Recognizing both the stakes of traditional European common bean diversity and the role farmers' and gardeners' networks play in maintaining this diversity, the present study examines the role that local adaptation plays for the management of common bean diversity in situ. To the purpose, four historical bean varieties and one modern control were multiplied on two organic farms for three growing seasons. The fifteen resulting populations, the initial ones and two populations of each variety obtained after the three years of multiplication, were then grown in a common garden. Twenty-two Simple Sequence Repeat (SSR) markers and 13 phenotypic traits were assessed. In total, 68.2% of tested markers were polymorphic and a total of 66 different alleles were identified. F-ST analysis showed that the genetic composition of two varieties multiplied in different environments changed. At the phenotypic level, differences were observed in flowering date and leaf length. Results indicate that three years of multiplication suffice for local adaptation to occur. The spatial dynamics of genetic and phenotypic bean diversity imply that the maintenance of diversity should be considered at the scale of the network, rather than individual farms and gardens. The microevolution of bean populations within networks of gardens and farms emerges as a research perspective.

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Short-Term Local Adaptation of Historical Common Bean (Phaseolus vulgaris L.) Varieties and Implications for In Situ Management of Bean Diversity.

Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix–best linear unbiased predictions model (RA–BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.

https://www.genetics.org/content/genetics/192/2/715.full.pdf

Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds ( Zea mays L.)

https://ueaeprints.uea.ac.uk/54099/1/Seed_Network_Misconceptions_on_line_first.pdf

Farmer seed networks make a limited contribution to agriculture? Four common misconceptions

Comparative analysis of performance and stability among composite cross populations, variety mixtures and pure lines of winter wheat in organic and conventional cropping systems

Crop diversity underpins the productivity, resilience, and adaptive capacity of agriculture. Loss of this diversity, termed crop genetic erosion, is therefore concerning. While alarms regarding evident declines in crop diversity have been raised for over a century, the magnitude, trajectory, drivers, and significance of these losses remain insufficiently understood. We outline the various definitions, measurements, scales, and sources of information on crop genetic erosion. We then provide a synthesis of evidence regarding changes in the diversity of traditional crop landraces on farms, modern crop cultivars in agriculture, crop wild relatives in their natural habitats, and crop genetic resources held in conservation repositories. This evidence indicates that marked losses, but also maintenance and increases in diversity, have occurred in all these contexts, the extent depending on species, taxonomic and geographic scale, and region, as well as analytical approach. We discuss steps needed to further advance knowledge around the agricultural and societal significance, as well as conservation implications, of crop genetic erosion. Finally, we propose actions to mitigate, stem, and reverse further losses of crop diversity.

Crop genetic erosion: understanding and responding to loss of crop diversity

Since the domestication of crop species, humans have derived specific varieties for particular uses and shaped the genetic diversity of these varieties. Here, using an interdisciplinary approach combining ethnobotany and population genetics, we document the within-variety genetic structure of a population-variety of bread wheat (Triticum aestivum L.) in relation to farmers’ practices to decipher their contribution to crop species evolution. Using 19 microsatellites markers, we conducted two complementary graph theory-based methods to analyze population structure and gene flow among 19 sub-populations of a single population-variety [Rouge de Bordeaux (RDB)]. The ethnobotany approach allowed us to determine the RDB history including diffusion and reproduction events. We found that the complex genetic structure among the RDB sub-populations is highly consistent with the structure of the seed diffusion and reproduction network drawn based on the ethnobotanical study. This structure highlighted the key role of the farmer-led seed diffusion through founder effects, selection and genetic drift because of human practices. An important result is that the genetic diversity conserved on farm is complementary to that found in the genebank indicating that both systems are required for a more efficient crop diversity conservation.

On-farm dynamic management of genetic diversity: the impact of seed diffusions and seed saving practices on a population-variety of bread wheat

While modern agriculture relies on genetic homogeneity, diversifying practices associated with seed exchange and seed recycling may allow crops to adapt to their environment. This socio-genetic model is an original experimental evolution design referred to as on-farm dynamic management of crop diversity. Investigating such model can help in understanding how evolutionary mechanisms shape crop diversity submitted to diverse agro-environments. We studied a French farmer-led initiative where a mixture of four wheat landraces called 'Melange de Touselles' (MDT) was created and circulated within a farmers' network. The 15 sampled MDT subpopulations were simultaneously submitted to diverse environments (e.g. altitude, rainfall) and diverse farmers' practices (e.g. field size, sowing and harvesting date). Twenty-one space-time samples of 80 individuals each were genotyped using 17 microsatellite markers and characterized for their heading date in a 'common-garden' experiment. Gene polymorphism was studied using four markers located in earliness genes. An original network-based approach was developed to depict the particular and complex genetic structure of the landraces composing the mixture. Rapid differentiation among populations within the mixture was detected, larger at the phenotypic and gene levels than at the neutral genetic level, indicating potential divergent selection. We identified two interacting selection processes: variation in the mixture component frequencies, and evolution of within-variety diversity, that shaped the standing variability available within the mixture. These results confirmed that diversifying practices and environments maintain genetic diversity and allow for crop evolution in the context of global change. Including concrete measurements of farmers' practices is critical to disentangle crop evolution processes.

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Diversifying mechanisms in the on‐farm evolution of crop mixtures

While modern agriculture relies on genetic homogeneity in the field, some farmers grow genetically heterogeneous crops and exchange seeds. Such diversifying practices associated with seed recycling may allow adaptation of crops to their environment. This socio-genetical model constitutes an original experimental evolution design called On-Farm Dynamic Management (OFDM). Studying OFDM can help understanding how evolutionary mechanisms shape crop diversity submitted to diverse agro-environmental conditions. We studied a farmer-led initiative where a mixture of four French wheat landraces called "Melange de Touselles" (MDT) was created and distributed within a farmers' network. Fifteen populations derived by farmers from the initial mixture were sampled after 2 to 7 generations of cultivation on their farm. Twenty-one space-time samples of 80 individuals were genotyped using 17 microsatellites markers and characterized for their heading date in a "common-garden" experiment. Gene polymorphism was studied using four markers located in earliness genes. An original network-based approach was developed to depict the particular and complex genetic structure of the landraces composing the mixture. A rapid differentiation of the mixture was detected, larger at the phenotypic and gene levels compared to the neutral genetic level, indicating a potential divergent selection. We identified two interacting selection processes: variation of the mixture component frequencies and evolution of the within-variety diversity, that shaped the standing variability available within the mixture. These results confirm that farmers' practices increase genetic diversity and allow crop evolution, which is critical in the context of global change. OFDM appears as a promising model of crop experimental evolution.

https://www.biorxiv.org/content/biorxiv/early/2014/10/02/009829.full.pdf

Sophie Jouanne-Pin

Papers

On-farm dynamic management of genetic diversity: the impact of seed diffusions and seed saving practices on a population-variety of bread wheat

Diversifying mechanisms in the on‐farm evolution of crop mixtures

Diversifying mechanisms in the on-farm evolution of crop mixtures