Dictionary Definition
polygenic adj : of or relating to an inheritable
character that is controlled by several genes at once; of or
related to or determined by polygenes
User Contributed Dictionary
English
Adjective
polygenic- controlled by the interaction of more than one gene
- (of a function) having an infinite number of derivatives at a point (otherwise it is monogenic)
Extensive Definition
Inheritance of quantitative traits or polygenic
inheritance refers to the inheritance of a phenotypic characteristic that
varies in degree and can be attributed to the interactions between
two or more genes and
their environment. Though not necessarily genes themselves, quantitative
trait loci (QTLs) are stretches of DNA that are closely linked to
the genes that underlie the trait in question. QTLs can be
molecularly identified (for example, with PCR) to help map
regions of the genome that contain genes involved in specifying a
quantitative trait. This can be an early step in identifying and
sequencing these genes.
Quantitative traits
Polygenic inheritance, also known as quantitative or multifactorial inheritance refers to inheritance of a phenotypic characteristic (trait) that is attributable to two or more genes and their interaction with the environment. Unlike monogenic traits, polygenic traits do not follow patterns of Mendelian inheritance (qualitative traits). Instead, their phenotypes typically vary along a continuous gradient depicted by a bell curve.An example of a polygenic trait is human skin
color. Many genes factor into determining a person's natural skin
color, so modifying only one of those genes changes the color only
slightly. Many disorders with genetic
components are polygenic, including autism, cancer, diabetes and numerous others.
Most phenotypic characteristics are the result of the interaction
of multiple genes.
Examples of disease processes generally
considered to be results of multifactorial etiology:
Congenital malformation
Adult
onset diseases
Multifactorial traits in general
Generally, multifactorial traits outside of illness contribute to what we see as continuous characteristics in organisms, such as height. All of these phenotypes are complicated by a great deal of interplay between genes and environment.Thus, due to the nature of polygenic traits,
inheritance will not follow the same pattern as a simple monohybrid
or dihybrid
cross
More often than not, investigators will
hypothesise that a disease is multifactorially heritable, along
with a cluster of other hypotheses when it is not known what causes
the disease.
Quantitative trait locus
Typically, QTLs underlie continuous traits
(those traits that vary continuously - the trait could have any
value within a range - e.g., height) as opposed to discrete traits
(traits that have two or several character values - e.g., eye
colour or smooth vs. wrinkled peas used by Mendel in
his experiments).
Moreover, a single phenotypic trait
is usually determined by many genes. Consequently, many QTLs are
associated with a single trait.
A quantitative trait locus (QTL) is a region of
DNA that is
associated with a particular phenotypic
trait
- these QTLs are often found on different chromosomes. Knowing the
number of QTLs that explains variation in the phenotypic trait
tells us about the genetic
architecture of a trait. It may tell us that plant height is
controlled by many genes of small effect, or by a few genes of
large effect.
Another use of QTLs is to identify candidate
genes underlying a trait. Once a region of DNA is identified as
contributing to a phenotype, it can be sequenced. The DNA sequence of
any genes in this region can then be compared to a database of DNA
for genes whose function is already known.
In a recent development, classical QTL analyses
are combined with gene expression profiling i.e. by DNA
microarrays. Such expression QTLs (e-QTLs) describe cis- and trans-controlling elements for the
expression of often disease-associated genes. Observed epistatic effects have been
found beneficial to identify the gene responsible by a
cross-validation of genes within the interacting loci with metabolic
pathway- and scientific
literature databases.
QTL mapping
QTL mapping
is the statistical
study of the alleles that occur in a locus and the phenotypes
(physical forms or traits) that they produce. Because most traits
of interest are governed by more than one gene, defining and
studying the entire locus of genes related to a trait gives hope of
understanding what effect the genotype of an individual might have
in the real world.
Statistical analysis is required to demonstrate
that different genes interact with one another and to determine
whether they produce a significant effect on the phenotype. QTLs
identify a particular region of the genome as containing a gene that
is associated with the trait being assayed or measured. They are
shown as intervals across a chromosome, where the
probability of association is plotted for each marker used in the
mapping experiment.
The QTL techniques were developed in the late
1980s and can
be performed on inbred strains of any species.
To begin, a set of genetic markers must be
developed for the species in question. A marker is an identifiable
region of variable DNA. Biologists are interested in understanding
the genetic basis of phenotypes (physical traits).
The aim is to find a marker that is significantly more likely to
co-occur with the trait than expected by chance, that is, a marker
that has a statistical association with the trait. Ideally, they
would be able to find the specific gene or genes in question, but this
is a long and difficult undertaking. Instead, they can more readily
find regions of DNA that are very close to the genes in question.
When a QTL is found, it is often not the actual gene underlying the
phenotypic trait, but rather a region of DNA that is closely linked
with the gene.
For organisms whose genomes are known, one might
now try to exclude genes in the identified region whose function is
known with some certainty not to be connected with the trait in
question. If the genome is not available, it may be an option to
sequence the identified region and determine the putative functions
of genes by their similarity to genes with known function, usually
in other genomes.
Another interest of statistical geneticists using
QTL mapping is to determine the complexity of the genetic
architecture underlying a phenotypic trait. For example, they may
be interested in knowing whether a phenotype is shaped by many
independent loci, or by a few loci, and do those loci interact.
This can provide information on how the phenotype may be
evolving.
QTL mapping in plants
The beauty of QTL mapping in plants is facility of experimental crosses in contrast to humans.Analysis of variance
The simplest method for QTL mapping is analysis of variance (ANOVA, sometimes called "marker regression") at the marker loci. In this method, in a backcross, one may calculate a t-statistic to compare the averages of the two marker genotype groups. For other types of crosses (such as the intercross), where there are more than two possible genotypes, one uses a more general form of ANOVA, which provides a so-called F-statistic. The ANOVA approach for QTL mapping has three important weaknesses. First, we do not receive separate estimates of QTL location and QTL effect. QTL location is indicated only by looking at which markers give the greatest differences between genotype group averages, and the apparent QTL effect at a marker will be smaller than the true QTL effect as a result of recombination between the marker and the QTL. Second, we must discard individuals whose genotypes are missing at the marker. Third, when the markers are widely spaced, the QTL may be quite far from all markers, and so the power for QTL detection will decrease.Interval mapping
Lander and Botstein developed interval mapping,
which overcomes the three disadvantages of analysis of variance at
marker loci. Interval mapping is currently the most popular
approach for QTL mapping in experimental crosses. The method makes
use of a genetic map of the typed markers, and, like analysis of
variance, assumes the presence of a single QTL. Each location in
the genome is posited, one at a time, as the location of the
putative QTL.
Composite interval mapping (CIM)
In this method, one performs interval mapping
using a subset of marker loci as covariates. These markers serve as
proxies for other QTLs to increase the resolution of interval
mapping, by accounting for linked QTLs and reducing the residual
variation. The key problem with CIM concerns the choice of suitable
marker loci to serve as covariates; once these have been chosen,
CIM turns the model selection problem into a single-dimensional
scan. The choice of marker covariates has not been solved, however.
Not surprisingly, the appropriate markers are those closest to the
true QTLs, and so if one could find these, the QTL mapping problem
would be complete anyway.
Non-traditional methods: Family-pedigree based mapping
The human genetic approach has taken attention to
plant scientist to fit in to plant breeders families (for review-
Jannik et al., 2001). There are some successful attempts to do so.
One of quick method of QTL mapping is recently discussed (Rosyara
et al., 2007).
Jannink, J.; Bink, M. C.A.M.; and Jansen, R.C.
2001. Using complex plant pedigrees to map valuable genes. Trends
in Plant Science 6: 337-342.
Rosyara, U. R.; K.L. Maxson-Stein; K.D. Glover;
J.M. Stein; J.L. Gonzalez-Hernandez. 2007. Family-based mapping of
FHB resistance QTLs in hexaploid wheat. Proceedings of National
Fusarium head blight forum, 2007, Dec 2-4, Kansas City, MO.
References
External links
polygenic in German: Quantitative Trait
Locus
polygenic in French: Quantitative Trait
Locus
polygenic in Italian: Tratto quantitativo
polygenic in Japanese: 量的形質座位