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1.
Transcriptomics View over the Germination Landscape in Biofortified Rice.
Dueñas, CJ, Slamet-Loedin, I, Macovei, A
Genes. 2021;(12)
Abstract
Hidden hunger, or micronutrient deficiency, is a worldwide problem. Several approaches are employed to alleviate its effects (e.g., promoting diet diversity, use of dietary supplements, chemical fortification of processed food), and among these, biofortification is considered as one of the most cost-effective and highly sustainable. Rice is one of the best targets for biofortification since it is a staple food for almost half of the world's population as a high-energy source but with low nutritional value. Multiple biofortified rice lines have been produced during the past decades, while few studies also reported modifications in germination behavior (in terms of enhanced or decreased germination percentage or speed). It is important to underline that rapid, uniform germination, and seedling establishment are essential prerequisites for crop productivity. Combining the two traits, biofortified, highly-nutritious seeds with improved germination behavior can be envisaged as a highly-desired target for rice breeding. To this purpose, information gathered from transcriptomics studies can reveal useful insights to unveil the molecular players governing both traits. The present review aims to provide an overview of transcriptomics studies applied at the crossroad between biofortification and seed germination, pointing out potential candidates for trait pyramiding.
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Application of Computational Biology to Decode Brain Transcriptomes.
Li, J, Wang, GZ
Genomics, proteomics & bioinformatics. 2019;(4):367-380
Abstract
The rapid development of high-throughput sequencing technologies has generated massive valuable brain transcriptome atlases, providing great opportunities for systematically investigating gene expression characteristics across various brain regions throughout a series of developmental stages. Recent studies have revealed that the transcriptional architecture is the key to interpreting the molecular mechanisms of brain complexity. However, our knowledge of brain transcriptional characteristics remains very limited. With the immense efforts to generate high-quality brain transcriptome atlases, new computational approaches to analyze these high-dimensional multivariate data are greatly needed. In this review, we summarize some public resources for brain transcriptome atlases and discuss the general computational pipelines that are commonly used in this field, which would aid in making new discoveries in brain development and disorders.
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Comparative Genomics and Transcriptome Profiling in Primary Aldosteronism.
Aristizabal Prada, ET, Castellano, I, Sušnik, E, Yang, Y, Meyer, LS, Tetti, M, Beuschlein, F, Reincke, M, Williams, TA
International journal of molecular sciences. 2018;(4)
Abstract
Primary aldosteronism is the most common form of endocrine hypertension with a prevalence of 6% in the general population with hypertension. The genetic basis of the four familial forms of primary aldosteronism (familial hyperaldosteronism FH types I-IV) and the majority of sporadic unilateral aldosterone-producing adenomas has now been resolved. Familial forms of hyperaldosteronism are, however, rare. The sporadic forms of the disease prevail and these are usually caused by either a unilateral aldosterone-producing adenoma or bilateral adrenal hyperplasia. Aldosterone-producing adenomas frequently carry a causative somatic mutation in either of a number of genes with the KCNJ5 gene, encoding an inwardly rectifying potassium channel, a recurrent target harboring mutations at a prevalence of more than 40% worldwide. Other than genetic variations, gene expression profiling of aldosterone-producing adenomas has shed light on the genes and intracellular signalling pathways that may play a role in the pathogenesis and pathophysiology of these tumors.
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Experimental design for single-cell RNA sequencing.
Baran-Gale, J, Chandra, T, Kirschner, K
Briefings in functional genomics. 2018;(4):233-239
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Abstract
Single-cell RNA sequencing (scRNA-seq) has opened new avenues for the characterization of heterogeneity in a large variety of cellular systems. As this is a relatively new technique, the field is fast evolving. Here, we discuss general considerations in experimental design and the two most popular approaches, plate-based Smart-Seq2 and microdroplet-based scRNA-seq at the example of 10x Chromium. We discuss advantages and disadvantages of both methods and point out major factors to consider in designing successful experiments.
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5.
Omics methods for probing the mode of action of natural and synthetic phytotoxins.
Duke, SO, Bajsa, J, Pan, Z
Journal of chemical ecology. 2013;(2):333-47
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Abstract
For a little over a decade, omics methods (transcriptomics, proteomics, metabolomics, and physionomics) have been used to discover and probe the mode of action of both synthetic and natural phytotoxins. For mode of action discovery, the strategy for each of these approaches is to generate an omics profile for phytotoxins with known molecular targets and to compare this library of responses to the responses of compounds with unknown modes of action. Using more than one omics approach enhances the probability of success. Generally, compounds with the same mode of action generate similar responses with a particular omics method. Stress and detoxification responses to phytotoxins can be much clearer than effects directly related to the target site. Clues to new modes of action must be validated with in vitro enzyme effects or genetic approaches. Thus far, the only new phytotoxin target site discovered with omics approaches (metabolomics and physionomics) is that of cinmethylin and structurally related 5-benzyloxymethyl-1,2-isoxazolines. These omics approaches pointed to tyrosine amino-transferase as the target, which was verified by enzyme assays and genetic methods. In addition to being a useful tool of mode of action discovery, omics methods provide detailed information on genetic and biochemical impacts of phytotoxins. Such information can be useful in understanding the full impact of natural phytotoxins in both agricultural and natural ecosystems.
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Conventional and nanotechniques for DNA methylation profiling.
Shanmuganathan, R, Basheer, NB, Amirthalingam, L, Muthukumar, H, Kaliaperumal, R, Shanmugam, K
The Journal of molecular diagnostics : JMD. 2013;(1):17-26
Abstract
DNA methylation is critical for gene silencing and is associated with the incidence of many diseases, including cancer. Underlying molecular mechanisms of human diseases and tissue-specific gene expression have been elucidated based on DNA methylation studies. This review highlights the advantages and drawbacks of various methylation screening techniques: blotting, genomic sequencing, bisulfite sequencing, methylation-specific PCR, methylated DNA immunoprecipitation, microarray analysis, matrix-assisted laser desorption ionization time-of-flight mass spectroscopy, nanowire transistor detection procedure, quantum dot-based nanoassay, single-molecule real-time detection, fluorimetric assay, electrochemical detection, and atomic force spectroscopy. The review provides insight for selecting a method or a combination of methods for DNA methylation analysis. Convergence of conventional and contemporary nanotechniques to enumerate methylation at specific CpG sites of oncogene would fill the gap in diagnosis of cancer.
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Strategies for transcriptome analysis in nonmodel plants.
Ward, JA, Ponnala, L, Weber, CA
American journal of botany. 2012;(2):267-76
Abstract
Even with recent reductions in sequencing costs, most plants lack the genomic resources required for successful short-read transcriptome analyses as performed routinely in model species. Several approaches for the analysis of short-read transcriptome data are reviewed for nonmodel species for which the genome of a close relative is used as the reference genome. Two approaches using a data set from Phytophthora-challenged Rubus idaeus (red raspberry) are compared. Over 70000000 86-nt Illumina reads derived from R. idaeus roots were aligned to the Fragaria vesca genome using publicly available informatics tools (Bowtie/TopHat and Cufflinks). Alignment identified 16956 putatively expressed genes. De novo assembly was performed with the same data set and a publicly available transcriptome assembler (Trinity). A BLAST search with a maximum e-value threshold of 1.0 × 10(-3) revealed that over 36000 transcripts had matches to plants and over 500 to Phytophthora. Gene expression estimates from alignment to F. vesca and de novo assembly were compared for raspberry (Pearson's correlation = 0.730). Together, alignment to the genome of a close relative and de novo assembly constitute a powerful method of transcriptome analysis in nonmodel organisms. Alignment to the genome of a close relative provides a framework for differential expression testing if alignments are made to the predefined gene-space of a close relative and de novo assembly provides a more robust method of identifying unique sequences and sequences from other organisms in a system. These methods are considered experimental in nonmodel systems, but can be used to generate resources and specific testable hypotheses.
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Cellular defense system gene expression profiling of human whole blood: opportunities to predict health benefits in response to diet.
Drew, JE
Advances in nutrition (Bethesda, Md.). 2012;(4):499-505
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Abstract
Diet is a critical factor in the maintenance of human cellular defense systems, immunity, inflammation, redox regulation, metabolism, and DNA repair that ensure optimal health and reduce disease risk. Assessment of dietary modulation of cellular defense systems in humans has been limited due to difficulties in accessing target tissues. Notably, peripheral blood gene expression profiles associated with nonhematologic disease are detectable. Coupled with recent innovations in gene expression technologies, gene expression profiling of human blood to determine predictive markers associated with health status and dietary modulation is now a feasible prospect for nutrition scientists. This review focuses on cellular defense system gene expression profiling of human whole blood and the opportunities this presents, using recent technological advances, to predict health status and benefits conferred by diet.
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Online tools for bioinformatics analyses in nutrition sciences.
Malkaram, SA, Hassan, YI, Zempleni, J
Advances in nutrition (Bethesda, Md.). 2012;(5):654-65
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Abstract
Recent advances in "omics" research have resulted in the creation of large datasets that were generated by consortiums and centers, small datasets that were generated by individual investigators, and bioinformatics tools for mining these datasets. It is important for nutrition laboratories to take full advantage of the analysis tools to interrogate datasets for information relevant to genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This review provides guidance regarding bioinformatics resources that are currently available in the public domain, with the intent to provide a starting point for investigators who want to take advantage of the opportunities provided by the bioinformatics field.
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10.
Human muscle protein turnover--why is it so variable?
Smith, GI, Patterson, BW, Mittendorfer, B
Journal of applied physiology (Bethesda, Md. : 1985). 2011;(2):480-91
Abstract
We undertook a comprehensive review of the literature to unravel the nature of the variability in the reported rate of human muscle protein synthesis. We analyzed the results from studies that report the protein fractional synthesis rate (FSR) in the vastus lateralis in healthy, nonobese, untrained adults ≤50 yr of age in the postabsorptive state at rest by using the primed, constant tracer amino acid infusion method according to experimental design characteristics. We hypothesized that if the variability is methodological (rather than physiological) in nature, systematic clustering of FSR values would be evident, and outliers would become apparent. Overall, as expected, the mixed muscle protein FSR values were significantly (P < 0.001) greater when the muscle vs. the plasma free amino acid enrichment is used as the surrogate precursor pool enrichment, and the average mixed muscle protein FSR values were significantly greater (P = 0.05) than the myofibrillar/myosin heavy chain FSR values. The within-study variability (i.e., population variance) was somewhat smaller in studies that used plasma amino acid/ketoacid enrichments vs. muscle free amino acid enrichment (∼24 vs. ∼31%), but this was not apparent in all circumstances. Furthermore, the between-study consistency of measured FSR values (i.e., interquartile range) was inversely correlated with the average duration between biopsies. Aside from that, the variation in reported FSR values could not be explained by differences in the experimental design and analytical methods, and none of the most commonly used approaches stood out as clearly superior in terms of consistency of results and/or within-study variability. We conclude that the variability in reported values is in part due to 1) differences in experimental design (e.g., choice of precursor pool) and 2) considerable within-subject variability. The summary of the results from our analysis can be used as guidelines for "normal" average basal FSR values at rest in healthy adults.