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A quantitative trait locus (QTL) is a locus that correlates with variation of a quantitative trait in the phenotype of a population of organisms. QTLs are mapped by identifying which molecular markers correlate with an observed trait. This is often an early step in identifying and sequencing the actual genes that cause the trait variation.
Genetic architecture is the underlying genetic basis of a phenotypic trait and its variational properties. Phenotypic variation for quantitative traits is, at the most basic level, the result of the segregation of alleles at quantitative trait loci (QTL). Environmental factors and other external influences can also play a role in phenotypic variation. Genetic architecture is a broad term that can be described for any given individual based on information regarding gene and allele number, the distribution of allelic and mutational effects, and patterns of pleiotropy, dominance, and epistasis.
Genetic association is when one or more genotypes within a population co-occur with a phenotypic trait more often than would be expected by chance occurrence.
The thrifty gene hypothesis, or Gianfranco's hypothesis is an attempt by geneticist James V. Neel to explain why certain populations and subpopulations in the modern day are prone to diabetes mellitus type 2. He proposed the hypothesis in 1962 to resolve a fundamental problem: diabetes is clearly a very harmful medical condition, yet it is quite common, and it was already evident to Neel that it likely had a strong genetic basis. The problem is to understand how disease with a likely genetic component and with such negative effects may have been favoured by the process of natural selection. Neel suggested the resolution to this problem is that genes which predispose to diabetes were historically advantageous, but they became detrimental in the modern world. In his words they were "rendered detrimental by 'progress'". Neel's primary interest was in diabetes, but the idea was soon expanded to encompass obesity as well. Thrifty genes are genes which enable individuals to efficiently collect and process food to deposit fat during periods of food abundance in order to provide for periods of food shortage.
The common disease-common variant hypothesis predicts that common disease-causing alleles, or variants, will be found in all human populations which manifest a given disease. Common variants are known to exist in coding and regulatory sequences of genes. According to the CD-CV hypothesis, some of those variants lead to susceptibility to complex polygenic diseases. Each variant at each gene influencing a complex disease will have a small additive or multiplicative effect on the disease phenotype. These diseases, or traits, are evolutionarily neutral in part because so many genes influence the traits. The hypothesis has held in the case of putative causal variants in apolipoprotein E, including APOE ε4, associated with Alzheimer's disease. IL23R has been found to be associated with Crohn's disease; the at-risk allele has a frequency 93% in the general population.
Zinc transporter 8 (ZNT8) is a protein that in humans is encoded by the SLC30A8 gene. ZNT8 is a zinc transporter related to insulin secretion in humans. Certain alleles of the SLC30A8 gene may increase the risk for developing type 2 diabetes, but a loss-of-function mutation appears to greatly reduce the risk of diabetes.
In genomics, a genome-wide association study, also known as whole genome 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.
Like many other medical conditions, obesity is the result of an interplay between environmental and genetic factors. Studies have identified variants in several genes that may contribute to weight gain and body fat distribution; although, only in a few cases are genes the primary cause of obesity.
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.
3-Ketoacyl-CoA thiolase, mitochondrial also known as acetyl-Coenzyme A acyltransferase 2 is an enzyme that in humans is encoded by the ACAA2 gene.
The "missing heritability" problem is the fact that single genetic variations cannot account for much of the heritability of diseases, behaviors, and other phenotypes. This is a problem that has significant implications for medicine, since a person's susceptibility to disease may depend more on 'the combined effect of all the genes in the background than on the disease genes in the foreground', or the role of genes may have been severely overestimated.
Michael Lee Boehnke is an American geneticist. He is the Richard G. Cornell Distinguished University Professor of Biostatistics at the University of Michigan School of Public Health, where he also directs the Center for Statistical Genetics. His research focuses on the genetic dissection of complex traits; in a career spanning 25 years, he has developed methods for analysis of human pedigrees, examined the history of breast cancer in genetically at risk individuals, and contributed important discoveries on the genetics of type 2 diabetes and related traits, such as obesity and blood lipid levels.
Imputation in genetics refers to the statistical inference of unobserved genotypes. It is achieved by using known haplotypes in a population, for instance from the HapMap or the 1000 Genomes Project in humans, thereby allowing to test for association between a trait of interest and experimentally untyped genetic variants, but whose genotypes have been statistically inferred ("imputed"). Genotype imputation is usually performed on SNPs, the most common kind of genetic variation.
Mega2 allows the applied statistical geneticist to convert one's data from several input formats to a large number output formats suitable for analysis by commonly used software packages. In a typical human genetics study, the analyst often needs to use a variety of different software programs to analyze the data, and these programs usually require that the data be formatted to their precise input specifications. Conversion of one's data into these multiple different formats can be tedious, time-consuming, and error-prone. Mega2, by providing validated conversion pipelines, can accelerate the analyses while reducing errors.
A rare functional variant is a genetic variant which alters gene function, and which occurs at low frequency in a population. Rare variants may play a significant role in complex disease, as well as some Mendelian conditions. Rare variants may be responsible for a portion of the missing heritability of complex diseases. The theoretical case for a significant role of rare variants is that alleles that strongly predispose an individual to disease will be kept at low frequencies in populations by purifying selection. Rare variants are increasingly being studied, as a consequence of whole exome and whole genome sequencing efforts. While these variants are individually infrequent in populations, there are many in human populations, and they can be unique to specific populations. They are more likely to be deleterious than common variants, as a result of rapid population growth and weak purifying selection. They have been suspected of acting independently or along with common variants to cause disease states.
Predictive genomics is at the intersection of multiple disciplines: predictive medicine, personal genomics and translational bioinformatics. Specifically, predictive genomics deals with the future phenotypic outcomes via prediction in areas such as complex multifactorial diseases in humans. To date, the success of predictive genomics has been dependent on the genetic framework underlying these applications, typically explored in genome-wide association (GWA) studies. The identification of associated single-nucleotide polymorphisms underpin GWA studies in complex diseases that have ranged from Type 2 Diabetes (T2D), Age-related macular degeneration (AMD) and Crohn's disease.
Eleftheria Zeggini is a director of the institute of translational genomics in Helmholtz Zentrum München and a professor at the Technical University of Munich (TUM). Previously she served as a research group leader at the Wellcome Trust Sanger Institute from 2008 to 2018 and an honorary professor in the department of health sciences at the University of Leicester in the UK.
Complex traits, also known as quantitative traits, are traits that do not behave according to simple Mendelian inheritance laws. More specifically, their inheritance cannot be explained by the genetic segregation of a single gene. Such traits show a continuous range of variation and are influenced by both environmental and genetic factors. Compared to strictly Mendelian traits, complex traits are far more common, and because they can be hugely polygenic, they are studied using statistical techniques such as QTL mapping rather than classical genetics methods. Examples of complex traits include height, circadian rhythms, enzyme kinetics, and many diseases including diabetes and Parkinson's disease. One major goal of genetic research today is to better understand the molecular mechanisms through which genetic variants act to influence complex traits.
Anubha Mahajan is a human genetics researcher whose career has focused on genetic analysis of complex traits, with an emphasis on type 2 diabetes. Mahajan has co-led and led analysis of high-throughput genetic studies as part of large international consortia, such as DIAGRAM, GoT2D, T2D-GENES, and DIAMANTE, that explore the genetic architecture of type 2 diabetes. More recently, she has moved from genetic discovery to utilizing human genetics research to understand the pathophysiological mechanisms that contribute to type 2 diabetes.
References
- 1 2 "Karen L. Mohlke". Karen Mohlke Lab. Retrieved 8 December 2014.
- ↑ "Karen Mohlke Lab". The University of North Carolina at Chapel Hill. Retrieved 11 December 2014.
- ↑ "New Findings in the Search for Genetic Clues to Insulin Production". newswise.com. Retrieved 8 December 2014.
- ↑ "Gene variants influence insulin production". Futurity. 28 December 2012. Retrieved 8 December 2014.
- ↑ "Genetic Variations Cause Diabetes". Medical News Today. 26 December 2012. Retrieved 8 December 2014.
- ↑ "Karen Mohlke, PhD". UNC School of Medicine. Retrieved 8 December 2014.