Airborne and belowground phytotoxicity of invasive Ageratina adenophora on native species in Nepal

Plant Ecology - Volatile compounds from leaf litter of invasive alien Ageratina adenophora are known to inhibit growth of native species in sub-tropical Asia, but there is not...     

XomAnnotate: Analysis of Heterogeneous and Complex Exome- A Step towards Translational Medicine

In translational cancer medicine, implicated pathways and the relevant master genes are of focus. Exome''s specificity, processing-time, and cost advantage makes it a compelling tool for this purpose. However, analysis of exome lacks reliable combinatory analysis tools and techniques. In this paper we present XomAnnotate – a meta- and functional-analysis software for exome. We compared UnifiedGenotyper, Freebayes, Delly, and Lumpy algorithms that were designed for whole-genome and combined their strengths in XomAnnotate for exome data through meta-analysis to identify comprehensive mutation profile (SNPs/SNVs, short inserts/deletes, and SVs) of patients. The mutation profile is annotated followed by functional analysis through pathway enrichment and network analysis to identify most critical genes and pathways implicated in the disease genesis. The efficacy of the software is verified through MDS and clustering and tested with available 11 familial non-BRCA1/BRCA2 breast cancer exome data. The results showed that the most significantly affected pathways across all samples are cell communication and antigen processing and presentation. ESCO1, HYAL1, RAF1 and PRKCA emerged as the key genes. Network analysis further showed the purine and propanotate metabolism pathways along with RAF1 and PRKCA genes to be master regulators in these patients. Therefore, XomAnnotate is able to use exome data to identify entire mutation landscape, pathways, and the master genes accurately with wide concordance from earlier microarray and whole-genome studies -- making it a suitable biomedical software for using exome in next-generation translational medicine.

Availability

http://www.iomics.in/research/XomAnnotate     

A study on the susceptibility of rice cultivars to Striga hermonthica and mapping of Striga tolerance quantitative trait loci in rice

Striga is a parasitic weed attacking mainly maize, sorghum, millet and cowpea. Studying the interaction between rice and Striga is valuable since rice is a model monocot. In this paper, the susceptibility of different rice cultivars to S. hermonthica was tested and quantitative trait loci (QTL) for Striga tolerance mapped on the Bala x Azucena F(6) population. Seven rice cultivars were grown with and without S. hermonthica for 14 wk. For the mapping experiment, 115 recombinant inbred lines (RILs), along with Azucena and Bala, were grown with and without Striga for 11 wk. Rice cultivars tested had different susceptibilities to Striga, ranging from highly susceptible to completely resistant. Azucena and Bala differed in the speed of Striga emergence and the impact on host growth. A genomic region between positions 139 and 166 cM on chromosome 1 was identified containing strong QTL (LOD = 4.9-15.7) for all traits measured. This indicates that genes for Striga tolerance exist in rice germplasm and the mapped QTL can be further studied to promote understanding of the nature of resistance/tolerance and breeding for Striga-resistant crop plants.     

Carbamylation promotes amyloidogenesis and induces structural changes in Tau-core hexapeptide fibrils

Background

Carbamylation is a non-enzymatic post-translational modification (PTM), which involves the covalent modification of N-terminus of protein or ε-amino group of Lys. The role of carbamylation in several age-related disorders is well documented, however, the relationship between carbamylation and neurodegenerative disorders including Alzheimer's disease remains uncharted.

Application of the LUminometric Methylation Assay to ecological species: tissue quality requirements and a survey of DNA methylation levels in animals

The LUminometric Methylation Assay (LUMA) measures global DNA methylation. LUMA depends on digestion of DNA with methyl‐sensitive and methyl‐insensitive restriction enzymes, followed by pyrosequencing. Until recently, LUMA has been principally used for biomedical research. Here, we use chickens as a model to investigate sample quality issues relating to LUMA and then apply the method to ecological species. First, we assessed the effect of tissue storage conditions on DNA methylation values. This is an important consideration for ecological species because samples are not always ideally preserved and LUMA is sensitive to poor DNA quality. We found that good quality LUMA data could be obtained from chicken liver and brain tissues stored at 21 °C for at least 2 and 12 h, respectively. Longer storage times introduced nonspecific peaks to pyrograms which were associated with reduced DNA methylation. Repeatedly, freezing and thawing the tissues did not affect LUMA data. Second, we measured DNA methylation in 12 species representing five animal classes: amphibians (African and Western clawed frog), reptiles (green anole lizard), fish (yellow perch, goldfish, lake trout), mammals (American mink, polar bear, short‐beaked common dolphin, Atlantic white‐sided dolphin) and birds (chicken, Japanese quail). We saw a pattern of high DNA methylation in fish (84–87%), and intermediate levels in mammals (68–72%) and birds (52–71%). This pattern corresponds well with previous measures of DNA methylation generated by HPLC. Our data represent the first CpG methylation values to be reported in several species and provide a basis for studying patterns of epigenetic inheritance in an ecological context.