Showing papers by "Michael Snyder published in 2016"
TL;DR: The chromatin accessibility and transcriptional landscapes in 13 human primary blood cell types that span the hematopoietic hierarchy are defined and 'enhancer cytometry' is enabled for enumeration of pure cell types from complex populations.
Abstract: We define the chromatin accessibility and transcriptional landscapes in 13 human primary blood cell types that span the hematopoietic hierarchy. Exploiting the finding that the enhancer landscape better reflects cell identity than mRNA levels, we enable 'enhancer cytometry' for enumeration of pure cell types from complex populations. We identify regulators governing hematopoietic differentiation and further show the lineage ontogeny of genetic elements linked to diverse human diseases. In acute myeloid leukemia (AML), chromatin accessibility uncovers unique regulatory evolution in cancer cells with a progressively increasing mutation burden. Single AML cells exhibit distinctive mixed regulome profiles corresponding to disparate developmental stages. A method to account for this regulatory heterogeneity identified cancer-specific deviations and implicated HOX factors as key regulators of preleukemic hematopoietic stem cell characteristics. Thus, regulome dynamics can provide diverse insights into hematopoietic development and disease.
888 citations
TL;DR: A view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC is provided.
728 citations
TL;DR: It is suggested that automatically derived image features can predict the prognosis of lung cancer patients and thereby contribute to precision oncology.
Abstract: Lung cancer is the most prevalent cancer worldwide, and histopathological assessment is indispensable for its diagnosis. However, human evaluation of pathology slides cannot accurately predict patients' prognoses. In this study, we obtain 2,186 haematoxylin and eosin stained histopathology whole-slide images of lung adenocarcinoma and squamous cell carcinoma patients from The Cancer Genome Atlas (TCGA), and 294 additional images from Stanford Tissue Microarray (TMA) Database. We extract 9,879 quantitative image features and use regularized machine-learning methods to select the top features and to distinguish shorter-term survivors from longer-term survivors with stage I adenocarcinoma (P<0.003) or squamous cell carcinoma (P=0.023) in the TCGA data set. We validate the survival prediction framework with the TMA cohort (P<0.036 for both tumour types). Our results suggest that automatically derived image features can predict the prognosis of lung cancer patients and thereby contribute to precision oncology. Our methods are extensible to histopathology images of other organs.
726 citations
TL;DR: This work recommends five conceptual 'pillars' for antibody validation to be used in an application-specific manner and provides guidelines that ensure antibody reproducibility.
Abstract: We convened an ad hoc International Working Group for Antibody Validation in order to formulate the best approaches for validating antibodies used in common research applications and to provide guidelines that ensure antibody reproducibility. We recommend five conceptual 'pillars' for antibody validation to be used in an application-specific manner.
423 citations
TL;DR: It is concluded that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa, but that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.
Abstract: The Out-of-Africa (OOA) dispersal ∼ 50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.
238 citations
TL;DR: Results reveal how disease-causing missense mutations can disrupt transcriptional cooperativity, leading to aberrant chromatin states and cellular dysfunction, including those related to morphogenetic defects.
196 citations
Agriculture and Agri-Food Canada1, University of Western Ontario2, Chinese Academy of Sciences3, Fujian Agriculture and Forestry University4, University of California, Riverside5, Hebei Normal University6, Carnegie Institution for Science7, Zhejiang University8, Stanford University9, National Taiwan University10, University of California, San Francisco11, Sun Yat-sen University12
TL;DR: This work identifies a new genomic targeting mechanism for an H3K27 demethylase and demonstrates its key role in recruiting the BRM chromatin remodeler.
Abstract: Yuhai Cui and colleagues report that the H3K27 demethylase REF6 targets genomic loci containing a specific DNA motif via its zinc-finger domains. They show that REF6 facilitates the recruitment of BRM and that deleting the DNA motif from a target gene in Arabidopsis makes it inaccessible to REF6.
168 citations
01 Jun 2016
TL;DR: In this article, a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer was provided, such as how different copy-number alterna-tions in the Proteome, the proteins associated with chromosomal instability, the sets of signalingpathways that diverse genome rearrangements converge on, and the ones associated with short overall survival.
Abstract: To provide a detailed analysis of the molecular com-ponents and underlying mechanisms associatedwith ovarian cancer, we performed a comprehensivemass-spectrometry-based proteomic characteriza-tion of 174 ovarian tumors previously analyzed byThe Cancer Genome Atlas (TCGA), of which 169were high-grade serous carcinomas (HGSCs). Inte-grating our proteomic measurements with thegenomic data yielded a number of insights into dis-ease, such as how different copy-number alterna-tionsinfluencetheproteome,theproteinsassociatedwith chromosomal instability, the sets of signalingpathways that diverse genome rearrangementsconverge on, and the ones most associated withshort overall survival. Specific protein acetylationsassociated with homologous recombination defi-ciency suggest a potential means for stratifying pa-tients for therapy. In addition to providing a valuableresource,thesefindingsprovideaviewofhowtheso-maticgenomedrivesthecancerproteomeandasso-ciations between protein and post-translationalmodification levels and clinical outcomes in HGSC.
160 citations
TL;DR: It is shown that patient-specific induced pluripotent stem cell-derived cardiomyocytes generated from LVNC patients carrying a mutation in the cardiac transcription factor TBX20 recapitulate a key aspect of the pathological phenotype at the single-cell level and this was associated with perturbed transforming growth factor beta (TGF-β) signalling.
Abstract: Left ventricular non-compaction (LVNC) is the third most prevalent cardiomyopathy in children and its pathogenesis has been associated with the developmental defect of the embryonic myocardium. We show that patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) generated from LVNC patients carrying a mutation in the cardiac transcription factor TBX20 recapitulate a key aspect of the pathological phenotype at the single-cell level and this was associated with perturbed transforming growth factor beta (TGF-β) signalling. LVNC iPSC-CMs have decreased proliferative capacity due to abnormal activation of TGF-β signalling. TBX20 regulates the expression of TGF-β signalling modifiers including one known to be a genetic cause of LVNC, PRDM16, and genome editing of PRDM16 caused proliferation defects in iPSC-CMs. Inhibition of TGF-β signalling and genome correction of the TBX20 mutation were sufficient to reverse the disease phenotype. Our study demonstrates that iPSC-CMs are a useful tool for the exploration of pathological mechanisms underlying poorly understood cardiomyopathies including LVNC.
136 citations
TL;DR: In this paper, human induced pluripotent stem cells (hiPSCs) were used to study pharmacological and toxicological responses in patient-specific cardiomyocytes (CMs) and may serve as preclinical platforms for precision medicine.
126 citations
TL;DR: Mannose is identified as one of the best plasma metabolites in explaining the variance in obesity-independent IR and is validated by detecting mannose levels in the plasma of the lean and obese subjects.
TL;DR: A large number of patients with common, complex conditions like obesity, inflammation, and insulin resistance, which underlie a host of metabolic diseases are being treated with genome-based approaches.
Abstract: Precision medicine utilizes genomic and other data to optimize and personalize treatment. Although more than 2,500 genetic tests are currently available, largely for extreme and/or rare phenotypes, the question remains whether this approach can be used for the treatment of common, complex conditions like obesity, inflammation, and insulin resistance, which underlie a host of metabolic diseases.
TL;DR: This work presents an analysis of a human gut microbiome using TruSeq synthetic long reads combined with computational tools for metagenomic long-read assembly, variant calling and haplotyping (Nanoscope and Lens), identifying 178 bacterial species.
Abstract: Identifying bacterial strains in metagenome and microbiome samples using computational analyses of short-read sequences remains a difficult problem. Here, we present an analysis of a human gut microbiome using TruSeq synthetic long reads combined with computational tools for metagenomic long-read assembly, variant calling and haplotyping (Nanoscope and Lens). Our analysis identifies 178 bacterial species, of which 51 were not found using shotgun reads alone. We recover bacterial contigs that comprise multiple operons, including 22 contigs of >1 Mbp. Furthermore, we observe extensive intraspecies variation within microbial strains in the form of haplotypes that span up to hundreds of Kbp. Incorporation of synthetic long-read sequencing technology with standard short-read approaches enables more precise and comprehensive analyses of metagenomic samples.
TL;DR: The techniques used for tumor omics analysis are summarized, the key findings in cancer omics studies are recapitulated, and areas requiring further research on precision oncology are pointed to.
TL;DR: D density-based clustering methods in 21 tumor types are employed to detect variably sized significantly mutated regions (SMRs), revealing recurrent alterations across a spectrum of coding and noncoding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼15% of specific tumor types.
Abstract: Cancer sequencing studies have primarily identified cancer driver genes by the accumulation of protein-altering mutations. An improved method would be annotation independent, sensitive to unknown distributions of functions within proteins and inclusive of noncoding drivers. We employed density-based clustering methods in 21 tumor types to detect variably sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and noncoding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼ 15% of specific tumor types. SMRs demonstrate spatial clustering of alterations in molecular domains and at interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated across tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest that mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally agnostic driver identification.
TL;DR: Findings identify EPHB4 as a critical regulator of early lymphatic vascular development and demonstrate that mutations in the gene can cause an autosomal dominant form of LRHF that is associated with a high mortality rate.
Abstract: Hydrops fetalis describes fluid accumulation in at least 2 fetal compartments, including abdominal cavities, pleura, and pericardium, or in body tissue. The majority of hydrops fetalis cases are nonimmune conditions that present with generalized edema of the fetus, and approximately 15% of these nonimmune cases result from a lymphatic abnormality. Here, we have identified an autosomal dominant, inherited form of lymphatic-related (nonimmune) hydrops fetalis (LRHF). Independent exome sequencing projects on 2 families with a history of in utero and neonatal deaths associated with nonimmune hydrops fetalis uncovered 2 heterozygous missense variants in the gene encoding Eph receptor B4 (EPHB4). Biochemical analysis determined that the mutant EPHB4 proteins are devoid of tyrosine kinase activity, indicating that loss of EPHB4 signaling contributes to LRHF pathogenesis. Further, inactivation of Ephb4 in lymphatic endothelial cells of developing mouse embryos led to defective lymphovenous valve formation and consequent subcutaneous edema. Together, these findings identify EPHB4 as a critical regulator of early lymphatic vascular development and demonstrate that mutations in the gene can cause an autosomal dominant form of LRHF that is associated with a high mortality rate.
TL;DR: Investigations revealed that the whole PRV genome is utilized for transcription, including both DNA strands in all coding and intergenic regions, and genome-wide occurrence of transcript overlaps suggests a crosstalk between genes through a network formed by interacting transcriptional machineries with a potential function in the control of gene expression.
Abstract: Whole transcriptome studies have become essential for understanding the complexity of genetic regulation. However, the conventionally applied short-read sequencing platforms cannot be used to reliably distinguish between many transcript isoforms. The Pacific Biosciences (PacBio) RS II platform is capable of reading long nucleic acid stretches in a single sequencing run. The pseudorabies virus (PRV) is an excellent system to study herpesvirus gene expression and potential interactions between the transcriptional units. In this work, non-amplified and amplified isoform sequencing protocols were used to characterize the poly(A+) fraction of the lytic transcriptome of PRV, with the aim of a complete transcriptional annotation of the viral genes. The analyses revealed a previously unrecognized complexity of the PRV transcriptome including the discovery of novel protein-coding and non-coding genes, novel mono- and polycistronic transcription units, as well as extensive transcriptional overlaps between neighboring and distal genes. This study identified non-coding transcripts overlapping all three replication origins of the PRV, which might play a role in the control of DNA synthesis. We additionally established the relative expression levels of gene products. Our investigations revealed that the whole PRV genome is utilized for transcription, including both DNA strands in all coding and intergenic regions. The genome-wide occurrence of transcript overlaps suggests a crosstalk between genes through a network formed by interacting transcriptional machineries with a potential function in the control of gene expression.
TL;DR: The results indicate that cellular origin may influence lineage differentiation propensity of human iPSCs; hence, the somatic memory carried by early passage iPSC should be carefully considered before clinical translation.
Abstract: Human induced pluripotent stem cells (iPSCs) can be derived from various types of somatic cells by transient overexpression of 4 Yamanaka factors (OCT4, SOX2, C-MYC, and KLF4). Patient-specific iPSC derivatives (e.g., neuronal, cardiac, hepatic, muscular, and endothelial cells [ECs]) hold great promise in drug discovery and regenerative medicine. In this study, we aimed to evaluate whether the cellular origin can affect the differentiation, in vivo behavior, and single-cell gene expression signatures of human iPSC–derived ECs. We derived human iPSCs from 3 types of somatic cells of the same individuals: fibroblasts (FB-iPSCs), ECs (EC-iPSCs), and cardiac progenitor cells (CPC-iPSCs). We then differentiated them into ECs by sequential administration of Activin, BMP4, bFGF, and VEGF. EC-iPSCs at early passage (10 < P < 20) showed higher EC differentiation propensity and gene expression of EC-specific markers (PECAM1 and NOS3) than FB-iPSCs and CPC-iPSCs. In vivo transplanted EC-iPSC–ECs were recovered with a higher percentage of CD31+ population and expressed higher EC-specific gene expression markers (PECAM1, KDR, and ICAM) as revealed by microfluidic single-cell quantitative PCR (qPCR). In vitro EC-iPSC–ECs maintained a higher CD31+ population than FB-iPSC–ECs and CPC-iPSC–ECs with long-term culturing and passaging. These results indicate that cellular origin may influence lineage differentiation propensity of human iPSCs; hence, the somatic memory carried by early passage iPSCs should be carefully considered before clinical translation.
TL;DR: It is suggested that only a very limited portion of the proteome becomes targeted by the immune system in APS1, which contrasts the broad defect of thymic presentation associated with AIRE-deficiency and raises novel questions what other factors are needed for break of tolerance.
Abstract: Autoimmune polyendocrine syndrome type 1 (APS1) is a monogenic disorder that features multiple autoimmune disease manifestations. It is caused by mutations in the Autoimmune regulator (AIRE) gene, which promote thymic display of thousands of peripheral tissue antigens in a process critical for establishing central immune tolerance. We here used proteome arrays to perform a comprehensive study of autoimmune targets in APS1. Interrogation of established autoantigens revealed highly reliable detection of autoantibodies, and by exploring the full panel of more than 9000 proteins we further identified MAGEB2 and PDILT as novel major autoantigens in APS1. Our proteome-wide assessment revealed a marked enrichment for tissue-specific immune targets, mirroring AIRE’s selectiveness for this category of genes. Our findings also suggest that only a very limited portion of the proteome becomes targeted by the immune system in APS1, which contrasts the broad defect of thymic presentation associated with AIRE-deficiency and raises novel questions what other factors are needed for break of tolerance.
TL;DR: Simul-seq provides a new streamlined approach for generating comprehensive genome and transcriptome profiles from limited quantities of clinically relevant samples and is applied to laser-capture-microdissected esophageal adenocarcinoma tissue, revealing a highly aneuploid tumor genome with extensive blocks of increased homozygosity and corresponding increases in allele-specific expression.
Abstract: Paired DNA and RNA profiling is increasingly employed in genomics research to uncover molecular mechanisms of disease and to explore personal genotype and phenotype correlations. Here, we introduce Simul-seq, a technique for the production of high-quality whole-genome and transcriptome sequencing libraries from small quantities of cells or tissues. We apply the method to laser-capture-microdissected esophageal adenocarcinoma tissue, revealing a highly aneuploid tumor genome with extensive blocks of increased homozygosity and corresponding increases in allele-specific expression. Among this widespread allele-specific expression, we identify germline polymorphisms that are associated with response to cancer therapies. We further leverage this integrative data to uncover expressed mutations in several known cancer genes as well as a recurrent mutation in the motor domain of KIF3B that significantly affects kinesin-microtubule interactions. Simul-seq provides a new streamlined approach for generating comprehensive genome and transcriptome profiles from limited quantities of clinically relevant samples.
TL;DR: Effects of cell cycle progression on the expression of lineage specific genes in precursor cells are revealed, and it is suggested that hematopoietic stress changes the balance of renewal and differentiation in these homeostatic cells.
Abstract: Molecular changes underlying stem cell differentiation are of fundamental interest. scRNA-seq on murine hematopoietic stem cells (HSC) and their progeny MPP1 separated the cells into 3 main clusters with distinct features: active, quiescent, and an un-characterized cluster. Induction of anemia resulted in mobilization of the quiescent to the active cluster and of the early to later stage of cell cycle, with marked increase in expression of certain transcription factors (TFs) while maintaining expression of interferon response genes. Cells with surface markers of long term HSC increased the expression of a group of TFs expressed highly in normal cycling MPP1 cells. However, at least Id1 and Hes1 were significantly activated in both HSC and MPP1 cells in anemic mice. Lineage-specific genes were differently expressed between cells, and correlated with the cell cycle stages with a specific augmentation of erythroid related genes in the G2/M phase. Most lineage specific TFs were stochastically expressed in the early precursor cells, but a few, such as Klf1, were detected only at very low levels in few precursor cells. The activation of these factors may correlate with stages of differentiation. This study reveals effects of cell cycle progression on the expression of lineage specific genes in precursor cells, and suggests that hematopoietic stress changes the balance of renewal and differentiation in these homeostatic cells.
TL;DR: Findings further support the East Asian origins of the RNF213 (p.R4810K) variant and more fully describe the genetic landscape of multiethnic MMD, revealing novel, alternative candidate variants and genes that may be important in MMD etiology and diagnosis.
Abstract: Moyamoya disease (MMD) is a rare disorder characterized by cerebrovascular occlusion and development of hemorrhage-prone collateral vessels. Approximately 10–12% of cases are familial, with a presumed low penetrance autosomal dominant pattern of inheritance. Diagnosis commonly occurs only after clinical presentation. The recent identification of the RNF213 founder mutation (p.R4810K) in the Asian population has made a significant contribution, but the etiology of this disease remains unclear. To further develop the variant landscape of MMD, we performed high-depth whole exome sequencing of 125 unrelated, predominantly nonfamilial, ethnically diverse MMD patients in parallel with 125 internally sequenced, matched controls using the same exome and analysis platform. Three subpopulations were established: Asian, Caucasian, and non-RNF213 founder mutation cases. We provided additional support for the previously observed RNF213 founder mutation (p.R4810K) in Asian cases (P = 6.01×10−5) that was enriched among East Asians compared to Southeast Asian and Pacific Islander cases (P = 9.52×10−4) and was absent in all Caucasian cases. The most enriched variant in Caucasian (P = 7.93×10−4) and non-RNF213 founder mutation (P = 1.51×10−3) cases was ZXDC (p.P562L), a gene involved in MHC Class II activation. Collapsing variant methodology ranked OBSCN, a gene involved in myofibrillogenesis, as most enriched in Caucasian (P = 1.07×10−4) and non-RNF213 founder mutation cases (P = 5.31×10−5). These findings further support the East Asian origins of the RNF213 (p.R4810K) variant and more fully describe the genetic landscape of multiethnic MMD, revealing novel, alternative candidate variants and genes that may be important in MMD etiology and diagnosis.
TL;DR: Genetic factors play a significant role in the development of Bronchopulmonary dysplasia, and recent studies suggested that rare variants in genes participating in lung development pathways could contribute to BPD susceptibility.
Abstract: Purpose of reviewBronchopulmonary dysplasia (BPD) is a prevalent chronic lung disease in premature infants. Twin studies have shown strong heritability underlying this disease; however, the genetic architecture of BPD remains unclear.Recent findingsA number of studies employed different approaches t
TL;DR: It is found that Nat1 (mouse ortholog of NAT2) is co-regulated with key mitochondrial genes and Nat1 deficiency results in mitochondrial dysfunction, which may constitute a mechanistic link between this gene and IR.
TL;DR: Unlike previous assembly strategies, Architect does not require a costly subassembly step; instead it assembles genomes directly from the SLR’s underlying short reads, which it refers to as read clouds, which enables a 4- to 20-fold reduction in sequencing requirements and a 5-fold increase in assembly contiguity.
Abstract: Motivation: Despite rapid progress in sequencing technology, assembling de novo the genomes of new species as well as reconstructing complex metagenomes remains major technological challenges. New synthetic long read (SLR) technologies promise significant advances towards these goals; however, their applicability is limited by high sequencing requirements and the inability of current assembly paradigms to cope with combinations of short and long reads.
Results: Here, we introduce Architect, a new de novo scaffolder aimed at SLR technologies. Unlike previous assembly strategies, Architect does not require a costly subassembly step; instead it assembles genomes directly from the SLR’s underlying short reads, which we refer to as read clouds. This enables a 4- to 20-fold reduction in sequencing requirements and a 5-fold increase in assembly contiguity on both genomic and metagenomic datasets relative to state-of-the-art assembly strategies aimed directly at fully subassembled long reads.
Availability and Implementation: Our source code is freely available at https://github.com/kuleshov/architect.
Contact: ude.drofnats@vohseluk
TL;DR: It is demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics.
Abstract: Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P < 0.0001). We further built a least absolute shrinkage and selection operator (LASSO)-Cox proportional hazards model that stratified patients into early relapse and late relapse groups (P = 0.00013). The top proteomic features indicative of platinum response were involved in ATP synthesis pathways and Ran GTPase binding. Overall, we demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers.
18 Feb 2016
TL;DR: It is reported that the heavy isotopic forms of common elements, a universal feature of metabolites, decline in yeast cells undergoing chronological aging and Supplementation of deuterium through heavy water (D2O) uptake extends yeast chronological lifespan (CLS) by up to 85% with minimal effects on growth.
Abstract: The lifespan of yeast cells can be extended by supplying them with heavy isotopes of common elements, according to US researchers. Heavy isotopes such as deuterium–a type of hydrogen containing a neutron–exist in small quantities in natural environments, but their effects on living organisms are unclear. Michael Snyder and Xiyan Li at Stanford University showed for the first time that amino acids in yeast cells tend to contain lower levels of heavy isotopes as the cells age. They then incubated yeast cells with increased doses of ‘heavy water’ (which contains deuterium instead of hydrogen) and found that, remarkably, the yeast’s lifespan was extended by up to 85%. The researchers suggest that heavy isotopes affect biochemical reactions by strengthening molecular bonds, and suppress reactive oxygen species, thereby slowing the metabolism and prolonging life.
TL;DR: The date of October 2014 was chosen because no papers were shown on Kadmon’s website earlier than that date, which is five years after the company was founded, and the company has a responsibility to share its discoveries with the scientific community in peerreviewed journals.
Abstract: Understanding Cloud security for genomics data is challenging but a critical need. It is our observation that security requirements are often inconsistent not only across datasets but also between on-premise solutions and Cloud for the same dataset. We attempt to summarize these security requirements across a wide range of regulatory bodies from government and private sources. While we expect the implementation to be different between Clouds and evolution in implementation methodology in time, we expect these guidelines to be applicable in foreseeable future. We also note that security does not necessary provide privacy and significant effort is needed to address privacy for a research centric platform.
TL;DR: Combining genetic and metabolic information provides a unique opportunity to gain further insights on how the genetic program is translated into biological function through metabolites, and how alterations in the program associate with the onset of diseases.
Abstract: The past decade has witnessed considerable advancements in sequencing technologies, which have allowed comprehensive investigation of genetic variation of individuals at a moderate cost and within a reasonable time frame. Personalized disease risk and drug response predictions based on genomic sequences are a cornerstone of preventive precision medicine, and have also been successful at informing therapeutic decisions. However, genomics is limited in predicting the onset of most common diseases (i.e., cancer, diabetes, and cardiovascular disorders) because genetic information is mostly static and does not account for dynamic environmental (i.e., diet and lifestyle) or gut microbiota influences.
Metabolomics, the study of a large collection of metabolites, offers the advantage to measure the functional readout of activity and phenotype encoded in the genome. Hence, combining genetic and metabolic information provides a unique opportunity to gain further insights on how the genetic program is translated into biological function through metabolites, and how alterations in the program associate with the onset of diseases. This approach has already proven very useful at diagnosing and understanding the pathogenesis of rare inherited metabolic disorders. Furthermore, metabolic profiles are influenced by the environment and the gut microbes; thus metabolomics has the potential to unravel the impact of nongenetic factors on disease onset as well as reveal early biomarkers that may improve risk assessment and diagnosis of complex diseases. Thanks to rapid improvements in technology, mass spectrometry–based metabolomics can now robustly profile a broad spectrum of metabolites at a relatively low cost (1).
The concept that genetic variations can be captured at the metabolite level in a population was first demonstrated in 2008 by Gieger et al. (2). That study gave a glimpse of the usefulness of combining genetic information with metabolic traits to understand the pathogenesis of common diseases and the influence of environment. In 2015, Guo …