Epistasis Blog

From the Computational Genetics Laboratory at Dartmouth Medical School (www.epistasis.org)

Saturday, March 26, 2005

Tree Scanning

Tree scanning is a new method for using haplotype trees in phenotype/genotype association studies. See:

Templeton et al. Tree scanning: a method for using haplotype trees in phenotype/genotype association studies. Genetics. 2005 Jan;169(1):441-53. [PubMed]

Posada et al. TreeScan: a bioinformatic application to search for genotype/phenotype associations using haplotype trees. Bioinformatics. 2005 Jan 28. [PubMed]

This work is related to Alan Templeton's work on cladistic analysis. The following paper extends the cladistic approach:

Durrant et al. Linkage disequilibrium mapping via cladistic analysis of single-nucleotide polymorphism haplotypes. Am J Hum Genet. 2004 Jul;75(1):35-43. [PubMed]

Here is an application of cladistic analysis to the liporptein lipase gene:

Templeton et al. Cladistic structure within the human Lipoprotein lipase gene and its implications for phenotypic association studies. Genetics. 2000 Nov;156(3):1259-75. [PubMed]

Here is an older review of cladistic analysis:

Templeton. Cladistic approaches to identifying determinants of variability in multifactorial phenotypes and the evolutionary significance of variation in the human genome. Ciba Found Symp. 1996;197:259-77. [PubMed]

Friday, March 18, 2005

Epistasis among Presynaptic Serotonergic System Components

A new paper by Stoltenberg studies epistasis among regulatory components of the serotonin (5-HT) neurotransmitter system using computer simulations.

Stoltenberg SF. Epistasis among Presynaptic Serotonergic System Components. Behav Genet. 2005 Mar;35(2):199-209. [PubMed]

Here is the abstract:

Epistatic interactions among regulatory components of the serotonin (5-HT) neurotransmitter system may be an important aspect of 5-HT function. Because 5-HT dysregulation is associated with several common psychiatric disorders, the potential for epistasis among genetic variants in the 5-HT transporter (SERT), 5-HT ( 1B) terminal autoreceptor and the 5-HT(1A) somatodendritic autoreceptor should be examined. In this study, output from a dynamic minimal model of 5-HT function was compared to empirical results in the literature. Parameters representing extracellular 5-HT clearance rates (SERT), 5-HT release levels (5-HT (1B)) and inhibitory thresholds (the amount of extracellular 5-HT above which cell firing is inhibited, an indication of 5-HT (1A)autoreceptor sensitivity) were varied to simulate genetic deletion (i.e. knockout) of each component singly, and in combination. Simulated knockout effects on extracellular 5-HT level and presynaptic neural firing rates were in the same direction and of similar relative magnitude as studies in the literature. Epistasis among presynaptic components appears to be important in the 5-HT system's regulation of extracellular 5-HT levels, but not of firing rates.

Monday, March 14, 2005

BioGEC Deadline Extended

The paper submission deadline for the GECCO 2005 Workshop on the Biological Applications of Genetic and Evolutionary Computation (BioGEC) has been extended to April 11th.

Tuesday, March 08, 2005

MDR Released in Weka-CG

The Dartmouth Computational Genetics Laboratory (CGL) is happy to announce the release of of Weka-CG, an open-source version of the Weka machine learning software for computational genetics (CG) . This initial release includes our multifactor dimensionality reduction (MDR) constructive induction algorithm as a 'filter' module in Weka. This makes it possible to combine MDR with a number of other data mining algorithms. Weka-CG can be downloaded from here.

Sunday, March 06, 2005

BioGEC Workshop Paper Deadline: March 14

This is a reminder that papers are due March 14th for the Biological Applications of Genetic and Evolutionary Computation (BioGEC) workshop. The fourth annual BioGEC workshop, organized in connection with the 2005 Genetic and Evolutionary Computation Conference (GECCO-2005) in Washington DC, USA, is intended to explore and critically evaluate the application of genetic and evolutionary computing (GEC) to biological problems. Specifically, the goal is to bring biologists and computer scientists together to foster an exchange of ideas that will yield emergent properties that will move the field forward in unpredictable ways. In order to facilitate interaction and discussion, the workshop invites papers in the form of commentaries, essays, perspectives, surveys, tutorials, and reviews that focus on ideas for discussion rather than specific research results. Questions that might be addressed in a paper include (but are not limited to):

1) What biological problems are GEC methods well-suited for?
2) What biological problems are GEC methods not well-suited for?
3) Which of the many GEC methods should be used for a specific biological problem?
4) What are the successes and failures of GEC for a specific biological problem?
5) What impact has GEC had on biology/bioinformatics?
6) Should all biologists/bioinformaticists be using GEC?
7) What is the future of GEC for solving biological problems?
8) What GEC software tools are available for use by biologists/bioinformaticists?
9) What unanswered questions in GEC are relevant to solving biological problems?

Important Dates:

March 14, 2005: papers due
April 8, 2005: acceptance notices
April 22, 2005: camera ready revisions due
June 25-26, 2005: BioGEC workshop

Canalization and Epistasis

Epistasis has been defined in multiple different ways (e.g. Hollander 1955; Philips 1998; Brodie 2000; Wade et al. 2001; Cordell 2002; Moore and Williams 2005). Most definitions relate back to early work by Bateson (1909) and Fisher (1918) that focused on "biological epistasis" and "statistical epistasis", respectively. A biological system is said to be canalized (Waddington 1942, 1957) when it is buffered against mutations and/or environmental change. Canalization results from stabilizing selection and leads to robust genetic networks that exhibit epistasis (e.g. Gibson and Wagner 2000; de Visser et al. 2003). A new review by Proulx and Phillips (2005) discusses canalization and the evolution of genetic networks.

Bateson W. Mendel's Principles of Heredity. Cambridge University Press, Cambridge, 1909.

Brodie III ED. Why evolutionary genetics does not always add up. In: Wolf J, Brodie III B, Wade M (eds) Epistasis and the Evolutionary Process, Oxford University Press, New York, pp. 3-19, 2000.

Cordell. Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans. Hum Mol Genet. 2002 Oct 1;11(20):2463-8. [PubMed]

de Visser et al. Perspective: Evolution and detection of genetic robustness. Evolution Int J Org Evolution. 2003 Sep;57(9):1959-72. [PubMed]

Fisher RA. The correlations between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinb 52:399-433, 1918.

Gibson G, Wagner G. Canalization in evolutionary genetics: a stabilizing theory? Bioessays. 2000 Apr;22(4):372-80. [PubMed]

Hollander WF. Epistasis and hypostasis. J Hered 1955;46:222-225.

Moore and WIlliams. Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis. BioEssays 2005 June, in press. [BioEssays]

Phillips. The language of gene interaction. Genetics. 1998 Jul;149(3):1167-71. [PubMed]

Proulx and Phillips. The opportunity for canalization and the evolution of genetic networks. Am Nat. 2005 Feb;165(2):147-62. [PubMed]

Wade et al. Alternative definitions of epistasis: dependence and interaction. Trends in Ecology and Evolution 2001;16:498-504. [pdf]

Waddington CH. Canalization of development and the inheritance of acquired characters. Nature 1942;150:563-5.

Waddington CH. The Strategy of the Genes. MacMillan, New York, 1957.