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Can genomics deliver climate-change ready crops?
Varshney, RK, Singh, VK, Kumar, A, Powell, W, Sorrells, ME
Current opinion in plant biology. 2018;(Pt B):205-211
Abstract
Development of climate resilient crops with accelerating genetic gains in crops will require integration of different disciplines/technologies, to see the impact in the farmer's field. In this review, we summarize how we are utilizing our germplasm collections to identify superior alleles/haplotypes through NGS based sequencing approaches and how genomics-enabled technologies together with precise phenotyping are being used in crop breeding. Pre-breeding and genomics-assisted breeding approaches are contributing to the more efficient development of climate-resilient crops. It is anticipated that the integration of several disciplines/technologies will result in the delivery of climate change ready crops in less time.
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Current advances in chickpea genomics: applications and future perspectives.
Jha, UC
Plant cell reports. 2018;(7):947-965
Abstract
Chickpea genomics promises to illuminate our understanding of genome organization, structural variations, evolutionary and domestication-related insights and fundamental biology of legume crops. Unprecedented advancements of next generation sequencing (NGS) technologies have enabled in decoding of multiple chickpea genome sequences and generating huge genomic resources in chickpea both at functional and structural level. This review is aimed to update the current progress of chickpea genomics ranging from high density linkage map development, genome-wide association studies (GWAS), functional genomics resources for various traits, emerging role of abiotic stress responsive coding and non-coding RNAs after the completion of draft chickpea genome sequences. Additionally, the current efforts of whole genome re-sequencing (WGRS) approach of global chickpea germplasm to capture the global genetic diversity existing in the historically released varieties across the world and increasing the resolution of the previously identified candidate gene(s) of breeding importance have been discussed. Thus, the outcomes of these genomics resources will assist in genomics-assisted selection and facilitate breeding of climate-resilient chickpea cultivars for sustainable agriculture.
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Genomic Approach to Understand the Association of DNA Repair with Longevity and Healthy Aging Using Genomic Databases of Oldest-Old Population.
Kim, YJ, Kim, HS, Seo, YR
Oxidative medicine and cellular longevity. 2018;:2984730
Abstract
Aged population is increasing worldwide due to the aging process that is inevitable. Accordingly, longevity and healthy aging have been spotlighted to promote social contribution of aged population. Many studies in the past few decades have reported the process of aging and longevity, emphasizing the importance of maintaining genomic stability in exceptionally long-lived population. Underlying reason of longevity remains unclear due to its complexity involving multiple factors. With advances in sequencing technology and human genome-associated approaches, studies based on population-based genomic studies are increasing. In this review, we summarize recent longevity and healthy aging studies of human population focusing on DNA repair as a major factor in maintaining genome integrity. To keep pace with recent growth in genomic research, aging- and longevity-associated genomic databases are also briefly introduced. To suggest novel approaches to investigate longevity-associated genetic variants related to DNA repair using genomic databases, gene set analysis was conducted, focusing on DNA repair- and longevity-associated genes. Their biological networks were additionally analyzed to grasp major factors containing genetic variants of human longevity and healthy aging in DNA repair mechanisms. In summary, this review emphasizes DNA repair activity in human longevity and suggests approach to conduct DNA repair-associated genomic study on human healthy aging.
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'Democratized' genomic enzymology web tools for functional assignment.
Zallot, R, Oberg, NO, Gerlt, JA
Current opinion in chemical biology. 2018;:77-85
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Abstract
The protein databases contain an exponentially growing number of sequences as a result of the recent increase in ease and decrease in cost of genome sequencing. The rate of data accumulation far exceeds the rate of functional studies, producing an increase in genomic 'dark matter', sequences for which no precise and validated function is defined. Publicly accessible, that is 'democratized,' genomic enzymology web tools are essential to leverage the protein and genome databases for discovery of the in vitro activities and in vivo functions of novel enzymes and proteins belonging to the dark matter. In this review, we discuss the use of web tools that have proven successful for functional assignment. We also describe a mechanism for ensuring the capture of published functional data so that the quality of both curated and automated annotations transfer can be improved.
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Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions.
Kavvas, ES, Seif, Y, Yurkovich, JT, Norsigian, C, Poudel, S, Greenwald, WW, Ghatak, S, Palsson, BO, Monk, JM
BMC systems biology. 2018;(1):25
Abstract
BACKGROUND The efficacy of antibiotics against M. tuberculosis has been shown to be influenced by experimental media conditions. Investigations of M. tuberculosis growth in physiological conditions have described an environment that is different from common in vitro media. Thus, elucidating the interplay between available nutrient sources and antibiotic efficacy has clear medical relevance. While genome-scale reconstructions of M. tuberculosis have enabled the ability to interrogate media differences for the past 10 years, recent reconstructions have diverged from each other without standardization. A unified reconstruction of M. tuberculosis H37Rv would elucidate the impact of different nutrient conditions on antibiotic efficacy and provide new insights for therapeutic intervention. RESULTS We present a new genome-scale model of M. tuberculosis H37Rv, named iEK1011, that unifies and updates previous M. tuberculosis H37Rv genome-scale reconstructions. We functionally assess iEK1011 against previous models and show that the model increases correct gene essentiality predictions on two different experimental datasets by 6% (53% to 60%) and 18% (60% to 71%), respectively. We compared simulations between in vitro and approximated in vivo media conditions to examine the predictive capabilities of iEK1011. The simulated differences recapitulated literature defined characteristics in the rewiring of TCA metabolism including succinate secretion, gluconeogenesis, and activation of both the glyoxylate shunt and the methylcitrate cycle. To assist efforts to elucidate mechanisms of antibiotic resistance development, we curated 16 metabolic genes related to antimicrobial resistance and approximated evolutionary drivers of resistance. Comparing simulations of these antibiotic resistance features between in vivo and in vitro media highlighted condition-dependent differences that may influence the efficacy of antibiotics. CONCLUSIONS iEK1011 provides a computational knowledge base for exploring the impact of different environmental conditions on the metabolic state of M. tuberculosis H37Rv. As more experimental data and knowledge of M. tuberculosis H37Rv become available, a unified and standardized M. tuberculosis model will prove to be a valuable resource to the research community studying the systems biology of M. tuberculosis.
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[Development of Plant Metabolomics and Medicinal Plant Genomics].
Saito, K
Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan. 2018;(1):1-18
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Abstract
A variety of chemicals produced by plants, often referred to as 'phytochemicals', have been used as medicines, food, fuels and industrial raw materials. Recent advances in the study of genomics and metabolomics in plant science have accelerated our understanding of the mechanisms, regulation and evolution of the biosynthesis of specialized plant products. We can now address such questions as how the metabolomic diversity of plants is originated at the levels of genome, and how we should apply this knowledge to drug discovery, industry and agriculture. Our research group has focused on metabolomics-based functional genomics over the last 15 years and we have developed a new research area called 'Phytochemical Genomics'. In this review, the development of a research platform for plant metabolomics is discussed first, to provide a better understanding of the chemical diversity of plants. Then, representative applications of metabolomics to functional genomics in a model plant, Arabidopsis thaliana, are described. The extension of integrated multi-omics analyses to non-model specialized plants, e.g., medicinal plants, is presented, including the identification of novel genes, metabolites and networks for the biosynthesis of flavonoids, alkaloids, sulfur-containing metabolites and terpenoids. Further, functional genomics studies on a variety of medicinal plants is presented. I also discuss future trends in pharmacognosy and related sciences.
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Truncation- and motif-based pan-cancer analysis reveals tumor-suppressing kinases.
Hudson, AM, Stephenson, NL, Li, C, Trotter, E, Fletcher, AJ, Katona, G, Bieniasz-Krzywiec, P, Howell, M, Wirth, C, Furney, S, et al
Science signaling. 2018;(526)
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Abstract
A major challenge in cancer genomics is identifying "driver" mutations from the many neutral "passenger" mutations within a given tumor. To identify driver mutations that would otherwise be lost within mutational noise, we filtered genomic data by motifs that are critical for kinase activity. In the first step of our screen, we used data from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas to identify kinases with truncation mutations occurring within or before the kinase domain. The top 30 tumor-suppressing kinases were aligned, and hotspots for loss-of-function (LOF) mutations were identified on the basis of amino acid conservation and mutational frequency. The functional consequences of new LOF mutations were biochemically validated, and the top 15 hotspot LOF residues were used in a pan-cancer analysis to define the tumor-suppressing kinome. A ranked list revealed MAP2K7, an essential mediator of the c-Jun N-terminal kinase (JNK) pathway, as a candidate tumor suppressor in gastric cancer, despite its mutational frequency falling within the mutational noise for this cancer type. The majority of mutations in MAP2K7 abolished its catalytic activity, and reactivation of the JNK pathway in gastric cancer cells harboring LOF mutations in MAP2K7 or the downstream kinase JNK suppressed clonogenicity and growth in soft agar, demonstrating the functional relevance of inactivating the JNK pathway in gastric cancer. Together, our data highlight a broadly applicable strategy to identify functional cancer driver mutations and define the JNK pathway as tumor-suppressive in gastric cancer.
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Psychiatric Genomics: An Update and an Agenda.
Sullivan, PF, Agrawal, A, Bulik, CM, Andreassen, OA, Børglum, AD, Breen, G, Cichon, S, Edenberg, HJ, Faraone, SV, Gelernter, J, et al
The American journal of psychiatry. 2018;(1):15-27
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Abstract
The Psychiatric Genomics Consortium (PGC) is the largest consortium in the history of psychiatry. This global effort is dedicated to rapid progress and open science, and in the past decade it has delivered an increasing flow of new knowledge about the fundamental basis of common psychiatric disorders. The PGC has recently commenced a program of research designed to deliver "actionable" findings-genomic results that 1) reveal fundamental biology, 2) inform clinical practice, and 3) deliver new therapeutic targets. The central idea of the PGC is to convert the family history risk factor into biologically, clinically, and therapeutically meaningful insights. The emerging findings suggest that we are entering a phase of accelerated genetic discovery for multiple psychiatric disorders. These findings are likely to elucidate the genetic portions of these truly complex traits, and this knowledge can then be mined for its relevance for improved therapeutics and its impact on psychiatric practice within a precision medicine framework. [AJP at 175: Remembering Our Past As We Envision Our Future November 1946: The Genetic Theory of Schizophrenia Franz Kallmann's influential twin study of schizophrenia in 691 twin pairs was the largest in the field for nearly four decades. (Am J Psychiatry 1946; 103:309-322 )].
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Genomics of lipid-laden human hepatocyte cultures enables drug target screening for the treatment of non-alcoholic fatty liver disease.
Breher-Esch, S, Sahini, N, Trincone, A, Wallstab, C, Borlak, J
BMC medical genomics. 2018;(1):111
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) is a major health burden in need for new medication. To identify potential drug targets a genomic study was performed in lipid-laden primary human hepatocyte (PHH) and human hepatoma cell cultures. METHODS PHH, HuH7 and HepG2 hepatoma cell cultures were treated with lipids and/or TNFα. Intracellular lipid load was quantified with the ORO assay. The Affymetrix HG-U133+ array system was employed to perform transcriptome analysis. The lipid droplet (LD) growth and fusion was determined by fluorescence microscopy. LD associated proteins were imaged by confocal immunofluorescence microscopy and confirmed by Western immunoblotting. Bioinformatics defined perturbed metabolic pathways. RESULTS Whole genome expression profiling identified 227, 1031 and 571 significant regulated genes. Likewise, the combined lipid and TNFα treatment of PHH, HuH7 and HepG2 cell cultures revealed 154, 1238 and 278 differentially expressed genes. Although genomic responses differed among in-vitro systems, commonalities were ascertained by filtering the data for LD associated gene regulations. Among others the LD-growth and fusion associated cell death inducing DFFA like effector C (CIDEC), perilipins (PLIN2, PLIN3), the synaptosome-associated-protein 23 and the vesicle associated membrane protein 3 were strongly up-regulated. Likewise, the PPAR targets pyruvate-dehydrogenase-kinase-4 and angiopoietin-like-4 were up-regulated as was hypoxia-inducible lipid droplet-associated (HILPDA), flotilin and FGF21. Their inhibition ameliorates triglyceride and cholesterol accumulation. TNFα treatment elicited strong induction of the chemokine CXCL8, the kinases MAP3K8, MAP4K4 and negative regulators of cytokine signaling, i.e. SOCS2&SOCS3. Live cell imaging of DsRED calreticulin plasmid transfected HuH7 cells permitted an assessment of LD growth and fusion and confocal immunofluorescence microscopy evidenced induced LD-associated PLIN2, CIDEC, HIF1α, HILPDA, JAK1, PDK4 and ROCK2 expression. Notwithstanding, CPT1A protein was repressed to protect mitochondria from lipid overload. Pharmacological inhibition of the GTPase-dynamin and the fatty acid transporter-2 reduced lipid uptake by 28.5 and 35%, respectively. Finally, a comparisons of in-vitro/NAFLD patient biopsy findings confirmed common gene regulations thus demonstrating clinical relevance. CONCLUSION The genomics of fat-laden hepatocytes revealed LD-associated gene regulations and perturbed metabolic pathways. Immunofluorescence microscopy confirmed expression of coded proteins to provide a rationale for therapeutic intervention strategies. Collectively, the in-vitro system permits testing of drug candidates.
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The social network of microorganisms - how auxotrophies shape complex communities.
Zengler, K, Zaramela, LS
Nature reviews. Microbiology. 2018;(6):383-390
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Abstract
Microorganisms engage in complex interactions with other organisms and their environment. Recent studies have shown that these interactions are not limited to the exchange of electron donors. Most microorganisms are auxotrophs, thus relying on external nutrients for growth, including the exchange of amino acids and vitamins. Currently, we lack a deeper understanding of auxotrophies in microorganisms and how nutrient requirements differ between different strains and different environments. In this Opinion article, we describe how the study of auxotrophies and nutrient requirements among members of complex communities will enable new insights into community composition and assembly. Understanding this complex network over space and time is crucial for developing strategies to interrogate and shape microbial communities.