A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (Zea mays L.)

Despite QTL mapping being a routine procedure in plant breeding, approaches that fully exploit data from multi-trait multi-environment (MTME) trials are limited. Mixed models have been proposed both for multi-trait QTL analysis and multi-environment QTL analysis, but these approaches break down when the number of traits and environments increases. We present models for an efficient QTL analysis of MTME data with mixed models by reducing the dimensionality of the genetic variance¿covariance matrix by structuring this matrix using direct products of relatively simple matrices representing variation in the trait and environmental dimension. In the context of MTME data, we address how to model QTL by environment interactions and the genetic basis of heterogeneity of variance and correlations between traits and environments. We illustrate our approach with an example including five traits across eight stress trials in CIMMYT maize. We detected 36 QTLs affecting yield, anthesis-silking interval, male flowering, ear number, and plant height in maize. Our approach does not require specialised software as it can be implemented in any statistical package with mixed model facilities

Electrochemical impedance spectroscopy to study physiological changes affecting the red blood cell after invasion by malaria parasites

The malaria parasite, Plasmodium falciparum, invades human erythrocytes and induces dramatic changes in the host cell. The idea of this work was to use RBC modified electrode to perform electrochemical impedance spectroscopy (EIS) with the aim of monitoring physiological changes affecting the erythrocyte after invasion by the malaria parasite. Impedance cell-based devices are potentially useful to give insight into cellular behavior and to detect morphological changes. The modelling of impedance plots (Nyquist diagram) in equivalent circuit taking into account the presence of the cellular layer, allowed us pointing out specific events associated with the development of the parasite such as (i) strong changes in the host cell cytoplasm illustrated by changes in the film capacity, (ii) perturbation of the ionic composition of the host cell illustrated by changes in the film resistance, (iii) releasing of reducer (lactic acid or heme) and an enhanced oxygen consumption characterized by changes in the charge transfer resistance and in the Warburg coefficient characteristic of the redox species diffusion. These results show that the RBC-based device may help to analyze strategic events in the malaria parasite development constituting a new tool in antimalarial research

Characterization of oxidative stress in Leishmaniasis-infected or LPS-stimulated macrophages using electrochemical impedance spectroscopy

The physiological changes caused by external stimuli can be employed as parameters to study pathogen infection in cells and the effect of drugs. Among analytical methods, impedance is potentially useful to give insight into cellular behavior by studying morphological changes, alterations in the physiological state, production of charged or redox species without interfering with in vitro cellular metabolism and labeling. The present work describes the use of electrochemical impedances spectroscopy to simply monitor by modeling impedance plots (Nyquist diagram) in appropriate equivalent circuit, the changes affecting murine macrophage cell line (RAW 264.7) in response to parasite infection by Leishmania amazonensis or to lipopolysaccharide (LPS) treatment. These results demonstrate the ability of electrochemical impedance spectroscopy to discriminate between two opposite cell responses associated to two different stimuli, one caused by the internalization of a parasite, and the other by activation by a bacterium component. Indeed, the study has allowed the characterization, from an electrical point of view, of the extra-cellular NO radical produced endogenously and in great quantities by the inducible form of NO-synthase in the case of LPS-stimulatedmacrophages. This production was not observed in the case of Leishmania-infectedmacrophages for which to survive and multiply, the parasite itself possesses mechanisms which may interfere with NO production. In this latest case, only the intracellular production of ROS was observed. To confirm these interpretations confocal microscopy analysis using the ROS (reactive oxygen species) fluorescent probe 2′,7′-dichlorodihydrofluorescein diacetate and electron paramagnetic resonance experiments using Fe(DETC)2 as NO radical spin trap were carried out

The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis

Genotype-by-environment interaction (GEI) is an important phenomenon in plant breeding. This paper presents a series of models for describing, exploring, understanding, and predicting GEI. All models depart from a two-way table of genotype by environment means. First, a series of descriptive and explorative models/approaches are presented: Finlay–Wilkinson model, AMMI model, GGE biplot. All of these approaches have in common that they merely try to group genotypes and environments and do not use other information than the two-way table of means. Next, factorial regression is introduced as an approach to explicitly introduce genotypic and environmental covariates for describing and explaining GEI. Finally, QTL modeling is presented as a natural extension of factorial regression, where marker information is translated into genetic predictors. Tests for regression coefficients corresponding to these genetic predictors are tests for main effect QTL expression and QTL by environment interaction (QEI). QTL models for which QEI depends on environmental covariables form an interesting model class for predicting GEI for new genotypes and new environments. For realistic modeling of genotypic differences across multiple environments, sophisticated mixed models are necessary to allow for heterogeneity of genetic variances and correlations across environments. The use and interpretation of all models is illustrated by an example data set from the CIMMYT maize breeding program, containing environments differing in drought and nitrogen stress. To help readers to carry out the statistical analyses, GenStat® programs, 15th Edition and Discovery® version, are presented as “Appendix.

Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield components and secondary traits

A recombinant inbred line (RIL) population was evaluated in seven field experiments representing four environments: water stress at flowering (WS) and well-watered (WW) conditions in Mexico and Zimbabwe. The QTLs were identified for each trait in each individual experiment (single-experiment analysis) as well as per environment, per water regime across locations and across all experiments (joint analyses). For the six target traits (male flowering, anthesis-to-silking interval, grain yield, kernel number, 100-kernel fresh weight and plant height) 81, 57, 51 and 34 QTLs were identified in the four step-wise analyses, respectively. Despite high values of heritability, the phenotypic variance explained by QTLs was reduced, indicating epistatic interactions. About 80, 60 and 6% of the QTLs did not present significant QTL-by-environment interactions (QTL×E) in the joint analyses per environment, per water regime and across all experiments. The expression of QTLs was quite stable across years at a given location and across locations under the same water regime. However, the stability of QTLs decreased drastically when data were combined across water regimes, reflecting a different genetic basis of the target traits in the drought and well-watered trials. Several clusters of QTLs for different traits were identified by the joint analyses of the WW (chromosomes 1 and 8) and WS (chromosomes 1, 3 and 5) treatments and across water regimes (chromosome 1). Those regions are clear targets for future marker-assisted breeding, and our results confirm that the best approach to breeding for drought tolerance includes selection under water stres

The CGIAR’s Challenge Program Experiences: A Critical Analysis

This document has been prepared by staff of the four Challenge Programs (CPs) established by the CGIAR in 2002-2004 as a contribution to the first meeting of the Consortium Planning Team (CPT) with the Alliance Executive and Deputy Executive (17-20 February 2009)

CropSight: A scalable and open-source information management system for distributed plant phenotyping and IoT-based crop management

Background: High-quality plant phenotyping and climate data lay the foundation of phenotypic analysis and genotype-environment interaction, providing important evidence not only for plant scientists to understand the dynamics between crop performance, genotypes, and environmental factors, but also for agronomists and farmers to closely monitor crops in fluctuating agricultural conditions. With the rise of Internet of Things technologies (IoT) in recent years, many IoT-based remote sensing devices have been applied to plant phenotyping and crop monitoring, which are generating terabytes of biological datasets every day. However, it is still technically challenging to calibrate, annotate, and aggregate the big data effectively, especially when they were produced in multiple locations, at different scales. Findings: CropSight is a PHP and SQL based server platform, which provides automated data collation, storage, and information management through distributed IoT sensors and phenotyping workstations. It provides a two-component solution to monitor biological experiments through networked sensing devices, with interfaces specifically designed for distributed plant phenotyping and centralised data management. Data transfer and annotation are accomplished automatically though an HTTP accessible RESTful API installed on both device-side and server-side of the CropSight system, which synchronise daily representative crop growth images for visual-based crop assessment and hourly microclimate readings for GxE studies. CropSight also supports the comparison of historical and ongoing crop performance whilst different experiments are being conducted. Conclusions: As a scalable and open-source information management system, CropSight can be used to maintain and collate important crop performance and microclimate datasets captured by IoT sensors and distributed phenotyping installations. It provides near real-time environmental and crop growth monitoring in addition to historical and current experiment comparison through an integrated cloud-ready server system. Accessible both locally in the field through smart devices and remotely in an office using a personal computer, CropSight has been applied to field experiments of bread wheat prebreeding since 2016 and speed breeding since 2017. We believe that the CropSight system could have a significant impact on scalable plant phenotyping and IoT-style crop management to enable smart agricultural practices in the near future

The Predicted Usage Model (PUM)

Executive Master of Management i Analytics for Strategic Management fra Handelshøyskolen BI, 2023This predictive analytics project explores how machine learning can contribute to increased customer usage of NTB’s foreign news articles. The result of this research is the Predicted Usage Model (PUM) – a regression model that forecasts the number of NTB customers that will run any given syndicated international news story. The idea is that PUM can help the foreign duty editors select the stories that have the greatest potential usage. The current baseline process does not involve the use of analytical tools but is mainly based on editors’ individual skills and experience. Thus, it is person-dependent and prone to variability. The proposed model outperformed a simple baseline model that uses the mean as a constant value for all the predictions. The paper describes how the model can be further improved in subsequent iterations, outlines how it can be operationalized within the existing system architecture, and lays out a way forward