ABSTRACT
Bivalve molluscs of the genus Mytilus are considered a model organism in ecotoxicology and are known to be well adapted to marine ecosystems affected by multiple anthropogenic factors, including pollution. In order to assess whether pollution interferes with the reproductive success of Mytilus and affects the diversity within and between populations, we sequenced the transcriptomes of 72 individuals from 9 populations of Mytilus galloprovincialis collected along a ca. 130-km north-south transect on the Western coast of the Iberian Peninsula. We found that polluted areas are acting as a barrier to gene flow, potentially because of the detrimental effect of anthropogenic chemicals on larvae carried from more pristine environments. Furthermore, we observed an increase in genetic diversity in populations from polluted site, which could be indicative of higher mutagenicity driven by the environment. We propose that a microevolutionary perspective is essential for a full characterization of human activities on the dispersal of M. galloprovincialis and that it should be incorporated into management, and conservation plans and policies in the context of the effects of pollution on populations.
Subject(s)
Genetic Variation/drug effects , Mytilus/genetics , Transcriptome/drug effects , Water Pollution, Chemical/adverse effects , Animals , Metagenomics , Portugal , SpainABSTRACT
Bradyrhizobium sp. LMTR 3 is a representative strain of one of the geno(species) of diazotrophic symbionts associated with Lima bean (Phaseolus lunatus) in Peru. Its 7.83 Mb genome was sequenced using the Illumina technology and found to encode a complete set of genes required for nodulation and nitrogen fixation, and additional genes putatively involved in root colonization. Its draft genome sequence and annotation have been deposited at GenBank under the accession number MAXC00000000.
ABSTRACT
Bradyrhizobium paxllaeri is a prevalent species in root nodules of the Lima bean (Phaseolus lunatus) in Peru. LMTR 21T is the type strain of the species and was isolated from a root nodule collected in an agricultural field in the Peruvian central coast. Its 8.29 Mbp genome encoded 7635 CDS, 71 tRNAs and 3 rRNAs genes. All genes required to stablish a nitrogen-fixing symbiosis with its host were present. The draft genome sequence and annotation have been deposited at GenBank under the accession number MAXB00000000.
ABSTRACT
With the advance of modern molecular biology it has become increasingly clear that few cellular processes are unaffected by protein phosphorylation. Therefore, computational identification of phosphorylation sites is very helpful to accelerate the functional understanding of huge available protein sequences obtained from genomic and proteomic studies. Using a genetic algorithm integrated neural network (GANN), a new bioinformatics method named GANNPhos has been developed to predict phosphorylation sites in proteins. Aided by a genetic algorithm to optimize the weight values within the network, GANNPhos has demonstrated a high accuracy of 81.1, 76.7 and 73.3% in predicting phosphorylated S, T and Y sites, respectively. When benchmarked against Back-Propagation neural network and Support Vector Machine algorithms, GANNPhos gives better performance, suggesting the GANN program can be used for other prediction tasks in the field of protein bioinformatics.