Sawyer 9707045 The investigator develops statistical tests for detecting gene conversion. Gene conversion is any process in biology that causes a segment of DNA to be copied to another DNA segment. Gene conversion is an important process in evolution, and also has consequences for human health. For example, it can cause the transference of pathogenic traits between bacteria and parts of viral genomes between viruses. Statistical tests for detecting gene conversion in aligned DNA or amino acid sequences are studied and extended. Particular emphasis is given to permutation or permutation-like tests that can evaluate unusually long segments on which two sequences are similar, or else on which a single sequence is unusually divergent. (This includes tests of Karlin-Altschul type, which are faster to perform but are not as accurate as permutation tests.) Some specific aims of the proposal are: (i) to extend these tests to allow occasional mismatches and alignment gaps by finding high-scoring segments for a similarity score rather than segment length, (ii) develop ways to improve the power and effectiveness of these tests, (iii) compare statistical procedures for detecting gene conversion in regards to efficiency and power, and (iv) make the resulting improved software available to the biological community on a Web site. Human HIV and influenza viruses belong to a family of viruses (RNA retroviruses) that not only are highly changeable, but can also exchange pieces of genetic material among themselves. Viruses that can exchange blocks of genetic material are more dangerous since the more adaptive parts of the virus can spread rapidly, and since vaccines that target only part of the virus can become rapidly obsolete. There are also several families of plant viruses in this viral family that cause damage to food crops of economic importance. The project extends a statistical test that can detect a history of such exchanges from a sample of genetic sequ ences and assign measures of statistical likelihood to the most likely events. This will help to understand the nature of the evolution of these particular viruses. The work extends earlier work of the investigator that looked for possible exchange events in aligned DNA sequences under the assumption that the exchanged material had not undergone later mutation. This assumption does not hold for these highly mutable viruses. In addition, recent work has shown that the earlier test has biases in some of its procedures that can hide evidence for some exchange (or gene conversion) events. This bias is removed. Finally, computer software that implements the improved procedures, including listing the most likely exchange events and their statistical likelihood, is made more available on the internet for the biological community. (Software that implements the earlier procedures has been widely used.)
