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Microbial Bioremediation of Petroleum Hydrocarbons in Moderate to Extreme Environments and Application of “omics” Techniques to Evaluate Bioremediation Approaches and Efficiency
Published in Gunjan Mukherjee, Sunny Dhiman, Waste Management, 2023
Maricy Raquel Lindenbah Bonfá, Rodrigo Matheus Pereira, Francine Amaral Piubeli, Lucia Regina Durrant
The metatranscriptomic technique is the most adequate to answer which genes of the microbiota are active at the moment of the analysis of the environmental sample; for that, an RNA extraction is made in the material to be analyzed. A limitation of transcriptomics can be in the collection of samples, which frequently results in destruction of the RNA. This can be avoided by ensuring that a sufficient amount of intact RNA is obtained for the subsequent sequencing of the cDNA. Furthermore, metatranscriptomics is not always able to detect all the diversity of RNAs that are being expressed in a sample due to the high diversity and different proportions of members of some microbial communities. Another problem inherent in this technique is the short half-life of RNA before converting it into cDNA for sequencing (Leary et al. 2013, Shakya et al. 2019).
Genetic Diversity in Natural Resources Management
Published in Yeqiao Wang, Landscape and Land Capacity, 2020
Thomas Joseph McGreevy, Jeffrey A. Markert
The transition of conservation genetics to conservation genomics represents a major shift in the types of questions that can be addressed and how the questions can be addressed. Conservation genetic studies have mainly been limited to correlative studies. The development of genomic tools has allowed for a shift to a causative approach that can directly investigate evolutionary processes.[41] Genomic tools can be used to investigate gene expression using transcriptomics,[57] rather than just measuring nucleotide variation. Transcriptomics is a field of study that investigates genes that are actually expressed in an organism. Ouborg et al.[41] identified four main questions that can be addressed using genomic tools that involve: 1) measuring the impact of small population size on levels of adaptive variation; 2) identifying the underlying mechanisms that connect adaptive genetic variation and fitness; 3) determining how genes and the environment interact; and 4) estimating the impact of inbreeding and genetic drift on gene expression. Genomic tools will greatly improve the quantity and quality of information gained from genetic analyses; however, genomic tools will not be a panacea. Identifying the genetic mechanisms of adaptation is a difficult endeavor and will require a multidisciplinary approach.[50]
Current Use and Future Promise of Genetic Engineering
Published in Michael Hehenberger, Zhi Xia, Huanming Yang, Our Animal Connection, 2020
Michael Hehenberger, Zhi Xia, Huanming Yang
Transcriptomics is the study of the transcriptome, defined as the set of all RNA molecules, including mRNA, rRNA, tRNA, and other noncoding RNA produced in one or a population of cells. Because it includes all mRNA transcripts in the cell, the transcriptome reflects the genes that are expressed at any given time. The study of transcriptomics, also referred to as gene expression profiling, examines the expression level of mRNAs in a given cell population, often using high-throughput techniques based on DNA microarray technology. The transcriptomes of stem cells and cancer cells are of particular interest: transcriptomics applied to those cells help us in the understanding of cellular differentiation and carcinogenesis.
Advancements of next generation sequencing in the field of Rheumatoid Arthritis
Published in Egyptian Journal of Basic and Applied Sciences, 2023
Ankita Pati, Dattatreya Kar, Jyoti Ranjan Parida, Ananya Kuanar
Transcriptomics involves certain technologies that can be implemented for a high throughput identification of RNA. This type of gene-wide gene expression system by implementing the RNA sequencing is being used in rheumatoid diseases. The actual clinical utility reading the determination of robust patterns of the expression of the genes is yet to be discovered that accurately informs the taken decisions in treatment [31]. The DNA sequencing method can be sewed to determine the mutations that have the bolt to cause cancers and thus allow the diagnosis and informed options for treatment, the complex structure of genes as well as the crucial role of the environmental factors in RA evince a specific requirement for the approaches such that the measures facets within the active genome [32].
Current opinion on risk assessment of cosmetics
Published in Journal of Toxicology and Environmental Health, Part B, 2021
Kyu-Bong Kim, Seung Jun Kwack, Joo Young Lee, Sam Kacew, Byung-Mu Lee
Omics technology is an emerging technology developed to identify interactions and correlations by analyzing intracellular molecules, such as genes, proteins, and metabolites (Lee et al. 2020b; Pirih and Kunej 2017). Exposure of the body to chemicals might initiate various changes at the molecular level. Omics technology has been determined as an important technique for identifying functional or structural changes in cells (Brockmeier et al. 2017). Transcriptomics, proteomics, and metabolomics are typical omics technologies. Transcriptomics provides information about expressed genes in cells or tissues. Proteomics provides information on the proteins expressed in cells and tissues. Metabolomics provides information on all of the metabolites produced by cells or tissues. The integrated analysis of omics has been observed to improve the assessment of hazardous chemical reactions (Lee et al. 2020a). A method to evaluate skin sensitization by analyzing the transcriptome of the MUTZ-3 human cell line has been proposed (Johansson et al. 2011). This method provides insight into the gene expression of cells exposed to chemicals and can further predict the potential for skin sensitization. The integrated analysis of omics can group or cluster chemical substances on the basis of their similarity in exerting a biological response and can provide information as to whether chemicals share the same MOA. Furthermore, it is possible to determine the concentration at which the level of differential gene expression does not appear compared with the control. This level can be set to No-Observed-Transcriptional-Effect-Level in an invitro test similar to the NOAEL used in animal experiments (Baltazar et al. 2020). A metabolomics profiling was applied for data gap filling of read-across submitted under the REACH regulation (Sperber et al. 2019). The whole plasma metabolite profile of animals treated with 3-aminopropanol was correlated with the metabolite profile of 2-aminoethanol and it was concluded that metabolome data from 2-aminoethanol and 3-aminopropanol added confidence concerning mechanistic similarity in read-across approach (Sperber et al. 2019). Therefore, it is expected that such omics technology may provide important information for the evaluation of risk and safety for cosmetic ingredients that cannot be tested in animals.