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Key message The Common Bean Angular Leaf Spot Resistance Gene Phg-2 was fine-mapped to a 409-Kbp region, and molecular markers for breeders were developed and validated in field experiments. Abstract Common bean (Phaseolus vulgaris L.) is an important food legume in Latin America, Asia and Africa. It is an important source of protein, carbohydrates and micro-minerals, particularly for smallholder farmers. Common bean productivity is affected by angular leaf spot (ALS) disease caused by the pathogenic fungus Pseudocercospora griseola, resulting in significant yield losses, particularly in low-input smallholder farming systems in the tropics. The ALS resistance gene Phg-2, which was found in several highly resistant common bean genotypes, was investigated in crosses between Mesoamerican pre-breeding lines and elite Andean breeding lines. Next-generation sequencing (NGS) data sets were used to design new SNP-based molecular markers. The Phg-2 locus was confirmed to be the major locus providing ALS resistance in these crosses. The locus was fine-mapped to a 409-Kbp region on chromosome 8. Two clusters of highly related LRR genes were identified in this region, which are the best candidate genes for Phg-2. Molecular markers were identified that are closely linked to the Phg-2 resistance gene and also highly specific to the donor germplasm. Marker-assisted selection (MAS) was used to introgress the Phg-2 resistance locus into Andean breeding germplasm using MAB lines. The usefulness of molecular markers in MAS was confirmed in several field evaluations in complex breeding crosses, under inoculation with different ALS pathotypes. This project demonstrates that NGS data are a powerful tool for the characterization of genetic loci and can be applied in the development of breeding tools. Electronic supplementary material The online version of this article (10.1007/s00122-019-03334-z) contains supplementary material, which is available to authorized users.

Bacterial panicle blight (BPB) caused by Burkholderia glumae is one of the main concerns for rice production in the Americas since bacterial infection can interfere with the grain-filling process and under severe conditions can result in high sterility. B. glumae has been detected in several rice-growing areas of Colombia and other countries of Central and Andean regions in Latin America, although evidence of its involvement in decreasing yield under these conditions is lacking. Analysis of different parameters in trials established in three rice-growing areas showed that, despite BPB presence, severity did not explain the sterility observed in fields. PCR tests for B. glumae confirmed low infection in all sites and genotypes, only 21.4% of the analyzed samples were positive for B. glumae. Climate parameters showed that Montería and Saldaña registered maximum temperature above 34°C, minimum temperature above 23°C, and Relative Humidity above 80%, conditions that favor the invasion model described for this pathogen in Asia. Our study found that in Colombia, minimum temperature above 23°C during 10 days after flowering is the condition that correlates with disease incidence. Therefore, this correlation, and the fact that Montería and Saldaña had a higher level of infected samples according to PCR tests, high minimum temperature, but not maximum temperature, seems to be determinant for B. glumae colonization under studied field conditions. This knowledge is a solid base line to design strategies for disease control, and is also a key element for breeders to develop strategies aimed to decrease the effect of B. glumae and high night-temperature on rice yield under tropical conditions.

Insects are essential for the reproduction of pollinator-dependent crops and contribute to the pollination of 87% of wild plants and 75% of the world’s food crops. Understanding pollen flow dynamics between plants and pollinators is thus essential to manage and conserve wild plants and ensure yields are maximized in food crops. However, the determination of pollen transfer in the field is complex and laborious. We developed a field experiment in a pollinator-dependent crop and used high throughput RNA sequencing (RNA-seq) to quantify pollen flow by measuring changes in gene expression between pollination treatments across different apple (Malus domestica Borkh.) cultivars. We tested three potential molecular indicators of successful pollination and validated these results with field data by observing single and multiple visits by honey bees (Apis mellifera) to apple flowers and measured fruit set in a commercial apple orchard. The first indicator of successful outcrossing was revealed via differential gene expression in the cross-pollination treatments after 6 h. The second indicator of successful outcrossing was revealed by the expression of specific genes related to pollen tube formation and defense response at three different time intervals in the stigma and the style following cross-pollination (i.e. after 6, 24, and 48 h). Finally, genotyping variants specific to donor pollen could be detected in cross-pollination treatments, providing a third indicator of successful outcrossing. Field data indicated that one or five flower visits by honey bees were insufficient and at least 10 honey bee flower visits were required to achieve a 25% probability of fruit set under orchard conditions. By combining the genotyping data, the differential expression analysis, and the traditional fruit set field experiments, it was possible to evaluate the pollination effectiveness of honey bee visits under orchards conditions. This is the first time that pollen-stigma-style mRNA expression analysis has been conducted after a pollinator visit (honey bee) to a plant (in vivo apple flowers). This study provides evidence that mRNA sequencing can be used to address complex questions related to stigma–pollen interactions over time in pollination ecology.

Protective covers (i.e., glasshouses, netting enclosures, and polytunnels) are increasingly used in crop production to enhance crop quality, yield, and production efficiency. However, many protected crops require insect pollinators to achieve optimal pollination and there is no consensus about how best to manage pollinators and crop pollination in these environments. We conducted a systematic literature review to synthesise knowledge about the effect of protective covers on pollinator health and pollination services and identified 290 relevant studies. Bees were the dominant taxon used in protected systems (90%), represented by eusocial bees (e.g., bumble bees (Bombus spp.), honey bees (Apis spp.), stingless bees (Apidae: Meliponini)) and solitary bees (e.g., Amegilla spp., Megachile spp., and Osmia spp.). Flies represented 9% of taxa and included Calliphoridae, Muscidae, and Syrphidae. The remaining 1% of taxa was represented by Lepidoptera and Coleoptera. Of the studies that assessed pollination services, 96% indicate that pollinators were active on the crop and/or their visits resulted in improved fruit production compared with flowers not visited by insects (i.e., insect visits prevented, or flowers were self- or mechanically pollinated). Only 20% of studies evaluated pollinator health. Some taxa, such as mason or leafcutter bees, and bumble bees can function well in covered environments, but the effect of covers on pollinator health was negative in over 50% of the studies in which health was assessed. Negative effects included decreased reproduction, adult mortality, reduced forager activity, and increased disease prevalence. These effects may have occurred as a result of changes in temperature/humidity, light quality/quantity, pesticide exposure, and/or reduced access to food resources. Strategies reported to successfully enhance pollinator health and efficiency in covered systems include: careful selection of bee hive location to reduce heat stress and improve dispersal through the crop; increased floral diversity; deploying appropriate numbers of pollinators; and manipulation of flower physiology to increase attractiveness to pollinating insects. To improve and safeguard crop yields in pollinator dependent protected cropping systems, practitioners need to ensure that delivery of crop pollination services is compatible with suitable conditions for pollinator health.

© Crop Science Society of America. Common bean (Phaseolus vulgaris L.) is the most important grain legume for human consumption and is a major nutrition source in the tropics. Because bean production is reduced by both abiotic and biotic constraints, current breeding efforts are focused on the development of improved varieties with tolerance to these stresses. We characterized materials from different breeding programs spanning three continents to understand their sequence diversity and advance the development of molecular breeding tools. For this, 37 varieties belonging to P. vulgaris, Phaseolus acutifolius (A. Gray), and Phaseolus coccineus L. were sequenced by whole-genome sequencing, identifying more than 40 million genomic variants. Evaluation of nuclear DNA content and analysis of copy number variation revealed important differences in genomic content not only between P. vulgaris and the two other domesticated Phaseolus species, but also within P. vulgaris, affecting hundreds of protein-coding genomic regions. A large number of inter–gene pool introgressions were identified. Furthermore, interspecific introgressions for disease resistance in breeding lines were mapped. Evaluation of newly developed single nucleotide polymorphism markers within previously discovered quantitative trait loci for common bacterial blight and angular leaf spot provides improved specificity to tag sources of resistance to these diseases. We expect that this dataset will provide a deeper molecular understanding of breeding germplasm and deliver molecular tools for germplasm development, aiming to increase the efficiency of bean breeding programs.

Common bean (Phaseolus vulgaris L.) is an important grain legume and an essential protein source for human nutrition in developing countries. Angular leaf spot (ALS) caused by the pathogen Pseudocercospora griseola (Sacc.) Crous and U. Braun is responsible for severe yield losses of up to 80 %. Breeding for resistant cultivars is the most ecological and economical means to control ALS and is particularly important for yield stability in low-input agriculture. Here, we report on a fine-mapping approach of a major quantitative trait locus (QTL) ALS4.1GS, UC for ALS resistance in a mapping population derived from the resistant genotype G5686 and the susceptible cultivar Sprite. 180 F3 individuals of the mapping population were evaluated for ALS resistance and genotyped with 22 markers distributed over 11 genome regions colocating with previously reported QTL for ALS resistance. Multiple QTL analysis identified three QTL regions, including one major QTL on chromosome Pv04 at 43.7 Mbp explaining over 75 % of the observed variation for ALS resistance. Additional evaluation of 153 F4, 89 BC1F2 and 139 F4/F5/BC1F3 descendants with markers in the region of the major QTL delimited the region to 418 kbp harboring 36 candidate genes. Among these, 11 serine/threonine protein kinases arranged in a repetitive array constitute promising candidate genes for controlling ALS resistance. Single nucleotide polymorphism markers cosegregating with the major QTL for ALS resistance have been developed and constitute the basis for marker-assisted introgression of ALS resistance into advanced breeding germplasm of common bean., Theoretical and Applied Genetics, 128 (5), ISSN:0040-5752, ISSN:1432-2242

Background Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris/trypanosome Crithidia bombi model system (two bumblebee colonies by two Crithidia strains), we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C. bombi infection, 3) determining the differential gene expression associated with the bumblebee-Crithidia genotype-genotype interaction at 24 hours after infection and 4) determining the alternative splicing associated with the bumblebee-Crithidia genotype-genotype interaction at 24 hours post infection. Results We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly, we found differential expression and alternative splicing of immunoglobulin related genes (Dscam and Twitchin) are associated with the genotype-genotype interactions of the given bumblebee colony and Crithidia strain. Conclusions In this paper we have shown that the expression and alternative splicing of immune genes is associated with specific interactions between different host and parasite genotypes in this bumblebee/trypanosome model., BMC Genomics, 15, ISSN:1471-2164

Background Therecent development and availability of different genotype by sequencing (GBS) protocols provided a cost-effective approach to perform high-resolution genomic analysis of entire populations in different species. The central component of all these protocols is the digestion of the initial DNA with known restriction enzymes, to generate sequencing fragments at predictable and reproducible sites. This allows to genotype thousands of genetic markers on populations with hundreds of individuals. Because GBS protocols achieve parallel genotyping through high throughput sequencing (HTS), every GBS protocol must include a bioinformatics pipeline for analysis of HTS data. Our bioinformatics group recently developed the Next Generation Sequencing Eclipse Plugin (NGSEP) for accurate, efficient, and user-friendly analysis of HTS data. Results Here we present the latest functionalities implemented in NGSEP in the context of the analysis of GBS data. We implemented a one step wizard to perform parallel read alignment, variants identification and genotyping from HTS reads sequenced from entire populations. We added different filters for variants, samples and genotype calls as well as calculation of summary statistics overall and per sample, and diversity statistics per site. NGSEP includes a module to translate genotype calls to some of the most widely used input formats for integration with several tools to perform downstream analyses such as population structure analysis, construction of genetic maps, genetic mapping of complex traits and phenotype prediction for genomic selection. We assessed the accuracy of NGSEP on two highly heterozygous F1 cassava populations and on an inbred common bean population, and we showed that NGSEP provides similar or better accuracy compared to other widely used software packages for variants detection such as GATK, Samtools and Tassel. Conclusions NGSEP is a powerful, accurate and efficient bioinformatics software tool for analysis of HTS data, and also one of the best bioinformatic packages to facilitate the analysis and to maximize the genomic variability information that can be obtained from GBS experiments for population genomics. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2827-7) contains supplementary material, which is available to authorized users.