Periodic Reporting for period 3 - EUCLEG (Breeding forage and grain legumes to increase EU's and China's protein self-sufficiency)
Periodo di rendicontazione: 2020-09-01 al 2021-12-31
EUCLEG aimed at providing tools and knowledge to improve the genetic progress in five major legume species: two forages, alfalfa and red clover, and three grain legumes, pea, faba bean and soybean. This implied genotyping, phenotyping and statistical work.
In WP1, we developed molecular and genomic tools. For the two outbreeding forage crops, we used genotyping by sequencing (GBS) to obtain marker frequency from pooled individuals of each accession (pool-GBS). For the three autogamous grain legumes, we used SNP array technology to genotype the accessions.
In WP2, we structured and improved access to data on European and Chinese plant genetic resources collections. We identifed gaps (both passport and phenotypic data) in existing information systems and encouraged collection holders to close these gaps. We created an efficient infrastructure for the central management of the data collected during the project (the Progeno database). Finally, the legal challenges and risks associated with the exchange of plant genetic resources and their data, but also intellectual property issues, were considered.
In WP3, we described the genetic structure of germplasm collections using both phenotypic traits and molecular markers. Trials were established in a network of environments in EU and China. Relevant phenotypic traits were evaluated: germination, crop establishment, response to biotic and abiotic stress, forage and seed yield, forage and grain quality. A description of Chinese and European germplasm, an overview of genotype x environment interaction were provided and promising germplasm was identified. The genetic structure of the germplasm was described with genotype data obtained in WP1.
In WP4, we identified genes, alleles and molecular markers that explained a large part of the phenotypic variation available for traits involved in crop yield and its stability including resistance to biotic and abiotic stresses. The WP2 database containing genotype and phenotype data was used for genome-wide association analyses (GWAS).
WP5 delivered knowledge and tools to breeders to implement genomic selection, a form of marker-assisted selection which is more efficient than phenotypic selection in many cases. A user-friendly tool was developed for managing data and performing the calculation of breeding values (BV) and genomic breeding values (GEBV). The effects of several determinants of the accuracy of the equation of prediction of GEBV were tested and we proposed breeding solutions including genomic selection.
WP6 disseminated the project outcomes to the scientific community and transferred the innovations to stakeholders.
In WP1, we developed molecular and genomic tools. For the two outbreeding forage crops, we used genotyping by sequencing (GBS) to obtain marker frequency from pooled individuals of each accession (pool-GBS). For the three autogamous grain legumes, we used SNP array technology to genotype the accessions.
In WP2, we structured and improved access to data on European and Chinese plant genetic resources collections. We identifed gaps (both passport and phenotypic data) in existing information systems and encouraged collection holders to close these gaps. We created an efficient infrastructure for the central management of the data collected during the project (the Progeno database). Finally, the legal challenges and risks associated with the exchange of plant genetic resources and their data, but also intellectual property issues, were considered.
In WP3, we described the genetic structure of germplasm collections using both phenotypic traits and molecular markers. Trials were established in a network of environments in EU and China. Relevant phenotypic traits were evaluated: germination, crop establishment, response to biotic and abiotic stress, forage and seed yield, forage and grain quality. A description of Chinese and European germplasm, an overview of genotype x environment interaction were provided and promising germplasm was identified. The genetic structure of the germplasm was described with genotype data obtained in WP1.
In WP4, we identified genes, alleles and molecular markers that explained a large part of the phenotypic variation available for traits involved in crop yield and its stability including resistance to biotic and abiotic stresses. The WP2 database containing genotype and phenotype data was used for genome-wide association analyses (GWAS).
WP5 delivered knowledge and tools to breeders to implement genomic selection, a form of marker-assisted selection which is more efficient than phenotypic selection in many cases. A user-friendly tool was developed for managing data and performing the calculation of breeding values (BV) and genomic breeding values (GEBV). The effects of several determinants of the accuracy of the equation of prediction of GEBV were tested and we proposed breeding solutions including genomic selection.
WP6 disseminated the project outcomes to the scientific community and transferred the innovations to stakeholders.
Genotype data have been generated:
1. Alfalfa – Europe: 1061 accessions were genotyped by GBS. Allele frequency for 228K SNP with less than 5% missing data and 118k SNP without any missing data. China: 220 individuals were genotyped using whole genome sequencing (560K SNP).
2. Red clover: 641 accessions were genotyped by GBS. Allele frequency data for 65K SNP markers.
3. Faba bean: 400 accessions were genotyped with a 50K Faba bean Axiom array. Genotype data for 35K markers.
4. Pea: 260 accessions were genotyped using the 13K GenoPea array. Genotype data for 12K markers.
5. Soybean: 479 European and 326 Chinese accessions were genotyped with the 355K SoySNP array.
Inventories of plant genetic resources of the five focus species in Europe and China were compiled and gaps between the EURISCO system and the European Central Crop Databases have been reduced. Reports have been produced to describe (1) challenges and risks related to the exchange of plant genetic resources, (2) China’s plant variety protection system and its relevance for European breeders.
A total of 34 field experiments have been conducted in Europe and China with hundreds of accessions, and traits related to yield, quality, stress resistance have been measured. In addition, experiments have been carried out under controlled conditions for the evaluation of traits related to biotic and abiotic stress and seedling vigour. A central infrastructure for project data management was set up in the Progeno system, where partners have imported genotype and phenotype data.
A huge phenotypic and genetic diversity has been revealed in all five species. Because many markers have been used, the genetic structure added to the current knowledge. For example, on alfalfa, diversity in China and in EU-America is largely different, and among EU-America diversity, there is a range of diversity partly related to the geographical origin of the varieties. On soybean, a genome-wide genetic diversity scan revealed multiple signatures of selection in an European soybean collection compared to Chinese collections of wild and cultivated soybean accessions. Genotype x Environment interactions were usually important but highly performing accessions and/or accessions carrying positive traits were identified. GWAS has been conducted and revealed lists of QTL for almost all traits in the five species. An analysis of the genome annotation on the QTL regions provided lists of potential candidate genes whose sequence diversity may explain phenotypic variation.
The routines needed to implement genomic prediction have been developed and EUCLEG members have been trained. Genomic predictions were more accurate than in most of the studies already published, probably because we have used large numbers of accessions and many markers. Standard genomic prediction were often higher than 0.5 while the addition of QTL in the genomic prediction equations raised the predictive ability to 0.8.
In WP6, a collaborative website has been created for sharing of project outcomes and project newsletters have been produced and distributed. Results have been presented at a number of scientific conferences and several papers have been published in peer reviewed journals, other are under preparation.
1. Alfalfa – Europe: 1061 accessions were genotyped by GBS. Allele frequency for 228K SNP with less than 5% missing data and 118k SNP without any missing data. China: 220 individuals were genotyped using whole genome sequencing (560K SNP).
2. Red clover: 641 accessions were genotyped by GBS. Allele frequency data for 65K SNP markers.
3. Faba bean: 400 accessions were genotyped with a 50K Faba bean Axiom array. Genotype data for 35K markers.
4. Pea: 260 accessions were genotyped using the 13K GenoPea array. Genotype data for 12K markers.
5. Soybean: 479 European and 326 Chinese accessions were genotyped with the 355K SoySNP array.
Inventories of plant genetic resources of the five focus species in Europe and China were compiled and gaps between the EURISCO system and the European Central Crop Databases have been reduced. Reports have been produced to describe (1) challenges and risks related to the exchange of plant genetic resources, (2) China’s plant variety protection system and its relevance for European breeders.
A total of 34 field experiments have been conducted in Europe and China with hundreds of accessions, and traits related to yield, quality, stress resistance have been measured. In addition, experiments have been carried out under controlled conditions for the evaluation of traits related to biotic and abiotic stress and seedling vigour. A central infrastructure for project data management was set up in the Progeno system, where partners have imported genotype and phenotype data.
A huge phenotypic and genetic diversity has been revealed in all five species. Because many markers have been used, the genetic structure added to the current knowledge. For example, on alfalfa, diversity in China and in EU-America is largely different, and among EU-America diversity, there is a range of diversity partly related to the geographical origin of the varieties. On soybean, a genome-wide genetic diversity scan revealed multiple signatures of selection in an European soybean collection compared to Chinese collections of wild and cultivated soybean accessions. Genotype x Environment interactions were usually important but highly performing accessions and/or accessions carrying positive traits were identified. GWAS has been conducted and revealed lists of QTL for almost all traits in the five species. An analysis of the genome annotation on the QTL regions provided lists of potential candidate genes whose sequence diversity may explain phenotypic variation.
The routines needed to implement genomic prediction have been developed and EUCLEG members have been trained. Genomic predictions were more accurate than in most of the studies already published, probably because we have used large numbers of accessions and many markers. Standard genomic prediction were often higher than 0.5 while the addition of QTL in the genomic prediction equations raised the predictive ability to 0.8.
In WP6, a collaborative website has been created for sharing of project outcomes and project newsletters have been produced and distributed. Results have been presented at a number of scientific conferences and several papers have been published in peer reviewed journals, other are under preparation.
Based on project results, legume breeders of public institutes or private companies can modify their breeding schemes to make the best use of genetic diversity and to implement marker assisted breeding. Genetic progress will be boosted in the next years, with the creation of new varieties, improved to deal with feed and food usages and regional constraints. In the meanwhile, farmers can rely on existing varieties that have shown high yield and quality performance and yield stability under contrasted conditions. This wide use of legume varieties into farming systems is expected to secure farm budget balance. It will also have a high impact on EU protein autonomy for feed and food, increase ecosystem services related to crop diversification and contribute to nitrogen input in the farming systems.