Characterization of Reference Materials for CYP3A4 and CYP3A5: A (GeT-RM) Collaborative Project.

Pharmacogenetic testing for CYP3A4 is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the CYP3A4 variants included in clinical tests. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM), in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 30 DNA samples derived from Coriell cell lines for CYP3A4. Samples were distributed to five volunteer laboratories for genotyping using a variety of commercially available and laboratory-developed tests. Sanger and next-generation sequencing were also utilized by some of the laboratories. Whole-genome sequencing data from the 1000 Genomes Projects were utilized to inform genotype. Twenty CYP3A4 alleles were identified in the 30 samples characterized for CYP3A4: CYP3A4∗4, ∗5, ∗6, ∗7, ∗8, ∗9, ∗10, ∗11, ∗12, ∗15, ∗16, ∗18, ∗19, ∗20, ∗21, ∗22, ∗23, ∗24, ∗35, and a novel allele, CYP3A4∗38. Nineteen additional samples with preexisting data for CYP3A4 or CYP3A5 were re-analyzed to generate comprehensive reference material panels for these genes. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

A draft human pangenome reference.

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

A fast machine-learning-guided primer design pipeline for selective whole genome amplification.

Addressing many of the major outstanding questions in the fields of microbial evolution and pathogenesis will require analyses of populations of microbial genomes. Although population genomic studies provide the analytical resolution to investigate evolutionary and mechanistic processes at fine spatial and temporal scales-precisely the scales at which these processes occur-microbial population genomic research is currently hindered by the practicalities of obtaining sufficient quantities of the relatively pure microbial genomic DNA necessary for next-generation sequencing. Here we present swga2.0, an optimized and parallelized pipeline to design selective whole genome amplification (SWGA) primer sets. Unlike previous methods, swga2.0 incorporates active and machine learning methods to evaluate the amplification efficacy of individual primers and primer sets. Additionally, swga2.0 optimizes primer set search and evaluation strategies, including parallelization at each stage of the pipeline, to dramatically decrease program runtime. Here we describe the swga2.0 pipeline, including the empirical data used to identify primer and primer set characteristics, that improve amplification performance. Additionally, we evaluate the novel swga2.0 pipeline by designing primer sets that successfully amplify Prevotella melaninogenica, an important component of the lung microbiome in cystic fibrosis patients, from samples dominated by human DNA.

Selective whole-genome amplification reveals population genetics of Leishmania braziliensis directly from patient skin biopsies.

In Brazil, Leishmania braziliensis is the main causative agent of the neglected tropical disease, cutaneous leishmaniasis (CL). CL presents on a spectrum of disease severity with a high rate of treatment failure. Yet the parasite factors that contribute to disease presentation and treatment outcome are not well understood, in part because successfully isolating and culturing parasites from patient lesions remains a major technical challenge. Here we describe the development of selective whole genome amplification (SWGA) for Leishmania and show that this method enables culture-independent analysis of parasite genomes obtained directly from primary patient skin samples, allowing us to circumvent artifacts associated with adaptation to culture. We show that SWGA can be applied to multiple Leishmania species residing in different host species, suggesting that this method is broadly useful in both experimental infection models and clinical studies. SWGA carried out directly on skin biopsies collected from patients in Corte de Pedra, Bahia, Brazil, showed extensive genomic diversity. Finally, as a proof-of-concept, we demonstrated that SWGA data can be integrated with published whole genome data from cultured parasite isolates to identify variants unique to specific geographic regions in Brazil where treatment failure rates are known to be high. SWGA provides a relatively simple method to generate Leishmania genomes directly from patient samples, unlocking the potential to link parasite genetics with host clinical phenotypes.

Semi-automated assembly of high-quality diploid human reference genomes.

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.

Characterization of Reference Materials for TPMT and NUDT15: A GeT-RM Collaborative Project.

Pharmacogenetic testing is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the TPMT and NUDT15 variants included in clinical tests. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention-based Genetic Testing Reference Material (GeT-RM) coordination program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 19 DNA samples derived from Coriell cell lines. DNA samples were distributed to four volunteer testing laboratories for genotyping using a variety of commercially available and laboratory developed tests and/or Sanger sequencing. Of the 12 samples characterized for TPMT, newly identified variants include TPMT∗2, ∗6, ∗12, ∗16, ∗21, ∗24, ∗32, ∗33, and ∗40; for the 7 NUDT15 reference material samples, newly identified variants are NUDT15∗2, ∗3, ∗4, ∗5, ∗6, and ∗9. In addition, a novel haplotype, TPMT∗46, was identified in this study. Preexisting data on an additional 11 Coriell samples, as well as some supplemental testing, were used to create comprehensive reference material panels for TPMT and NUDT15. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

An induced pluripotent stem cell line (CIMRi001-A) from a Vici syndrome donor with a homozygous recessive c.1007A>G (p.Q336R) mutation in the EPG5 gene.

Vici syndrome is a rare, congenital disorder that affects multiple systems and is caused by mutations in the EPG5 gene that encodes for ectopic P-granules autophagy protein 5 (EPG5). The induced pluripotent stem cell (iPSC) line described here was generated from a dermal fibroblast cell line from an 8-year-old male donor with a homozygous recessive c.1007A>G (p.Q336R) mutation in the EPG5 gene. This iPSC model of Vici syndrome provides a unique and valuable resource for investigators to study the pathology of EPG5 mutations and the aetiology of the disease as well as develop therapeutic treatments for those with Vici syndrome.

Habitat differentiation among three Nigeria-Cameroon chimpanzee (Pan troglodytes ellioti) populations.

Ecological niche models (ENMs) are often used to predict species distribution patterns from datasets that describe abiotic and biotic factors at coarse spatial scales. Ground-truthing ENMs provide important information about how these factors relate to species-specific requirements at a scale that is biologically relevant for the species. Chimpanzees are territorial and have a predominantly frugivorous diet. The spatial and temporal variation in fruit availability for different chimpanzee populations is thus crucial, but rarely depicted in ENMs. The genetic and geographic distinction within Nigeria-Cameroon chimpanzee (Pan troglodytes ellioti) populations represents a unique opportunity to understand fine scale species-relevant ecological variation in relation to ENMs. In Cameroon, P. t. ellioti is composed of two genetically distinct populations that occupy different niches: rainforests in western Cameroon and forest-woodland-savanna mosaic (ecotone) in central Cameroon. We investigated habitat variation at three representative sites using chimpanzee-relevant environmental variables, including fruit availability, to assess how these variables distinguish these niches from one another. Contrary to the assumption of most ENM studies that intact forest is essential for the survival of chimpanzees, we hypothesized that the ecotone and human-modified habitats in Cameroon have sufficient resources to sustain large chimpanzee populations. Rainfall, and the diversity, density, and size of trees were higher at the rainforest. The ecotone had a higher density of terrestrial herbs and lianas. Fruit availability was higher at Ganga (ecotone) than at Bekob and Njuma. Seasonal variation in fruit availability was highest at Ganga, and periods of fruit scarcity were longer than at the rainforest sites. Introduced and secondary forest species linked with anthropogenic modification were common at Bekob, which reduced seasonality in fruit availability. Our findings highlight the value of incorporating fine scale species-relevant ecological data to create more realistic models, which have implications for local conservation planning efforts.

Acetaminophen (Paracetamol) Use Modifies the Sulfation of Sex Hormones.

BACKGROUND: Acetaminophen (paracetamol) is one of the most common medications used for management of pain in the world. There is lack of consensus about the mechanism of action, and concern about the possibility of adverse effects on reproductive health. METHODS: We first established the metabolome profile that characterizes use of acetaminophen, and we subsequently trained and tested a model that identified metabolomic differences across samples from 455 individuals with and without acetaminophen use. We validated the findings in a European ancestry adult twin cohort of 1880 individuals (TwinsUK), and in a study of 1235 individuals of African American and Hispanic ancestry. We used genomics to elucidate the mechanisms targeted by acetaminophen. FINDINGS: We identified a distinctive pattern of depletion of sulfated sex hormones with use of acetaminophen across all populations. We used a Mendelian randomization approach to characterize the role of Sulfotransferase Family 2A Member 1 (SULT2A1) as the site of the interaction. Although CYP3A7-CYP3A51P variants also modified levels of some sulfated sex hormones, only acetaminophen use phenocopied the effect of genetic variants of SULT2A1. Overall, acetaminophen use, age, gender and SULT2A1 and CYP3A7-CYP3A51P genetic variants are key determinants of variation in levels of sulfated sex hormones in blood. The effect of taking acetaminophen on sulfated sex hormones was roughly equivalent to the effect of 35years of aging. INTERPRETATION: These findings raise concerns of the impact of acetaminophen use on hormonal homeostasis. In addition, it modifies views on the mechanism of action of acetaminophen in pain management as sulfated sex hormones can function as neurosteroids and modify nociceptive thresholds.

Conservation strategies for understanding and combating the primate bushmeat trade on Bioko Island, Equatorial Guinea.

Bioko Island, Equatorial Guinea is among the important places in Africa for the conservation of primates, but a cultural preference for bushmeat and a lack of effective law enforcement has encouraged commercial bushmeat hunting, threatening the survival of the remaining primate population. For over 13 years, we collected bushmeat market data in the Malabo market, recording over 35,000 primate carcasses, documenting "mardi gras" consumption patterns, seasonal carcass availability, and negative effects resulting from government intervention. We also conducted forest surveys throughout Bioko's two protected areas in order to localize and quantify primate populations and hunting pressure. Using these data, we were able to document the significant negative impact bushmeat hunting had on monkey populations, estimate which species are most vulnerable to hunting, and develop ecological niche models to approximate the distribution of each of Bioko's diurnal primate species. These results also have allowed for the identification of primate hotspots, such as the critically important southwest region of the Gran Caldera Scientific Reserve, and thus, priority areas for conservation on Bioko, leading to more comprehensive conservation recommendations. Current and future efforts now focus on bridging the gap between investigators and legislators in order to develop and effectively implement a management plan for Bioko's Gran Caldera Scientific Reserve and to develop a targeted educational campaign to reduce demand by changing consumer attitudes toward bushmeat. Using this multidisciplinary approach, informed by biological, socioeconomic, and cultural research, there may yet be a positive future for the primates of Bioko.

Why Are Nigeria-Cameroon Chimpanzees (Pan troglodytes ellioti) Free of SIVcpz Infection?

Simian immunodeficiency virus (SIV) naturally infects two subspecies of chimpanzee: Pan troglodytes troglodytes from Central Africa (SIVcpzPtt) and P. t. schweinfurtii from East Africa (SIVcpzPts), but is absent in P. t. verus from West Africa and appears to be absent in P. t. ellioti inhabiting Nigeria and western Cameroon. One explanation for this pattern is that P. t. troglodytes and P. t schweinfurthii may have acquired SIVcpz after their divergence from P. t. verus and P. t. ellioti. However, all of the subspecies, except P. t. verus, still occasionally exchange migrants making the absence of SIVcpz in P. t. ellioti puzzling. Sampling of P. t. ellioti has been minimal to date, particularly along the banks of the Sanaga River, where its range abuts that of P. t. troglodytes. This study had three objectives. First, we extended the sampling of SIVcpz across the range of chimpanzees north of the Sanaga River to address whether under-sampling might account for the absence of evidence for SIVcpz infection in P. t. ellioti. Second, we investigated how environmental variation is associated with the spread and prevalence of SIVcpz in the two chimpanzee subspecies inhabiting Cameroon since environmental variation has been shown to contribute to their divergence from one another. Finally, we compared the prevalence and distribution of SIVcpz with that of Simian Foamy Virus (SFV) to examine the role of ecology and behavior in shaping the distribution of diseases in wild host populations. The dataset includes previously published results on SIVcpz infection and SFVcpz as well as newly collected data, and represents over 1000 chimpanzee fecal samples from 41 locations across Cameroon. Results revealed that none of the 181 P. t. ellioti fecal samples collected across the range of P. t. ellioti tested positive for SIVcpz. In addition, species distribution models suggest that environmental variation contributes to differences in the distribution and prevalence of SIVcpz and SFVcpz. The ecological niches of these two viruses are largely non-overlapping, although stronger statistical support for this conclusion will require more sampling. Overall this study demonstrates that SIVcpz infection is absent or very rare in P. t. ellioti, despite multiple opportunities for transmission. The reasons for its absence remain unclear, but might be explained by one or more factors, including environmental variation, viral competition, and/or local adaptation-all of which should be explored in greater detail through continued surveillance of this region.

Plasma metabolomic profiles enhance precision medicine for volunteers of normal health.

Precision medicine, taking account of human individuality in genes, environment, and lifestyle for early disease diagnosis and individualized therapy, has shown great promise to transform medical care. Nontargeted metabolomics, with the ability to detect broad classes of biochemicals, can provide a comprehensive functional phenotype integrating clinical phenotypes with genetic and nongenetic factors. To test the application of metabolomics in individual diagnosis, we conducted a metabolomics analysis on plasma samples collected from 80 volunteers of normal health with complete medical records and three-generation pedigrees. Using a broad-spectrum metabolomics platform consisting of liquid chromatography and GC coupled with MS, we profiled nearly 600 metabolites covering 72 biochemical pathways in all major branches of biosynthesis, catabolism, gut microbiome activities, and xenobiotics. Statistical analysis revealed a considerable range of variation and potential metabolic abnormalities across the individuals in this cohort. Examination of the convergence of metabolomics profiles with whole-exon sequences (WESs) provided an effective approach to assess and interpret clinical significance of genetic mutations, as shown in a number of cases, including fructose intolerance, xanthinuria, and carnitine deficiency. Metabolic abnormalities consistent with early indications of diabetes, liver dysfunction, and disruption of gut microbiome homeostasis were identified in several volunteers. Additionally, diverse metabolic responses to medications among the volunteers may assist to identify therapeutic effects and sensitivity to toxicity. The results of this study demonstrate that metabolomics could be an effective approach to complement next generation sequencing (NGS) for disease risk analysis, disease monitoring, and drug management in our goal toward precision care.

A comparison of aggregate p-value methods and multivariate statistics for self-contained tests of metabolic pathway analysis.

For pathway analysis of genomic data, the most common methods involve combining p-values from individual statistical tests. However, there are several multivariate statistical methods that can be used to test whether a pathway has changed. Because of the large number of variables and pathway sizes in genomics data, some of these statistics cannot be computed. However, in metabolomics data, the number of variables and pathway sizes are typically much smaller, making such computations feasible. Of particular interest is being able to detect changes in pathways that may not be detected for the individual variables. We compare the performance of both the p-value methods and multivariate statistics for self-contained tests with an extensive simulation study and a human metabolomics study. Permutation tests, rather than asymptotic results are used to assess the statistical significance of the pathways. Furthermore, both one and two-sided alternatives hypotheses are examined. From the human metabolomic study, many pathways were statistically significant, although the majority of the individual variables in the pathway were not. Overall, the p-value methods perform at least as well as the multivariate statistics for these scenarios.

Environmental variation and rivers govern the structure of chimpanzee genetic diversity in a biodiversity hotspot.

BACKGROUND: The mechanisms that underlie the diversification of tropical animals remain poorly understood, but new approaches that combine geo-spatial modeling with spatially explicit genetic data are providing fresh insights on this topic. Data about the diversification of tropical mammals remain particularly sparse, and vanishingly few opportunities exist to study endangered large mammals that increasingly exist only in isolated pockets. The chimpanzees of Cameroon represent a unique opportunity to examine the mechanisms that promote genetic differentiation in tropical mammals because the region is home to two chimpanzee subspecies: Pan troglodytes ellioti and P. t. trogolodytes. Their ranges converge in central Cameroon, which is a geographically, climatically and environmentally complex region that presents an unparalleled opportunity to examine the roles of rivers and/or environmental variation in influencing the evolution of chimpanzee populations. RESULTS: We analyzed microsatellite genotypes and mtDNA HVRI sequencing data from wild chimpanzees sampled at a fine geographic scale across Cameroon and eastern Nigeria using a spatially explicit approach based upon Generalized Dissimilarity Modeling. Both the Sanaga River and environmental variation were found to contribute to driving separation of the subspecies. The importance of environmental variation differed among subspecies. Gene-environment associations were weak in P. t. troglodytes, whereas environmental variation was found to play a much larger role in shaping patterns of genetic differentiation in P. t. ellioti. CONCLUSIONS: We found that both the Sanaga River and environmental variation likely play a role in shaping patterns of chimpanzee genetic diversity. Future studies using single nucleotide polymorphism (SNP) data are necessary to further understand how rivers and environmental variation contribute to shaping patterns of genetic variation in chimpanzees.

Chimpanzee population structure in Cameroon and Nigeria is associated with habitat variation that may be lost under climate change.

BACKGROUND: The Nigeria-Cameroon chimpanzee (Pan troglodytes ellioti) is found in the Gulf of Guinea biodiversity hotspot located in western equatorial Africa. This subspecies is threatened by habitat fragmentation due to logging and agricultural development, hunting for the bushmeat trade, and possibly climate change. Although P. t. ellioti appears to be geographically separated from the neighboring central chimpanzee (P. t. troglodytes) by the Sanaga River, recent population genetics studies of chimpanzees from across this region suggest that additional factors may also be important in their separation. The main aims of this study were: 1) to model the distribution of suitable habitat for P. t. ellioti across Cameroon and Nigeria, and P. t. troglodytes in southern Cameroon, 2) to determine which environmental factors best predict their optimal habitats, and 3) to compare modeled niches and test for their levels of divergence from one another. A final aim of this study was to examine the ways that climate change might impact suitable chimpanzee habitat across the region under various scenarios. RESULTS: Ecological niche models (ENMs) were created using the software package Maxent for the three populations of chimpanzees that have been inferred to exist in Cameroon and eastern Nigeria: (i) P. t. troglodytes in southern Cameroon, (ii) P. t. ellioti in northwestern Cameroon, and (iii) P. t. ellioti in central Cameroon. ENMs for each population were compared using the niche comparison test in ENMtools, which revealed complete niche divergence with very little geographic overlap of suitable habitat between populations. CONCLUSIONS: These findings suggest that a positive relationship may exist between environmental variation and the partitioning of genetic variation found in chimpanzees across this region. ENMs for each population were also projected under three different climate change scenarios for years 2020, 2050, and 2080. Suitable habitat of P. t. ellioti in northwest Cameroon / eastern Nigeria is expected to remain largely unchanged through 2080 in all considered scenarios. In contrast, P. t. ellioti in central Cameroon, which represents half of the population of this subspecies, is expected to experience drastic reductions in its ecotone habitat over the coming century.

The population genetics of wild chimpanzees in Cameroon and Nigeria suggests a positive role for selection in the evolution of chimpanzee subspecies.

BACKGROUND: Chimpanzees (Pan troglodytes) can be divided into four subspecies. Substantial phylogenetic evidence suggests that these subspecies can be grouped into two distinct lineages: a western African group that includes P. t. verus and P. t. ellioti and a central/eastern African group that includes P. t. troglodytes and P. t. schweinfurthii. The geographic division of these two lineages occurs in Cameroon, where the rages of P. t. ellioti and P. t. troglodytes appear to converge at the Sanaga River. Remarkably, few population genetic studies have included wild chimpanzees from this region. RESULTS: We analyzed microsatellite genotypes of 187 wild, unrelated chimpanzees, and mitochondrial control region sequencing data from 604 chimpanzees. We found that chimpanzees in Cameroon and eastern Nigeria comprise at least two, and likely three populations. Both the mtDNA and microsatellite data suggest that there is a primary separation of P. t. troglodytes in southern Cameroon from P. t. ellioti north and west of the Sanaga River. These two populations split ~200-250 thousand years ago (kya), but have exchanged one migrant per generation since separating. In addition, P. t. ellioti consists of two populations that split from one another ~4 kya. One population is located in the rainforests of western Cameroon and eastern Nigeria, whereas the second population appears to be confined to a savannah-woodland mosaic in central Cameroon. CONCLUSIONS: Our findings suggest that there are as many as three genetically distinct populations of chimpanzees in Cameroon and eastern Nigeria. P. t. troglodytes in southern Cameroon comprises one population that is separated from two populations of P. t. ellioti in western and central Cameroon, respectively. P. t. ellioti and P. t. troglodytes appear to be characterized by a pattern of isolation-with-migration, and thus, we propose that neutral processes alone can not explain the differentiation of P. t. ellioti and P. t. troglodytes.

Bladder cancer biomarker discovery using global metabolomic profiling of urine.

Bladder cancer (BCa) is a common malignancy worldwide and has a high probability of recurrence after initial diagnosis and treatment. As a result, recurrent surveillance, primarily involving repeated cystoscopies, is a critical component of post diagnosis patient management. Since cystoscopy is invasive, expensive and a possible deterrent to patient compliance with regular follow-up screening, new non-invasive technologies to aid in the detection of recurrent and/or primary bladder cancer are strongly needed. In this study, mass spectrometry based metabolomics was employed to identify biochemical signatures in human urine that differentiate bladder cancer from non-cancer controls. Over 1000 distinct compounds were measured including 587 named compounds of known chemical identity. Initial biomarker identification was conducted using a 332 subject sample set of retrospective urine samples (cohort 1), which included 66 BCa positive samples. A set of 25 candidate biomarkers was selected based on statistical significance, fold difference and metabolic pathway coverage. The 25 candidate biomarkers were tested against an independent urine sample set (cohort 2) using random forest analysis, with palmitoyl sphingomyelin, lactate, adenosine and succinate providing the strongest predictive power for differentiating cohort 2 cancer from non-cancer urines. Cohort 2 metabolite profiling revealed additional metabolites, including arachidonate, that were higher in cohort 2 cancer vs. non-cancer controls, but were below quantitation limits in the cohort 1 profiling. Metabolites related to lipid metabolism may be especially interesting biomarkers. The results suggest that urine metabolites may provide a much needed non-invasive adjunct diagnostic to cystoscopy for detection of bladder cancer and recurrent disease management.

Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome.

Genetically modified (GM) crops currently constitute a significant and growing part of agriculture.An important aspect of GM crop adoption is to demonstrate safety; identifying differences in end points with respect to conventional crops is a part of the safety assessment process [corrected]. Untargeted metabolomics has the ability to profile diverse classes of metabolites and thus could be an adjunct for identification of differences between the GM crop and its conventional counterpart [corrected].To account for environmental effects and introgression of GM traits into diverse genetic backgrounds, we propose that the assessment for GM crop metabolic composition should be understood within the context of the natural variation for the crop. Using a non-targeted metabolomics platform, we profiled 169 metabolites and established their dynamic ranges from the seeds of 49 conventional soybean lines representing the current commercial genetic diversity. We further demonstrated that the metabolome of a GM line had no significant deviation from natural variation within the soybean metabolome, with the exception of changes in the targeted engineered pathway.

Mining the unknown: a systems approach to metabolite identification combining genetic and metabolic information.

Recent genome-wide association studies (GWAS) with metabolomics data linked genetic variation in the human genome to differences in individual metabolite levels. A strong relevance of this metabolic individuality for biomedical and pharmaceutical research has been reported. However, a considerable amount of the molecules currently quantified by modern metabolomics techniques are chemically unidentified. The identification of these "unknown metabolites" is still a demanding and intricate task, limiting their usability as functional markers of metabolic processes. As a consequence, previous GWAS largely ignored unknown metabolites as metabolic traits for the analysis. Here we present a systems-level approach that combines genome-wide association analysis and Gaussian graphical modeling with metabolomics to predict the identity of the unknown metabolites. We apply our method to original data of 517 metabolic traits, of which 225 are unknowns, and genotyping information on 655,658 genetic variants, measured in 1,768 human blood samples. We report previously undescribed genotype-metabotype associations for six distinct gene loci (SLC22A2, COMT, CYP3A5, CYP2C18, GBA3, UGT3A1) and one locus not related to any known gene (rs12413935). Overlaying the inferred genetic associations, metabolic networks, and knowledge-based pathway information, we derive testable hypotheses on the biochemical identities of 106 unknown metabolites. As a proof of principle, we experimentally confirm nine concrete predictions. We demonstrate the benefit of our method for the functional interpretation of previous metabolomics biomarker studies on liver detoxification, hypertension, and insulin resistance. Our approach is generic in nature and can be directly transferred to metabolomics data from different experimental platforms.

Evidence from Cameroon reveals differences in the genetic structure and histories of chimpanzee populations.

The history of the genus Pan is a topic of enduring interest. Chimpanzees (Pan troglodytes) are often divided into subspecies, but the population structure and genetic history of chimpanzees across Africa remain unclear. Some population genetics studies have led to speculation that, until recently, this species constituted a single population with ongoing gene flow across its range, which resulted in a continuous gradient of allele frequencies. Chimpanzees, designated here as P. t. ellioti, occupy the Gulf of Guinea region that spans southern Nigeria and western Cameroon at the center of the distribution of this species. Remarkably, few studies have included individuals from this region, hindering the examination of chimpanzee population structure across Africa. Here, we analyzed microsatellite genotypes of 94 chimpanzees, including 32 designated as P. t. ellioti. We find that chimpanzees fall into three major populations: (i) Upper Guinea in western Africa (P. t. verus); (ii) the Gulf of Guinea region (P. t. ellioti); and (iii) equatorial Africa (P. t. troglodytes and P. t. schweinfurthii). Importantly, the Gulf of Guinea population is significantly different genetically from the others, sharing a last common ancestor with the populations in Upper Guinea ~0.46 million years ago (mya) and equatorial Africa ~0.32 mya. Equatorial chimpanzees are subdivided into up to three populations occupying southern Cameroon, central Africa, and eastern Africa, which may have constituted a single population until ~0.10-0.11 mya. Finally, occasional hybridization may be occurring between the Gulf of Guinea and southern Cameroon populations.