Maize Lethal Necrosis (MLN) – Prevention and management

The Maize Lethal Necrosis (MLN) disease of maize emerged in eastern Africa in 2011-2012, affecting the food security and livelihoods of several million smallholder farmers. Intensive efforts by CGIAR, together with national and international partners, helped in implementing a modern surveillance and monitoring system, spread improved agricultural practices for the disease control, deploy MLN-tolerant/resistant varieties, and curb the spread of the disease through safe germplasm exchange and distribution. An MLN Phytosanitary Community of Practice was established among national plant protection organizations and commercial seed sector. MLN is still prevalent however in eastern Africa. Continued efforts are needed through the CGIAR Plant Health Initiative to implement MLN monitoring and management strategies to contain the disease in eastern Africa, and prevent its spread to other regions in sub-Saharan Africa

Comparison of non-overlapping maize populations of unequal sizes for resistance to maize lethal necrosis

Contrast between marker-assisted backcross (MABC) and doubled haploid (DH) methods in transferring genes for resistance to maize lethal necrosis (MLN) in maize (Zea mays L.) is not well understood. The MLN is caused by co-infection of maize plant by maize chlorotic mottle virus and sugarcane mosaic virus. Two maize panels consisting of four BC3F2 and six DH populations, separately developed through marker-assisted selection from crosses between susceptible CIMMYT lines and MLN-resistant donor parent (KS23-6), were used in the current study. The two populations were of different population structures with unequal sizes. Experiments were conducted under artificial MLN inoculations for two seasons in 2018. Analyses of variance revealed significant variations among genotypes in both panels (p ≤ 0.001). Levene’s and Welch’s tests found that variances and means of the BC3F2 and DH populations were highly unequal (p ≤ 0.001). The study identified genotypes with reduced MLN infections in both populations; however, lower means for MLN severity and area under disease progress curve (AUDPC) values, and higher heritability estimates were obtained in the DH populations than in the BC3F2 populations. Additionally, the DH populations showed higher relative genetic gains for resistance to MLN compared with the BC3F2 populations. The current study detected superiority of DH over MABC populations for breeding for resistance to MLN. Nevertheless, the results observed in the present study warrant further investigations using the same genetic materials with identical population sizes

Identification of genomic regions associated with agronomic and disease resistance traits in a large set of multiple DH populations

Breeding maize lines with the improved level of desired agronomic traits under optimum and drought conditions as well as increased levels of resistance to several diseases such as maize lethal necrosis (MLN) is one of the most sustainable approaches for the sub-Saharan African region. In this study, 879 doubled haploid (DH) lines derived from 26 biparental populations were evaluated under artificial inoculation of MLN, as well as under well-watered (WW) and water-stressed (WS) conditions for grain yield and other agronomic traits. All DH lines were used for analyses of genotypic variability, association studies, and genomic predictions for the grain yield and other yield-related traits. Genome-wide association study (GWAS) using a mixed linear FarmCPU model identified SNPs associated with the studied traits i.e., about seven and eight SNPs for the grain yield; 16 and 12 for anthesis date; seven and eight for anthesis silking interval; 14 and 5 for both ear and plant height; and 15 and 5 for moisture under both WW and WS environments, respectively. Similarly, about 13 and 11 SNPs associated with gray leaf spot and turcicum leaf blight were identified. Eleven SNPs associated with senescence under WS management that had depicted drought-stress-tolerant QTLs were identified. Under MLN artificial inoculation, a total of 12 and 10 SNPs associated with MLN disease severity and AUDPC traits, respectively, were identified. Genomic prediction under WW, WS, and MLN disease artificial inoculation revealed moderate-to-high prediction accuracy. The findings of this study provide useful information on understanding the genetic basis for the MLN resistance, grain yield, and other agronomic traits under MLN artificial inoculation, WW, and WS conditions. Therefore, the obtained information can be used for further validation and developing functional molecular markers for marker-assisted selection and for implementing genomic prediction to develop superior elite lines