The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems

Implementation of theoretical non-photochemical quenching (NPQ(T)) to investigate NPQ of chickpea under drought stress with High-throughput Phenotyping

Non-photochemical quenching (NPQ) is a protective mechanism for dissipating excess energy generated during photosynthesis in the form of heat. The accelerated relaxation of the NPQ in fluctuating light can lead to an increase in the yield and dry matter productivity of crops. Since the measurement of NPQ is time-consuming and requires specific light conditions, theoretical NPQ (NPQ(T)) was introduced for rapid estimation, which could be suitable for High-throughput Phenotyping. We investigated the potential of NPQ(T) to be used for testing plant genetic resources of chickpea under drought stress with non-invasive High-throughput Phenotyping complemented with yield traits. Besides a high correlation between the hundred-seed-weight and the Estimated Biovolume, significant differences were observed between the two types of chickpea desi and kabuli for Estimated Biovolume and NPQ(T). Desi was able to maintain the Estimated Biovolume significantly better under drought stress. One reason could be the effective dissipation of excess excitation energy in photosystem II, which can be efficiently measured as NPQ(T). Screening of plant genetic resources for photosynthetic performance could take pre-breeding to a higher level and can be implemented in a variety of studies, such as here with drought stress or under fluctuating light in a High-throughput Phenotyping manner using NPQ(T).

Genotype Combinations Drive Variability in the Microbiome Configuration of the Rhizosphere of Maize/Bean Intercropping System

In an intercropping system, the interplay between cereals and legumes, which is strongly driven by the complementarity of below-ground structures and their interactions with the soil microbiome, raises a fundamental query: Can different genotypes alter the configuration of the rhizosphere microbial communities? To address this issue, we conducted a field study, probing the effects of intercropping and diverse maize (Zea mays L.) and bean (Phaseolus vulgaris L., Phaseolus coccineus L.) genotype combinations. Through amplicon sequencing of bacterial 16S rRNA genes from rhizosphere samples, our results unveil that the intercropping condition alters the rhizosphere bacterial communities, but that the degree of this impact is substantially affected by specific genotype combinations. Overall, intercropping allows the recruitment of exclusive bacterial species and enhances community complexity. Nevertheless, combinations of maize and bean genotypes determine two distinct groups characterized by higher or lower bacterial community diversity and complexity, which are influenced by the specific bean line associated. Moreover, intercropped maize lines exhibit varying propensities in recruiting bacterial members with more responsive lines showing preferential interactions with specific microorganisms. Our study conclusively shows that genotype has an impact on the rhizosphere microbiome and that a careful selection of genotype combinations for both species involved is essential to achieve compatibility optimization in intercropping.

Fine-mapping and evolutionary history of R-BPMV, a dominant resistance gene to Bean pod mottle virus in Phaseolus vulgaris L

KEY MESSAGE

R-BPMV is located within a recently expanded TNL cluster in the Phaseolus genus with suppressed recombination and known for resistance to multiple pathogens including potyviruses controlled by the I gene. Bean pod mottle virus (BPMV) is a comovirus that infects common bean and legumes in general. BPMV is distributed throughout the world and is a major threat on soybean, a closely related species of common bean. In common bean, BAT93 was reported to carry the R-BPMV resistance gene conferring resistance to BPMV and linked with the I resistance gene. To fine map R-BPMV, 182 recombinant inbred lines (RILs) derived from the cross BAT93 × JaloEEP558 were genotyped with polymerase chain reaction (PCR)-based markers developed using genome assemblies from G19833 and BAT93, as well as BAT93 BAC clone sequences. Analysis of RILs carrying key recombination events positioned R-BPMV to a target region containing at least 16 TIR-NB-LRR (TNL) sequences in BAT93. Because the I cluster presents a suppression of recombination and a large number of repeated sequences, none of the 16 TNLs could be excluded as R-BPMV candidate gene. The evolutionary history of the TNLs for the I cluster were reconstructed using microsynteny and phylogenetic analyses within the legume family. A single I TNL was present in Medicago truncatula and lost in soybean, mirroring the absence of complete BPMV resistance in soybean. Amplification of TNLs in the I cluster predates the divergence of the Phaseolus species, in agreement with the emergence of R-BPMV before the separation of the common bean wild centers of diversity. This analysis provides PCR-based markers useful in marker-assisted selection (MAS) and laid the foundation for cloning of R-BPMV resistance gene in order to transfer the resistance into soybean.

The 'microbiome counterattack': Insights on the soil and root-associated microbiome in diverse chickpea and lentil genotypes after an erratic rainfall event

Legumes maintain soil fertility thanks to their associated microbiota but are threatened by climate change that causes soil microbial community structural and functional modifications. The core microbiome associated with different chickpea and lentil genotypes was described after an unexpected climatic event. Results showed that chickpea and lentil bulk soil microbiomes varied significantly between two sampling time points, the first immediately after the rainfall and the second 2 weeks later. Rhizobia were associated with the soil of the more productive chickpea genotypes in terms of flower and fruit number. The root-associated bacteria and fungi were surveyed in lentil genotypes, considering that several parcels showed disease symptoms. The metabarcoding analysis revealed that reads related to fungal pathogens were significantly associated with one lentil genotype. A lentil core prokaryotic community common to all genotypes was identified as well as a genotype-specific one. A higher number of specific bacterial taxa and an enhanced tolerance to fungal diseases characterized a lentil landrace compared to the commercial varieties. This outcome supported the hypothesis that locally adapted landraces might have a high recruiting efficiency of beneficial soil microbes.

A comprehensive metabolomics and lipidomics atlas for the legumes common bean, chickpea, lentil and lupin

Legumes represent an important component of human and livestock diets; they are rich in macro- and micronutrients such as proteins, dietary fibers and polyunsaturated fatty acids. Whilst several health-promoting and anti-nutritional properties have been associated with grain content, in-depth metabolomics characterization of major legume species remains elusive. In this article, we used both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to assess the metabolic diversity in the five legume species commonly grown in Europe, including common bean (Phaseolus vulgaris), chickpea (Cicer arietinum), lentil (Lens culinaris), white lupin (Lupinus albus) and pearl lupin (Lupinus mutabilis), at the tissue level. We were able to detect and quantify over 3400 metabolites covering major nutritional and anti-nutritional compounds. Specifically, the metabolomics atlas includes 224 derivatized metabolites, 2283 specialized metabolites and 923 lipids. The data generated here will serve the community as a basis for future integration to metabolomics-assisted crop breeding and facilitate metabolite-based genome-wide association studies to dissect the genetic and biochemical bases of metabolism in legume species.

Automating high-throughput screening for anthracnose resistance in common bean using allele specific PCR

BACKGROUND

Common beans (Phaseolus vulgaris L.) provide important protein and calories globally. Anthracnose (Colletotrichum lindemuthianum (Sacc. & Magnus) Briosi & Cavara, 1889) is a major disease in common bean and causes significant yield losses in bean production areas. Screening for markers linked to known disease resistance genes provides useful information for plant breeders to develop improved common bean varieties. The Kompetitive Allele Specific PCR (KASP) assay is an affordable genetic screening technique that can be used to accelerate breeding programs, but manual DNA extraction and KASP assay preparation are time-consuming. Several KASP markers have been developed for genes involved in resistance to bean anthracnose, which can reduce yield by up to 100%, but their usefulness is hindered by the labor required to screen a significant number of bean lines. Our research objective was to develop publicly available protocols for DNA extraction and KASP assaying using a liquid handling robot (LHR) which would facilitate high-throughput genetic screening with less active human time required. Anthracnose resistance markers were used to compare manual and automated results.

RESULTS

The 12 bean anthracnose differential cultivars were screened for four anthracnose KASP markers linked to the resistance genes Co-1, Co-3 and Co-42 both by hand and with the use of an LHR. A protocol was written for DNA extraction and KASP assay thermocycling to implement the LHR. The LHR protocol reduced the active human screening time of 24 samples from 3h44 to 1h23. KASP calls were consistent across replicates but not always accurate for their known linked resistance genes, suggesting more specific markers still need to be developed. Using an LHR, information from KASP assays can be accumulated with little active human time.

CONCLUSION

Results suggest that LHRs can be used to expedite time-consuming and tedious lab work such as DNA extraction or PCR plate filling. Notably, LHRs can be used to prepare KASP assays for large sample sizes, facilitating higher throughput use of genetic marker screening tools.

Challenges and Opportunities behind the Use of Herbaria in Paleogenomics Studies

Paleogenomics focuses on the recovery, manipulation, and analysis of ancient DNA (aDNA) from historical or long-dead organisms to reconstruct and analyze their genomes. The aDNA is commonly obtained from remains found in paleontological and archaeological sites, conserved in museums, and in other archival collections. Herbarium collections represent a great source of phenotypic and genotypic information, and their exploitation has allowed for inference and clarification of previously unsolved taxonomic and systematic relationships. Moreover, herbarium specimens offered a new source for studying phenological traits in plants and for disentangling biogeography and evolutionary scenarios of species. More recently, advances in molecular technologies went in parallel with the decreasing costs of next-generation sequencing (NGS) approaches, which paved the way to the utilization of aDNA for whole-genome studies. Although many studies have been carried out combining modern analytic techniques and ancient samples, such as herbarium specimens, this research field is still relatively unexplored due to the need for improving strategies for aDNA manipulation and exploitation from ancient samples. The higher susceptibility of aDNA to degradation and contamination during herbarium conservation and manipulation and the occurrence of biochemical postmortem damage can result in a more challenging reconstruction of the original DNA sequence. Here, we review the methodological approaches that have been developed for the exploitation of historical herbarium plant materials, such as best practices for aDNA extraction, amplification, and genotyping. We also focus on some strategies to overcome the main problems related to the utilization of herbarium specimens for their exploitation in plant evolutionary studies.

Engaging Precision Phenotyping to Scrutinize Vegetative Drought Tolerance and Recovery in Chickpea Plant Genetic Resources

Precise and high-throughput phenotyping (HTP) of vegetative drought tolerance in chickpea plant genetic resources (PGR) would enable improved screening for genotypes with low relative loss of biomass formation and reliable physiological performance. It could also provide a basis to further decipher the quantitative trait drought tolerance and recovery and gain a better understanding of the underlying mechanisms. In the context of climate change and novel nutritional trends, legumes and chickpea in particular are becoming increasingly important because of their high protein content and adaptation to low-input conditions. The PGR of legumes represent a valuable source of genetic diversity that can be used for breeding. However, the limited use of germplasm is partly due to a lack of available characterization data. The development of HTP systems offers a perspective for the analysis of dynamic plant traits such as abiotic stress tolerance and can support the identification of suitable genetic resources with a potential breeding value. Sixty chickpea accessions were evaluated on an HTP system under contrasting water regimes to precisely evaluate growth, physiological traits, and recovery under optimal conditions in comparison to drought stress at the vegetative stage. In addition to traits such as Estimated Biovolume (EB), Plant Height (PH), and several color-related traits over more than forty days, photosynthesis was examined by chlorophyll fluorescence measurements on relevant days prior to, during, and after drought stress. With high data quality, a wide phenotypic diversity for adaptation, tolerance, and recovery to drought was recorded in the chickpea PGR panel. In addition to a loss of EB between 72% and 82% after 21 days of drought, photosynthetic capacity decreased by 16-28%. Color-related traits can be used as indicators of different drought stress stages, as they show the progression of stress.

Impact of drought and salt stress on galactinol and raffinose family oligosaccharides in common bean (Phaseolus vulgaris)

Due to climate change, farmers will face more extreme weather conditions and hence will need crops that are better adapted to these challenges. The raffinose family oligosaccharides (RFOs) could play a role in the tolerance of crops towards abiotic stress. To investigate this, we determined for the first time the importance of galactinol and RFOs in the roots and leaves of common bean under drought and salt stress conditions. Initially, the physiological characteristics of common bean under agronomically relevant abiotic stress conditions were investigated by measuring the growth rate, transpiration rate, chlorophyll concentration and membrane stability, allowing to establish relevant sampling points. Subsequently, the differential gene expression profiles of the galactinol and RFO biosynthetic genes and the amount of galactinol and RFO molecules were measured in the primary leaves and roots of Phaseolus vulgaris cv. CIAP7247F at these sampling points, using RT-qPCR and HPAEC-PAD, respectively. Under drought stress, the genes galactinol synthase 1, galactinol synthase 3 and stachyose synthase were significantly upregulated in the leaves and had a high transcript level in comparison with the other galactinol and RFO biosynthetic genes. This was in accordance with the significantly higher amount of galactinol and raffinose detected in the leaves. Under salt stress, raffinose was also present in a significantly higher quantity in the leaves. In the roots, transcript levels of the RFO biosynthetic genes were generally low and no galactinol, raffinose or stachyose could be detected. These results suggest that in the leaves, both galactinol and raffinose could play a role in the protection of common bean against abiotic stresses. Especially, the isoform galactinol synthase 3 could have a specific role during drought stress and forms an interesting candidate to improve the abiotic stress resistance of common bean or other plant species.

CRISPR-Cas9-based repeat depletion for high-throughput genotyping of complex plant genomes

High-throughput genotyping enables the large-scale analysis of genetic diversity in population genomics and genome-wide association studies that combine the genotypic and phenotypic characterization of large collections of accessions. Sequencing-based approaches for genotyping are progressively replacing traditional genotyping methods because of the lower ascertainment bias. However, genome-wide genotyping based on sequencing becomes expensive in species with large genomes and a high proportion of repetitive DNA. Here we describe the use of CRISPR-Cas9 technology to deplete repetitive elements in the 3.76-Gb genome of lentil (Lens culinaris), 84% consisting of repeats, thus concentrating the sequencing data on coding and regulatory regions (single-copy regions). We designed a custom set of 566,766 gRNAs targeting 2.9 Gbp of repeats and excluding repetitive regions overlapping annotated genes and putative regulatory elements based on ATAC-seq data. The novel depletion method removed ∼40% of reads mapping to repeats, increasing those mapping to single-copy regions by ∼2.6-fold. When analyzing 25 million fragments, this repeat-to-single-copy shift in the sequencing data increased the number of genotyped bases of ∼10-fold compared to nondepleted libraries. In the same condition, we were also able to identify ∼12-fold more genetic variants in the single-copy regions and increased the genotyping accuracy by rescuing thousands of heterozygous variants that otherwise would be missed because of low coverage. The method performed similarly regardless of the multiplexing level, type of library or genotypes, including different cultivars and a closely related species (L. orientalis). Our results showed that CRISPR-Cas9-driven repeat depletion focuses sequencing data on single-copy regions, thus improving high-density and genome-wide genotyping in large and repetitive genomes.

Selection and adaptive introgression guided the complex evolutionary history of the European common bean

Domesticated crops have been disseminated by humans over vast geographic areas. Common bean (Phaseolus vulgaris L.) was introduced in Europe after 1492. Here, by combining whole-genome profiling, metabolic fingerprinting and phenotypic characterisation, we show that the first common bean cultigens successfully introduced into Europe were of Andean origin, after Francisco Pizarro's expedition to northern Peru in 1529. We reveal that hybridisation, selection and recombination have shaped the genomic diversity of the European common bean in parallel with political constraints. There is clear evidence of adaptive introgression into the Mesoamerican-derived European genotypes, with 44 Andean introgressed genomic segments shared by more than 90% of European accessions and distributed across all chromosomes except PvChr11. Genomic scans for signatures of selection highlight the role of genes relevant to flowering and environmental adaptation, suggesting that introgression has been crucial for the dissemination of this tropical crop to the temperate regions of Europe.

CRISPR/Cas9-Mediated Enrichment Coupled to Nanopore Sequencing Provides a Valuable Tool for the Precise Reconstruction of Large Genomic Target Regions

Complete and accurate identification of genetic variants associated with specific phenotypes can be challenging when there is a high level of genomic divergence between individuals in a study and the corresponding reference genome. We have applied the Cas9-mediated enrichment coupled to nanopore sequencing to perform a targeted de novo assembly and accurately reconstruct a genomic region of interest. This approach was used to reconstruct a 250-kbp target region on chromosome 5 of the common bean genome (Phaseolus vulgaris) associated with the shattering phenotype. Comparing a non-shattering cultivar (Midas) with the reference genome revealed many single-nucleotide variants and structural variants in this region. We cut five 50-kbp tiled sub-regions of Midas genomic DNA using Cas9, followed by sequencing on a MinION device and de novo assembly, generating a single contig spanning the whole 250-kbp region. This assembly increased the number of Illumina reads mapping to genes in the region, improving their genotypability for downstream analysis. The Cas9 tiling approach for target enrichment and sequencing is a valuable alternative to whole-genome sequencing for the assembly of ultra-long regions of interest, improving the accuracy of downstream genotype-phenotype association analysis.

Genomic Prediction Strategies for Dry-Down-Related Traits in Maize

For efficient mechanical harvesting, low grain moisture content at harvest time is essential. Dry-down rate (DR), which refers to the reduction in grain moisture content after the plants enter physiological maturity, is one of the main factors affecting the amount of moisture in the kernels. Dry-down rate is estimated using kernel moisture content at physiological maturity and at harvest time; however, measuring kernel water content at physiological maturity, which is sometimes referred as kernel water content at black layer formation (BWC), is time-consuming and resource-demanding. Therefore, inferring BWC from other correlated and easier to measure traits could improve the efficiency of breeding efforts for dry-down-related traits. In this study, multi-trait genomic prediction models were used to estimate genetic correlations between BWC and water content at harvest time (HWC) and flowering time (FT). The results show there is moderate-to-high genetic correlation between the traits (0.24-0.66), which supports the use of multi-trait genomic prediction models. To investigate genomic prediction strategies, several cross-validation scenarios representing possible implementations of genomic prediction were evaluated. The results indicate that, in most scenarios, the use of multi-trait genomic prediction models substantially increases prediction accuracy. Furthermore, the inclusion of historical records for correlated traits can improve prediction accuracy, even when the target trait is not measured on all the plots in the training set.

Towards the Development, Maintenance and Standardized Phenotypic Characterization of Single-Seed-Descent Genetic Resources for Chickpea

Here we present the approach used to develop the INCREASE "Intelligent Chickpea" Collections, from analysis of the information on the life history and population structure of chickpea germplasm, the availability of genomic and genetic resources, the identification of key phenotypic traits and methodologies to characterize chickpea. We present two phenotypic protocols within H2O20 Project INCREASE to characterize, develop, and maintain chickpea single-seed-descent (SSD) line collections. Such protocols and related genetic resource data from the project will be available for the legume community to apply the standardized approaches to develop Chickpea Intelligent Collections further or for multiplication/seed-increase purposes. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Characterization of chickpea seeds for seed-trait descriptors Basic Protocol 2: Characterization of chickpea lines for plant-trait descriptors specific for primary seed increase.

Comparative Flower Transcriptome Network Analysis Reveals DEGs Involved in Chickpea Reproductive Success during Salinity

Salinity is increasingly becoming a significant problem for the most important yet intrinsically salt-sensitive grain legume chickpea. Chickpea is extremely sensitive to salinity during the reproductive phase. Therefore, it is essential to understand the molecular mechanisms by comparing the transcriptomic dynamics between the two contrasting genotypes in response to salt stress. Chickpea exhibits considerable genetic variation amongst improved cultivars, which show better yields in saline conditions but still need to be enhanced for sustainable crop production. Based on previous extensive multi-location physiological screening, two identified genotypes, JG11 (salt-tolerant) and ICCV2 (salt-sensitive), were subjected to salt stress to evaluate their phenological and transcriptional responses. RNA-Sequencing is a revolutionary tool that allows for comprehensive transcriptome profiling to identify genes and alleles associated with stress tolerance and sensitivity. After the first flowering, the whole flower from stress-tolerant and sensitive genotypes was collected. A total of ~300 million RNA-Seq reads were sequenced, resulting in 2022 differentially expressed genes (DEGs) in response to salt stress. Genes involved in flowering time such as FLOWERING LOCUS T (FT) and pollen development such as ABORTED MICROSPORES (AMS), rho-GTPase, and pollen-receptor kinase were significantly differentially regulated, suggesting their role in salt tolerance. In addition to this, we identify a suite of essential genes such as MYB proteins, MADS-box, and chloride ion channel genes, which are crucial regulators of transcriptional responses to salinity tolerance. The gene set enrichment analysis and functional annotation of these genes in flower development suggest that they can be potential candidates for chickpea crop improvement for salt tolerance.

Towards Development, Maintenance, and Standardized Phenotypic Characterization of Single-Seed-Descent Genetic Resources for Lupins

Well-characterized genetic resources are fundamental to maintain and provide the various genotypes for pre-breeding programs for the production of new cultivars (e.g., wild relatives, unimproved material, landraces). The aim of the current article is to provide protocols for the characterization of the genetic resources of two lupin crop species: the European Lupinus albus and the American Lupinus mutabilis. Intelligent nested collections of lupins derived from homozygous lines (single-seed descent) are being developed, established, and exploited using cutting-edge approaches for genotyping, phenotyping, data management, and data analysis within the INCREASE project (EU Horizon 2020). This will allow us to predict the phenotypic performance of genotyped lines, and will further boost research and development in lupins. Lupins stand out due to their high-quality seed protein (∼40% of seed dry weight) and other primary components in the seeds, which include fatty acids, dietary fiber, and minerals. The potential of lupins as a crop is highlighted by the multiple benefits of plant-based food in terms of food security, nutrition, human health, and sustainable production. The use of lupins in foods, along with other well-studied and widely used food legumes, will also provide a greatly diversified plant-based food palette to meet the Global Goals for Sustainable Development to improve people's lives by 2030. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Lupin seed phenotypic descriptors Basic Protocol 2: Lupin seed imaging Basic Protocol 3: Standardized phenotypic characterization of lupin genetic resources grown towards primary seed increase (development of single-seed descent genetic resources).