Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userInfluence of a small fraction of individuals with enhanced mutations on a population genetic pool
156
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Computer simulations of the Penna ageing model suggest that already a small fraction of births with enhanced number of new mutations can negatively influence the whole population.
rate research
Read More
We will give a simple, unified, possible explanation of several debated genetic issues on todays humans, Neandertals and Denisovans. In particular it is shown by means of a simple mathematical model why there is little genetic variation in todayss human population or in Western Neandertal population, why all mtDNA and y-chromosomes in todays humans seem to have African origin with no trace of Neandertal nor Denosovan mtDNA or y-chromosomes, why a big part of the European gene pool is young (from Neolitic time), and why todays East Asians have mode Neandertal genes than todays Europeans.
In order to analyze data from cancer genome sequencing projects, we need to be able to distinguish causative, or driver, mutations from passenger mutations that have no selective effect. Toward this end, we prove results concerning the frequency of neutural mutations in exponentially growing multitype branching processes that have been widely used in cancer modeling. Our results yield a simple new population genetics result for the site frequency spectrum of a sample from an exponentially growing population.
There is an urgent and well-recognized need to extend genetic studies to diverse populations, but several obstacles continue to be prohibitive, including (but not limited to) the difficulty of recruiting individuals from diverse populations in large numbers and the lack of representation in available genomic references. These obstacles notwithstanding, studying multiple diverse populations would provide informative, population-specific insights. Using Native Hawaiians as an example of an understudied population with a unique evolutionary history, I will argue that by developing key genomic resources and integrating evolutionary thinking into genetic epidemiology, we will have the opportunity to efficiently advance our knowledge of the genetic risk factors, ameliorate health disparity, and improve healthcare in this underserved population.
We build upon our previous analytical results for the Penna model of senescence to include positive mutations. We investigate whether a small but non-zero positive mutation rate gives qualitatively different results to the traditional Penna model in which no positive mutations are considered. We find that the high-lifespan tail of the distribution is radically changed in structure, but that there is not much effect on the bulk of the population. Th e mortality plateau that we found previously for a stochastic generalization of the Penna model is stable to a small positive mutation rate.
Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through time and the distribution of the sampling times depends on the effective population size, explicit statistical modeling of sampling times improves population size estimation. Previous work assumed that the genealogy relating sampled sequences is known and modeled sampling times as an inhomogeneous Poisson process with log-intensity equal to a linear function of the log-transformed effective population size. We improve this approach in two ways. First, we extend the method to allow for joint Bayesian estimation of the genealogy, effective population size trajectory, and other model parameters. Next, we improve the sampling time model by incorporating additional sources of information in the form of time-varying covariates. We validate our new modeling framework using a simulation study and apply our new methodology to analyses of population dynamics of seasonal influenza and to the recent Ebola virus outbreak in West Africa.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
