Construction of high-resolution likelihood-based integrated genetic and physical map of Neurospora crassa
Abstract
Neurospora crassa, a model organism has been extensively used to explore fundamental cellular processes, such as recombination and for construction of high-resolution maps because of its excellent biological characteristics. In this thesis we bring to bear statistical techniques to integrate genome map information gleaned from two different sources with varying resolution to create a high resolution integrated physical and genetic map. Those two different sources of genomic information in our case are a high resolution restriction frequent length polymorphism (RFLP) DNA markers and hybridization based physical data. Recombination has long been used to create genetic maps starting from the rudimentary but powerful empirical pair-wise frequency analysis to sophisticated statistical models with generalized cross-over phenomena. Most of these approaches are theoretical lacking any practical model estimation, or fail to capture the details of the crossover process. In recent times the need has come up to analyze more number of genes to answer more complex problems as gene discovery and disease tracing. In the first chapter we give a synopsis of the entire work. In the second chapter of the thesis we have included published work that formulates a detailed mathematical model of the recombination process. In the third chapter we detail on a novel recursive linking algorithm that overcomes a computational bottleneck often faced in gene mapping, the exponential time complexity of the algorithm in the number of markers. In the fourth chapter we integrate physical and genetic maps to produce a high resolution integrated physical and genetic map and study various genomic questions. For example, we construct empirical mapping functions that relate the amount of genetic recombination to physical distance. At the end we study the distribution of repeated DNA markers and outline the potential for progress in future endeavors.