Cell lineage analysis of the mammalian female germline

Fundamental aspects of embryonic and post-natal development, including maintenance of the mammalian female germline, are largely unknown. Here we employ a retrospective, phylogenetic-based method for reconstructing cell lineage trees utilizing somatic mutations accumulated in microsatellites, to study female germline dynamics in mice. Reconstructed cell lineage trees can be used to estimate lineage relationships between different cell types, as well as cell depth (number of cell divisions since the zygote). We show that, in the reconstructed mouse cell lineage trees, oocytes form clusters that are separate from hematopoietic and mesenchymal stem cells, both in young and old mice, indicating that these populations belong to distinct lineages. Furthermore, while cumulus cells sampled from different ovarian follicles are distinctly clustered on the reconstructed trees, oocytes from the left and right ovaries are not, suggesting a mixing of their progenitor pools. We also observed an increase in oocyte depth with mouse age, which can be explained either by depth-guided selection of oocytes for ovulation or by post-natal renewal. Overall, our study sheds light on substantial novel aspects of female germline preservation and development.     

Living in the city: can anyone become an ‘urban exploiter'?

Aim As urban landscapes expand, shifts in biodiversity are occurring. This is leading biogeographers and ecologists to consider human‐dominated landscapes in their current work. One question that arises is: what characterizes those species that are widespread in the most highly urban environments compared with those restricted to less urbanized areas in the city? Here, we aim to identify the traits that enable species to become urban exploiters, i.e. to dominate highly urbanized surroundings. Identifying these traits may help us better predict and possibly mitigate the biotic homogenization occurring in these areas. Location Israel in general, with special focus on the city of Jerusalem. Methods Combining literature and field‐based data for birds in Israel we compared phenotypic, behavioural and life‐history traits between urban exploiters and urban adapters. The latter occur in urban landscapes, but are characteristic of the less urbanized parts of the city. We then examined the trends along a finer field‐sampled gradient of increasing urbanization from sub‐natural to downtown areas within the city of Jerusalem. Results Urban exploiters and adapters differed primarily in social structure and migratory status: exploiters were significantly more social and sedentary than urban adapters. Clear trends were also seen for dietary preferences along a gradient of increasing urbanization in Jerusalem, such that, with increasing urbanization, the proportion of granivorous species increased whereas the proportion of species feeding on invertebrates declined. In contrast, neither relative brain size nor behavioural flexibility, as measured by feeding innovations, differed significantly among urban exploiters and adapters in Israel or along the urbanization gradient in Jerusalem specifically. Main conclusions The results of our study suggest that being successful in more vs. less urbanized environments in the city is not necessarily a factor of brain size nor of how flexible and behaviourally innovative the species is; rather, it depends on a combination of traits, including diet, degree of sociality, sedentariness and preferred nesting sites.     

Probabilistic discovery of overlapping cellular processes and their regulation.

In this paper, we explore modeling overlapping biological processes. We discuss a probabilistic model of overlapping biological processes, gene membership in those processes, and an addition to that model that identifies regulatory mechanisms controlling process activation. A key feature of our approach is that we allow genes to participate in multiple processes, thus providing a more biologically plausible model for the process of gene regulation. We present algorithms to learn each model automatically from data, using only genomewide measurements of gene expression as input. We compare our results to those obtained by other approaches and show that significant benefits can be gained by modeling both the organization of genes into overlapping cellular processes and the regulatory programs of these processes. Moreover, our method successfully grouped genes known to function together, recovered many regulatory relationships that are known in the literature, and suggested novel hypotheses regarding the regulatory role of previously uncharacterized proteins.     

HAPLOFREQ--estimating haplotype frequencies efficiently.

A commonly used tool in disease association studies is the search for discrepancies between the haplotype distribution in the case and control populations. In order to find this discrepancy, the haplotypes frequency in each of the populations is estimated from the genotypes. We present a new method HAPLOFREQ to estimate haplotype frequencies over a short genomic region given the genotypes or haplotypes with missing data or sequencing errors. Our approach incorporates a maximum likelihood model based on a simple random generative model which assumes that the genotypes are independently sampled from the population. We first show that if the phased haplotypes are given, possibly with missing data, we can estimate the frequency of the haplotypes in the population by finding the global optimum of the likelihood function in polynomial time. If the haplotypes are not phased, finding the maximum value of the likelihood function is NP-hard. In this case, we define an alternative likelihood function which can be thought of as a relaxed likelihood function. We show that the maximum relaxed likelihood can be found in polynomial time and that the optimal solution of the relaxed likelihood approaches asymptotically to the haplotype frequencies in the population. In contrast to previous approaches, our algorithms are guaranteed to converge in polynomial time to a global maximum of the different likelihood functions. We compared the performance of our algorithm to the widely used program PHASE, and we found that our estimates are at least 10% more accurate than PHASE and about ten times faster than PHASE. Our techniques involve new algorithms in convex optimization. These algorithms may be of independent interest. Particularly, they may be helpful in other maximum likelihood problems arising from survey sampling.     

Axoplasmic importins enable retrograde injury signaling in lesioned nerve

Axoplasmic proteins containing nuclear localization signals (NLS) signal retrogradely by an unknown mechanism in injured nerve. Here we demonstrate that the importin/karyopherin alpha and beta families underlie this process. We show that importins are found in axons at significant distances from the cell body and that importin beta protein is increased after nerve lesion by local translation of axonal mRNA. This leads to formation of a high-affinity NLS binding complex that traffics retrogradely with the motor protein dynein. Trituration of synthetic NLS peptide at the injury site of axotomized dorsal root ganglion (DRG) neurons delays their regenerative outgrowth, and NLS introduction to sciatic nerve concomitantly with a crush injury suppresses the conditioning lesion induced transition from arborizing to elongating growth in L4/L5 DRG neurons. These data suggest a model whereby lesion-induced upregulation of axonal importin beta may enable retrograde transport of signals that modulate the regeneration of injured neurons.