Omics Knowledge Portal for Rice
What is Omics?
- Omics is a discipline of science and engineering for analyzing the functions and interactions of biological information entities in various –ome layers(clusters) of life. It is involved with a series of state of the art technology for large-scale studies of genes (genomics and epigenomics), transcripts (transcriptomics), proteins (proteomics), metabolites (metabolomics), lipids (lipidomics), interactions (interactomics) and phenotype (Phenomics).
- 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 main focus is on: 1) mapping information objects such as genes, proteins, and ligands; 2) finding interaction relationships among the objects; 3) engineering the networks and objects to understand and manipulate the regulatory mechanisms; and 4) integrating various omes and omics subfields."
- The rapid advances in 'omics' technologies for both model and non-model organism transformed biological research from a relatively data-poor discipline into the one that is data rich (The Big Data Area in Biology), marking a significant phase transition in the history of biological research. Integration of genome and functional omics data with genetic and phenotypic information is leading to the identification of genes and pathways responsible for important agronomic phenotypes. In addition, high-throughput genotyping technologies enable the screening of large germplasm collections to identify novel alleles from diverse sources, thus offering a major expansion in the variation available for breeding.
- Take the Model of "Multi-Dimensional Approaches to Systems Understanding of Leaf Senescence" from Jeongsik Kim (pulished in June 2016 ) (Figure 2) for example, Given the multifaceted nature of the leaf senes- cence process, multi-dimensional approaches are required for the systems understanding of the mechanistic principles governing leaf senescence. The Age/environment dimension includes internal (age) and external (environmental) factors that regulate leaf senescence. The Organization dimension refers to various analytic layers, including organelle, cell, organ, and organism. The Analysis dimension defines diverse high-throughput omics technologies. Efforts to integrate multi-omics data, including genomic, epigenomic, transcriptomic, proteomic, metabolomic, and phenomic data, on leaf senescence are essential for an in-depth understanding of the molecular nature of leaf senescence.
The Omics Knowledge Portal for Rice
- In order to make a comprehensive integration of published omics knowledge for rice, here we establish Omics Knowledge Portal for Rice (OKP4R) in RiceWiki. If you are interested, please join us.
- The basis of all biological life is the genetic code. Thus, access to the primary DNA sequence, i.e. the genome, and how genes are encoded within the genome, has become a fundamental resource in biology. Genome sequencing (also known as full genome sequencing, complete genome sequencing, or entire genome sequencing) is a laboratory process that determines the complete DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.(More...)
Transcriptomic Studies in Rice
- The 'transcriptome' is defined as 'the complete of RNA molecules generated by a cell or population of cells'. The term was first proposed by Charles Auffray in 1996, and first used in a scientific paper in 1997. It encompass many species of RNA, for example, mRNA, miRNA, lnRNA et al. Over the past decades, transcriptomic study has advanced from traditional Northern blotting to Highthroughput RNA sequencing (RNA-seq). Besides them, the quantitative polymerase chain reaction (PCR) and microarray are also very impressive technology.
- RNA-seq (RNA sequencing), also called whole transcriptome sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample representing a specific tissue and at a specific given moment in time. RNA-seq can be used to analyze the continually changing transcriptome in cells. It can facilitate the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs and changes in gene expression. It can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries.(More...)
- microRNA (abbreviated miRNA) is a kind of small non-coding RNA molecules (containing about 22 nucleotides) that functions in RNA silencing and post-transcriptional regulation of gene expression. In short， MicroRNAs (miRNAs) are a class of small, endogenous, nonoding RNAs with a big impact on virtually all biological processes. Investigations suggest that miRNAs control the gene expression of at least 30% of the protein-coding genes in human beings. Although the diverse fundamental functions of miRNAs have now been well demonstrated in both plants and animals over the past several years, little attention has been paid to this class of small RNAs for about a decade after the first miRNAs were identified in the soil nematode Caenorhabditis elegans in 1993.(More...)
- Long non-coding RNAs (long ncRNAs, lncRNA) are non-protein coding transcripts longer than 200 nucleotides. This somewhat arbitrary limit distinguishes long ncRNAs from small regulatory RNAs such as microRNAs (miRNAs), short interfering RNAs (siRNAs), Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and other short RNAs. It is generally believed that lncRNAs, RNA molecules longer than 200 nucleotides, belong to a group of RNAs with broad biogenesis, and that these molecules are always capped and polyadenylated.(More...)
- A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate (usually a glass slide or silicon thin-film cell) that assays large amounts of biological material using high-throughput screening miniaturized, multiplexed and parallel processing and detection methods. The concept and methodology of microarrays was first introduced and illustrated in antibody microarrays (also referred to as antibody matrix) by Tse Wen Chang in 1983 in a scientific publication and a series of patents.(More...)
- Proteins are vital parts of living organisms as they are the main components of the physiological metabolic pathways of cells, and Proteomics is the large-scale study of proteins, particularly their structures and functions. The word proteome is a portmanteau of protein and genome, it was initially coined by Marc Wilkins (Ph. D. student at Australia's Macquarie University) during the first Siena meeting (2D Electrophoresis-From Protein Maps to Genomes, Siena, Italy, September 5-7, 1994).Three years later, by 1997, the first book on proteomics was published. As the genomes of an increasing number of species were sequenced and released, and mass spectrometry equipment and bioinformatics tools more and more developed, proteomics took leadership in the biological research arena,(More...)
- A genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease or develop high-efficiency method for crops breeding. GWASs typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits.(More...)
- An epigenome consists of a record of the chemical changes to the DNA and histone proteins of an organism; these changes can be passed down to an organism's offspring via transgenerational epigenetic inheritance. Changes to the epigenome can result in changes to the structure of chromatin and changes to the function of the genome. The epigenome is involved in regulating gene expression, development, tissue differentiation, and suppression of transposable elements.(More...)
- Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes. mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, (More...)
- Phenomics is an area of biology concerned with the measurement of phenomes—the physical and biochemical traits of organisms—as they change in response to genetic mutation and environmental influences. It is used in functional genomics, pharmaceutical research, metabolic engineering and increasingly in phylogenetics. Plant phenomics is the study of plant growth, performance and composition. Forward phenomics uses phenotyping tools to 'sieve' collections of germplasm for valuable traits. The sieve or screen could be high-throughput and fully automated and low resolution, (More...)
- ↑ 1.0 1.1 https://en.wikipedia.org/wiki/Omics
- ↑ Langridge, Peter, and Delphine Fleury. "Making the most of ‘omics’ for crop breeding." Trends in biotechnology 29.1 (2011): 33-40.
- ↑ Kushalappa, Ajjamada C., and Raghavendra Gunnaiah. "Metabolo-proteomics to discover plant biotic stress resistance genes." Trends in Plant Science 18.9 (2013): 522-531.
- ↑ 4.0 4.1 4.2 Kim, Jeongsik, Hye Ryun Woo, and Hong Gil Nam. "Toward Systems Understanding of Leaf Senescence: An Integrated Multi-Omics Perspective on Leaf Senescence Research." Molecular Plant 9.6 (2016): 813-825.
- ↑ McGettigan, Paul A. "Transcriptomics in the RNA-seq era." Current opinion in chemical biology 17.1 (2013): 4-11.
- ↑ Piétu, Geneviève, et al. "The Genexpress IMAGE knowledge base of the human brain transcriptome: a prototype integrated resource for functional and computational genomics." Genome research 9.2 (1999): 195-209.
- ↑ Velculescu, Victor E., et al. "Characterization of the yeast transcriptome." Cell 88.2 (1997): 243-251.