441 research outputs found
Agromorphological Characterization of Hibiscus sabdariffa L. Collection from Burkina Faso
Hibiscus sabdariffa L. or roselle is an important vegetable crop in several African countries. It is rich in vitamins and minerals and is widely used in the diet of local populations in Africa, especially in Burkina Faso. However, up to now, there is no in-depth study describing roselle genetic diversity that has been carried out to assess ecotypes cultivated in Burkina Faso. Thus, this study aims to contribute to providing more insights into Hibiscus sabdariffa genetic variability in Burkina Faso through an agromorphological characterization. For this purpose, a trial was carried out using a Randomized Complete Block Design (RCBD) with three replications. 48 accessions collected from farmers were assessed. Agromorphological data collection involved 12 qualitative and 18 quantitative traits. The qualitative traits analysis showed high variability in leaf, stem, and flower color and shape. Analysis of variance (ANOVA), hierarchical cluster analysis (HCA), and principal component analysis (PCA) were performed using quantitative data. The results indicated significant differences among all genotypes for all the traits measured. The first three axes of the PCA explain 69.62% of the genetic variability. Furthermore, the results showed a high agromophological variability which is structured in three (03) groups. This variability will contribute to the enhancement and genetic improvement of Hibiscus sabdariffa
PCSF: An R-package for network-based interpretation of high-throughput data
With the recent technological developments a vast amount of high-throughput data has been profiled to understand the mechanism of complex diseases. The current bioinformatics challenge is to interpret the data and underlying biology, where efficient algorithms for analyzing heterogeneous high-throughput data using biological networks are becoming increasingly valuable. In this paper, we propose a software package based on the Prize-collecting Steiner Forest graph optimization approach. The PCSF package performs fast and user-friendly network analysis of high-throughput data by mapping the data onto a biological networks such as protein-protein interaction, gene-gene interaction or any other correlation or coexpression based networks. Using the interaction networks as a template, it determines high-confidence subnetworks relevant to the data, which potentially leads to predictions of functional units. It also interactively visualizes the resulting subnetwork with functional enrichment analysis
Genetic Diversity of Jatropha curcas in Burkina Faso Revealed by Microsatellite Markers
Jatropha curcas L. is a perennial oleaginous plant commonly used in tropical areas as a medicinal plant in the construction of defensive hedges against animals, and in the fight against water erosion. It produces oil which can be used as agrofuel or soap-making. Despite its potential, the species remain under-exploited and its genetic diversity is still not very well-known in Burkina Faso. This paper focuses on determining the level and structure of the genetic diversity of 50 accessions collected in three phytogeographical sectors of the country using 12 microsatellite markers. Resultsrevealed a total of 37 alleles in the studied population with an average of 3 alleles per locus, a number of 2.717 effective alleles, and a Shannon diversity index of 1.663. Mean observed heterozygosity and mean expected heterozygosity were 0.144 and 0.356, respectively. Accessions were structured into three genetic groups. The high genetic distance of 0.177 was observed between groups A and B, and a low genetic distance of 0.075 was observed between groups B and C. These preliminary results showed that microsatellites are promising tools that can be used for the characterization of J. curcas. They indicate that the population studied has a low genetic diversity, but it is sufficient to develop programs for conservation and sustainable development of the species
Cell freezing protocol suitable for ATAC-Seq on motor neurons derived from human induced pluripotent stem cells
In recent years, the assay for transposase-accessible chromatin using sequencing (ATAC-Seq) has become a fundamental tool of epigenomic research. However, it is difficult to perform this technique on frozen samples because freezing cells before extracting nuclei can impair nuclear integrity and alter chromatin structure, especially in fragile cells such as neurons. Our aim was to develop a protocol for freezing neuronal cells that is compatible with ATAC-Seq; we focused on a disease-relevant cell type, namely motor neurons differentiated from induced pluripotent stem cells (iMNs) from a patient affected by spinal muscular atrophy. We found that while flash-frozen iMNs are not suitable for ATAC-Seq, the assay is successful with slow-cooled cryopreserved cells. Using this method, we were able to isolate high quality, intact nuclei, and we verified that epigenetic results from fresh and cryopreserved iMNs quantitatively agree.National Institutes of Health (U.S.) (Grants U54-NS-091046 and U01-CA-184898
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