In Mendelian inheritance a genotype always matches a particular phenotype. This is not always the case! Some phenotypes may be controlled by several genes, which may have varying levels of influence over the trait. These are known as complex traits.
Example: Eye colour perfectly highlights the difference between Mendelian and complex traits. In drosophila, eye colour is a Mendelian trait, as you will most likely remember from high school biology class, red is dominant and white is recessive. In humans, eye colour is a complex trait; it is thought that as many as 16 genes could be involved in eye colour. This is why we see a range of eye colours in human populations rather than the clear-cut red or white seen in drosophila.
Complex traits – many genes to one trait
Complex traits also differ from Mendelian traits in that the environment along with the genotype can influence the phenotype on display. Height is a good example of this, it has been proven that several genes contribute to the potential height of an individual but nutrition is as, if not more important.
Complex traits are typically studied by looking at QTLs (Quantitative Trait Loci); these are pieces of DNA (genomic regions) that have been linked to a complex trait.
QTL mapping has become one of the most intriguing research tools in modern genomics. SNPs can be tagged within the human genome based on linkage dis equilibrium association and this allows for genome wide association scans to be carried out. Genome wide association scans have contributed greatly to research on genetics and disease
The graph above displays the typical bell curve sometimes used to illustrate the genetic control of a complex trait – height. Close the origin you would find individuals with few genes associated with “tallness”, and at the 3 value on the X-axis you would find individuals with many genes associated with “tallness”. Therefore, the height of the individuals represented in the graph increases as we move along the X-axis and the genetic control of the trait increases. Note: that the majority of the population represented have some genes for the trait and therefore are of average height.
Autism provides an excellent opportunity to study the genetic control of a complex trait. It has been estimated that the disease has a heritability of almost 90%. Several genes have been linked to both classical autism, the kind that leads to severe mental retardation and Asperger’s syndrome, the version of the disease that leads to severe social difficulties but often leads to above average gifts in subjects like math. To link genes to autism, genome wide scans are used. Statistical tests are used to determine what regions of the genome are linked to autistic traits, i.e. if the P value is 0.05 or lower then the region is a candidate region. Genetic regions on chromosomes 2q, 7q, 16p and 19p have been strongly linked to autistic traits and may have a large influence of the traits displayed. However, many other genes have been linked to autism, and some may only have minute effects. An autistic spectrum has been developed to measure the variation of autistic disorders present within the population. This reflects the fact that the traits are under the control over several genes, so depending on which genes are present in the individual they may display a higher or lower score on the autistic spectrum. This is highlighted by studies that indicate that the siblings of children with classical autism or Asperger’s syndrome score higher than average on the autistic spectrum
Linkage studies involving patients with schizophrenia and their unaffected family members have identified chromosome 5 and chromosome 19 as being linked to schizophrenia. The same genetic deficits have in some cases been found in patients and unaffected relatives but not in the general population. This has led to suggestions that genetics may leave individual susceptible to schizophrenia but other factors are required before the disease will develop.
Systems genetics – many genes many traits
Example: A recent study using drosophila has found that several genes can be linked to several different ecologically relevant traits. This means that the genetic make up of drosophila may be able to be linked to the phenotypes that make them successful in their environment.
Systems genetics are becoming a key area of modern biomedical research. Studying the links between genetic make up and phenotypic traits and disease is the focus of genomics and bioinformatics. Computer databases like GeneNetwork and GenBank contain huge levels of genetic data. This information can be used for bioinformatics research by manipulating the data using computer programming languages such as Python or Perl.
Alcoholism is a very complex condition as it is linked not only to genetics and genetics and environmental conditions but also the social conventions surrounding the individuals. The systems biology study of alcoholism has studied not only the genetic variations between individuals but also the genetic variation within individuals. In this case it is possible to study how the variations within one individual interact with each other and the environment to leave an individual more or less susceptible to becoming addicted to alcohol.
A great review article on the interaction between genes that generate complex traits:
Shao, H., L. C. Burrage, et al. (2008). "Genetic architecture of complex traits: Large phenotypic effects and pervasive epistasis." Proceedings of the National Academy of Sciences 105(50): 19910-19914.
Another review on the methods used to understand complex traits:
Lander, E. S. and N. J. Schork (1994). "Genetic dissection of complex traits." Science 265(5181): 2037-2048.
A book chapter on the genetics of autism:
Ijichi, S., N. Ijichi, et al. "The Genetic Basis of Phenotypic Diversity: Autism as an Extreme Tail of a Complex Dimensional Trait."
The study of Drosophila mentioned in the systems biology section, an overvie of systems genetics in the Fly:
Ayroles, J. F., M. A. Carbone, et al. (2009). "Systems genetics of complex traits in Drosophila melanogaster." Nature genetics 41(3): 299-307.
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