Potato (Solanum tuberosum L.) cultivars physiological, biochemical performance and yield parameters response to acid mine water irrigation and soil physiochemical properties.

This paper aimed to analyse the potato cultivar's response to physiological, biochemical performance, yield parameters and soil physiochemical properties when subjected to quicklime (un)treated acid mine drainage (AMD) irrigation. A randomized design experiment was conducted with five water treatment levels: TW1; TW2; TW3; TW4 to TW5 replicated four times. The results showed that the quicklime treatment increased the pH of the AMD water, reduced the concentration of EC, NO3-, SO42- and ameliorated heavy metals. However, unsafe levels of heavy metals above the maximum permissible (WHO/FAO) levels were found in Pb, Mg and Mo for water (TW4 and TW5), while As, Cd and Cr for soils (ST4 and ST5) respectively. For potato tubers (TT4 and TT5) concentrations of As, Cd, Cr, and Pb were above the maximum levels. Stomatal conductance, chlorophyll content and yield parameters responded positively by increasing significantly on TW4 and TW5 treatments, but negatively (reduced) towards TW2 and TW3 treatments. A higher bioaccumulation factor was obtained for Zn ˃ Cu ˃ Mg ˃ Pb ˃ Mn, which was an indication of the contamination status of soil, with Zn being more concentrated than other metals. The findings indicate that quicklime-treated AMD is usable for potato irrigation with regular monitoring of heavy metal levels and strict observation of water reuse protocols. The use of this large source of ameliorated (AMD) water will go a long way in improving food security in South Africa and/or in countries where agriculture production is around mining areas.

1H-NMR and LC-MS Based Metabolomics Analysis of Potato (Solanum tuberosum L.) Cultivars Irrigated with Fly Ash Treated Acid Mine Drainage.

1H NMR and LC-MS, commonly used metabolomics analytical platforms, were used to annotate the metabolites found in potato (Solanum tuberosum L.) irrigated with four different treatments based on FA to AMD ratios, namely: control (0% AMD; tap water), 1:1 (50% AMD), 3:1 (75% AMD is 75% FA: AMD), and 100% AMD (untreated). The effects of stress on plants were illustrated by the primary metabolite shifts in the region from δH 0.0 to δH 4.0 and secondary metabolites peaks were prominent in the region ranging from δH 4.5 to δH 8.0. The 1:3 irrigation treatment enabled, in two potato cultivars, the production of significantly high concentrations of secondary metabolites due to the 75% FA: AMD content in the irrigation mixture, which induced stress. The findings suggested that 1:1 irrigation treatment induced production of lower amounts of secondary metabolites in all crops compared to crops irrigated with untreated acid mine drainage treatment and with other FA-treated AMD solutions.

Correction: Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species.

[This corrects the article DOI: 10.1371/journal.pone.0192678.].

Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species.

BACKGROUND: Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. METHODS: In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. RESULTS: Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs associated with different traits that are responsive to multiple stresses. Ontology mapping was used to validate the identified genes, while reconstruction of the phylogenetic tree was instrumental to infer the evolutionary relationship of the sorghum orthologs. The results also show specific genes responsible for various interrelated components of drought response mechanism such as drought tolerance, drought avoidance and drought escape. CONCLUSIONS: We submit that this approach is novel and to our knowledge, has not been used previously in any other research; it enables us to perform cross-species queries for genes that are likely to be associated with multiple stress tolerance, as a means to identify novel targets for engineering stress resistance in sorghum and possibly, in other crop species.

De novo transcriptome sequencing in Monsonia burkeana revealed putative genes for key metabolic pathways involved in tea quality and medicinal value.

Monsonia (Monsonia burkeana Planch. ex Harv) is one of the most valuable tea and traditional medicinal plants used in Southern Africa. In spite of this, there is no sequence information regarding this plant in literature. To provide understanding of the naturally occurring tea and drug-specific products and the key pathways for the biosynthesis of these molecules, we sequenced the leaf transcriptome using Illumina MiSeq platform and generated 2,590,652 paired-end reads that were assembled de novo into 45,450 high-quality transcripts. Annotation of these transcripts revealed best hits for homology to discover more than 17,800 functional genes and conserved domains. A total of 93 KEGG pathways and associated genes encoded by more than 90% of the coding transcripts are responsible for the biosynthesis of these life-saving metabolites. We validated and enriched the genes by GO annotation and linked this to enzyme-powered pathways through interactive network map. Caffeine metabolism, flavonoid, phenylpropanoid and terpenoids biosynthesis and xenobiotics degradation were typical in tea quality and drug therapy. The relatedness of more than 80 gene families encoding key enzymes was shown using unrooted phylogenetic tree. In conclusion, the M. burkeana leaf transcriptome gives insight into tea and drug-specific products, therefore representing basis in further investigation of the plant.