The branches of science known informally as omics are various disciplines in biology whose names end in the suffix -omics , such as genomics, proteomics, metabolomics, metagenomics, phenomics and transcriptomics. Omics aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms.
The related suffix -ome is used to address the objects of study of such fields, such as the genome, proteome or metabolome respectively. The suffix -ome as used in molecular biology refers to a totality of some sort; it is an example of a "neo-suffix" formed by abstraction from various Greek terms in -ωμα, a sequence that does not form an identifiable suffix in Greek.
Functional genomics aims at identifying the functions of as many genes as possible of a given organism. It combines different -omics techniques such as transcriptomics and proteomics with saturated mutant collections.
The Oxford English Dictionary (OED) distinguishes three different fields of application for the -ome suffix:
The -ome suffix originated as a variant of -oma, and became productive in the last quarter of the 19th century. It originally appeared in terms like sclerome -ωμα, a sequence that is not a single suffix, but analyzable as -ω-μα, the -ω- belonging to the word stem (usually a verb) and the -μα being a genuine Greek suffix forming abstract nouns.or rhizome . All of these terms derive from Greek words in
The OED suggests that its third definition originated as a back-formation from mitome ,Early attestations include biome (1916) and genome (first coined as German Genom in 1920 ).
The association with chromosome in molecular biology is by false etymology. The word chromosome derives from the Greek stems χρωμ(ατ)- "colour" and σωμ(ατ)- "body". While σωμα "body" genuinely contains the -μα suffix, the preceding -ω- is not a stem-forming suffix but part of the word's root. Because genome refers to the complete genetic makeup of an organism, a neo-suffix -ome suggested itself as referring to "wholeness" or "completion".
Bioinformaticians and molecular biologists figured amongst the first scientists to apply the "-ome" suffix widely.[ citation needed ] Early advocates included bioinformaticians in Cambridge, UK, where there were many early bioinformatics labs such as the MRC centre, Sanger centre, and EBI (European Bioinformatics Institute); for example, the MRC centre carried out the first genome and proteome projects.
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The epigenome is the supporting structure of the genome, including protein and RNA binders, alternative DNA structures, and chemical modifications on DNA.
The lipidome is the entire complement of cellular lipids, including the modifications made to a particular set of lipids, produced by an organism or system.
The proteome is the entire complement of proteins, including the modifications made to a particular set of proteins, produced by an organism or system.
Glycomics is the comprehensive study of the glycome i.e. sugars and carbohydrates.
Foodomics was defined by Alejandro Cifuentes in 2009 as “a discipline that studies the food and nutrition domains through the application and integration of advanced omics technologies to improve consumer’s well-being, health, and knowledge.”
Transcriptome is the set of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA, produced in one or a population of cells.
The metabolome is the ensemble of small molecule found within a biological matrix.
Inspired by foundational questions in evolutionary biology, a Harvard team around Jean-Baptiste Michel and Erez Lieberman Aiden created the American neologism culturomics for the application of big data collection and analysis to cultural studies.
The word "comic" does not use the "omics" suffix; it derives from Greek "κωμ(ο)-" (merriment) + "-ικ(ο)-" (an adjectival suffix), rather than presenting a truncation of "σωμ(ατ)-".
Similarly, the word "economy" is assembled from Greek "οικ(ο)-" (household) + "νομ(ο)-" (law or custom), and "economic(s)" from "οικ(ο)-" + "νομ(ο)-" + "-ικ(ο)-". The suffix -omics is sometimes used to create names for schools of economics, such as Reaganomics.
Many "omes" beyond the original "genome" have become useful and have been widely adopted by research scientists. "Proteomics" has become well-established as a term for studying proteins at a large scale. "Omes" can provide an easy shorthand to encapsulate a field; for example, an interactomics study is clearly recognisable as relating to large-scale analyses of gene-gene, protein-protein, or protein-ligand interactions. Researchers are rapidly taking up omes and omics, as shown by the explosion of the use of these terms in PubMed since the mid 1990s.
Ich schlage vor, für den haploiden Chromosomensatz, der im Verein mit dem zugehörigen Protoplasma die materielle Grundlage der systematischen Einheit darstellt den Ausdruck: das Genom zu verwenden ... " In English: " I propose the expression Genom for the haploid chromosome set, which, together with the pertinent protoplasm, specifies the material foundations of the species ...
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. As an interdisciplinary field of science, bioinformatics combines biology, chemistry, physics, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data. Bioinformatics has been used for in silico analyses of biological queries using computational and statistical techniques.
The proteome is the entire set of proteins that is, or can be, expressed by a genome, cell, tissue, or organism at a certain time. It is the set of expressed proteins in a given type of cell or organism, at a given time, under defined conditions. Proteomics is the study of the proteome.
Genomics is an interdisciplinary field of biology focusing on the structure, function, evolution, mapping, and editing of genomes. A genome is an organism's complete set of DNA, including all of its genes as well as its hierarchical, three-dimensional structural configuration. In contrast to genetics, which refers to the study of individual genes and their roles in inheritance, genomics aims at the collective characterization and quantification of all of an organism's genes, their interrelations and influence on the organism. Genes may direct the production of proteins with the assistance of enzymes and messenger molecules. In turn, proteins make up body structures such as organs and tissues as well as control chemical reactions and carry signals between cells. Genomics also involves the sequencing and analysis of genomes through uses of high throughput DNA sequencing and bioinformatics to assemble and analyze the function and structure of entire genomes. Advances in genomics have triggered a revolution in discovery-based research and systems biology to facilitate understanding of even the most complex biological systems such as the brain.
Proteomics is the large-scale study of proteins. Proteins are vital parts of living organisms, with many functions such as the formation of structural fibers of muscle tissue, enzymatic digestion of food, or synthesis and replication of DNA. In addition, other kinds of proteins include antibodies that protect an organism from infection, and hormones that send important signals throughout the body.
Molecular genetics is a sub-field of biology that addresses how differences in the structures or expression of DNA molecules manifests as variation among organisms. Molecular genetics often applies an "investigative approach" to determine the structure and/or function of genes in an organism's genome using genetic screens. The field of study is based on the merging of several sub-fields in biology: classical Mendelian inheritance, cellular biology, molecular biology, biochemistry, and biotechnology. Researchers search for mutations in a gene or induce mutations in a gene to link a gene sequence to a specific phenotype. Molecular genetics is a powerful methodology for linking mutations to genetic conditions that may aid the search for treatments/cures for various genetics diseases.
Systems biology is the computational and mathematical analysis and modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach to biological research.
A protein isoform, or "protein variant", is a member of a set of highly similar proteins that originate from a single gene or gene family and are the result of genetic differences. While many perform the same or similar biological roles, some isoforms have unique functions. A set of protein isoforms may be formed from alternative splicings, variable promoter usage, or other post-transcriptional modifications of a single gene; post-translational modifications are generally not considered. Through RNA splicing mechanisms, mRNA has the ability to select different protein-coding segments (exons) of a gene, or even different parts of exons from RNA to form different mRNA sequences. Each unique sequence produces a specific form of a protein.
Functional genomics is a field of molecular biology that attempts to describe gene functions and interactions. Functional genomics make use of the vast data generated by genomic and transcriptomic projects. Functional genomics focuses on the dynamic aspects such as gene transcription, translation, regulation of gene expression and protein–protein interactions, as opposed to the static aspects of the genomic information such as DNA sequence or structures. A key characteristic of functional genomics studies is their genome-wide approach to these questions, generally involving high-throughput methods rather than a more traditional "gene-by-gene" approach.
The transcriptome is the set of all RNA transcripts, including coding and non-coding, in an individual or a population of cells. The term can also sometimes be used to refer to all RNAs, or just mRNA, depending on the particular experiment. The term transcriptome is a portmanteau of the words transcript and genome; it is associated with the process of transcript production during the biological process of transcription.
A phenome, similar to phenotype, is the set of all traits expressed by a cell, tissue, organ, organism, or species.
Proteogenomics is a field of biological research that utilizes a combination of proteomics, genomics, and transcriptomics to aid in the discovery and identification of peptides. Proteogenomics is used to identify new peptides by comparing MS/MS spectra against a protein database that has been derived from genomic and transcriptomic information. Proteogenomics often refers to studies that use proteomic information, often derived from mass spectrometry, to improve gene annotations. The utilization of both proteomics and genomics data alongside advances in the availability and power of spectrographic and chromatographic technology led to the emergence of proteogenomics as its own field in 2004.
In the field of cellular biology, single-cell analysis is the study of genomics, transcriptomics, proteomics, metabolomics and cell–cell interactions at the single cell level. The concept of single-cell analysis originated in the 1970s. Before the discovery of heterogeneity, single-cell analysis mainly referred to the analysis or manipulation of an individual cell in a bulk population of cells at a particular condition using optical or electronic microscope. To date, due to the heterogeneity seen in both eukaryotic and prokaryotic cell populations, analyzing a single cell makes it possible to discover mechanisms not seen when studying a bulk population of cells. Technologies such as fluorescence-activated cell sorting (FACS) allow the precise isolation of selected single cells from complex samples, while high throughput single cell partitioning technologies, enable the simultaneous molecular analysis of hundreds or thousands of single unsorted cells; this is particularly useful for the analysis of transcriptome variation in genotypically identical cells, allowing the definition of otherwise undetectable cell subtypes. The development of new technologies is increasing our ability to analyze the genome and transcriptome of single cells, as well as to quantify their proteome and metabolome. Mass spectrometry techniques have become important analytical tools for proteomic and metabolomic analysis of single cells. Recent advances have enabled quantifying thousands of protein across hundreds of single cells, and thus make possible new types of analysis. In situ sequencing and fluorescence in situ hybridization (FISH) do not require that cells be isolated and are increasingly being used for analysis of tissues.
Foodomics was defined in 2009 as "a discipline that studies the Food and Nutrition domains through the application and integration of advanced -omics technologies to improve consumer's well-being, health, and knowledge". Foodomics requires the combination of food chemistry, biological sciences, and data analysis.
Pan-cancer analysis aims to examine the similarities and differences among the genomic and cellular alterations found across diverse tumor types. International efforts have performed pan-cancer analysis on exomes and the whole genomes of cancers, the latter including their non-coding regions. In 2018, The Cancer Genome Atlas (TCGA) Research Network used exome, transcriptome, and DNA methylome data to develop an integrated picture of commonalities, differences, and emergent themes across tumor types.
Metatranscriptomics is the set of techniques used to study gene expression of microbes within natural environments, i.e., the metatranscriptome.
Multiomics, multi-omics, integrative omics, "panomics" or "pan-omics" is a biological analysis approach in which the data sets are multiple "omes", such as the genome, proteome, transcriptome, epigenome, metabolome, and microbiome ; in other words, the use of multiple omics technologies to study life in a concerted way. By combining these "omes", scientists can analyze complex biological big data to find novel associations between biological entities, pinpoint relevant biomarkers and build elaborate markers of disease and physiology. In doing so, multiomics integrates diverse omics data to find a coherently matching geno-pheno-envirotype relationship or association. The OmicTools service lists more than 99 softwares related to multiomic data analysis, as well as more than 99 databases on the topic.
Michael P. Snyder is an American genomicist who is the Stanford B. Ascherman Professor and as of 2009, Chair of Genetics and Director of Genomics and Personalized Medicine at Stanford University, and the former Director of the Yale Center for Genomics and Proteomics. He was elected to The American Academy of Arts and Sciences in 2015. During his tenure as chair of the department at Stanford, the U.S. News & World Report has ranked Stanford University first or tied for first in Genetics, Genomics and Bioinformatics under his leadership.
Translatomics is the study of all open reading frames (ORFs) that are being actively translated in a cell or organism. This collection of ORFs is called the translatome. Characterizing a cell's translatome can give insight into the array of biological pathways that are active in the cell. According to the central dogma of molecular biology, the DNA in a cell is transcribed to produce RNA, which is then translated to produce a protein. Thousands of proteins are encoded in an organism's genome, and the proteins present in a cell cooperatively carry out many functions to support the life of the cell. Under various conditions, such as during stress or specific timepoints in development, the cell may require different biological pathways to be active, and therefore require a different collection of proteins. Depending on intrinsic and environmental conditions, the collection of proteins being made at one time varies. Translatomic techniques can be used to take a "snapshot" of this collection of actively translating ORFs, which can give information about which biological pathways the cell is activating under the present conditions.
Precision diagnostics is a branch of precision medicine where a patient's healthcare model is precisely managed and specific diseases are diagnosed based on the patient's customized omics data analytics.