Maize Lethal Necrosis disease: review of molecular and genetic resistance mechanisms, socio-economic impacts, and mitigation strategies in sub-Saharan Africa.

BACKGROUND: Maize lethal necrosis (MLN) disease is a significant constraint for maize producers in sub-Saharan Africa (SSA). The disease decimates the maize crop, in some cases, causing total crop failure with far-reaching impacts on regional food security. RESULTS: In this review, we analyze the impacts of MLN in Africa, finding that resource-poor farmers and consumers are the most vulnerable populations. We examine the molecular mechanism of MLN virus transmission, role of vectors and host plant resistance identifying a range of potential opportunities for genetic and phytosanitary interventions to control MLN. We discuss the likely exacerbating effects of climate change on the MLN menace and describe a sobering example of negative genetic association between tolerance to heat/drought and susceptibility to viral infection. We also review role of microRNAs in host plant response to MLN causing viruses as well as heat/drought stress that can be carefully engineered to develop resistant varieties using novel molecular techniques. CONCLUSIONS: With the dual drivers of increased crop loss due to MLN and increased demand of maize for food, the development and deployment of simple and safe technologies, like resistant cultivars developed through accelerated breeding or emerging gene editing technologies, will have substantial positive impact on livelihoods in the region. We have summarized the available genetic resources and identified a few large-effect QTLs that can be further exploited to accelerate conversion of existing farmer-preferred varieties into resistant cultivars.

Genome-wide association study in Asia-adapted tropical maize reveals novel and explored genomic regions for sorghum downy mildew resistance.

Globally, downy mildews are among the important foliar diseases of maize that cause significant yield losses. We conducted a genome-wide association study for sorghum downy mildew (SDM; Peronosclerospora sorghi) resistance in a panel of 368 inbred lines adapted to the Asian tropics. High density SNPs from Genotyping-by-sequencing were used in GWAS after controlling for population structure and kinship in the panel using a single locus mixed model. The study identified a set of 26 SNPs that were significantly associated with SDM resistance, with Bonferroni corrected P values ≤ 0.05. Among all the identified SNPs, the minor alleles were found to be favorable to SDM resistance in the mapping panel. Trend regression analysis with 16 independent genetic variants including 12 SNPs and four haplotype blocks identified SNP S2_6154311 on chromosome 2 with P value 2.61E-24 and contributing 26.7% of the phenotypic variation. Six of the SNPs/haplotypes were within the same chromosomal bins as the QTLs for SDM resistance mapped in previous studies. Apart from this, eight novel genomic regions for SDM resistance were identified in this study; they need further validation before being applied in the breeding pipeline. Ten SNPs identified in this study were co-located in reported mildew resistance genes.

Genotypic and phenotypic diversity of Anabaena isolates from diverse rice agro-ecologies of India.

The genus Anabaena is one of the commonly observed genera in the rice fields in South-east Asia. Diversity analyses of a set of 70 Anabaena strains (including 67 strains isolated from diverse rice agro ecologies of India, and three International Reference/Type strains), was carried out using morphological and molecular datasets. The pattern of growth in liquid and solid medium and microscopic observations revealed tremendous diversity in the Anabaena germplasm analysed. The species wise distribution in different soil types and soil pH revealed that Anabaena iyengarii was present at pH ranging from 5.5-8.5 and all the species of Anabaena except A. oscillarioides were present in alluvium soils. Molecular profiling using primers based on HipTG, STRR(mod) and STRR1A sequences generated specific fingerprints for individual isolates. STRR1A was observed to be the most informative and useful for differentiating the isolates. Analyses of a combined dataset, including both morphological and molecular data, proved highly effective in discerning the genetic relationships among the 70 Anabaena strains. The present study provided useful information for the development of a comprehensive database based on the distribution of Anabaena strains in diverse agro ecologies of India and identified useful primers for PCR based differentiation of isolates.