Inferring multilocal typologies of agrosystems and farmers' practices: A methodological basis for the setting of participatory breeding designs.

Family farms play an essential role in agroecological transition in Sahelian countries and worldwide. They present diversified features in terms of socio-economic organization, agrobiodiversity management and cropping systems diversity. Decentralized participatory breeding approaches aim to sustain the diversity of varieties adapted for such smallholder farmers' contexts. However the lack of clear target population of environments limits the focus and the efficiency of these approaches given the large diversification of the local contexts. In this study, we surveyed variables linked to agrosystems, crop management options and farmers' criteria of varietal evaluation from 254 family farms sampled along 13 locations spanning the target area of a decentralized participatory breeding program of cowpea crop (Vigna unguiculata L. Walp) in Niger. The objective of our study was to infer typologies of family farms in the study area based on relevant variables supporting the setting of target population of environments (TPEs) to be considered in the breeding program. We used factorial analysis of mixed data (FAMD) and the Discriminant Analysis of Principal Components (DAPC) to infer the clusters. Chi square test, analysis of variance and generalized linear model were used to identify key variables discriminating the clusters. These clusters were geographically mapped to analyze their multilocal distribution. So, we identified and characterized four clusters structuring the diversity of the local agrosystems (Typologie G), five clusters structuring the diversity of cowpea cropping management options (Typologie C) and five clusters structuring the diversity of criteria used by farmers to evaluate the performance of cowpea varieties in the local contexts (Typologie P). Typology G distinguished farms based on discriminating variables linked for instance to secondary activities, cultivated species, soil fertility management practices and farm resources including land and livestock. Typology C distinguished farms based on cowpea management pratices including the secondary crop intercropped with cowpea (sorghum, Guinea sorrel, sesame or groundnut) and the use of cowpea harvest products (seeds, haulms, hulls). Typology P was based on discriminating performance criteria including cycle length, insect resistance, striga resistance, drought resistance, haulm production and economic value of cowpea variety. This methodology provides a robust and replicable way for the definition of clusters capturing the diversity of farms and local contexts. We discussed the perspective of using these clusters to set target population of environments for decentralized breeding programs.

The witchweed Striga gesnerioides and the cultivated cowpea: A geographical and historical analysis of their West African distribution points to the prevalence of agro-ecological factors and the parasite's multilocal evolution potential.

The increasing severity of Striga gesnerioides attacks on cowpea across West Africa has been related to its prolificity, seed mobility and longevity, and adaptation to aridity, in a context of agricultural intensification. To understand this fast extension, we analyzed (1) the distributions of the crop and the witchweed with ecological niche modeling and multivariate climate analysis, and (2) the chronological information available from collections and the literature. The ecoclimatic envelope of S. gesnerioides attacks on cowpea is the same as on wild hosts. Consistently, the modeled distribution of cowpea infestations is closely similar to the simple superposition of the parasite model (involving all hosts) and the crop model. Striga gesnerioides infestations are restricted to the driest component of the cultivated cowpea ecoclimatic niche, corresponding to the Sahelian and Sudano-Sahelian belts and the Dahomey gap. Thus, the parasite distribution, determined by its own requirements, does not constrain cowpea cultivation under Guinean climates. The spatial and temporal distributions of S. gesnerioides field infestations are consistent with an earlier impact on cowpea production in eastern West Africa, related itself to a similar trend in cowpea cultivation intensification from Niger, Nigeria and Benin to Burkina Faso and Ghana. Mali and Senegal were affected later, and literature reports of Senegalese strains of S. gesnerioides from the wild developing virulence on cowpea offer a model for the diffusion of witchweed parasitism by multilocal evolution, through host-driven selection, instead of epidemic diffusion. A contrario, in Côte d'Ivoire, cowpea is much less widespread, so the parasite has remained confined to the wild compartment. Thus, both historical and ecogeographic analyses refute the vision of S. gesnerioides as an invader. Instead, they point to the increasing importance and intensification of the crop, and the consequent loss of biodiversity, as the main drivers of the extension and diversification of its crop-specific strains.

Population genomics of sorghum (Sorghum bicolor) across diverse agroclimatic zones of Niger.

Improving adaptation of staple crops in developing countries is important to ensure food security. In the West African country of Niger, the staple crop sorghum (Sorghum bicolor) is cultivated across diverse agroclimatic zones, but the genetic basis of local adaptation has not been described. The objectives of this study were to characterize the genomic diversity of sorghum from Niger and to identify genomic regions conferring local adaptation to agroclimatic zones and farmer preferences. We analyzed 516 Nigerien accessions for which local variety name, botanical race, and geographic origin were known. We discovered 144 299 single nucleotide polymorphisms (SNPs) using genotyping-by-sequencing (GBS). We performed discriminant analysis of principal components (DAPC), which identified six genetic groups, and performed a genome scan for loci with high discriminant loadings. The highest discriminant coefficients were on chromosome 9, near the putative ortholog of maize flowering time adaptation gene Vgt1. Next, we characterized differentiation among local varieties and used a genome scan of pairwise FST values to identify SNPs associated with specific local varieties. Comparison of varieties named for light- versus dark-grain identified differentiation near Tannin1, the major gene responsible for grain tannins. These findings could facilitate genomics-assisted breeding of locally adapted and farmer-preferred sorghum varieties for Niger.

Association studies including genotype by environment interactions: prospects and limits.

BACKGROUND: Association mapping studies offer great promise to identify polymorphisms associated with phenotypes and for understanding the genetic basis of quantitative trait variation. To date, almost all association mapping studies based on structured plant populations examined the main effects of genetic factors on the trait but did not deal with interactions between genetic factors and environment. In this paper, we propose a methodological prospect of mixed linear models to analyze genotype by environment interaction effects using association mapping designs. First, we simulated datasets to assess the power of linear mixed models to detect interaction effects. This simulation was based on two association panels composed of 90 inbreds (pearl millet) and 277 inbreds (maize). RESULTS: Based on the simulation approach, we reported the impact of effect size, environmental variation, allele frequency, trait heritability, and sample size on the power to detect the main effects of genetic loci and diverse effect of interactions implying these loci. Interaction effects specified in the model included SNP by environment interaction, ancestry by environment interaction, SNP by ancestry interaction and three way interactions. The method was finally used on real datasets from field experiments conducted on the two considered panels. We showed two types of interactions effects contributing to genotype by environment interactions in maize: SNP by environment interaction and ancestry by environment interaction. This last interaction suggests differential response at the population level in function of the environment. CONCLUSIONS: Our results suggested the suitability of mixed models for the detection of diverse interaction effects. The need of samples larger than that commonly used in current plant association studies is strongly emphasized to ensure rigorous model selection and powerful interaction assessment. The use of ancestry interaction component brought valuable information complementary to other available approaches.

Association mapping, patterns of linkage disequilibrium and selection in the vicinity of the PHYTOCHROME C gene in pearl millet.

KEY MESSAGE: Linkage analysis confirmed the association in the region of PHYC in pearl millet. The comparison of genes found in this region suggests that PHYC is the best candidate. Major efforts are currently underway to dissect the phenotype-genotype relationship in plants and animals using existing populations. This method exploits historical recombinations accumulated in these populations. However, linkage disequilibrium sometimes extends over a relatively long distance, particularly in genomic regions containing polymorphisms that have been targets for selection. In this case, many genes in the region could be statistically associated with the trait shaped by the selected polymorphism. Statistical analyses could help in identifying the best candidate genes into such a region where an association is found. In a previous study, we proposed that a fragment of the PHYTOCHROME C gene (PHYC) is associated with flowering time and morphological variations in pearl millet. In the present study, we first performed linkage analyses using three pearl millet F2 families to confirm the presence of a QTL in the vicinity of PHYC. We then analyzed a wider genomic region of ~100 kb around PHYC to pinpoint the gene that best explains the association with the trait in this region. A panel of 90 pearl millet inbred lines was used to assess the association. We used a Markov chain Monte Carlo approach to compare 75 markers distributed along this 100-kb region. We found the best candidate markers on the PHYC gene. Signatures of selection in this region were assessed in an independent data set and pointed to the same gene. These results foster confidence in the likely role of PHYC in phenotypic variation and encourage the development of functional studies.

Selection for earlier flowering crop associated with climatic variations in the Sahel.

Climate changes will have an impact on food production and will require costly adaptive responses. Adapting to a changing environment will be particularly challenging in sub-Saharan Africa where climate change is expected to have a major impact. However, one important phenomenon that is often overlooked and is poorly documented is the ability of agro-systems to rapidly adapt to environmental variations. Such an adaptation could proceed by the adoption of new varieties or by the adaptation of varieties to a changing environment. In this study, we analyzed these two processes in one of the driest agro-ecosystems in Africa, the Sahel. We performed a detailed study in Niger where pearl millet is the main crop and covers 65% of the cultivated area. To assess how the agro-system is responding to recent recurrent drought, we analyzed samples of pearl millet landraces collected in the same villages in 1976 and 2003 throughout the entire cultivated area of Niger. We studied phenological and morphological differences in the 1976 and 2003 collections by comparing them over three cropping seasons in a common garden experiment. We found no major changes in the main cultivated varieties or in their genetic diversity. However, we observed a significant shift in adaptive traits. Compared to the 1976 samples, samples collected in 2003 displayed a shorter lifecycle, and a reduction in plant and spike size. We also found that an early flowering allele at the PHYC locus increased in frequency between 1976 and 2003. The increase exceeded the effect of drift and sampling, suggesting a direct effect of selection for earliness on this gene. We conclude that recurrent drought can lead to selection for earlier flowering in a major Sahelian crop. Surprisingly, these results suggest that diffusion of crop varieties is not the main driver of short term adaptation to climatic variation.

Genetic basis of pearl millet adaptation along an environmental gradient investigated by a combination of genome scan and association mapping.

Identifying the molecular bases of adaptation is a key issue in evolutionary biology. Genome scan is an efficient approach for identifying important molecular variation involved in adaptation. Association mapping also offers an opportunity to gain insight into genotype-phenotype relationships. Using these two approaches coupled with environmental data should help to come up with a refined picture of the evolutionary process underlying adaptation. In this study, we first conducted a selection scan analysis on a transcription factor gene family. We focused on the MADS-box gene family, a gene family which plays a crucial role in vegetative and flower development. Twenty-one pearl millet populations were sampled along an environmental gradient in West Africa. We identified one gene, i.e. PgMADS11, using Bayesian analysis to detect selection signatures. Polymorphism at this gene was also associated with flowering time variation in an association mapping framework. Finally, we found that PgMADS11 allele frequencies were closely associated with annual rainfall. Overall, we determined an efficient way to detect functional polymorphisms associated with climate variation in non-model plants by combining genome scan and association mapping. These results should help monitor the impact of recent climatic changes on plant adaptation.

Association studies identify natural variation at PHYC linked to flowering time and morphological variation in pearl millet.

The identification of genes selected during and after plant domestication is an important research topic to enhance knowledge on adaptative evolution. Adaptation to different climates was a key factor in the spread of domesticated crops. We conducted a study to identify genes responsible for these adaptations in pearl millet and developed an association framework to identify genetic variations associated with the phenotype in this species. A set of 90 inbred lines genotyped using microsatellite loci and AFLP markers was used. The population structure was assessed using two different Bayesian approaches that allow inbreeding or not. Association studies were performed using a linear mixed model considering both the population structure and familial relationships between inbred lines. We assessed the ability of the method to limit the number of false positive associations on the basis of the two different Bayesian methods, the number of populations considered and different morphological traits while also assessing the power of the methodology to detect given additive effects. Finally, we applied this methodology to a set of eight pearl millet genes homologous to cereal flowering pathway genes. We found significant associations between several polymorphisms of the pearl millet PHYC gene and flowering time, spike length, and stem diameter in the inbred line panel. To validate this association, we performed a second association analysis in a different set of pearl millet individuals from Niger. We confirmed a significant association between genetic variation in this gene and these characters.