Modernising breeding for orphan crops: tools, methodologies, and beyond.

MAIN CONCLUSION: In spite of the limited investment in orphan crops, access to new technologies such as bioinformatics and low-cost genotyping opens new doors to modernise their breeding effectively. Innovation in plant breeding is imperative to meet the world's growing demand for staple food and feed crops, and orphan crops can play a significant role in increasing productivity and quality, especially in developing countries. The short breeding history of most orphan crops implies that genetic gain should be achievable through easy-to-implement approaches such as forward breeding for simple traits or introgression of elite alleles at key target trait loci. However, limited financial support and access to sufficient, relevant and reliable phenotypic data continue to pose major challenges in terms of resources and capabilities. Digitalisation of orphan-crop breeding programmes can help not only to improve data quality and management, but also to mitigate data scarcity by allowing data to be accumulated and analysed over time and across teams. Bioinformatics tools and access to technologies such as molecular markers, some of them provided as services via specific platforms, allow breeders to implement modern strategies to improve breeding efficiency. In orphan crops, more marker-trait associations relevant to breeding germplasm are generally needed, but implementing digitalization, marker-based quality control or simple trait screening and introgression will help modernising breeding. Finally, the development of local capacities-of both people and infrastructure-remains a necessity to ensure the sustainable adoption of modern breeding approaches.

QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance.

Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or less uniformly in diverse genetic backgrounds across contrasting water regimes could significantly complement conventional breeding efforts to improve drought tolerance. We evaluated three tropical bi-parental populations under water-stress (WS) and well-watered (WW) regimes in Mexico, Kenya and Zimbabwe to identify genomic regions responsible for grain yield (GY) and anthesis-silking interval (ASI) across multiple environments and diverse genetic backgrounds. Across the three populations, on average, drought stress reduced GY by more than 50 % and increased ASI by 3.2 days. We identified a total of 83 and 62 QTL through individual environment analyses for GY and ASI, respectively. In each population, most QTL consistently showed up in each water regime. Across the three populations, the phenotypic variance explained by various individual QTL ranged from 2.6 to 17.8 % for GY and 1.7 to 17.8 % for ASI under WS environments and from 5 to 19.5 % for GY under WW environments. Meta-QTL (mQTL) analysis across the three populations and multiple environments identified seven genomic regions for GY and one for ASI, of which six mQTL on chr.1, 4, 5 and 10 for GY were constitutively expressed across WS and WW environments. One mQTL on chr.7 for GY and one on chr.3 for ASI were found to be 'adaptive' to WS conditions. High throughput assays were developed for SNPs that delimit the physical intervals of these mQTL. At most of the QTL, almost equal number of favorable alleles was donated by either of the parents within each cross, thereby demonstrating the potential of drought tolerant × drought tolerant crosses to identify QTL under contrasting water regimes.

Marker-assisted selection to improve drought adaptation in maize: the backcross approach, perspectives, limitations, and alternatives.

A number of different marker-assisted selection (MAS) approaches do exist for the improvement of polygenic traits. Results of a marker-assisted backcross (MABC) selection experiment aimed at improving grain yield under drought conditions in tropical maize are presented and compared with alternative MAS strategies. The introgression of favourable alleles at five target regions involved in the expression of yield components and flowering traits increased grain yield and reduced the asynchrony between male and female flowering under water-limited conditions. Eighty-five per cent of the recurrent parent's genotype at non-target loci was recovered in only four generations of MABC by screening large segregating populations (2200 individuals) for three of the four generations. Selected MABC-derived BC(2)F(3) families were crossed with two testers and evaluated under different water regimes. Mean grain yield of MABC-derived hybrids was consistently higher than that of control hybrids (crosses from the recurrent parent to the same two testers as the MABC-derived families) under severe water stress conditions. Under those conditions, the best five MABC-derived hybrids yielded, on average, at least 50% more than control hybrids. Under mild water stress, defined as resulting in <50% yield reduction, no difference was observed between MABC-derived hybrids and the control plants, thus confirming that the genetic regulation for drought tolerance is dependent on stress intensity. MABC conversions involving several target regions are likely to result in partial rather than complete line conversion. Simulations were conducted to assess the utility of such partial conversions, i.e. containing favourable donor alleles at non-target regions, for subsequent phenotypic selection. The results clearly showed that selecting several genotypes (10-20) at each MABC cycle was most efficient. In the light of these results, alternative approaches to MABC are discussed, including recurrent selection, illustrated by an example of improving the adaptation of maize to low temperatures. Given the current approaches for MAS and the choices of marker technologies available now and potential for future developments, the use of MAS techniques in further improving grain yield under abiotic stresses in maize appears very promising.

Mapping QTLs and QTL x environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods.

The study of QTL x environment interaction (QEI) is important for understanding genotype x environment interaction (GEI) in many quantitative traits. For modeling GEI and QEI, factorial regression (FR) models form a powerful class of models. In FR models, covariables (contrasts) defined on the levels of the genotypic and/or environmental factor(s) are used to describe main effects and interactions. In FR models for QTL expression, considerable numbers of genotypic covariables can occur as for each putative QTL an additional covariable needs to be introduced. For large numbers of genotypic and/or environmental covariables, least square estimation breaks down and partial least squares (PLS) estimation procedures become an attractive alternative. In this paper we develop methodology for analyzing QEI by FR for estimating effects and locations of QTLs and QEI and interpreting QEI in terms of environmental variables. A randomization test for the main effects of QTLs and QEI is presented. A population of F2 derived F3 families was evaluated in eight environments differing in drought stress and soil nitrogen content and the traits yield and anthesis silking interval (ASI) were measured. For grain yield, chromosomes 1 and 10 showed significant QEI, whereas in chromosomes 3 and 8 only main effect QTLs were observed. For ASI, QTL main effects were observed on chromosomes 1, 2, 6, 8, and 10, whereas QEI was observed only on chromosome 8. The assessment of the QEI at chromosome 1 for grain yield showed that the QTL main effect explained 35.8% of the QTL + QEI variability, while QEI explained 64.2%. Minimum temperature during flowering time explained 77.6% of the QEI. The QEI analysis at chromosome 10 showed that the QTL main effect explained 59.8% of the QTL + QEI variability, while QEI explained 40.2%. Maximum temperature during flowering time explained 23.8% of the QEI. Results of this study show the possibilities of using FR for mapping QTL and for dissecting QEI in terms of environmental variables. PLS regression is efficient in accounting for background noise produced by other QTLs.

Maize HSP101 plays important roles in both induced and basal thermotolerance and primary root growth.

HSP101 belongs to the ClpB protein subfamily whose members promote the renaturation of protein aggregates and are essential for the induction of thermotolerance. We found that maize HSP101 accumulated in mature kernels in the absence of heat stress. At optimal temperatures, HSP101 disappeared within the first 3 days after imbibition, although its levels increased in response to heat shock. In embryonic cells, HSP101 concentrated in the nucleus and in some nucleoli. Hsp101 maps near the umc132 and npi280 markers on chromosome 6. Five maize hsp101-m-::Mu1 alleles were isolated. Mutants were null for HSP101 and defective in both induced and basal thermotolerance. Moreover, during the first 3 days after imbibition, primary roots grew faster in the mutants at optimal temperature. Thus, HSP101 is a nucleus-localized protein that, in addition to its role in thermotolerance, negatively influences the growth rate of the primary root. HSP101 is dispensable for proper embryo and whole plant development in the absence of heat stress.