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Societies with exposure to preindustrial diets exhibit improved markers of health. Our study used a comprehensive multi-omic approach to reveal that the gut microbiome of the Ju/'hoansi hunter-gatherers, one of the most remote KhoeSan groups, exhibit a higher diversity and richness, with an abundance of microbial species lost in the western population. The Ju/'hoansi microbiome showed enhanced global transcription and enrichment of complex carbohydrate metabolic and energy generation pathways. The Ju/'hoansi also show high abundance of short-chain fatty acids that are associated with health and optimal immune function. In contrast, these pathways and their respective species were found in low abundance or completely absent in Western populations. Amino acid and fatty acid metabolism pathways were observed prevalent in the Western population, associated with biomarkers of chronic inflammation. Our study provides the first in-depth multi-omic characterization of the Ju/'hoansi microbiome, revealing uncharacterized species and functional pathways that are associated with health., Competing Interests: Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Background: Prostate cancer (PCa) is a significant health burden for African men, with mortality rates more than double global averages. The prostate specific Anoctamin 7 (ANO7) gene linked with poor patient outcomes has recently been identified as the target for an African-specific protein-truncating PCa-risk allele., Methods: Here we determined the role of ANO7 in a study of 889 men from southern Africa, leveraging exomic genotyping array PCa case-control data (n = 780, 17 ANO7 alleles) and deep sequenced whole genome data for germline and tumour ANO7 interrogation (n = 109), while providing clinicopathologically matched European-derived sequence data comparative analyses (n = 57). Associated predicted deleterious variants (PDVs) were further assessed for impact using computational protein structure analysis., Results: Notably rare in European patients, we found the common African PDV p.Ile740Leu (rs74804606) to be associated with PCa risk in our case-control analysis (Wilcoxon rank-sum test, false discovery rate/FDR = 0.03), while sequencing revealed co-occurrence with the recently reported African-specific deleterious risk variant p.Ser914* (rs60985508). Additional findings included a novel protein-truncating African-specific frameshift variant p.Asp789Leu, African-relevant PDVs associated with altered protein structure at Ca 2+ binding sites, early-onset PCa associated with PDVs and germline structural variants in Africans (Linear regression models, -6.42 years, 95% CI = -10.68 to -2.16, P-value = 0.003) and ANO7 as an inter-chromosomal PCa-related gene fusion partner in African derived tumours., Conclusions: Here we provide not only validation for ANO7 as an African-relevant protein-altering PCa-risk locus, but additional evidence for a role of inherited and acquired ANO7 variance in the observed phenotypic heterogeneity and African-ancestral health disparity., (© 2023. Crown.)

Population history-focused DNA and ancient DNA (aDNA) research in Africa has dramatically increased in the past decade, enabling increasingly fine-scale investigations into the continent's past. However, while international interest in human genomics research in Africa grows, major structural barriers limit the ability of African scholars to lead and engage in such research and impede local communities from partnering with researchers and benefitting from research outcomes. Because conversations about research on African people and their past are often held outside Africa and exclude African voices, an important step for African DNA and aDNA research is moving these conversations to the continent. In May 2023 we held the DNAirobi workshop in Nairobi, Kenya and here we synthesize what emerged most prominently in our discussions. We propose an ideal vision for population history-focused DNA and aDNA research in Africa in ten years' time and acknowledge that to realize this future, we need to chart a path connecting a series of "landmarks" that represent points of consensus in our discussions. These include effective communication across multiple audiences, reframed relationships and capacity building, and action toward structural changes that support science and beyond. We concluded there is no single path to creating an equitable and self-sustaining research ecosystem, but rather many possible routes linking these landmarks. Here we share our diverse perspectives as geneticists, anthropologists, archaeologists, museum curators, and educators to articulate challenges and opportunities for African DNA and aDNA research and share an initial map toward a more inclusive and equitable future., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The telomere repetitive TTAGGG motif at the ends of chromosomes, serves to preserve genomic integrity and chromosomal stability. In turn, genomic instability is a hallmark of cancer-implicating telomere disturbance. Prostate cancer (PCa) shows significant ancestral disparities, with men of African ancestry at the greatest risk for aggressive disease and associated genomic instability. Yet, no study has explored the role of telomere length (TL) with respect to ancestrally driven PCa health disparities. Patient- and technically-matched tumour-blood whole genome sequencing data for 179 ancestrally defined treatment naïve PCa patients (117 African, 62 European), we assessed for TL (blood and tumour) associations. We found shortened tumour TL to be associated with aggressive PCa presentation and elevated genomic instabilities, including percentage of genome alteration and copy number gains, in men of African ancestry. For European patients, tumour TL showed significant associations with PCa driver genes PTEN, TP53, MSH2, SETBP1 and DDX11L1, while shorter blood TL (< 3200 base pairs) and tumour TL (< 2861 base pairs) were correlated with higher risk for biochemical recurrence. Concurring with previous studies linking TL to PCa diagnosis and/or prognosis, for the first time we correlated TL differences with patient ancestry with important implications for future treatments targeting telomere dysfunction., (© 2024. The Author(s).)

African ancestry is a significant risk factor for prostate cancer and advanced disease. Yet, genetic studies have largely been conducted outside the context of Sub-Saharan Africa, identifying 278 common risk variants contributing to a multiethnic polygenic risk score, with rare variants focused on a panel of roughly 20 pathogenic genes. Based on this knowledge, we are unable to determine polygenic risk or differentiate prostate cancer status interrogating whole genome data for 113 Black South African men. To further assess for potentially functional common and rare variant associations, here we interrogate 247,780 exomic variants for 798 Black South African men using a case versus control or aggressive versus non-aggressive study design. Notable genes of interest include HCP5, RFX6 and H3C1 for risk, and MKI67 and KLF5 for aggressive disease. Our study highlights the need for further inclusion across the African diaspora to establish African-relevant risk models aimed at reducing prostate cancer health disparities., (© 2023. The Author(s).)

Prostate cancer (PCa) is a significant health burden in Sub-Saharan Africa, with mortality rates loosely linked to African ancestry. Yet studies aimed at identifying contributing risk factors are lacking within the continent and as such exclude for significant ancestral diversity. Here, we investigate a series of epidemiological demographic and lifestyle risk factors for 1387 men recruited as part of the multi-ethnic Southern African Prostate Cancer Study (SAPCS). We found poverty to be a decisive factor for disease grade and age at diagnosis, with other notably significant PCa associated risk factors including sexually transmitted diseases, erectile dysfunction, gynaecomastia, and vertex or complete pattern balding. Aligned with African American data, Black ethnicity showed significant risk for PCa diagnosis (OR = 1.44, 95% CI 1.05-2.00), and aggressive disease presentation (ISUP ≥ 4: OR = 2.25, 95% CI   1.49-3.40). New to this study, we demonstrate African ancestral population substructure associated PCa disparity, observing increased risk for advanced disease for the southern African Tsonga people (ISUP ≥ 4: OR = 3.43, 95% CI   1.62-7.27). Conversely, South African Coloured were less likely to be diagnosed with aggressive disease overall (ISUP ≥ 3: OR = 0.38, 95% 0.17-0.85). Understanding the basis for PCa health disparities calls for African inclusion, however, lack of available data has limited the power to begin discussions. Here, focusing on arguably the largest study of its kind for the African continent, we draw attention to the contribution of within African ancestral diversity as a contributing factor to PCa health disparities within the genetically diverse region of southern Africa., (© 2023. The Author(s).)

Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry as a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Investigating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found that African-derived tumors present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63), including several putative therapeutic targets ( CHD7 , DPF3 , POLR1B , SETD1B , UBTF , and VPS72 ). Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified the top genes in African- and European-derived tumors representing a multifunctional "generic machinery", the alteration of which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis, but African-derived tumors appear to achieve this state with greater diversity among such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African-tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.

Background: Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the identification of various malignancies. Initially, a series of preprocessing steps and image segmentation steps are performed to extract region of interest features from noisy features. Then, the extracted features are applied to several machine learning and deep learning methods for the detection of cancer., Methods: In this work, a review of all the methods that have been applied to develop machine learning algorithms that detect cancer is provided. With more than 100 types of cancer, this study only examines research on the four most common and prevalent cancers worldwide: lung, breast, prostate, and colorectal cancer. Next, by using state-of-the-art sentence transformers namely: SBERT (2019) and the unsupervised SimCSE (2021), this study proposes a new methodology for detecting cancer. This method requires raw DNA sequences of matched tumor/normal pair as the only input. The learnt DNA representations retrieved from SBERT and SimCSE will then be sent to machine learning algorithms (XGBoost, Random Forest, LightGBM, and CNNs) for classification. As far as we are aware, SBERT and SimCSE transformers have not been applied to represent DNA sequences in cancer detection settings., Results: The XGBoost model, which had the highest overall accuracy of 73 ± 0.13 % using SBERT embeddings and 75 ± 0.12 % using SimCSE embeddings, was the best performing classifier. In light of these findings, it can be concluded that incorporating sentence representations from SimCSE's sentence transformer only marginally improved the performance of machine learning models., (© 2023. The Author(s).)

Background: Germline testing for prostate cancer is on the increase, with clinical implications for risk assessment, treatment, and management. Regardless of family history, NCCN recommends germline testing for patients with metastatic, regional, very-high-risk localized, and high-risk localized prostate cancer. Although African ancestry is a significant risk factor for aggressive prostate cancer, due to a lack of available data no testing criteria have been established for ethnic minorities., Patients and Methods: Through deep sequencing, we interrogated the 20 most common germline testing panel genes in 113 Black South African males presenting with largely advanced prostate cancer. Bioinformatic tools were then used to identify the pathogenicity of the variants., Results: After we identified 39 predicted deleterious variants (16 genes), further computational annotation classified 17 variants as potentially oncogenic (12 genes; 17.7% of patients). Rare pathogenic variants included CHEK2 Arg95Ter, BRCA2 Trp31Arg, ATM Arg3047Ter (2 patients), and TP53 Arg282Trp. Notable oncogenic variants of unknown pathogenicity included novel BRCA2 Leu3038Ile in a patient with early-onset disease, whereas patients with FANCA Arg504Cys and RAD51C Arg260Gln reported a family history of prostate cancer. Overall, rare pathogenic and early-onset or familial-associated oncogenic variants were identified in 6.9% (5/72) and 9.2% (8/87) of patients presenting with a Gleason score ≥8 or ≥4 + 3 prostate cancer, respectively., Conclusions: In this first-of-its-kind study of southern African males, we provide support of African inclusion for advanced, early-onset, and familial prostate cancer genetic testing, indicating clinical value for 30% of current gene panels. Recognizing current panel limitations highlights an urgent need to establish testing guidelines for men of African ancestry. We provide a rationale for considering lowering the pathologic diagnostic inclusion criteria and call for further genome-wide interrogation to ensure the best possible African-relevant prostate cancer gene panel.

Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages 1 . The contributing genetic and non-genetic factors, and associated mutational processes, are unknown 2,3 . Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2, STK19, DDX11L1, PCAT1 and SETBP1. Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African-European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene-environment interaction-defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa-we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies., (© 2022. Crown.)

Background: African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation., Methods: Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa., Results: Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7, GTF3C2, NTNG1 and YPEL5. Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2, LSAMP, PTPRD, PDE4D and PACRG having therapeutic implications for African patients., Conclusions: In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry., (© 2022. The Author(s).)

Background: Germline variants explain more than a third of prostate cancer (PrCa) risk, but very few associations have been identified between heritable factors and clinical progression., Objective: To find rare germline variants that predict time to biochemical recurrence (BCR) after radical treatment in men with PrCa and understand the genetic factors associated with such progression., Design, Setting, and Participants: Whole-genome sequencing data from blood DNA were analysed for 850 PrCa patients with radical treatment from the Pan Prostate Cancer Group (PPCG) consortium from the UK, Canada, Germany, Australia, and France. Findings were validated using 383 patients from The Cancer Genome Atlas (TCGA) dataset., Outcome Measurements and Statistical Analysis: A total of 15,822 rare (MAF <1%) predicted-deleterious coding germline mutations were identified. Optimal multifactor and univariate Cox regression models were built to predict time to BCR after radical treatment, using germline variants grouped by functionally annotated gene sets. Models were tested for robustness using bootstrap resampling., Results and Limitations: Optimal Cox regression multifactor models showed that rare predicted-deleterious germline variants in "Hallmark" gene sets were consistently associated with altered time to BCR. Three gene sets had a statistically significant association with risk-elevated outcome when modelling all samples: PI3K/AKT/mTOR, Inflammatory response, and KRAS signalling (up). PI3K/AKT/mTOR and KRAS signalling (up) were also associated among patients with higher-grade cancer, as were Pancreas-beta cells, TNFA signalling via NKFB, and Hypoxia, the latter of which was validated in the independent TCGA dataset., Conclusions: We demonstrate for the first time that rare deleterious coding germline variants robustly associate with time to BCR after radical treatment, including cohort-independent validation. Our findings suggest that germline testing at diagnosis could aid clinical decisions by stratifying patients for differential clinical management., Patient Summary: Prostate cancer patients with particular genetic mutations have a higher chance of relapsing after initial radical treatment, potentially providing opportunities to identify patients who might need additional treatments earlier., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological pattern. However, this is not only laborious, but also relies on the experience of the pathologist and tends to suffer from the lack of reproducibility of biopsy outcomes across pathologists. As a result, computational approaches are being sought and machine learning has been gaining momentum in the prediction of the Gleason grade group. To date, machine learning literature has addressed this problem by using features from magnetic resonance imaging images, whole slide images, tissue microarrays, gene expression data, and clinical features. However, there is a gap with regards to predicting the Gleason grade group using DNA sequences as the only input source to the machine learning models. In this work, using whole genome sequence data from South African prostate cancer patients, an application of machine learning and biological experiments were combined to understand the challenges that are associated with the prediction of the Gleason grade group. A series of machine learning binary classifiers (XGBoost, LSTM, GRU, LR, RF) were created only relying on DNA sequences input features. All the models were not able to adequately discriminate between the DNA sequences of the studied Gleason grade groups (Gleason grade group 1 and 5). However, the models were further evaluated in the prediction of tumor DNA sequences from matched-normal DNA sequences, given DNA sequences as the only input source. In this new problem, the models performed acceptably better than before with the XGBoost model achieving the highest accuracy of 74 ± 01, F1 score of 79 ± 01, recall of 99 ± 0.0, and precision of 66 ± 0.1., Competing Interests: The authors have declared that no competing interests exist.

Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers., (© The Author(s) 2020. Published by Oxford University Press.)

Genomes of KhoeSan individuals of the Kalahari Desert provide the greatest understanding of single nucleotide diversity in the human genome. Compared with individuals in industrialized environments, the KhoeSan have a unique foraging and hunting lifestyle. Given these dramatic environmental differences, and the responsiveness of the methylome to environmental exposures of many types, we hypothesized that DNA methylation patterns would differ between KhoeSan and neighbouring agropastoral and/or industrial Bantu. We analysed Illumina HumanMethylation 450 k array data generated from blood samples from 38 KhoeSan and 42 Bantu, and 6 Europeans. After removing CpG positions associated with annotated and novel polymorphisms and controlling for white blood cell composition, sex, age and technical variation we identified 816 differentially methylated CpG loci, out of which 133 had an absolute beta-value difference of at least 0.05. Notably SLC39A4 / ZIP4 , which plays a role in zinc transport, was one of the most differentially methylated loci. Although the chronological ages of the KhoeSan are not formally recorded, we compared historically estimated ages to methylation-based calculations. This study demonstrates that the epigenetic profile of KhoeSan individuals reveals differences from other populations, and along with extensive genetic diversity, this community brings increased accessibility and understanding to the diversity of the human genome.

Somatic structural variants are an important contributor to cancer development and evolution. Accurate detection of these complex variants from whole genome sequencing data is influenced by a multitude of parameters. However, there are currently no tools for guiding study design nor are there applications that could predict the performance of somatic structural variant detection. To address this gap, we developed Shiny-SoSV, a user-friendly web-based calculator for determining the impact of common variables on the sensitivity, precision and F1 score of somatic structural variant detection, including choice of variant detection tool, sequencing depth of coverage, variant allele fraction, and variant breakpoint resolution. Using simulation studies, we determined singular and combinatoric effects of these variables, modelled the results using a generalised additive model, allowing structural variant detection performance to be predicted for any combination of predictors. Shiny-SoSV provides an interactive and visual platform for users to easily compare individual and combined impact of different parameters. It predicts the performance of a proposed study design, on somatic structural variant detection, prior to the commencement of benchwork. Shiny-SoSV is freely available at https://hcpcg.shinyapps.io/Shiny-SoSV with accompanying user's guide and example use-cases., Competing Interests: The authors have declared that no competing interests exist.

The latency associated with bone metastasis emergence in castrate-resistant prostate cancer is attributed to dormancy, a state in which cancer cells persist prior to overt lesion formation. Using single-cell transcriptomics and ex vivo profiling, we have uncovered the critical role of tumor-intrinsic immune signaling in the retention of cancer cell dormancy. We demonstrate that loss of tumor-intrinsic type I IFN occurs in proliferating prostate cancer cells in bone. This loss suppresses tumor immunogenicity and therapeutic response and promotes bone cell activation to drive cancer progression. Restoration of tumor-intrinsic IFN signaling by HDAC inhibition increased tumor cell visibility, promoted long-term antitumor immunity, and blocked cancer growth in bone. Key findings were validated in patients, including loss of tumor-intrinsic IFN signaling and immunogenicity in bone metastases compared to primary tumors. Data herein provide a rationale as to why current immunotherapeutics fail in bone-metastatic prostate cancer, and provide a new therapeutic strategy to overcome the inefficacy of immune-based therapies in solid cancers., (© 2020 Peter MacCallum Cancer Centre. Published under the terms of the CC BY NC ND 4.0 license.)

Background: While critical insights have been gained from evaluating the genomic landscape of metastatic prostate cancer, utilizing this information to inform personalized treatment is in its infancy. We performed a retrospective pilot study to assess the current impact of precision medicine for locally advanced and metastatic prostate adenocarcinoma and evaluate how genomic data could be harnessed to individualize treatment., Methods: Deep whole genome-sequencing was performed on 16 tumour-blood pairs from 13 prostate cancer patients; whole genome optical mapping was performed in a subset of 9 patients to further identify large structural variants. Tumour samples were derived from prostate, lymph nodes, bone and brain., Results: Most samples had acquired genomic alterations in multiple therapeutically relevant pathways, including DNA damage response (11/13 cases), PI3K (7/13), MAPK (10/13) and Wnt (9/13). Five patients had somatic copy number losses in genes that may indicate sensitivity to immunotherapy ( LRP1B, CDK12, MLH1) and one patient had germline and somatic BRCA2 alterations., Conclusions: Most cases, whether primary or metastatic, harboured therapeutically relevant alterations, including those associated with PARP inhibitor sensitivity, immunotherapy sensitivity and resistance to androgen pathway targeting agents. The observed intra-patient heterogeneity and presence of genomic alterations in multiple growth pathways in individual cases suggests that a precision medicine model in prostate cancer needs to simultaneously incorporate multiple pathway-targeting agents. Our whole genome approach allowed for structural variant assessment in addition to the ability to rapidly reassess an individual's molecular landscape as knowledge of relevant biomarkers evolve. This retrospective oncological assessment highlights the genomic complexity of prostate cancer and the potential impact of assessing genomic data for an individual at any stage of the disease.

Background: The German Shepherd Dog (GSD) is one of the most common breeds on earth and has been bred for its utility and intelligence. It is often first choice for police and military work, as well as protection, disability assistance, and search-and-rescue. Yet, GSDs are well known to be susceptible to a range of genetic diseases that can interfere with their training. Such diseases are of particular concern when they occur later in life, and fully trained animals are not able to continue their duties., Findings: Here, we provide the draft genome sequence of a healthy German Shepherd female as a reference for future disease and evolutionary studies. We generated this improved canid reference genome (CanFam&#95;GSD) utilizing a combination of Pacific Bioscience, Oxford Nanopore, 10X Genomics, Bionano, and Hi-C technologies. The GSD assembly is ∼80 times as contiguous as the current canid reference genome (20.9 vs 0.267 Mb contig N50), containing far fewer gaps (306 vs 23,876) and fewer scaffolds (429 vs 3,310) than the current canid reference genome CanFamv3.1. Two chromosomes (4 and 35) are assembled into single scaffolds with no gaps. BUSCO analyses of the genome assembly results show that 93.0% of the conserved single-copy genes are complete in the GSD assembly compared with 92.2% for CanFam v3.1. Homology-based gene annotation increases this value to ∼99%. Detailed examination of the evolutionarily important pancreatic amylase region reveals that there are most likely 7 copies of the gene, indicative of a duplication of 4 ancestral copies and the disruption of 1 copy., Conclusions: GSD genome assembly and annotation were produced with major improvement in completeness, continuity, and quality over the existing canid reference. This resource will enable further research related to canine diseases, the evolutionary relationships of canids, and other aspects of canid biology., (© The Author(s) 2020. Published by Oxford University Press.)

Background: Current array-based methods for the measurement of DNA methylation rely on the process of sodium bisulfite conversion to differentiate between methylated and unmethylated cytosine bases in DNA. In the absence of genotype data this process can lead to ambiguity in data interpretation when a sample has polymorphisms at a methylation probe site. A common way to minimize this problem is to exclude such potentially problematic sites, with some methods removing as much as 60% of array probes from consideration before data analysis., Results: Here, we present an algorithm implemented in an R Bioconductor package, MethylToSNP, which detects a characteristic data pattern to infer sites likely to be confounded by polymorphisms. Additionally, the tool provides a stringent reliability score to allow thresholding on SNP predictions. We calibrated parameters and thresholds used by the algorithm on simulated and real methylation data sets. We illustrate findings using methylation data from YRI (Yoruba in Ibadan, Nigeria), CEPH (European descent) and KhoeSan (southern African) populations. Our polymorphism predictions made using MethylToSNP have been validated through SNP databases and bisulfite and genomic sequencing., Conclusions: The benefits of this method are threefold. First, it prevents extensive data loss by considering only SNPs specific to the individuals in the study. Second, it offers the possibility to identify new polymorphisms in samples for which there is little known about the genetic landscape. Third, it identifies variants as they exist in functional regions of a genome, such as in CTCF (transcriptional repressor) sites and enhancers, that may be common alleles or personal mutations with potential to deleteriously affect genomic regulatory activities. We demonstrate that MethylToSNP is applicable to the Illumina 450K and Illumina 850K EPIC array data and is also backwards compatible to the 27K methylation arrays. Going forward, this kind of nuanced approach can increase the amount of information derived from precious data sets by considering samples of the project individually to enable more informed decisions about data cleaning.

Anatomically modern humans originated in Africa around 200 thousand years ago (ka) 1-4 . Although some of the oldest skeletal remains suggest an eastern African origin 2 , southern Africa is home to contemporary populations that represent the earliest branch of human genetic phylogeny 5,6 . Here we generate, to our knowledge, the largest resource for the poorly represented and deepest-rooting maternal L0 mitochondrial DNA branch (198 new mitogenomes for a total of 1,217 mitogenomes) from contemporary southern Africans and show the geographical isolation of L0d1'2, L0k and L0g KhoeSan descendants south of the Zambezi river in Africa. By establishing mitogenomic timelines, frequencies and dispersals, we show that the L0 lineage emerged within the residual Makgadikgadi-Okavango palaeo-wetland of southern Africa 7 , approximately 200 ka (95% confidence interval, 240-165 ka). Genetic divergence points to a sustained 70,000-year-long existence of the L0 lineage before an out-of-homeland northeast-southwest dispersal between 130 and 110 ka. Palaeo-climate proxy and model data suggest that increased humidity opened green corridors, first to the northeast then to the southwest. Subsequent drying of the homeland corresponds to a sustained effective population size (L0k), whereas wet-dry cycles and probable adaptation to marine foraging allowed the southwestern migrants to achieve population growth (L0d1'2), as supported by extensive south-coastal archaeological evidence 8-10 . Taken together, we propose a southern African origin of anatomically modern humans with sustained homeland occupation before the first migrations of people that appear to have been driven by regional climate changes.

Background: Inflammation is a hallmark of prostate cancer (PCa), yet no pathogenic agent has been identified. Men from Africa are at increased risk for both aggressive prostate disease and infection. We hypothesize that pathogenic microbes may be contributing, at least in part, to high-risk PCa presentation within Africa and in turn the observed ethnic disparity., Methods: Here we reveal through metagenomic analysis of host-derived whole-genome sequencing data, the microbial content within prostate tumor tissue from 22 men. What is unique about this study is that patients were separated by ethnicity, African vs European, and environments, Africa vs Australia., Results: We identified 23 common bacterial genera between the African, Australian, and Chinese prostate tumor samples, while nonbacterial microbes were notably absent. While the most abundant genera across all samples included: Escherichia, Propionibacterium, and Pseudomonas, the core prostate tumor microbiota was enriched for Proteobacteria. We observed a significant increase in the richness of the bacterial communities within the African vs Australian samples (t = 4.6-5.5; P = .0004-.001), largely driven by eight predominant genera. Considering core human gut microbiota, African prostate tissue samples appear enriched for Escherichia and Acidovorax, with an abundance of Eubacterium associated with host tumor hypermutation., Conclusions: Our study provides suggestive evidence for the presence of a core, bacteria-rich, prostate microbiome. While unable to exclude for fecal contamination, the observed increased bacterial content and richness within the African vs non-African samples, together with elevated tumor mutational burden, suggests the possibility that bacterially-driven oncogenic transformation within the prostate microenvironment may be contributing to aggressive disease presentation in Africa., (© 2019 The Authors. The Prostate published by Wiley Periodicals, Inc.)

Background: The androgen-regulated gene TMPRSS2 to the ETS transcription factor gene ERG fusion is the most common genomic alteration acquired during prostate tumorigenesis and biased toward men of European ancestry. In contrast, African American men present with more advanced disease, yet their tumors are less likely to acquire TMPRSS2-ERG. Data for Africa is scarce., Methods: RNA was made available for genomic analyses from 181 prostate tissue biopsy cores from Black South African men, 94 with and 87 without pathological evidence for prostate cancer. Reverse transcription polymerase chain reaction was used to screen for the TMPRSS2-ERG fusion, while transcript junction coordinates and isoform frequencies, including novel gene fusions, were determined using targeted RNA sequencing., Results: Here we report a frequency of 13% for TMPRSS2-ERG in tumors from Black South Africans. Present in 12/94 positive versus 1/87 cancer negative prostate tissue cores, this suggests a 92.62% predictivity for a positive cancer diagnosis (P = 0.0031). At a frequency of almost half that reported for African Americans and roughly a quarter of that reported for men of European ancestry, acquisition of TMPRSS2-ERG appears to be inversely associated with aggressive prostate cancer. Further support was provided by linking the presence of TMPRSS2-ERG to low-grade disease in younger patients (P = 0.0466), with higher expressing distal ERG fusion junction coordinates., Conclusions: Only the second study of its kind for the African continent, we support a link between TMPRSS2-ERG status and prostate cancer racial health disparity beyond the borders of the United States. We call for urgent evaluation of androgen deprivation therapy within Africa., (© 2019 The Authors. The Prostate Published by Wiley Periodicals, Inc.)

Backgrounds: Genetic diversity is greatest within Africa, in particular the KhoeSan click-speaking peoples of southern Africa. South African populations represent admixture fractions including differing degrees of African, African-KhoeSan and non-African genetic ancestries. Within the United States, African ancestry has been linked to prostate cancer presentation and mortality. Together with environmental contributions, genetics is a significant risk factor for high-risk prostate cancer, defined by a pathological Gleason score ≥ 8., Methods: Using genotype array data merged with ancestry informative reference data, we investigate the contribution of African ancestral fractions to high-risk prostate cancer. Our study includes 152 South African men of African (Black) or African-admixed (Coloured) ancestries, in which 40% showed high-risk prostate cancer., Results: Genetic fractions were determined for averaging an equal African to non-African genetic ancestral contribution in the Coloured; we found African ancestry to be linked to high-risk prostate cancer (P-value = 0.0477). Adjusting for age, the associated African ancestral fraction was driven by a significant KhoeSan over Bantu contribution, defined by Gleason score ≥ 8 (P-value = 0.02329) or prostate specific antigen levels ≥20 ng/ml (P-value = 0.03713). Additionally, we observed the mean overall KhoeSan contribution to be increased in Black patients with high-risk (11.8%) over low-risk (10.9%) disease. Linking for the first time KhoeSan ancestry to a common modern disease, namely high-risk prostate cancer, we tested in this small study the validity of using KhoeSan ancestry as a surrogate for identifying potential high-risk prostate cancer risk loci. As such, we identified four loci within chromosomal regions 2p11.2, 3p14, 8q23 and 22q13.2 (P-value = all age-adjusted < 0.01), two of which have previously been associated with high-risk prostate cancer., Conclusions: Our study suggests that ancient KhoeSan ancestry may be linked to common modern diseases, specifically those of late onset and therefore unlikely to have undergone exclusive selective pressure. As such we show within a uniquely admixed South African population a link between KhoeSan ancestry and high-risk prostate cancer, which may explain the 2-fold increase in presentation in Black South Africans compared with African Americans.

Fusion genes are a major cause of cancer. Their rapid and accurate diagnosis can inform clinical action, but current molecular diagnostic assays are restricted in resolution and throughput. Here, we show that targeted RNA sequencing (RNAseq) can overcome these limitations. First, we establish that fusion gene detection with targeted RNAseq is both sensitive and quantitative by optimising laboratory and bioinformatic variables using spike-in standards and cell lines. Next, we analyse a clinical patient cohort and improve the overall fusion gene diagnostic rate from 63% with conventional approaches to 76% with targeted RNAseq while demonstrating high concordance for patient samples with previous diagnoses. Finally, we show that targeted RNAseq offers additional advantages by simultaneously measuring gene expression levels and profiling the immune-receptor repertoire. We anticipate that targeted RNAseq will improve clinical fusion gene detection, and its increasing use will provide a deeper understanding of fusion gene biology.

Background: Prostate cancer (PCa) is the most common malignant neoplasm among men in many countries. Since most precancerous and cancerous tissues show signs of inflammation, chronic bacterial prostatitis has been hypothesized to be a possible etiology. However, establishing a causal relationship between microbial inflammation and PCa requires a comprehensive analysis of the prostate microbiome. The aim of this study was to characterize the microbiome in prostate tissue of PCa patients and investigate its association with tumour clinical characteristics as well as host expression profiles., Results: The metagenome and metatranscriptome of tumour and the adjacent benign tissues were assessed in 65 Chinese radical prostatectomy specimens. Escherichia, Propionibacterium, Acinetobacter and Pseudomonas were abundant in both metagenome and metatranscriptome, thus constituting the core of the prostate microbiome. The biodiversity of the microbiomes could not be differentiated between the matched tumour/benign specimens or between the tumour specimens of low and high Gleason Scores. The expression profile of ten Pseudomonas genes was strongly correlated with that of eight host small RNA genes; three of the RNA genes may negatively associate with metastasis. Few viruses could be identified from the prostate microbiomes., Conclusions: This is the first study of the human prostate microbiome employing an integrated metagenomics and metatranscriptomics approach. In this Chinese cohort, both metagenome and metatranscriptome analyses showed a non-sterile microenvironment in the prostate of PCa patients, but we did not find links between the microbiome and local progression of PCa. However, the correlated expression of Pseudomonas genes and human small RNA genes may provide tantalizing preliminary evidence that Pseudomonas infection may impede metastasis.

: African-American men are more likely than any other racial group to die from prostate cancer. The contribution of acquired genomic variation to this racial disparity is largely unknown, as genomic from Africa is lacking. Here, we performed the first tumor-normal paired deep whole-genome sequencing for Africa. A direct study-matched comparison between African- and European-derived, treatment-naïve, high-risk prostate tumors for 15 cases allowed for further comparative analyses of existing data. Excluding a single hypermutated tumor with 55 mutations per megabase, we observed a 1.8-fold increase in small somatic variants in African- versus European-derived tumors ( P = 1.02e-04), rising to 4-fold when compared with published tumor-matched data. Furthermore, we observed an increase in oncogenic driver mutations in African tumors ( P = 2.92e-03); roughly 30% of impacted genes were novel to prostate cancer, and 79% of recurrent driver mutations appeared early in tumorigenesis. Although complex genomic rearrangements were less frequent in African tumors, we describe a uniquely hyperduplicated tumor affecting 149 transposable elements. Comparable with African Americans, ERG fusions and PIK3CA mutations were absent and PTEN loss less frequent. CCND1 and MYC were frequently gained, with somatic copy-number changes more likely to occur late in tumorigenesis. In addition to traditional prostate cancer gene pathways, genes regulating calcium ion-ATPase signal transduction were disrupted in African tumors. Although preliminary, our results suggest that further validation and investigation into the potential implications for elevated tumor mutational burden and tumor-initiating mutations in clinically unfavorable prostate cancer can improve patient outcomes in Africa. SIGNIFICANCE: The first whole-genome sequencing study for high-risk prostate cancer in African men allows a simultaneous comparison of ethnic differences relative to European populations and of the influences of the environment relative to African-American men. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/78/24/6736/F1.large.jpg. See related commentary by Huang, p. 6726 ., (©2018 American Association for Cancer Research.)

Background: Comprehensive genome-wide DNA methylation profiling is critical to gain insights into epigenetic reprogramming during development and disease processes. Among the different genome-wide DNA methylation technologies, whole genome bisulphite sequencing (WGBS) is considered the gold standard for assaying genome-wide DNA methylation at single base resolution. However, the high sequencing cost to achieve the optimal depth of coverage limits its application in both basic and clinical research. To achieve 15× coverage of the human methylome, using WGBS, requires approximately three lanes of 100-bp-paired-end Illumina HiSeq 2500 sequencing. It is important, therefore, for advances in sequencing technologies to be developed to enable cost-effective high-coverage sequencing., Results: In this study, we provide an optimised WGBS methodology, from library preparation to sequencing and data processing, to enable 16-20× genome-wide coverage per single lane of HiSeq X Ten, HCS 3.3.76. To process and analyse the data, we developed a WGBS pipeline (METH10X) that is fast and can call SNPs. We performed WGBS on both high-quality intact DNA and degraded DNA from formalin-fixed paraffin-embedded tissue. First, we compared different library preparation methods on the HiSeq 2500 platform to identify the best method for sequencing on the HiSeq X Ten. Second, we optimised the PhiX and genome spike-ins to achieve higher quality and coverage of WGBS data on the HiSeq X Ten. Third, we performed integrated whole genome sequencing (WGS) and WGBS of the same DNA sample in a single lane of HiSeq X Ten to improve data output. Finally, we compared methylation data from the HiSeq 2500 and HiSeq X Ten and found high concordance (Pearson r > 0.9×)., Conclusions: Together we provide a systematic, efficient and complete approach to perform and analyse WGBS on the HiSeq X Ten. Our protocol allows for large-scale WGBS studies at reasonable processing time and cost on the HiSeq X Ten platform.

Genomic rearrangements are common in cancer, with demonstrated links to disease progression and treatment response. These rearrangements can be complex, resulting in fusions of multiple chromosomal fragments and generation of derivative chromosomes. Although methods exist for detecting individual fusions, they are generally unable to reconstruct complex chained events. To overcome these limitations, we adopted a new optical mapping approach, allowing megabase-length genome maps to be reconstructed and rearranged genomes to be visualized without loss of integrity. Whole-genome mapping (Bionano Genomics) of a well-studied highly rearranged liposarcoma cell line resulted in 3338 assembled consensus genome maps, including 72 fusion maps. These fusion maps represent 112.3 Mb of highly rearranged genomic regions, illuminating the complex architecture of chained fusions, including content, order, orientation, and size. Spanning the junction of 147 chromosomal translocations, we found a total of 28 Mb of interspersed sequences that could not be aligned to the reference genome. Traversing these interspersed sequences using short-read sequencing breakpoint calls, we were able to identify and place 399 sequencing fragments within the optical mapping gaps, thus illustrating the complementary nature of optical mapping and short-read sequencing. We demonstrate that optical mapping provides a powerful new approach for capturing a higher level of complex genomic architecture, creating a scaffold for renewed interpretation of sequencing data of particular relevance to human cancer., (© 2018 Chan et al.; Published by Cold Spring Harbor Laboratory Press.)