Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping.

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

Aflatoxin Contamination of Maize, Groundnut, and Sorghum Grown in Burkina Faso, Mali, and Niger and Aflatoxin Exposure Assessment.

Aflatoxin contamination of staple crops by Aspergillus flavus and closely related fungi is common across the Sahel region of Africa. Aflatoxins in maize, groundnut, and sorghum collected at harvest or from farmers' stores within two weeks of harvest from Burkina Faso, Mali, and Niger were quantified. Thereafter, aflatoxin exposure values were assessed using per capita consumption rates of those crops. Mean aflatoxin concentrations in maize were high, 128, 517, and 659 µg/kg in Mali, Burkina Faso, and Niger, respectively. The estimated probable daily intake (PDI) of aflatoxins from maize ranged from 6 to 69, 29 to 432, and 310 to 2100 ng/kg bw/day in Mali, Burkina Faso, and Niger, respectively. Similarly, mean aflatoxin concentrations in sorghum were high, 76 and 259 µg/kg in Mali and Niger, respectively, with an estimated PDI of 2-133 and 706-2221. For groundnut, mean aflatoxin concentrations were 115, 277, and 628 µg/kg in Mali, Burkina Faso, and Niger, respectively. Aflatoxin exposure values were high with an estimated 9, 28, and 126 liver cancer cases/100,000 persons/year in Mali, Burkina Faso, and Niger, respectively. Several samples were extremely unsafe, exceeding manyfold regulatory levels of diverse countries (up to 2000 times more). Urgent attention is needed across the Sahel for integrated aflatoxin management for public health protection, food and nutrition security, and access to trade opportunities.

Allelic variation for broad-spectrum resistance and susceptibility to bacterial pathogens identified in a rice MAGIC population.

Quantitative trait loci (QTL) that confer broad-spectrum resistance (BSR), or resistance that is effective against multiple and diverse plant pathogens, have been elusive targets of crop breeding programmes. Multiparent advanced generation intercross (MAGIC) populations, with their diverse genetic composition and high levels of recombination, are potential resources for the identification of QTL for BSR. In this study, a rice MAGIC population was used to map QTL conferring BSR to two major rice diseases, bacterial leaf streak (BLS) and bacterial blight (BB), caused by Xanthomonas oryzae pathovars (pv.) oryzicola (Xoc) and oryzae (Xoo), respectively. Controlling these diseases is particularly important in sub-Saharan Africa, where no sources of BSR are currently available in deployed varieties. The MAGIC founders and lines were genotyped by sequencing and phenotyped in the greenhouse and field by inoculation with multiple strains of Xoc and Xoo. A combination of genomewide association studies (GWAS) and interval mapping analyses revealed 11 BSR QTL, effective against both diseases, and three pathovar-specific QTL. The most promising BSR QTL (qXO-2-1, qXO-4-1 and qXO-11-2) conferred resistance to more than nine Xoc and Xoo strains. GWAS detected 369 significant SNP markers with distinguishable phenotypic effects, allowing the identification of alleles conferring disease resistance and susceptibility. The BSR and susceptibility QTL will improve our understanding of the mechanisms of both resistance and susceptibility in the long term and will be immediately useful resources for rice breeding programmes.