Giovanni Galli

Universidade de São Paulo

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Roberto Fritsche‐Neto

Louisiana State University Agricultural Center

Donatella Caruso

University of Milan

M. Galli Kienle

University of Milano-Bicocca

Alberto Fiecchi

Brunel University of London

Giuliana Cighetti

University of Milan

Filipe Couto Alves

Universidade de São Paulo

R. Paoletti

University of Milan

Elena Tremoli

Maria Cecilia Hospital

Antonio Scala

Institute for Complex Systems

E. Bosisio

University of Milan

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University of Milan

204

Istituti di Ricovero e Cura a Carattere Scientifico

University of Padua

University of Pavia

Universidade de São Paulo

University of Bologna

Centre National de la Recherche Scientifique

University of Turin

University of Pittsburgh

Inserm

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Genome-wide association analysis of hyperspectral reflectance data to dissect growth-related traits genetic architecture in maize under inoculation with plant growth-promoting bacteria

bioRxiv (Cold Spring Harbor Laboratory) (2022)

Rafael Massahiro Yassue Giovanni Galli Chunpeng James Chen Roberto Fritsche‐Neto Gota Morota

Abstract Plant growth-promoting bacteria (PGPB) may be of use for increasing crop yield and plant resilience to biotic and abiotic stressors. Using hyperspectral reflectance data to assess growth-related traits may shed light on the underlying genetics as such data can help assess biochemical and physiological traits. This study aimed to integrate hyperspectral reflectance data with genome-wide association analyses to examine maize growth-related traits under PGPB inoculation. A total of 360 inbred maize lines with 13,826 single nucleotide polymorphisms (SNPs) were evaluated with and without PGPB inoculation; 150 hyperspectral wavelength reflectances at 386–1,021 nm and 131 hyperspectral indices were used in the analysis. Plant height, stalk diameter, and shoot dry mass were measured manually. Overall, hyperspectral signatures produced similar or higher genomic heritability estimates than those of manually measured phenotypes, and they were genetically correlated with manually measured phenotypes. Furthermore, several hyperspectral reflectance values and spectral indices were identified by genome-wide association analysis as potential markers for growthrelated traits under PGPB inoculation. Eight SNPs were detected, which were associated with manually measured and hyperspectral phenotypes. Moreover, the hyperspectral phenotypes were associated with genes previously reported as candidates for nitrogen uptake efficiency, tolerance to abiotic stressors, and kernel size. In addition, a Shiny web application was developed to explore multi-phenotype genome-wide association results interactively. Taken together, our results demonstrate the usefulness of hyperspectral-based phenotyping for studying maize growth-related traits in response to PGPB inoculation.

Phenotypic trait

Genetic architecture

Association mapping

10.1101/2022.08.11.503682

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Citations (0)

Yield components and reproductive, physiological, and root traits used in early selection for nitrogen use efficiency in corn

Pesquisa Agropecuária Brasileira (2018)

Pedro Patric Pinho Morais Massáine Bandeira e Sousa Giovanni Galli Luciano Rogério Braatz de Andrade Roberto Fritsche‐Neto

Abstract: The objective of this work was to examine the possibility of using yield components and reproductive, physiological, and root traits in early selection for nitrogen use efficiency (NUE) in corn. Sixty-four inbred lines were evaluated under two nitrogen fertilization levels: ideal and low. The evaluations were performed at three phenological stages: eight fully-expanded leaves, tasseling stage, and physiological maturity. It is possible to select superior lines for NUE, but the yield components did not show differential behavior under the different nitrogen levels evaluated. Root, reproductive, and physiological traits are not promising for early selection of corn lines with high NUE. Likewise, the eight-leaves and tasseling stages were not promising for this purpose, since NUE should be estimated taking grain yield into account. However, indirect selection for NUE can be performed via number of ears or using the selection index considering number and weight of ears.

10.1590/s0100-204x2018000500011

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Analysis of cyclooxygenase and lipoxygenase products in incubation media

Prostaglandins (1984)

Lidia Sautebin Donatella Caruso Giovanni Galli

Defibrotide

10.1016/0090-6980(84)90192-8

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Citations (18)

Propane partial oxidation over M3+-substituted vanadyl phosphates dispersed on titania and silica

Applied Catalysis A General (2002)

S. Marengo P. Patrono P. Comotti Giovanni Galli Paola Gallì

Propane

Propene

Partial oxidation

Chemisorption

Physisorption

10.1016/s0926-860x(02)00003-0

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Citations (6)

ChemInform Abstract: SYNTHESIS OF CHOLESTANES CONTAINING AN OXYGENATED 14α‐METHYL GROUP

Chemischer Informationsdienst (1977)

M. ANASTASIA Alberto Fiecchi Giuliana Cighetti Giovanni Galli

10.1002/chin.197725369

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Rapid Evaluation of Phenolic Component Profile and Analysis of Oleuropein Aglycon in Olive Oil by Atmospheric Pressure Chemical Ionization−Mass Spectrometry (APCI−MS)

Journal of Agricultural and Food Chemistry (2000)

Donatella Caruso Roberto Colombo Rossana Patelli Flavio Giavarini Giovanni Galli

Epidemiological studies have linked the Mediterranean diet with a low incidence of cardiovascular diseases. Olive oil, the major fat component of this diet, is characterized by antioxidant properties related to their content in catecholic components, particularly oleuropein aglycon. Therefore quantification of these components in edible oils may be important in determining the quality, and consequently its commercial value. The present method allows us to obtain the profile of the phenolic components of the oil from the methanolic extracts of the crude olive oil. In particular tyrosol, hydroxytyrosol, elenolic acid, deacetoxyligstroside and deacetoxyoleuropein aglycons, ligstroside and oleuropein aglycons, and 10-hydroxy-oleuropein are clearly identified by atmospheric pressure chemical ionization-mass spectrometry (APCI-MS). Moreover, oleuropein and its isomers present in the oil are quantified by APCI-MS/MS analysis of the extracts without preliminary separation from other phenolic compounds.

Oleuropein

Hydroxytyrosol

Atmospheric-pressure chemical ionization

Tyrosol

Vegetable oil

10.1021/jf9905370

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Citations (89)

Influence of diamide on aggregation, cytoskeletal proteins, and arachidonic acid metabolism in human platelets

Thrombosis Research (1984)

Donatella Caruso Giovanni Galli U Till P. Spangenberg Wolfgang Lösche

Arachidonic acid metabolism

10.1016/0049-3848(84)90371-2

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Citations (7)

Olive oil phenolics are dose‐dependently absorbed in humans

FEBS Letters (2000)

Francesco Visioli Cláudio Galli Francis Bornet Alissa Mattei Rossana Patelli

Olive oil phenolic constituents have been shown, in vitro, to be endowed with potent biological activities including, but not limited to, an antioxidant action. To date, there is no information on the absorption and disposition of such compounds in humans. We report that olive oil phenolics, namely tyrosol and hydroxytyrosol, are dose‐dependently absorbed in humans after ingestion and that they are excreted in the urine as glucuronide conjugates. Furthermore, an increase in the dose of phenolics administered increased the proportion of conjugation with glucuronide.

Tyrosol

Hydroxytyrosol

Glucuronide

10.1016/s0014-5793(00)01216-3

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Citations (385)

Changes of energy fluxes in marine animal forests of the Anthropocene: factors shaping the future seascape

ICES Journal of Marine Science (2019)

Sergio Rossi Enrique Isla Mar Bosch-Belmar Giovanni Galli Andrea Gori

Abstract Climate change is already transforming the seascapes of our oceans by changing the energy availability and the metabolic rates of the organisms. Among the ecosystem-engineering species that structure the seascape, marine animal forests (MAFs) are the most widespread. These habitats, mainly composed of suspension feeding organisms, provide structural complexity to the sea floor, analogous to terrestrial forests. Because primary and secondary productivity is responding to different impacts, in particular to the rapid ongoing environmental changes driven by climate change, this paper presents some directions about what could happen to different MAFs depending on these fast changes. Climate change could modify the resistance or resilience of MAFs, potentially making them more sensitive to impacts from anthropic activities (i.e. fisheries and coastal management), and vice versa, direct impacts may amplify climate change constraints in MAFs. Such changes will have knock-on effects on the energy budgets of active and passive suspension feeding organisms, as well as on their phenology, larval nutritional condition, and population viability. How the future seascape will be shaped by the new energy fluxes is a crucial question that has to be urgently addressed to mitigate and adapt to the diverse impacts on natural systems.

Seascape

Marine ecosystem

Marine Spatial Planning

Anthropocene

Marine protected area

10.1093/icesjms/fsz147

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Citations (33)

Classification of plant growth-promoting bacteria inoculation status and prediction of growth-related traits in tropical maize using hyperspectral image and genomic data

bioRxiv (Cold Spring Harbor Laboratory) (2022)

Rafael Massahiro Yassue Giovanni Galli Roberto Fritsche‐Neto Gota Morota

Abstract Recent technological advances in high-throughput phenotyping have created new opportunities for the prediction of complex traits. In particular, phenomic prediction using hyper-spectral reflectance could capture various signals that affect phenotypes genomic prediction might not explain. A total of 360 inbred maize lines with or without plant growth-promoting bacterial inoculation management under nitrogen stress were evaluated using 150 spectral wavelengths ranging from 386 to 1021 nm and 13,826 single-nucleotide polymorphisms. Six prediction models were explored to assess the predictive ability of hyperspectral and genomic data for inoculation status and plant growth-related traits. The best models for hyperspectral prediction were partial least squares and automated machine learning. The Bayesian ridge regression and BayesB were the best performers for genomic prediction. Overall, hyper-spectral prediction showed greater predictive ability for shoot dry mass and stalk diameter, whereas genomic prediction was better for plant height. The prediction models that simultaneously accommodated both hyperspectral and genomic data resulted in a predictive ability as high as that of phenomics or genomics alone. Our results highlight the usefulness of hyperspectral-based phenotyping for management and phenomic prediction studies. Core ideas Hyperspectral reflectance data can classify plant growth-promoting bacteria inoculation status Phenomic prediction performs better than genomic prediction depending on the target phenotype AutoML is a promising approach for automating hyperparameter tuning for classification and prediction

Phenomics

Predictive modelling

Plant Breeding

10.1101/2022.03.04.483003

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Citations (2)