اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدSolvable senescence model with positive mutations
61
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
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.
قيم البحث
اقرأ أيضاً
A precise estimate of allele and haplotype polymorphism is of great interest for theoretical population genetics, but also practical issues, such as bone marrow registries. Allele polymorphism is driven mainly by point mutations, while haplotype poly
morphism is also affected by recombination events. Even in the simple case of two loci in a haploid individual, there is currently no good estimate of the number of haplotypes as a function of the mutation and recombination rates. We here propose such an estimate and show that the common approximation that recombination can be treated as mutations is limited to recombination rates of the same order as the mutation rate. Beyond this regime, the total number of haplotypes is much lower than expected from the approximation above. Moreover, in contrast with mutations, the number of haplotypes does not grow linearly with the population size. We apply this new estimate to very large-scale human haplotype frequencies from human populations to show that the current estimated haplotype recombination rate in the HLA region is underestimated. This high recombination rate may be the source of HLA haplotype extreme polymorphism.
Data from a long time evolution experiment with Escherichia Coli and from a large study on copy number variations in subjects with european ancestry are analyzed in order to argue that mutations can be described as Levy flights in the mutation space.
These Levy flights have at least two components: random single-base substitutions and large DNA rearrangements. From the data, we get estimations for the time rates of both events and the size distribution function of large rearrangements.
Contrary to long-held views, recent evidence indicates that $textit{de novo}$ birth of genes is not only possible, but is surprisingly prevalent: a substantial fraction of eukaryotic genomes are composed of orphan genes, which show no homology with a
ny conserved genes. And a remarkably large proportion of orphan genes likely originated $textit{de novo}$ from non-genic regions. Here, using a parsimonious mathematical model, we investigate the probability and timescale of $textit{de novo}$ gene birth due to spontaneous mutations. We trace how an initially non-genic locus accumulates beneficial mutations to become a gene. We sample across a wide range of biologically feasible distributions of fitness effects (DFE) of mutations, and calculate the conditions conducive to gene birth. We find that in a time frame of millions of years, gene birth is highly likely for a wide range of DFEs. Moreover, when we allow DFEs to fluctuate, which is expected given the long time frame, gene birth in the model becomes practically inevitable. This supports the idea that gene birth is a ubiquitous process, and should occur in a wide variety of organisms. Our results also demonstrate that intergenic regions are not inactive and silent but are more like dynamic storehouses of potential genes.
A didactic introduction, dated by 1999, to the ideas of the papers arXiv:q-bio/0701050 and arXiv:0704.0034
This thesis is aimed at studying mutations, understood as trajectories in the DNA configuration space. An evolutive model of mutations in terms of Levy flights is proposed. The parameters of the model are estimated by means of data from the Long-Term
Evolution Experiment (LTEE) with {it E. Coli} bacteria. The results of simulations on competition of clones, mean fitness, etc are compared with experimental data. We discuss the qualitative analogy found between the bacterial mutator phenotype and the cancerous cells. The role of radiation as source of mutations is analyzed. We focus on the case of Radons decay in the lungs in breathing.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
