Assessing genetic structure in common but ecologically distinct carnivores: the stone marten and red fox

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation

Child labour: the case study in Bangladesh

Child labour involves of person that age below than 17 years old. Child labour often happen in poor countries such as Bangladesh. In Bangladesh, the issue of child labour might be the biggest issue. Bangladesh come up with Bangladesh Labour Act (BLA) that did not allow any person age below from fourteen years old to work (Nawshin et al, 2019). One of the aim or purpose of this act is to prevent teen workers in order to get the proper payment of any work. This is because when organization use child labour, they might be paid at lower rate because children usually do not have much responsible in their family compared to teen workers. This indirectly cause an economic matter in a family

Offline and Online Density Estimation for Large High-Dimensional Data

Density estimation has wide applications in machine learning and data analysis techniques including clustering, classification, multimodality analysis, bump hunting and anomaly detection. In high-dimensional space, sparsity of data in local neighborhood makes many of parametric and nonparametric density estimation methods mostly inefficient. This work presents development of computationally efficient algorithms for high-dimensional density estimation, based on Bayesian sequential partitioning (BSP). Copula transform is used to separate the estimation of marginal and joint densities, with the purpose of reducing the computational complexity and estimation error. Using this separation, a parallel implementation of the density estimation algorithm on a 4-core CPU is presented. Also, some example applications of the high-dimensional density estimation in density-based classification and clustering are presented. Another challenge in the area of density estimation rises in dealing with online sources of data, where data is arriving over an open-ended and non-stationary stream. This calls for efficient algorithms for online density estimation. An online density estimator needs to be capable of providing up-to-date estimates of the density, bound to the available computing resources and requirements of the application. In response to this, BBSP method for online density estimation is introduced. It works based on collecting and processing the data in blocks of fixed size, followed by a weighted averaging over block-wise estimates of the density. Proper choice of block size is discussed via simulations for streams of synthetic and real datasets. Further, with the purpose of efficiency improvement in offline and online density estimation, progressive update of the binary partitions in BBSP is proposed, which as simulation results show, leads into improved accuracy as well as speed-up, for various block sizes

Challenging the spliceosome machine

BACKGROUND: Using cDNA copies of transcripts and corresponding genomic sequences from the Berkeley Drosophila Genome Project, a set of 24,753 donor and acceptor splice sites were computed with a scanning algorithm that tested for single nucleotide insertion, deletion and substitution polymorphisms. Using this dataset, we developed a progressive partitioning approach to examining the effects of challenging the spliceosome system. RESULTS: Our analysis shows that information content increases near splice sites flanking progressively longer introns and exons, suggesting that longer splice elements require stronger binding of spliceosome components. Information also increases at splice sites near very short introns and exons, suggesting that short splice elements have crowding problems. We observe that the information found at individual splice sites depends upon a balance of splice element lengths in the vicinity, including both flanking and non-adjacent introns and exons. CONCLUSION: These results suggest an interdependence of multiple splicing events along the pre-mRNA, which may have implications for how the macromolecular spliceosome machine processes sets of neighboring splice sites

Polygamy slows down population divergence in shorebirds.

Sexual selection may act as a promotor of speciation since divergent mate choice and competition for mates can rapidly lead to reproductive isolation. Alternatively, sexual selection may also retard speciation since polygamous individuals can access additional mates by increased breeding dispersal. High breeding dispersal should hence increase gene flow and reduce diversification in polygamous species. Here we test how polygamy predicts diversification in shorebirds using genetic differentiation and subspecies richness as proxies for population divergence. Examining microsatellite data from 79 populations in ten plover species (Genus: Charadrius) we found that polygamous species display significantly less genetic structure and weaker isolation-by-distance effects than monogamous species. Consistent with this result, a comparative analysis including 136 shorebird species showed significantly fewer subspecies for polygamous than for monogamous species. By contrast, migratory behaviour neither predicted genetic differentiation nor subspecies richness. Taken together, our results suggest that dispersal associated with polygamy may facilitate gene flow and limit population divergence. Therefore, intense sexual selection, as occurs in polygamous species, may act as a brake rather than an engine of speciation in shorebirds. We discuss alternative explanations for these results and call for further studies to understand the relationships between sexual selection, dispersal and diversification. This article is protected by copyright. All rights reserved