Promoter DNA methylation couples genome-defence mechanisms to epigenetic reprogramming in the mouse germline

Mouse primordial germ cells (PGCs) erase global DNA methylation (5mC) as part of the comprehensive epigenetic reprogramming that occurs during PGC development. 5mC plays an important role in maintaining stable gene silencing and repression of transposable elements (TE) but it is not clear how the extensive loss of DNA methylation impacts on gene expression and TE repression in developing PGCs. Using a novel epigenetic disruption and recovery screen and genetic analyses, we identified a core set of germline-specific genes that are dependent exclusively on promoter DNA methylation for initiation and maintenance of developmental silencing. These gene promoters appear to possess a specialised chromatin environment that does not acquire any of the repressive H3K27me3, H3K9me2, H3K9me3 or H4K20me3 histone modifications when silenced by DNA methylation. Intriguingly, this methylation-dependent subset is highly enriched in genes with roles in suppressing TE activity in germ cells. We show that the mechanism for developmental regulation of the germline genome-defence genes involves DNMT3B-dependent de novo DNA methylation. These genes are then activated by lineage-specific promoter demethylation during distinct global epigenetic reprogramming events in migratory (～E8.5) and post-migratory (E10.5-11.5) PGCs. We propose that genes involved in genome defence are developmentally regulated primarily by promoter DNA methylation as a sensory mechanism that is coupled to the potential for TE activation during global 5mC erasure, thereby acting as a failsafe to ensure TE suppression and maintain genomic integrity in the germline.     

Assessment of genetic variation within Indian mustard (Brassica juncea) germplasm using random amplified polymorphic DNA markers

Genetic diversity among 45 Indian mustard (Brassica Juncea L.) genotypes comprising 37 germplasm collections, five advance breeding lines and three improved cultivars was investigated at the DNA level using the random amplified polymorphic DNA (RAPD) technique. Fifteen primers used generated a total of 92 RAPD fragments, of which 81 (88%) were polymorphic. Of these, 13 were unique to accession 'Pak85559'. Each primer produced four to nine amplified products with an average of 6.13 bands per primer. Based on pairwise comparisons of RAPD amplification products, Nei and Li's similarity coefficients were calculated to evaluate the relationships among the accessions. Pairwise similarity indices were higher among the oilseed accessions and cultivars showing narrow ranges of 0.77-0.99. An unweighted pair-group method with arithmetic averages cluster analysis based on these genetic similarities placed most of the collections and oilseed cultivars close to each other, showing a low level of polymorphism between the accessions used. However, the clusters formed by oilseed collections and cultivars were comparatively distinct from that of advanced breeding lines. Genetically, all of the accessions were classified into a few major groups and a number of individual accessions. Advanced breeding lines were relatively divergent from the rest of the accessions and formed independent clusters. Clustering of the accessions did not show any pattern of association between the RAPD markers and the collection sites. A low level of genetic variability of oilseed mustard was attributed to the selection for similar traits and horticultural uses. Perhaps close parentage of these accessions further contributed towards their little diversity. The study demonstrated that RAPD is a simple and fast technique to compare the genetic relationship and pattern of variation among the gene pool of this crop.     

The Effects of Periphyton, Fish and Fertilizer Dose on Biological Processes Affecting Water Quality in Earthen Fish Ponds

The potential of periphyton-based aquaculture in South Asia is under investigation in an extensive research program. This paper is a further analysis of data from four experiments carried out in that framework, to explore periphyton, fish and fertilizer dose effects on water quality. Factor analysis and ANOVA models applied to a data matrix of water quality parameters in ponds with and without artificial substrates (bamboo poles and kanchi sticks), with and without fish (filter feeders catla and rohu, with and without bottom feeder kalbaush), and with a standard or 50% increased fertilizer dose, allowed us to identify the underlying ecological processes governing this novel periphyton-based pond system, and construct conceptual graphic models of the periphyton–environment relationships observed. We clearly established that the phosphorus flow is mainly linked to phytoplankton activity in the water column and decomposition on the pond bottom, while nitrogen flow is mainly linked to autotrophic (photosynthesis) and heterotrophic (decomposition and nitrification) processes that take place in the periphyton in addition to the water column and pond bottom. Consequently, disruption of the pond bottom by bottom feeding fish primarily promoted phosphate cycling and phytoplankton, while periphyton development on the supplied substrates and fertilization mainly improved oxygen balance and nitrogen related processes developing in the water column. The use of bamboo poles led to better results than kanchi sticks, related to the greater autotrophic periphyton development on bamboo and to the larger surface of bamboo poles that facilitate fish grazing and periphyton dislodgment that in turn have a renewal effect on periphyton. Stocking bottom feeding fish produces a fertilizing effect through the food web that benefits the filter-feeding fish and that makes it unnecessary to increase the dose of inorganic and organic fertilizers applied to the ponds. Thus, the output of this analysis will help the fish farmers in resource constrained countries to improve their production in periphyton-based ponds just by choosing bamboo substrates, stocking a bottom feeder fish together with the filter feeders, and saving money on fertilizers.     

DLG1: Chromosome Location of the Closest Human Homologue of the Drosophila Discs Large Tumor Suppressor Gene

The Drosophila discs large tumor suppressor protein, Dlg, is the prototype of a newly discovered family of proteins termed MAGUKs (membrane-associated guanylate kinase homologues). MAGUKs are localized at the membrane-cytoskeleton interface, usually at cell-cell junctions, where they appear to have both structural and signaling roles. They contain several distinct domains, including a modified guanylate kinase domain, an SH3 motif, and one or three copies of the DHR (GLGF/PDZ) domain. Recessive lethal mutations in the discs large tumor suppressor gene interfere with the formation of septate junctions (thought to be the arthropod equivalent of tight junctions) between epithelial cells, and they cause neoplastic overgrowth of imaginal discs, suggesting a role for cell junctions in proliferation control. A homologue of the Dlg protein, named Hdlg, has been isolated from human B lymphocytes. It shows 65-79% identity to Dlg in the different domains, and it binds to the cytoskeletal protein 4.1. Here, we report that the gene for lymphocyte Hdlg, named DLG1, is located at chromosome band 3q29. This finding identifies a novel site for a candidate tumor suppressor on chromosome 3.     

Bayesian Inference of the Evolution of a Phenotype Distribution on a Phylogenetic Tree

The distribution of a phenotype on a phylogenetic tree is often a quantity of interest. Many phenotypes have imperfect heritability, so that a measurement of the phenotype for an individual can be thought of as a single realization from the phenotype distribution of that individual. If all individuals in a phylogeny had the same phenotype distribution, measured phenotypes would be randomly distributed on the tree leaves. This is, however, often not the case, implying that the phenotype distribution evolves over time. Here we propose a new model based on this principle of evolving phenotype distribution on the branches of a phylogeny, which is different from ancestral state reconstruction where the phenotype itself is assumed to evolve. We develop an efficient Bayesian inference method to estimate the parameters of our model and to test the evidence for changes in the phenotype distribution. We use multiple simulated data sets to show that our algorithm has good sensitivity and specificity properties. Since our method identifies branches on the tree on which the phenotype distribution has changed, it is able to break down a tree into components for which this distribution is unique and constant. We present two applications of our method, one investigating the association between HIV genetic variation and human leukocyte antigen and the other studying host range distribution in a lineage of Salmonella enterica, and we discuss many other potential applications.