Omics Studies
Omics Studies - Related Videos
08:27
Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
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Cited by 4 •
2021
In this protocol, we present an optimized workflow, which combines an efficient and fast sample preparation of many samples. In addition, we provide a step-by-step guide to reduce analytical variations for high-throughput evaluation of metabolic GWAS studies.
10:12
The MPLEx Protocol for Multi-omic Analyses of Soil Samples
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Cited by 31 •
2018
A protocol is presented for simultaneously extracting metabolites, proteins, and lipids from a single soil sample, allowing reduced sample preparation times and enabling multi-omic mass spectrometry analyses of samples with limited quantities.
09:07
In Vitro Model for Studying Differentiation and Changes of Multi-Omics on Murine Airway Epithelial Cells Stimulated with Cigarette Smoke Extract
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2024
Here, we describe an in vitro model for isolating and differentiating murine airway epithelial cells, focusing on their acclimation to chronic cigarette smoke extract (CSE). The model could be utilized to comprehensively characterize the multi-omics impact of CSE, which possibly provides insights into the cellular responses under chronic smoke exposure.
15:31
Tissue Collection of Bats for -Omics Analyses and Primary Cell Culture
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Cited by 25 •
2019
This is a protocol for the optimal tissue preparation for genomic, transcriptomic, and proteomic analyses of bats caught in the wild. It includes protocols for bat capture and dissection, tissue preservation, and cell culturing of bat tissue.
08:33
Dissection of Drosophila melanogaster Flight Muscles for Omics Approaches
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Cited by 15 •
2019
Drosophila flight muscle is a powerful model to study transcriptional regulation, alternative splicing, metabolism, and mechanobiology. We present a protocol for dissection of fluorescent-labeled flight muscle from live pupae to generate highly enriched samples ideal for proteomics and deep-sequencing. These samples can offer important mechanistic insights into diverse aspects of muscle development.
FAQs
Omics studies become biologically informative by relating measurements from different molecular layers to one another and to observed conditions. Computational analysis searches for coordinated patterns, interactions, and changes across cells, tissues, or organisms. These relationships can connect molecular variation with function and produce testable hypotheses, although the measurements primarily reveal associations to investigate.
Which technology is appropriate depends on the molecular component being profiled. Sequencing supports measurement of genes or transcripts, whereas mass spectrometry supports analysis of proteins or metabolites. The choice also reflects the biological level of interest and the comparison being made, such as differences among tissues, organisms, or experimental conditions.
Combining gene, transcript, protein, and metabolite measurements allows researchers to examine how molecular layers relate rather than interpreting each layer in isolation. In systems biology, this integration can reveal regulatory relationships and connect molecular changes with biological function. The resulting patterns help generate hypotheses about complex traits, disease, or environmental responses.
The central workflow is to profile selected molecular components across defined cells, tissues, organisms, or conditions and then apply computational analysis to identify patterns, interactions, and changes. Researchers can compare molecular states with biological functions or responses to environmental or experimental factors. This workflow turns large molecular measurements into interpretable biological relationships and hypotheses.
Biologists use these studies when a question involves complex traits, development, disease, or responses to environmental or experimental factors. Broad molecular profiling can show which components vary across biological states and can help relate those changes to function. The approach is therefore useful for discovering patterns that support further investigation.
Results can support biomarker identification, diagnostics, therapeutics, and personalized biology by linking molecular variation to biological function or disease-related states. In practice, omics findings help characterize a system, highlight molecular patterns associated with a condition, and guide hypotheses for subsequent research. They are most valuable when interpreted in relation to the relevant biological context.