"Tall people have tall children, and short people have short children." For many this statement summarizes all that needs to be known regarding the relationship between a person’s height and heredity. For geneticists, however, these types of general observations represent an open intellectual challenge, since a more careful observation of the human population reveals that there is considerable variation with regards to height, and that it is possible for tall people to have short children, and vice versa.
A Quantitative And Multifactorial Trait
For years scientists have known that height is a quantitative trait, meaning that the population does not fall into distinct phenotypic classes. Anyone who purchases clothes knows that people are not "tall," "short" or "medium." Instead, height in humans is distributed around a mean value. This form of distribution, or bell-shaped curve, is characteristic of a trait that is under the influence of multiple genes, each one having an additive effect on the phenotype. The more of the
alleles that a person has, the further along the distribution the phenotype is located.
Geneticists also recognize that height is a multifactorial trait. Multifactorial does not mean simply that multiple genes are involved. The term multifactorial indicates that there are both genetic and environmental factors that are contributing to the observed phenotype.
A wonderful illustration of the multifactorial basis of human height is provided by Ricki Lewis in her textbook, Human Genetics, Seventh Edition. Lewis presents two photos of the graduating class of Connecticut Agricultural College, one taken circa 1920, the other in 1997. In both photos, the students were placed into phenotypic classes by height (to the nearest inch). The distribution of both classes follows a distinctive bell-shaped curve characteristic of a quantitative trait. The difference is that the mean height of the 1997 class was much greater than that of the 1920 class. Whereas the tallest individual in 1920 was 5’9", the tallest individual in 1997 was 6’5".
Since it is unlikely that a "tall" mutation has infiltrated the entire graduating class, and therefore the genetic basis of the two populations should be roughly the same, then there must be some other factor involved. Human geneticists and medical professionals say that the overall change in height over the past several decades is primarily due to improvements in human nutrition – an environmental factor. Building on this, geneticists have suggested that human height may be the
result of the interaction of environmental factors with several major genetic mechanisms and a host of minor genes.
Use Of Genome-Wide Association Studies
As a geneticist who has studied quantitative traits in Drosophila, I can testify that one of the hardest problems facing quantitative geneticists is the ability to tease out the influence of major and minor genes on a phenotype. Many methods exist to investigate the contributions of a single gene to a phenotype, but searching for all of the minor contributing genes has remained a relatively difficult task. Recently, a research group led by Timothy Frayling at Peninsula Medical School in Exeter, UK, reported the use of the genome-wide association studies (GWAs)
to identify genes responsible for variations in the height of humans (Nature Genetics, October 2007). The use of association studies in human genetic analysis is nothing new as they have been used with a variety of genetic markers for several decades. However, the use of GWAs in this manner is something significant as it allowed the researchers to look at contributing alleles across the genome, and not simply in the vicinity of candidate genes. This technique should give researchers the ability to identity a greater number of minor genes, or those that make smaller contributions to the phenotype in question. This could prove to be very useful for complex diseases and traits that are under the control of multiple genes.
Breakthroughs In HMGA2
The gene that Frayling’s group identified, HMGA2, is not a new discovery. As the researchers report, it has been known for some time that severe disruptions of this gene can cause drastic changes in the height phenotype (dwarfism and gigantism) of mice. What Frayling was able to show is that certain alleles of this gene are associated with height at specific times during development. Interestingly, the associations indicated that certain alleles are associated with an
increase in height between the ages of 7 and 11 years and persisting into adulthood. This identification of this temporal importance suggests that other genes remain to be identified that play a role earlier in life. But there is also a catch – the gene that is responsible for the added height is also associated with an increased risk of certain types of cancer. The gene product of HMGA2 belongs to a family of proteins that act as DNA-binding proteins, meaning that HMGA2 most likely has a role in the regulation of gene expression. Although HMGA2 is not an oncogene, it has been observed to be overexpressed in certain types of tumors, meaning that while a gene might be a minor gene in one quantitative trait, it may be a major gene for another trait.
With the developing promise of gene therapy might it be someday possible to prevent individuals from being vertically challenged? In today’s world there is always someone who will want to capitalize on a discovery such as this by promising increased height to short people. Though some might see it as an opportunity to change or select the phenotype of an individual, in reality this paper has a far greater significance. The identification of HMGA2’s role in height
is an important breakthrough in the study of complex quantitative traits, and it demonstrates the power of new genome analysis techniques that are coming online. As Frayling and his colleagues suggest, the true power of this technique will be when it is applied to the study of complex diseases.
A Quantitative And Multifactorial Trait
For years scientists have known that height is a quantitative trait, meaning that the population does not fall into distinct phenotypic classes. Anyone who purchases clothes knows that people are not "tall," "short" or "medium." Instead, height in humans is distributed around a mean value. This form of distribution, or bell-shaped curve, is characteristic of a trait that is under the influence of multiple genes, each one having an additive effect on the phenotype. The more of the
alleles that a person has, the further along the distribution the phenotype is located.
Geneticists also recognize that height is a multifactorial trait. Multifactorial does not mean simply that multiple genes are involved. The term multifactorial indicates that there are both genetic and environmental factors that are contributing to the observed phenotype.
A wonderful illustration of the multifactorial basis of human height is provided by Ricki Lewis in her textbook, Human Genetics, Seventh Edition. Lewis presents two photos of the graduating class of Connecticut Agricultural College, one taken circa 1920, the other in 1997. In both photos, the students were placed into phenotypic classes by height (to the nearest inch). The distribution of both classes follows a distinctive bell-shaped curve characteristic of a quantitative trait. The difference is that the mean height of the 1997 class was much greater than that of the 1920 class. Whereas the tallest individual in 1920 was 5’9", the tallest individual in 1997 was 6’5".
Since it is unlikely that a "tall" mutation has infiltrated the entire graduating class, and therefore the genetic basis of the two populations should be roughly the same, then there must be some other factor involved. Human geneticists and medical professionals say that the overall change in height over the past several decades is primarily due to improvements in human nutrition – an environmental factor. Building on this, geneticists have suggested that human height may be the
result of the interaction of environmental factors with several major genetic mechanisms and a host of minor genes.
Use Of Genome-Wide Association Studies
As a geneticist who has studied quantitative traits in Drosophila, I can testify that one of the hardest problems facing quantitative geneticists is the ability to tease out the influence of major and minor genes on a phenotype. Many methods exist to investigate the contributions of a single gene to a phenotype, but searching for all of the minor contributing genes has remained a relatively difficult task. Recently, a research group led by Timothy Frayling at Peninsula Medical School in Exeter, UK, reported the use of the genome-wide association studies (GWAs)
to identify genes responsible for variations in the height of humans (Nature Genetics, October 2007). The use of association studies in human genetic analysis is nothing new as they have been used with a variety of genetic markers for several decades. However, the use of GWAs in this manner is something significant as it allowed the researchers to look at contributing alleles across the genome, and not simply in the vicinity of candidate genes. This technique should give researchers the ability to identity a greater number of minor genes, or those that make smaller contributions to the phenotype in question. This could prove to be very useful for complex diseases and traits that are under the control of multiple genes.
Breakthroughs In HMGA2
The gene that Frayling’s group identified, HMGA2, is not a new discovery. As the researchers report, it has been known for some time that severe disruptions of this gene can cause drastic changes in the height phenotype (dwarfism and gigantism) of mice. What Frayling was able to show is that certain alleles of this gene are associated with height at specific times during development. Interestingly, the associations indicated that certain alleles are associated with an
increase in height between the ages of 7 and 11 years and persisting into adulthood. This identification of this temporal importance suggests that other genes remain to be identified that play a role earlier in life. But there is also a catch – the gene that is responsible for the added height is also associated with an increased risk of certain types of cancer. The gene product of HMGA2 belongs to a family of proteins that act as DNA-binding proteins, meaning that HMGA2 most likely has a role in the regulation of gene expression. Although HMGA2 is not an oncogene, it has been observed to be overexpressed in certain types of tumors, meaning that while a gene might be a minor gene in one quantitative trait, it may be a major gene for another trait.
With the developing promise of gene therapy might it be someday possible to prevent individuals from being vertically challenged? In today’s world there is always someone who will want to capitalize on a discovery such as this by promising increased height to short people. Though some might see it as an opportunity to change or select the phenotype of an individual, in reality this paper has a far greater significance. The identification of HMGA2’s role in height
is an important breakthrough in the study of complex quantitative traits, and it demonstrates the power of new genome analysis techniques that are coming online. As Frayling and his colleagues suggest, the true power of this technique will be when it is applied to the study of complex diseases.
This article was originally published in BioWorld Perspectives (vol 1 # 46) in November 2007 and is reprinted here by permission from AHC Media LLC.
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