rates were similar to previous father-son based estimates, while for six markers significant differences were observed. Male relative differentiation rates from the 30 RMplex Y-STRs were 43%, 84%, 96%, 99%, and 100% for relatives separated by one, four, six, nine, and twelve meioses, respectively, which largely exceeded rates obtained by 25 standard Y-STRs. Machine learning based models for predicting the degree of patrilineal consanguinity yielded accurate and reasonably precise predictions when using RM Y-STRs. Fully matching haplotypes resulted in a 95% confidence interval of 1-6 meioses with RMplex compared to 1-25 with Yfiler Plus. Our comprehensive pedigree study demonstrates the value of RM Y-STRs for differentiating male relatives of various types, in many cases achieving individual identification, thereby overcoming the largest limitation of forensic Y-chromosome analysis.

From collected stamps to hair locks: ethical and legal implications of testing DNA found on privately owned family artifacts.

Biological samples containing DNA that is attributed to deceased relatives, can now undergo genetic testing at a reasonable cost due to revolutionary improvements in sampling, sequencing, and analytical techniques. This artifact DNA testing, or 'artDNA', includes genetic analysis of hair locks, stamps, envelopes with saliva traces or teeth. ArtDNA can reveal valuable information about a deceased relative or one's genetic background, but it also presents novel ethical dilemmas and legal uncertainties for genetic researchers and commercial testing services. In this paper, we provide an analysis of some of the unique ethical and legal risks of such testing and provide needed recommendations for practitioners of private family artDNA testing. ArtDNA testing generates ethical and legal risks regarding the privacy and autonomy of deceased individuals, the rights of living relatives over their ancestor's genetic information, and the rights of living persons to control their own genetic information. To mitigate these risks, practitioners can conduct certain preliminary testing to ascertain the identity of a DNA donor and estimate the time that has elapsed postmortem. Generally, the ethical and legal concerns will be higher when a shorter period has passed between the death of the DNA donor and the time of artifact DNA testing. Regardless, all artDNA testing present some risks, and practitioners should exercise professional judgement as necessary.

Y-chromosome target enrichment reveals rapid expansion of haplogroup R1b-DF27 in Iberia during the Bronze Age transition.

The Y chromosome can yield a unique perspective into the study of human demographic history. However, due to the repetitive nature of part of its sequence, only a small set of regions are suitable for variant calling and discovery from short-read sequencing data. These regions combined represent 8.9 Mbp or 0.14% of a diploid human genome. Consequently, investing in whole-genome sequencing to resolve Y-chromosome questions is poorly efficient. Here we use, as an alternative, target enrichment technology to greatly increase sequencing effectiveness, validating and applying the technique to 181 males, for 162 of whom we obtained a positive result. Additionally, 75 samples sequenced for the whole genome were also included, for a total sample size of 237. These samples were chosen for their Y chromosome haplogroup: R1b-DF27. In the context of European populations, and particularly in Iberia, this haplogroup stands out for its high frequency and its demographic history. Current evidence indicates that the diffusion of this haplogroup is related to the population movements that mark the cultural Bronze Age transition, making it remarkably interesting for population geneticists. The results of this study show the effects of the rapid radiation of the haplogroup in Spain, as even with the higher discriminating power of whole sequences, most haplotypes still fall within the R1b-DF27* paragroup rather than in the main derived branches. However, we were able to refine the ISOGG 2019-2020 phylogeny, and its two main subbranches, namely L176.2 and Z272, which present geographical differentiation between the Atlantic and Mediterranean coasts of Iberia.

Extracting functional insights from loss-of-function screens using deep link prediction.

We present deep link prediction (DLP), a method for the interpretation of loss-of-function screens. Our approach uses representation-based link prediction to reprioritize phenotypic readouts by integrating screening experiments with gene-gene interaction networks. We validate on 2 different loss-of-function technologies, RNAi and CRISPR, using datasets obtained from DepMap. Extensive benchmarking shows that DLP-DeepWalk outperforms other methods in recovering cell-specific dependencies, achieving an average precision well above 90% across 7 different cancer types and on both RNAi and CRISPR data. We show that the genes ranked highest by DLP-DeepWalk are appreciably more enriched in drug targets compared to the ranking based on original screening scores. Interestingly, this enrichment is more pronounced on RNAi data compared to CRISPR data, consistent with the greater inherent noise of RNAi screens. Finally, we demonstrate how DLP-DeepWalk can infer the molecular mechanism through which putative targets trigger cell line mortality.

Halvade somatic: Somatic variant calling with Apache Spark.

BACKGROUND: The accurate detection of somatic variants from sequencing data is of key importance for cancer treatment and research. Somatic variant calling requires a high sequencing depth of the tumor sample, especially when the detection of low-frequency variants is also desired. In turn, this leads to large volumes of raw sequencing data to process and hence, large computational requirements. For example, calling the somatic variants according to the GATK best practices guidelines requires days of computing time for a typical whole-genome sequencing sample. FINDINGS: We introduce Halvade Somatic, a framework for somatic variant calling from DNA sequencing data that takes advantage of multi-node and/or multi-core compute platforms to reduce runtime. It relies on Apache Spark to provide scalable I/O and to create and manage data streams that are processed on different CPU cores in parallel. Halvade Somatic contains all required steps to process the tumor and matched normal sample according to the GATK best practices recommendations: read alignment (BWA), sorting of reads, preprocessing steps such as marking duplicate reads and base quality score recalibration (GATK), and, finally, calling the somatic variants (Mutect2). Our approach reduces the runtime on a single 36-core node to 19.5 h compared to a runtime of 84.5 h for the original pipeline, a speedup of 4.3 times. Runtime can be further decreased by scaling to multiple nodes, e.g., we observe a runtime of 1.36 h using 16 nodes, an additional speedup of 14.4 times. Halvade Somatic supports variant calling from both whole-genome sequencing and whole-exome sequencing data and also supports Strelka2 as an alternative or complementary variant calling tool. We provide a Docker image to facilitate single-node deployment. Halvade Somatic can be executed on a variety of compute platforms, including Amazon EC2 and Google Cloud. CONCLUSIONS: To our knowledge, Halvade Somatic is the first somatic variant calling pipeline that leverages Big Data processing platforms and provides reliable, scalable performance. Source code is freely available.

Network-Based Analysis to Identify Drivers of Metastatic Prostate Cancer Using GoNetic.

Most known driver genes of metastatic prostate cancer are frequently mutated. To dig into the long tail of rarely mutated drivers, we performed network-based driver identification on the Hartwig Medical Foundation metastatic prostate cancer data set (HMF cohort). Hereto, we developed GoNetic, a method based on probabilistic pathfinding, to identify recurrently mutated subnetworks. In contrast to most state-of-the-art network-based methods, GoNetic can leverage sample-specific mutational information and the weights of the underlying prior network. When applied to the HMF cohort, GoNetic successfully recovered known primary and metastatic drivers of prostate cancer that are frequently mutated in the HMF cohort (TP53, RB1, and CTNNB1). In addition, the identified subnetworks contain frequently mutated genes, reflect processes related to metastatic prostate cancer, and contain rarely mutated driver candidates. To further validate these rarely mutated genes, we assessed whether the identified genes were more mutated in metastatic than in primary samples using an independent cohort. Then we evaluated their association with tumor evolution and with the lymph node status of the patients. This resulted in forwarding several novel putative driver genes for metastatic prostate cancer, some of which might be prognostic for disease evolution.

CSYseq: The first Y-chromosome sequencing tool typing a large number of Y-SNPs and Y-STRs to unravel worldwide human population genetics.

Male-specific Y-chromosome (chrY) polymorphisms are interesting components of the DNA for population genetics. While single nucleotide polymorphisms (Y-SNPs) indicate distant evolutionary ancestry, short tandem repeats (Y-STRs) are able to identify close familial kinships. Detailed chrY analysis provides thus both biogeographical background information as paternal lineage identification. The rapid advancement of high-throughput massive parallel sequencing (MPS) technology in the past decade has revolutionized genetic research. Using MPS, single-base information of both Y-SNPs as Y-STRs can be analyzed in a single assay typing multiple samples at once. In this study, we present the first extensive chrY-specific targeted resequencing panel, the 'CSYseq', which simultaneously identifies slow mutating Y-SNPs as evolution markers and rapid mutating Y-STRs as patrilineage markers. The panel was validated by paired-end sequencing of 130 males, distributed over 65 deep-rooted pedigrees covering 1,279 generations. The CSYseq successfully targets 15,611 Y-SNPs including 9,014 phylogenetic informative Y-SNPs to identify 1,443 human evolutionary Y-subhaplogroup lineages worldwide. In addition, the CSYseq properly targets 202 Y-STRs, including 81 slow, 68 moderate, 27 fast and 26 rapid mutating Y-STRs to individualize close paternal relatives. The targeted chrY markers cover a high average number of reads (Y-SNP = 717, Y-STR = 150), easy interpretation, powerful discrimination capacity and chrY specificity. The CSYseq is interesting for research on different time scales: to identify evolutionary ancestry, to find distant family and to discriminate closely related males. Therefore, this panel serves as a unique tool valuable for a wide range of genetic-genealogical applications in interdisciplinary research within evolutionary, population, molecular, medical and forensic genetics.

3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies.

The analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.

Subdividing Y-chromosome haplogroup R1a1 reveals Norse Viking dispersal lineages in Britain.

The influence of Viking-Age migrants to the British Isles is obvious in archaeological and place-names evidence, but their demographic impact has been unclear. Autosomal genetic analyses support Norse Viking contributions to parts of Britain, but show no signal corresponding to the Danelaw, the region under Scandinavian administrative control from the ninth to eleventh centuries. Y-chromosome haplogroup R1a1 has been considered as a possible marker for Viking migrations because of its high frequency in peninsular Scandinavia (Norway and Sweden). Here we select ten Y-SNPs to discriminate informatively among hg R1a1 sub-haplogroups in Europe, analyse these in 619 hg R1a1 Y chromosomes including 163 from the British Isles, and also type 23 short-tandem repeats (Y-STRs) to assess internal diversity. We find three specifically Western-European sub-haplogroups, two of which predominate in Norway and Sweden, and are also found in Britain; star-like features in the STR networks of these lineages indicate histories of expansion. We ask whether geographical distributions of hg R1a1 overall, and of the two sub-lineages in particular, correlate with regions of Scandinavian influence within Britain. Neither shows any frequency difference between regions that have higher (≥10%) or lower autosomal contributions from Norway and Sweden, but both are significantly overrepresented in the region corresponding to the Danelaw. These differences between autosomal and Y-chromosomal histories suggest either male-specific contribution, or the influence of patrilocality. Comparison of modern DNA with recently available ancient DNA data supports the interpretation that two sub-lineages of hg R1a1 spread with the Vikings from peninsular Scandinavia.

Comparative analysis of somatic variant calling on matched FF and FFPE WGS samples.

BACKGROUND: Research grade Fresh Frozen (FF) DNA material is not yet routinely collected in clinical practice. Many hospitals, however, collect and store Formalin Fixed Paraffin Embedded (FFPE) tumor samples. Consequently, the sample size of whole genome cancer cohort studies could be increased tremendously by including FFPE samples, although the presence of artefacts might obfuscate the variant calling. To assess whether FFPE material can be used for cohort studies, we performed an in-depth comparison of somatic SNVs called on matching FF and FFPE Whole Genome Sequence (WGS) samples extracted from the same tumor. METHODS: Four variant callers (i.e. Strelka2, Mutect2, VarScan2 and Shimmer) were used to call somatic variants on matching FF and FFPE WGS samples from a metastatic prostate tumor. Using the variants identified by these callers, we developed a heuristic to maximize the overlap between the FF and its FFPE counterpart in terms of sensitivity and precision. The proposed variant calling approach was then validated on nine matched primary samples. Finally, we assessed what fraction of the discrepancy could be attributed to intra-tumor heterogeneity (ITH), by comparing the overlap in clonal and subclonal somatic variants. RESULTS: We first compared variants between an FF and an FFPE sample from a metastatic prostate tumor, showing that on average 50% of the calls in the FF are recovered in the FFPE sample, with notable differences between callers. Combining the variants of the different callers using a simple heuristic, increases both the precision and the sensitivity of the variant calling. Validating the heuristic on nine additional matched FF-FFPE samples, resulted in an average F1-score of 0.58 and an outperformance of any of the individual callers. In addition, we could show that part of the discrepancy between the FF and the FFPE samples can be attributed to ITH. CONCLUSION: This study illustrates that when using the correct variant calling strategy, the majority of clonal SNVs can be recovered in an FFPE sample with high precision and sensitivity. These results suggest that somatic variants derived from WGS of FFPE material can be used in cohort studies.

Identification and characterization of novel rapidly mutating Y-chromosomal short tandem repeat markers.

Short tandem repeat polymorphisms on the male-specific part of the human Y-chromosome (Y-STRs) are valuable tools in many areas of human genetics. Although their paternal inheritance and moderate mutation rate (~10-3 mutations per marker per meiosis) allow detecting paternal relationships, they typically fail to separate male relatives. Previously, we identified 13 Y-STR markers with untypically high mutation rates (>10-2 ), termed rapidly mutating (RM) Y-STRs, and showed that they improved male relative differentiation over standard Y-STRs. By applying a newly developed in silico search approach to the Y-chromosome reference sequence, we identified 27 novel RM Y-STR candidates. Genotyping them in 1,616 DNA-confirmed father-son pairs for mutation rate estimation empirically highlighted 12 novel RM Y-STRs. Their capacity to differentiate males related by 1, 2, and 3 meioses was 27%, 47%, and 61%, respectively, while for all 25 currently known RM Y-STRs, it was 44%, 69%, and 83%. Of the 647 Y-STR mutations observed in total, almost all were single repeat changes, repeat gains, and losses were well balanced; allele length and fathers' age were positively correlated with mutation rate. We expect these new RM Y-STRs, together with the previously known ones, to significantly improving male relative differentiation in future human genetic applications.

Review of policies of companies and databases regarding access to customers' genealogy data for law enforcement purposes.

The rapidly evolving popularity of direct-to-consumer genetic genealogy companies has made it possible to retrieve genomic information for unintended reasons by third parties, including the emerging use for law enforcement purposes. The question remains whether users of direct-to-consumer genetic genealogy companies and genealogical databases are aware that their genetic and/or genealogical data could be used as means to solving forensic cases. Our review of 22 companies' and databases' policies showed that only four companies have provided additional information on how law enforcement agencies should request permission to use their services for law enforcement purposes. Moreover, two databases have adopted a different approach by providing a special service for law enforcement. Although all companies and databases included in the study provide at least some provisions about police access, there is an ongoing debate over the ethics of these practices, and how to balance users' privacy with law enforcement requests.

The Dutch Y-chromosomal landscape.

Previous studies indicated existing, albeit limited, genetic-geographic population substructure in the Dutch population based on genome-wide data and a lack of this for mitochondrial SNP based data. Despite the aforementioned studies, Y-chromosomal SNP data from the Netherlands remain scarce and do not cover the territory of the Netherlands well enough to allow a reliable investigation of genetic-geographic population substructure. Here we provide the first substantial dataset of detailed spatial Y-chromosomal haplogroup information in 2085 males collected across the Netherlands and supplemented with previously published data from northern Belgium. We found Y-chromosomal evidence for genetic-geographic population substructure, and several Y-haplogroups demonstrating significant clinal frequency distributions in different directions. By means of prediction surface maps we could visualize (complex) distribution patterns of individual Y-haplogroups in detail. These results highlight the value of a micro-geographic approach and are of great use for forensic and epidemiological investigations and our understanding of the Dutch population history. Moreover, the previously noted absence of genetic-geographic population substructure in the Netherlands based on mitochondrial DNA in contrast to our Y-chromosome results, hints at different population histories for women and men in the Netherlands.

Correction to: The Dutch Y-chromosomal landscape.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.