Neutrophil “plucking” on megakaryocytes drives platelet production and boosts cardiovascular disease

Intravascular neutrophils and platelets collaborate in maintaining host integrity, but their interaction can also trigger thrombotic complications. We report here that cooperation between neutrophil and platelet lineages extends to the earliest stages of platelet formation by megakaryocytes in the bone marrow. Using intravital microscopy, we show that neutrophils "plucked" intravascular megakaryocyte extensions, termed proplatelets, to control platelet production. Following CXCR4-CXCL12-dependent migration towards perisinusoidal megakaryocytes, plucking neutrophils actively pulled on proplatelets and triggered myosin light chain and extracellular-signal-regulated kinase activation through reactive oxygen species. By these mechanisms, neutrophils accelerate proplatelet growth and facilitate continuous release of platelets in steady state. Following myocardial infarction, plucking neutrophils drove excessive release of young, reticulated platelets and boosted the risk of recurrent ischemia. Ablation of neutrophil plucking normalized thrombopoiesis and reduced recurrent thrombosis after myocardial infarction and thrombus burden in venous thrombosis. We establish neutrophil plucking as a target to reduce thromboischemic events

Improving association studies and genomic predictions for climbing beans with data from bush bean populations

Common bean (Phaseolus vulgaris L.) has two major origins of domestication, Andean and Mesoamerican, which contribute to the high diversity of growth type, pod and seed characteristics. The climbing growth habit is associated with increased days to flowering (DF), seed iron concentration (SdFe), nitrogen fixation, and yield. However, breeding efforts in climbing beans have been limited and independent from bush type beans. To advance climbing bean breeding, we carried out genome-wide association studies and genomic predictions using 1,869 common bean lines belonging to five breeding panels representing both gene pools and all growth types. The phenotypic data were collected from 17 field trials and were complemented with 16 previously published trials. Overall, 38 significant marker-trait associations were identified for growth habit, 14 for DF, 13 for 100 seed weight, three for SdFe, and one for yield. Except for DF, the results suggest a common genetic basis for traits across all panels and growth types. Seven QTL associated with growth habits were confirmed from earlier studies and four plausible candidate genes for SdFe and 100 seed weight were newly identified. Furthermore, the genomic prediction accuracy for SdFe and yield in climbing beans improved up to 8.8% when bush-type bean lines were included in the training population. In conclusion, a large population from different gene pools and growth types across multiple breeding panels increased the power of genomic analyses and provides a solid and diverse germplasm base for genetic improvement of common bean

Linking photosynthesis and yield reveals a strategy to improve light use efficiency in a climbing bean breeding population

Photosynthesis drives plant physiology, biomass accumulation and yield. Photosynthetic efficiency, specifically the operating efficiency of photosystem II (F_q’/F_m’), is highly responsive to actual growth conditions, especially to fluctuating photosynthetic photon fluence rate (PPFR). Under field conditions, plants constantly balance energy uptake to optimize growth. The dynamic regulation complicates the quantification of cumulative photochemical energy uptake based on the intercepted solar energy, its transduction into biomass and the identification of efficient breeding lines. Here, we show significant effects on biomass related to genetic variation in photosynthetic efficiency of 178 climbing bean (Phaseolus vulgaris L.) lines. Under fluctuating conditions, the F_q’/F_m’ was monitored throughout the growing period using hand-held and automated chlorophyll fluorescence phenotyping. The seasonal response of F_q’/F_m’ to PPFR (Response_G:PPFR) achieved significant correlations with biomass and yield ranging from 0.33 to 0.35 and 0.22 to 0.31 in two glasshouse and three field trials, respectively. Phenomic yield prediction outperformed genomic predictions for new environments in four trials under rather different growing conditions. Investigating genetic control over photosynthesis, one SNP (Chr09_37766289_13052) on chromosome 9 was significantly associated with ResponseG:PPFR in proximity to a candidate gene controlling chloroplast thylakoid formation. In conclusion, photosynthetic screening facilitates and accelerates selection for high yield potential.ISSN:1460-2431ISSN:0022-095

Replication Data for: Genomic prediction of agronomic traits in common bean under environmental stress

These datasets contain phenotypic and genotypic data of a panel of elite Andean breeding lines of common bean (Phaseolus vulgaris L.) from CIAT. This population has been tested in twelve yield trials carried out in Palmira and Darien (Colombia) between 2013 and 2018 to assess its performance under irrigated, drought and variable soil P conditions. These trials were laid out in the field with an alpha-lattice experimental design using two to three replicates, and a non-replicated trial in 2016. Meteorological data for these trials is also provided. Different agronomic traits were evaluated including Days to Flowering (DF), Days to Physiological Maturity (DPM), 100 seed weight (100SdW) and Yield (Yd). The agronomic performance of the population was modeled using linear mixed models with spatial correction. From these models, best linear unbiased estimators (BLUEs) and their corresponding standard errors (SE) were obtained. This population was genotyped by sequencing (GBS) using the ApeKI-based restriction digestion. The genotypic data is presented in a variant call format (VCF) file of 5,820 SNPs and 481 lines. The genotypic matrix was imputed using Beagle (v4.1). These datasets were used to test genomic prediction models on the panel in order to assess their prediction ability under different scenarios and parameter settings

Improving Association Studies and Genomic Predictions for Climbing Beans With Data From Bush Bean Populations

Common bean (Phaseolus vulgaris L.) has two major origins of domestication, Andean and Mesoamerican, which contribute to the high diversity of growth type, pod and seed characteristics. The climbing growth habit is associated with increased days to flowering (DF), seed iron concentration (SdFe), nitrogen fixation, and yield. However, breeding efforts in climbing beans have been limited and independent from bush type beans. To advance climbing bean breeding, we carried out genome-wide association studies and genomic predictions using 1,869 common bean lines belonging to five breeding panels representing both gene pools and all growth types. The phenotypic data were collected from 17 field trials and were complemented with 16 previously published trials. Overall, 38 significant marker-trait associations were identified for growth habit, 14 for DF, 13 for 100 seed weight, three for SdFe, and one for yield. Except for DF, the results suggest a common genetic basis for traits across all panels and growth types. Seven QTL associated with growth habits were confirmed from earlier studies and four plausible candidate genes for SdFe and 100 seed weight were newly identified. Furthermore, the genomic prediction accuracy for SdFe and yield in climbing beans improved up to 8.8% when bush-type bean lines were included in the training population. In conclusion, a large population from different gene pools and growth types across multiple breeding panels increased the power of genomic analyses and provides a solid and diverse germplasm base for genetic improvement of common bean.ISSN:1664-462

Reactive nitrogen and sulphate wet deposition at Zeppelin Station, Ny-Ålesund, Svalbard

As a potent fertilizer, reactive nitrogen plays an important role in Arctic ecosystems. Since the Arctic is a nutrient-limited environment, changes in nitrogen deposition can have severe impacts on local ecosystems. To quantify the amount of nitrogen deposited through snow and rain events, precipitation sampling was performed at Zeppelin Station, Svalbard, from November 2009 until May 2011. The samples were analysed for , nss- and concentrations, and the deposition of single precipitation events was calculated using precipitation measurements taken at nearby Ny-Ålesund. The majority of observed events showed concentrations ranging from 0.01 to 0.1 mg L−1 N for and and from 0.02 to 0.3 mg L−1 S for nss-. The majority of calculated depositions ranged from 0.01 to 0.1 mg m−2 N for and and from 0.02 to 0.3 mg m−2 S for nss-. The budget was controlled by strong deposition events, caused by long-lasting precipitation episodes that lasted for several days and which had raised concentrations of nitrogen and sulphur. Three future scenarios of increasing precipitation in the Arctic were considered. The results showed that deposition is mainly controlled by the amount of precipitation, which leads to the conclusion that increased precipitation might cause increases in deposition of the same magnitude