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Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.
The human genome is a complete set of nucleic acid sequences for humans, encoded as DNA within the 23 chromosome pairs in cell nuclei and in a small DNA molecule found within individual mitochondria. These are usually treated separately as the nuclear genome and the mitochondrial genome. Human genomes include both protein-coding DNA sequences and various types of DNA that does not encode proteins. The latter is a diverse category that includes DNA coding for non-translated RNA, such as that for ribosomal RNA, transfer RNA, ribozymes, small nuclear RNAs, and several types of regulatory RNAs. It also includes promoters and their associated gene-regulatory elements, DNA playing structural and replicatory roles, such as scaffolding regions, telomeres, centromeres, and origins of replication, plus large numbers of transposable elements, inserted viral DNA, non-functional pseudogenes and simple, highly repetitive sequences. Introns make up a large percentage of non-coding DNA. Some of this non-coding DNA is non-functional junk DNA, such as pseudogenes, but there is no firm consensus on the total amount of junk DNA.
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 "candidate-gene" approach.
In genomics, a genome-wide association study, is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms.
The 1000 Genomes Project, launched in January 2008, was an international research effort to establish by far the most detailed catalogue of human genetic variation. Scientists planned to sequence the genomes of at least one thousand anonymous participants from a number of different ethnic groups within the following three years, using newly developed technologies which were faster and less expensive. In 2010, the project finished its pilot phase, which was described in detail in a publication in the journal Nature. In 2012, the sequencing of 1092 genomes was announced in a Nature publication. In 2015, two papers in Nature reported results and the completion of the project and opportunities for future research.
Expression quantitative trait loci (eQTLs) are genomic loci that explain variation in expression levels of mRNAs.
Exome sequencing, also known as whole exome sequencing (WES), is a genomic technique for sequencing all of the protein-coding regions of genes in a genome. It consists of two steps: the first step is to select only the subset of DNA that encodes proteins. These regions are known as exons—humans have about 180,000 exons, constituting about 1% of the human genome, or approximately 30 million base pairs. The second step is to sequence the exonic DNA using any high-throughput DNA sequencing technology.
Eric Emil Schadt is an American mathematician and computational biologist. He is founder and former chief executive officer of Sema4, a patient-centered health intelligence company, and dean for precision medicine and Mount Sinai Professor in Predictive Health and Computational Biology at the Icahn School of Medicine at Mount Sinai. He was previously founding director of the Icahn Institute for Genomics and Multiscale Biology and chair of the Department of Genetics and Genomics Sciences at the Icahn School of Medicine at Mount Sinai.
The Icahn Genomics Institute is a biomedical and genomics research institute within the Icahn School of Medicine at Mount Sinai in New York City. Its aim is to establish a new generation of medicines that can better treat diseases afflicting the world, including cancer, heart disease and infectious pathogens. To do this, the institute’s doctors and scientists are developing and employing new types of treatments that utilize DNA and RNA based therapies, such as CRISPR, siRNA, RNA vaccines, and CAR T cells, and searching for novel drug targets through the use of functional genomics and data science. The institute is led by Brian Brown, a leading expert in gene therapy, genetic engineering, and molecular immunology.
Sociogenomics, also known as social genomics, is the field of research that examines why and how different social factors and processes affect the activity of the genome. Social genomics as a field is very young and was spurred by the scientific understanding that the expression of genes to their gene products, though not the DNA sequence itself, is affected by the external environment. Social genomics researchers have thus examined the role of social factors on the expression of individual genes, or more commonly, clusters of many genes.
Alicia Yinema Kate Nungarai Oshlack is an Australian bioinformatician and is Co-Head of Computational Biology at the Peter MacCallum Cancer Centre in Melbourne, Victoria, Australia. She is best known for her work developing methods for the analysis of transcriptome data as a measure of gene expression. She has characterized the role of gene expression in human evolution by comparisons of humans, chimpanzees, orangutans, and rhesus macaques, and works collaboratively in data analysis to improve the use of clinical sequencing of RNA samples by RNAseq for human disease diagnosis.
Single nucleotide polymorphism annotation is the process of predicting the effect or function of an individual SNP using SNP annotation tools. In SNP annotation the biological information is extracted, collected and displayed in a clear form amenable to query. SNP functional annotation is typically performed based on the available information on nucleic acid and protein sequences.
Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant. A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells. Another is how gene expression is regulated.
C16orf82 is a protein that, in humans, is encoded by the C16orf82 gene. C16orf82 encodes a 2285 nucleotide mRNA transcript which is translated into a 154 amino acid protein using a non-AUG (CUG) start codon. The gene has been shown to be largely expressed in the testis, tibial nerve, and the pituitary gland, although expression has been seen throughout a majority of tissue types. The function of C16orf82 is not fully understood by the scientific community.
FANTOM is an international research consortium first established in 2000 as part of the RIKEN research institute in Japan. The original meeting gathered international scientists from diverse backgrounds to help annotate the function of mouse cDNA clones generated by the Hayashizaki group. Since the initial FANTOM1 effort, the consortium has released multiple projects that look to understand the mechanisms governing the regulation of mammalian genomes. Their work has generated a large collection of shared data and helped advance biochemical and bioinformatic methodologies in genomics research.
Manolis Kellis is a professor of Computer Science at the Massachusetts Institute of Technology (MIT) in the area of Computational Biology and a member of the Broad Institute of MIT and Harvard. He is the head of the Computational Biology Group at MIT and is a Principal Investigator in the Computer Science and Artificial Intelligence Lab (CSAIL) at MIT.
Emmanouil Theophilos Dermitzakis is a Greek human geneticist and professor in the Department of Genetic Medicine and Development at the University of Geneva, where he is also Director of the Health 2030 Genome Center. He is an ISI Highly Cited Researcher and an elected member of the European Molecular Biology Organization. He is a member of the Swiss Institute of Bioinformatics, where his research group is focused on the genetics and genomics of complex traits in humans. He has joined GlaxoSmithKline as Vice President, Computational Biology in R&D.
Barbara Elizabeth Engelhardt is an American computer scientist and specialist in bioinformatics. Working as a Professor at Stanford University, her work has focused on latent variable models, exploratory data analysis for genomic data, and QTLs. In 2021, she was awarded the Overton Prize by the International Society for Computational Biology.
Transcriptome-wide association study (TWAS) is a genetic methodology that can be used to compare the genetic components of gene expression and the genetic components of a trait to determine if an association is present between the two components. TWAS are useful for the identification and prioritization of candidate causal genes in candidate gene analysis following genome-wide association studies. TWAS looks at the RNA products of a specific tissue and gives researchers the abilities to look at the genes being expressed as well as gene expression levels, which varies by tissue type. TWAS are valuable and flexible bioinformatics tools that looks at the associations between the expressions of genes and complex traits and diseases. By looking at the association between gene expression and the trait expressed, genetic regulatory mechanisms can be investigated for the role that they play in the development of specific traits and diseases.
Alexander (Sasha) Gusev is a computational biologist and an Assistant Professor of Medicine at Harvard Medical School.
References
- ↑ "Gamazon Lab". Vanderbilt University. Retrieved 2022-01-02.
- 1 2 "Papers co-authored by Life Member published in Science and Nature". Clare Hall, Cambridge. Retrieved 2021-12-24.
- ↑ "Visiting Fellows". Clare Hall, Cambridge. Retrieved 2021-12-24.
- ↑ "Eric R. Gamazon publications indexed by Google Scholar". scholar.google.com. Retrieved 2022-01-01.
- ↑ "Getting specific with disease locations". Broad Institute of MIT and Harvard. 29 June 2018. Retrieved 2021-12-28.
- 1 2 Li B, Ritchie MD (September 2021). "From GWAS to Gene: Transcriptome-Wide Association Studies and Other Methods to Functionally Understand GWAS Discoveries". Frontiers in Genetics. 12: 713230. doi: 10.3389/fgene.2021.713230 . PMC 8515949 . PMID 34659337.
- ↑ Wainberg M, Sinnott-Armstrong N, Mancuso N, Barbeira AN, Knowles DA, Golan D, Ermel R, Ruusalepp A, Quertermous T, Hao K, Björkegren JL, Im HK, Pasaniuc B, Rivas MA, Kundaje A (April 2019). "Opportunities and challenges for transcriptome-wide association studies". Nature Genetics. 51 (4): 592–599. doi:10.1038/s41588-019-0385-z. PMC 6777347 . PMID 30926968.
- ↑ Zhou D, Jiang Y, Zhong X, Cox NJ, Liu C, Gamazon ER (November 2020). "A unified framework for joint-tissue transcriptome-wide association and Mendelian randomization analysis". Nature Genetics. 52 (11): 1239–1246. doi:10.1038/s41588-020-0706-2. PMC 7606598 . PMID 33020666.
- ↑ "Pubmed.gov". www.ncbi.nlm.nih.gov. Retrieved 2021-12-24.
- ↑ "GTEx Creates a Reference Data Set to Study Genetic Changes and Gene Expression". National Institutes of Health. 8 February 2018. Retrieved 2021-12-24.
- ↑ "Award supports integration of genomic data, electronic health records". Vanderbilt University Medical Center Reporter. Retrieved 2022-01-03.
- ↑ Laura M. Zahn (2019-06-14). "Editors' Choice - Gene expression can point to disease risk". Science. doi: 10.1126/science.2019.364.6445.twil . Retrieved 2021-12-31.
- ↑ "Advancing drug repositioning and development for Alzheimer's Disease using functional genomics and computational phenomics". NIH Research Portfolio Online Reporting Tools (RePORT). Retrieved 2022-01-01.
- ↑ "Potential new drugs for Alzheimer's disease identified by researchers". QIMR Berghofer Medical Research Institute, Brisbane, Australia. Retrieved 2021-12-31.
- ↑ "NIH announces six inaugural Genomic Innovator Awards". National Institutes of Health. 27 August 2019. Retrieved 2021-12-24.
- ↑ "Gamazon receives NIH Genomic Innovator Award". Vanderbilt University Medical Center Reporter. Retrieved 2021-12-24.
- ↑ "The Biologist - New Members" (PDF). Royal Society of Biology. Retrieved 2021-12-28.
- ↑ "Biostatistical Methods and Research Design Roster". National Institutes of Health. Retrieved 2021-12-29.
- ↑ "BMRD Study Section". NIH Center for Scientific Review. Retrieved 2021-12-29.
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