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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 averages1. The contributing genetic and non-genetic factors, and associated mutational processes, are unknown2,3. 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.

Dogs are uniquely associated with human dispersal and bring transformational insight into the domestication process. Dingoes represent an intriguing case within canine evolution being geographically isolated for thousands of years. Here, we present a high-quality de novo assembly of a pure dingo (CanFam_DDS). We identified large chromosomal differences relative to the current dog reference (CanFam3.1) and confirmed no expanded pancreatic amylase gene as found in breed dogs. Phylogenetic analyses using variant pairwise matrices show that the dingo is distinct from five breed dogs with 100% bootstrap support when using Greenland wolf as the outgroup. Functionally, we observe differences in methylation patterns between the dingo and German shepherd dog genomes and differences in serum biochemistry and microbiome makeup. Our results suggest that distinct demographic and environmental conditions have shaped the dingo genome. In contrast, artificial human selection has likely shaped the genomes of domestic breed dogs after divergence from the dingo.

Prostate cancer is a genetic disease. While next generation sequencing has allowed for the emergence of molecular taxonomy, classification is restricted to the nuclear genome. Mutations within the maternally inherited mitochondrial genome are known to impact cancer pathogenesis, as a result of disturbances in energy metabolism and apoptosis. With a higher mutation rate, limited repair and increased copy number compared to the nuclear genome, the clinical relevance of mitochondrial DNA (mtDNA) variation requires deeper exploration. Here we provide a systematic review of the landscape of prostate cancer associated mtDNA variation. While the jury is still out on the association between inherited mtDNA variation and prostate cancer risk, we collate a total of 749 uniquely reported prostate cancer associated somatic mutations. Support exists for number of somatic events, extent of heteroplasmy, and rate of recurrence of mtDNA mutations, increasing with disease aggression. While, the predicted pathogenic impact for recurrent prostate cancer associated mutations appears negligible, evidence exists for carcinogenic mutations impacting the cytochrome c oxidase complex and regulating metastasis through elevated reactive oxygen species production. Due to a lack of lethal cohort analyses, we provide additional unpublished data for metastatic disease. Discussing the advantages of mtDNA as a prostate cancer biomarker, we provide a review of current progress of including elevated mtDNA levels, of a large somatic deletion, acquired tRNAs mutations, heteroplasmy and total number of somatic events (mutational load). We confirm via meta-analysis a significant association between mtDNA mutational load and pathological staging at diagnosis or surgery (p < 0.0001).

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 and precision 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.

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.

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_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.

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.

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 origin2, southern Africa is home to contemporary populations that represent the earliest branch of human genetic phylogeny5,6. 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 Africa7, 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 evidence8–10. 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. Analyses of mitochondrial genomes from populations in southern Africa provide evidence of a southern African origin of anatomically modern humans and a sustained occupation of the homeland before the first migrations of people appear to be driven by regional climate shifts.

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.

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.

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. While 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 for megabase length DNA to be captured, and in turn 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 3,338 assembled haploid genome maps, including 101 fusion maps. These fusion maps represent 175 Mb of highly rearranged genomic regions, illuminating the complex architecture of chained fusions, including content, order, orientation, and size. Spanning the junction of 151 chromosomal translocations, we found a total of 32 Mb of novel interspersed sequences that were not detected from 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.

The oldest contemporary human mitochondrial lineages arose in Africa. The earliest divergent extant maternal offshoot, namely haplogroup L0d, is represented by click-speaking forager peoples of southern Africa. Broadly defined as Khoesan, contemporary Khoesan are today largely restricted to the semidesert regions of Namibia and Botswana, whereas archeological, historical, and genetic evidence promotes a once broader southerly dispersal of click-speaking peoples including southward migrating pastoralists and indigenous marine-foragers. No genetic data have been recovered from the indigenous peoples that once sustained life along the southern coastal waters of Africa prepastoral arrival. In this study we generate a complete mitochondrial genome from a 2,330-year-old male skeleton, confirmed through osteological and archeological analysis as practicing a marine-based forager existence. The ancient mtDNA represents a new L0d2c lineage (L0d2c1c) that is today, unlike its Khoe-language based sister-clades (L0d2c1a and L0d2c1b) most closely related to contemporary indigenous San-speakers (specifically Ju). Providing the first genomic evidence that prepastoral Southern African marine foragers carried the earliest diverged maternal modern human lineages, this study emphasizes the significance of Southern African archeological remains in defining early modern human origins.

In 2013, approximately 14,000 students were enrolled at the Australian School of Business at the University of New South Wales. Although many of these students access the services and resources of the University of New South Wales’s Careers and Employment (5446 students in 2012), there are still a substantial number of students who approach the end of their degree and want to transition into the Australian workforce but have little understanding about the graduate recruitment process and how to best demonstrate their employability. As a result, the present study sought to identify an effective, resource efficient and inexpensive careers intervention that would have a wide reach to enable more students to increase their confidence in applying for graduate jobs.

// Weerachai Jaratlerdsiri 1, * , Eva K.F. Chan 1, 2, * , Desiree C. Petersen 1, 2, * , Claire Yang 3 , Peter I. Croucher 2, 4, 5 , M.S. Riana Bornman 6 , Palak Sheth 3 , Vanessa M. Hayes 1, 2, 6, 7 1 Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, Australia 2 St Vincent’s Clinical School, University of New South Wales, Randwick, Australia 3 Bionano Genomics Inc., San Diego, California, USA 4 Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, Australia 5 School of Biotechnology and Biomolecular Sciences, University of New South Wales, Randwick, Australia 6 School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa 7 Central Clinical School, University of Sydney, Camperdown, Australia * These authors contributed equally to this work Correspondence to: Vanessa M. Hayes, email: v.hayes@garvan.org.au Keywords: prostate cancer, structural genomic rearrangements, next generation mapping, next generation sequencing Received: August 15, 2016 Accepted: February 15, 2017 Published: March 01, 2017 ABSTRACT Complex genomic rearrangements are common molecular events driving prostate carcinogenesis. Clinical significance, however, has yet to be fully elucidated. Detecting the full range and subtypes of large structural variants (SVs), greater than one kilobase in length, is challenging using clinically feasible next generation sequencing (NGS) technologies. Next generation mapping (NGM) is a new technology that allows for the interrogation of megabase length DNA molecules outside the detection range of single-base resolution NGS. In this study, we sought to determine the feasibility of using the Irys (Bionano Genomics Inc.) nanochannel NGM technology to generate whole genome maps of a primary prostate tumor and matched blood from a Gleason score 7 (4 + 3), ETS-fusion negative prostate cancer patient. With an effective mapped coverage of 35X and sequence coverage of 60X, and an estimated 43% tumor purity, we identified 85 large somatic structural rearrangements and 6,172 smaller somatic variants, respectively. The vast majority of the large SVs (89%), of which 73% are insertions, were not detectable ab initio using high-coverage short-read NGS. However, guided manual inspection of single NGS reads and de novo assembled scaffolds of NGM-derived candidate regions allowed for confirmation of 94% of these large SVs, with over a third impacting genes with oncogenic potential. From this single-patient study, the first cancer study to integrate NGS and NGM data, we hypothesise that there exists a novel spectrum of large genomic rearrangements in prostate cancer, that these large genomic rearrangements are likely early events in tumorigenesis, and they have potential to enhance taxonomy.

The first single-nucleotide polymorphism (SNP) maps for watermelon [Citrullus lanatus (Thunb.) Matsum. et Nakai] were constructed and compared. Three populations were developed from crosses between two elite cultivars, Klondike Black Seeded × New Hampshire Midget (KBS × NHM), an elite cultivar and wild egusi accession, Strain II × PI 560023 (SII × Egusi) and an elite cultivar and a wild citron accession, ZWRM50 × PI 244019 (ZWRM × Citroides). The SII × Egusi and ZWRM × Citroides F(2) populations consisted of 187 and 182 individuals respectively while the KBS × NHM recombinant inbred line (RIL) population consisted of 164 lines. The length of the genetic maps were 1,438, 1,514 and 1,144 cM with average marker distances of 3.8, 4.2, and 3.4 cM for the KBS × NHM, SII × Egusi and ZWRM × Citroides populations, respectively. Shared markers were used to align the three maps so that the linkage groups (LGs) represented the 11 chromosomes of the species. Marker segregation distortion were observed in all three populations, but was highest (12.7 %) in the ZWRM × Citroides population, where Citroides alleles were favored. The three maps were used to construct a consensus map containing 378 SNP markers with an average distance of 5.1 cM between markers. Phenotypic data was collected for fruit weight (FWT), fruit length (FL), fruit width (FWD), fruit shape index (FSI), rind thickness (RTH) and Brix (BRX) and analyzed for quantitative trait loci (QTL) associated with these traits. A total of 40 QTL were identified in the three populations, including major QTL for fruit size and shape that were stable across genetic backgrounds and environments. The present study reports the first SNP maps for Citrullus and the first map constructed using two elite parents. We also report the first stable QTL associated with fruit size and shape in Citrullus lanatus. These maps, QTL and SNPs should be useful for the watermelon community and represent a significant step towards the potential use of molecular tools in watermelon breeding.

Beef cattle breeds consist of three major genetic subdivisions. The taurine group is adapted to temperate environments, and the zebu and Sanga groups are both adapted to tropical environments. With the advent of genotyping and sequencing technologies in agriculture, genome-wide exploration of the genetic basis for the differences in tropical adaptation has only just become possible. In this study, approximately 9000 single nucleotide polymorphism markers were genotyped on 317 animals of a selection of taurine, zebu, and composite breeds to characterize any systematic differences between these groups. We identified 91 intra-breed-class markers; 78 were polymorphic only within the zebu animals, while 13 were polymorphic only in the taurine animals. There were no fixed differences (fixed for alternate alleles between the two breed types) between zebu and taurine animals. We found 14 regions with significantly different allele frequencies between zebu and taurine animals indicative of variable selection pressure or genetic drift. We also found 12 independent regions of differential extended haplotype homozygosity (EHH), indicative of recent selection or rapid fixation of the alternate allele within a short period of time in one of the two breed classes. A preliminary functional genomics analysis of these regions pointed towards signatures of tropical attributes including keratins, heat-shock proteins and heat resistance genes. We anticipate this investigation to be a stepping-stone for future studies to identify genomic regions specific to the two cattle groups, and to subsequently assist in the discrimination between temperate and tropically adapted cattle.

With the improvement and decline in cost of high-throughput genotyping and phenotyping technologies, genome-wide association (GWA) studies are fast becoming a preferred approach for dissecting complex quantitative traits. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of quantitative traits. GSLs are key defenses against insects in the wild and the relatively large number of cloned quantitative trait locus (QTL) controlling GSL traits allows comparison of GWA to previous QTL analyses. To better understand the specieswide genomic architecture controlling plant-insect interactions and the relative strengths of GWA and QTL studies, we conducted a GWA mapping study using 96 A. thaliana accessions, 43 GSL phenotypes, and ∼230,000 SNPs. Our GWA analysis identified the two major polymorphic loci controlling GSL variation (AOP and MAM) in natural populations within large blocks of positive associations encompassing dozens of genes. These blocks of positive associations showed extended linkage disequilibrium (LD) that we hypothesize to have arisen from balancing or fluctuating selective sweeps at both the AOP and MAM loci. These potential sweep blocks are likely linked with the formation of new defensive chemistries that alter plant fitness in natural environments. Interestingly, this GWA analysis did not identify the majority of previously identified QTL even though these polymorphisms were present in the GWA population. This may be partly explained by a nonrandom distribution of phenotypic variation across population subgroups that links population structure and GSL variation, suggesting that natural selection can hinder the detection of phenotype–genotype associations in natural populations.

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

The view that changes to the control of gene expression rather than alterations to protein sequence are central to the evolution of organisms has become something of a truism in molecular biology. In reality, the direct evidence for this is limited, and only recently have we had the ability to look more globally at how genetic variation influences gene expression, focusing upon inter-individual variation in gene expression and using microarrays to test for differences in mRNA levels. Here, we review the scope of these experimental analyses, what they are designed to tell us about genetic variation, and what are their limitations from both a technical and a conceptual viewpoint. We conclude that while we are starting to understand the impact of this class of genetic variation upon steady-state mRNA levels, we are still far from identifying the potential phenotypic and evolutionary outcomes.

Hierarchical and empirical Bayes approaches to inference are attractive for data arising from microarray gene expression studies because of their ability to borrow strength across genes in making inferences. Here we focus on the simplest case where we have data from replicated two colour arrays which compare two samples and where we wish to decide which genes are differentially expressed and obtain estimates of operating characteristics such as false discovery rates. The purpose of this paper is to examine the frequentist performance of Bayesian variable selection approaches to this problem for different prior specifications and to examine the effect on inference of commonly used empirical Bayes approximations to hierarchical Bayes procedures. The paper makes three main contributions. First, we describe how the log odds of differential expression can usually be computed analytically in the case where a double tailed exponential prior is used for gene effects rather than a normal prior, which gives an alternative to the commonly used B-statistic for ranking genes in simple comparative experiments. The second contribution of the paper is to compare empirical Bayes procedures for detecting differential expression with hierarchical Bayes methods which account for uncertainty in prior hyperparameters to examine how much is lost in using the commonly employed empirical Bayes approximations. Third, we describe an efficient MCMC scheme for carrying out the computations required for the hierarchical Bayes procedures. Comparisons are made via simulation studies where the simulated data are obtained by fitting models to some real microarray data sets. The results have implications for analysis of microarray data using parametric hierarchical and empirical Bayes methods for more complex experimental designs: generally we find that the empirical Bayes methods work well, which supports their use in the analysis of more complex experiments when a full hierarchical Bayes analysis would impose heavy computational demands.

BACKGROUND Prostate cancer incidence and mortality rates are significantly increased in African–American men, but limited studies have been performed within Sub–Saharan African populations. As mitochondria control energy metabolism and apoptosis we speculate that somatic mutations within mitochondrial genomes are candidate drivers of aggressive prostate carcinogenesis. METHODS We used matched blood and prostate tissue samples from 87 South African men (77 with African ancestry) to perform deep sequencing of complete mitochondrial genomes. Clinical presentation was biased toward aggressive disease (Gleason score >7, 64%), and compared with men without prostate cancer either with or without benign prostatic hyperplasia. RESULTS We identified 144 somatic mtDNA single nucleotide variants (SNVs), of which 80 were observed in 39 men presenting with aggressive disease. Both the number and frequency of somatic mtDNA SNVs were associated with higher pathological stage. CONCLUSIONS Besides doubling the total number of somatic PCa‐associated mitochondrial genome mutations identified to date, we associate mutational load with aggressive prostate cancer status in men of African ancestry. Prostate 76:349–358, 2016. © 2015 The Authors. The Prostate published by Wiley Periodicals, Inc.

Made available in DSpace on 2015-03-18T15:56:05Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-11-24Bitstream added on 2015-03-18T16:28:27Z : No. of bitstreams: 1 WOS000346766900029.pdf: 849325 bytes, checksum: 346225604ca751c688aeebb064d7d71b (MD5) Cooperative Research Centre for Beef Genetic Technologies Cooperative Research Centre for Cattle and Beef Quality CSIRO through its Food Futures Flagship Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity. Queensland Biosci Precinct, CSIRO Food Futures Flagship, St Lucia, Qld, Australia Queensland Biosci Precinct, CSIRO Anim Food & Hlth Sci, St Lucia, Qld, Australia Zoetis Inc, Parkville, Vic, Australia Garvan Inst Med Res, Sydney, NSW, Australia Univ New England, Anim Genet & Breeding Unit, Armidale, NSW, Australia Cobb Vantress Inc, Siloam Springs, AZ USA Univ Queensland, Queensland Alliance Agr & Food Innovat, St Lucia, Qld, Australia UNESP Univ Estadual Paulista, Fac Med Vet Aracatuba, Sao Paulo, Brazil ARS, USDA, Bovine Funct Genom Lab, Beltsville, MD USA Dept Primary Ind Victoria, Bundoora, Vic, Australia UNESP Univ Estadual Paulista, Fac Med Vet Aracatuba, Sao Paulo, Brazil

Genome-wide association mapping is highly sensitive to environmental changes, but network analysis allows rapid causal gene identification., Background Genome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA. Methodology/Principal Findings To understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines. Conclusions/Significance Together, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse., Author Summary Understanding how genetic variation can control phenotypic variation is a fundamental goal of modern biology. A major push has been made using genome-wide association mapping in all organisms to attempt and rapidly identify the genes contributing to phenotypes such as disease and nutritional disorders. But a number of fundamental questions have not been answered about the use of genome-wide association: for example, how does the internal or external environment influence the genes found? Furthermore, the simple question of how many genes may influence a trait is unknown. Finally, a number of studies have identified significant false-positive and -negative issues within genome-wide association studies that are not solvable by direct statistical approaches. We have used genome-wide association mapping in the plant Arabidopsis thaliana to begin exploring these questions. We show that both external and internal environments significantly alter the identified genes, such that using different tissues can lead to the identification of nearly completely different gene sets. Given the large number of potential false-positives, we developed an orthogonal approach to filtering the possible genes, by identifying co-functioning networks using the nominal candidate gene list derived from genome-wide association studies. This allowed us to rapidly identify and validate a large number of novel and unexpected genes that affect Arabidopsis thaliana defense metabolism within phenotypic ranges that have been shown to be selectable within the field. These genes and the associated networks suggest that Arabidopsis thaliana defense metabolism is more readily similar to the infinite gene hypothesis, according to which there is a vast number of causative genes controlling natural variation in this phenotype. It remains to be seen how frequently this is true for other organisms and other phenotypes.

Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable., Author Summary Understanding how genetic variation can control phenotypic variation is a fundamental goal of modern biology. We combined genome-wide association mapping with metabolomics in the plant Arabidopsis thaliana to explore how species-wide genetic variation controls metabolism. We identified numerous naturally-variable genes that may influence plant metabolism, often clustering in “hotspots.” These hotspots were proximal to selective sweeps, regions of the genome showing decreased diversity possibly from a strong selective advantage of specific variants within the region. This suggests that metabolism may be connected to the selective advantage. Interestingly, metabolite variation in wild Arabidopsis is highly constrained despite the significant genetic variation, thus providing the plant un-sampled metabolic space if the environment shifts. The observed structuring of genetic and metabolic variation suggests individual convergence upon similar phenotypes via different genotypes, possibly intra-specific parallel evolution. This phenotypic convergence couples with a pattern of genotype—phenotype association consistent with metabolite variation largely controlled by numerous small effect genetic variants. This supports the supposition that large magnitude variation is likely unstable in a complex and interconnected metabolism. If this pattern proves generally applicable to other species, it could present a significant hurdle to identifying genes controlling metabolic trait variation via genome-wide association studies.

Despite the described central role of jasmonate signaling in plant defense against necrotrophic pathogens, the existence of intraspecific variation in pathogen capacity to activate or evade plant jasmonate-mediated defenses is rarely considered. Experimental infection of jasmonate-deficient and jasmonate-insensitive Arabidopsis thaliana with diverse isolates of the necrotrophic fungal pathogen Botrytis cinerea revealed pathogen variation for virulence inhibition by jasmonate-mediated plant defenses and induction of plant defense metabolites. Comparison of the transcriptional effects of infection by two distinct B. cinerea isolates showed only minor differences in transcriptional responses of wild-type plants, but notable isolate-specific transcript differences in jasmonate-insensitive plants. These transcriptional differences suggest B. cinerea activation of plant defenses that require plant jasmonate signaling for activity in response to only one of the two B. cinerea isolates tested. Thus, similar infection phenotypes observed in wild-type plants result from different signaling interactions with the plant that are likely integrated by jasmonate signaling., Author Summary While many important elements of plant defense signaling have been identified, the function of these defense signaling pathways may mask additional variation in the plant–pathogen interaction, including both pathogen variation and variation in downstream plant defense responses. Jasmonate plant hormones contribute to both plant development and defense, including plant defense against necrotrophic fungal pathogens such as the grey mold Botrytis cinerea. Ten diverse B. cinerea isolates all showed increased virulence and decreased induction of a plant antimicrobial metabolite in experimental infections of Arabidopsis thaliana lacking functional jasmonate signaling. Yet within this consistent result, B. cinerea isolates varied considerably. Through comparing the transcript profiles of A. thaliana infected with the two most disparate B. cinerea isolates, we found that wild-type plants showed similar transcriptional responses to infection with these two isolates, but the absence of functional jasmonate signaling revealed dramatic differences in plant response, including groups of co-regulated genes that may participate in undescribed plant response networks. Jasmonate signaling appears to integrate plant responses to diverse pathogen inputs, and its absence may reveal novel aspects of plant–pathogen interaction.

The last decade has seen rapid improvements in high-throughput single nucleotide polymorphism (SNP) genotyping technologies that have consequently made genome-wide association studies (GWAS) possible. With tens to hundreds of thousands of SNP markers being tested simultaneously in GWAS, it is imperative to appropriately pre-process, or filter out, those SNPs that may lead to false associations. This paper explores the relationships between various SNP genotype and phenotype attributes and their effects on false associations. We show that (i) uniformly distributed ordinal data as well as binary data are more easily influenced, though not necessarily negatively, by differences in various SNP attributes compared with normally distributed data; (ii) filtering SNPs on minor allele frequency (MAF) and extent of Hardy-Weinberg equilibrium (HWE) deviation has little effect on the overall false positive rate; (iii) in some cases, filtering on MAF only serves to exclude SNPs from the analysis without reduction of the overall proportion of false associations; and (iv) HWE, MAF and heterozygosity are all dependent on minor genotype frequency, a newly proposed measure for genotype integrity.

Background The success of genome-wide scans depends on the strength and magnitude of linkage disequilibrium (LD) present within the populations under investigation. High density SNP arrays are currently in development for the sheep genome, however little is known about the behaviour of LD in this livestock species. This study examined the behaviour of LD within five sheep populations using two LD metrics, D' and x2'. Four economically important Australian sheep flocks, three pure breeds (White Faced Suffolk, Poll Dorset, Merino) and a crossbred population (Merino × Border Leicester), along with an inbred Australian Merino museum flock were analysed. Results Short range LD (0 – 5 cM) was observed in all five populations, however the persistence with increasing distance and magnitude of LD varied considerably between populations. Average LD (x2') for markers spaced up to 20 cM exceeded the non-syntenic average within the White Faced Suffolk, Poll Dorset and Macarthur Merino. LD decayed faster within the Merino and Merino × Border Leicester, with LD below or consistent with observed background levels. Using marker-marker LD as a guide to the behaviour of marker-QTL LD, estimates of minimum marker spacing were made. For a 95% probability of detecting QTL, a microsatellite marker would be required every 0.1 – 2.5 centimorgans, depending on the population used. Conclusion Sheep populations were selected which were inbred (Macarthur Merino), highly heterogeneous (Merino) or intermediate between these two extremes. This facilitated analysis and comparison of LD (x2') between populations. The strength and magnitude of LD was found to differ markedly between breeds and aligned closely with both observed levels of genetic diversity and expectations based on breed history. This confirmed that breed specific information is likely to be important for genome wide selection and during the design of successful genome scans where tens of thousands of markers will be required.

The analysis of the influence of genetic variation on regulation of gene expression at a near-genome-wide level has become the focus of much recent interest. It is widely appreciated that many genes are expressed in a tissue-specific manner and that others are more ubiquitously expressed but relatively little is known about how genetic variation might influence these tissue patterns of gene expression. In this review we discuss what is known about the tissue specificity of the influence of genetic variation and review the challenges that we face in combining hugely parallel, microarray-based gene analysis with equally expensive genetic analysis. We conclude that the available data suggest that genetic variation is essentially tissue specific in its effects upon gene expression and this has important implications for experimental analysis.

The oldest extant human maternal lineages include mitochondrial haplogroups L0d and L0k found in the southern African click-speaking forager peoples broadly classified as Khoesan. Profiling these early mitochondrial lineages allows for better understanding of modern human evolution. In this study, we profile 77 new early-diverged complete mitochondrial genomes and sub-classify another 105 L0d/L0k individuals from southern Africa. We use this data to refine basal phylogenetic divergence, coalescence times and Khoesan prehistory. Our results confirm L0d as the earliest diverged lineage (∼172 kya, 95%CI: 149-199 kya), followed by L0k (∼159 kya, 95%CI: 136-183 kya) and a new lineage we name L0g (∼94 kya, 95%CI: 72-116 kya). We identify two new L0d1 subclades we name L0d1d and L0d1c4/L0d1e, and estimate L0d2 and L0d1 divergence at ∼93 kya (95%CI:76-112 kya). We concur the earliest emerging L0d1'2 sublineage L0d1b (∼49 kya, 95%CI:37-58 kya) is widely distributed across southern Africa. Concomitantly, we find the most recent sublineage L0d2a (∼17 kya, 95%CI:10-27 kya) to be equally common. While we agree that lineages L0d1c and L0k1a are restricted to contemporary inland Khoesan populations, our observed predominance of L0d2a and L0d1a in non-Khoesan populations suggests a once independent coastal Khoesan prehistory. The distribution of early-diverged human maternal lineages within contemporary southern Africans suggests a rich history of human existence prior to any archaeological evidence of migration into the region. For the first time, we provide a genetic-based evidence for significant modern human evolution in southern Africa at the time of the Last Glacial Maximum at between ∼21-17 kya, coinciding with the emergence of major lineages L0d1a, L0d2b, L0d2d and L0d2a.

In order to uncover genes with transcriptional activity linked to various beef quality phenotypes of interest, we designed a systems biology approach. We focussed on traits representing the three major categories of growth and development, fat depots and meat quality phenotypes. We proceeded by linking bovine gene expression data derived from 147 microarray hybridisation experiments and high density marker data from 9260 single nucleotide polymorphisms (SNP) on 189 steers. The individuals in the genotyping study were unrelated to the samples used for expression profiling. The linkage was performed by anchoring these data to a gene network for myogenin (MYOG), a muscle-specific transcription factor essential for the development of skeletal muscle. This approach was able to identify and estimate the strength of the relationship between the statistical association of a SNP to a phenotype of interest with the transcriptional activity of genes in the network. The genes from the MYOG-centred network that were significantly associated with the largest number of meat quality traits were PDLIM3, CALM1 and CRYAB. Among our findings, a novel association between desmin and meat colour points to an alternative biochemical basis for meat colour differences involving costameric structures and their previously reported relationship with tenderness. These newly generated hypotheses can help formulate sound research to further illuminate the genetic architecture of beef quality phenotypes.