Development, characterization and use of genomic SSR markers for assessment of genetic diversity in some Saudi date palm ( Phoenix dactylifera L.) cultivars

Background: The present study was undertaken towards the development of SSR markers and assessing genetic relationships among 32 date palm ( Phoenix dactylifera L.) representing common cultivars grown in different geographical regions in Saudi Arabia. Results: Ninety-three novel simple sequence repeat markers were developed and screened for their ability to detect polymorphism in date palm. Around 71% of genomic SSRs were dinucleotide, 25% tri, 3% tetra and 1% penta nucleotide motives. Twenty-two primers generated a total of 91 alleles with a mean of 4.14 alleles per locus and 100% polymorphism percentage. A 0.595 average polymorphic information content and 0.662 primer discrimination power values were recorded. The expected and observed heterozygosities were 0.676 and 0.763 respectively. Pair-wise similarity values ranged from 0.06 to 0.89 and the overall cultivars averaged 0.41. The UPGMA cluster analysis recovered by principal coordinate analysis illustrated that cultivars tend to group according to their class of maturity, region of cultivation, and fruit color. Analysis of molecular variations (AMOVA) revealed that genetic variation among and within cultivars were 27% and 73%, respectively according to geographical distribution of cultivars. Conclusions: The developed microsatellite markers are additional values to date palm characterization tools that can be used by researchers in population genetics, cultivar identification as well as genetic resource exploration and management. The tested cultivars exhibited a significant amount of genetic diversity and could be suitable for successful breeding program. Genomic sequences generated from this study are available at the National Center for Biotechnology Information (NCBI), Sequence Read Archive (Accession numbers. LIBGSS_039019).

Genetic diversity of Cryptosporidium identified in clinical samples from cities in Brazil and Argentina

The identification and characterisation of Cryptosporidium genotypes and subtypes are fundamental to the study of cryptosporidiosis epidemiology, aiding in prevention and control strategies. The objective was to determine the genetic diversity of Cryptosporidium in samples obtained from hospitals of Rio de Janeiro, Brazil, and Buenos Aires, Argentina. Samples were analysed by microscopy and TaqMan polymerase chain reaction (PCR) assays for Cryptosporidium detection, genotyped by nested-PCR-restriction fragment length polymorphism (RFLP) analysis of the 18S rRNA gene and subtyped by DNA sequencing of the gp60 gene. Among the 89 samples from Rio de Janeiro, Cryptosporidium spp were detected in 26 by microscopy/TaqMan PCR. In samples from Buenos Aires, Cryptosporidium was diagnosed in 15 patients of the 132 studied. The TaqMan PCR and the nested-PCR-RFLP detected Cryptosporidium parvum , Cryptosporidium hominis , and co-infections of both species. In Brazilian samples, the subtypes IbA10G2 and IIcA5G3 were observed. The subtypes found in Argentinean samples were IbA10G2, IaA10G1R4, IaA11G1R4, and IeA11G3T3, and mixed subtypes of Ia and IIa families were detected in the co-infections. C. hominis was the species more frequently detected, and subtype family Ib was reported in both countries. Subtype diversity was higher in Buenos Aires than in Rio de Janeiro and two new subtypes were described for the first time.

Pathway analysis for identification of potential biomarkers in severe cutaneous drug hypersensitivity reactions

Purpose: To construct a cluster model or a gene signature for Stevens-Johnson syndrome (SJS) using pathways analysis in order to identify some potential biomarkers that may be used for early detection of SJS and epidermal necrolysis (TEN) manifestations. Methods: Gene expression profiles of GSE12829 were downloaded from Gene Expression Omnibus database. A total of 193 differentially expressed genes (DEGs) were obtained. We applied these genes to geneMANIA database, to remove ambiguous and duplicated genes, and after that, characterized the gene expression profiles using geneMANIA, DAVID, REACTOME, STRING and GENECODIS which are online software and databases. Results: Out of 193 genes, only 91 were used (after removing the ambiguous and duplicated genes) for topological analysis. It was found by geneMANIA database search that majority of these genes were coexpressed yielding 84.63 % co-expression. It was found that ten genes were in Physical interactions comprising almost 14.33 %. There were < 1 % pathway and genetic interactions with values of 0.97 and 0.06 %, respectively. Final analyses revealed that there are two clusters of gene interactions and 13 genes were shown to be in evident relationship of interaction with regards to hypersensitivity. Conclusion: Analysis of differential gene expressions by topological and database approaches in the current study reveals 2 gene network clusters. These genes are CD3G, CD3E, CD3D, TK1, TOP2A, CDK1, CDKN3, CCNB1, and CCNF. There are 9 key protein interactions in hypersensitivity reactions and may serve as biomarkers for SJS and TEN. Pathways related gene clusters has been identified and a genetic model to predict SJS and TEN early incidence using these biomarker genes has been developed.