Chapter 8. Wheat rusts: Current status, prospects of genetic control and integrated approaches to enhance resistance durability

sridhar bhavani Ravi Singh David Hodson JULIO HUERTA_ESPINO Mandeep Randhawa (2022, [Capítulo de libro])

Rust Resistance Race Specific Genes Adult Plant Resistance Genes Breeding Technologies CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE ADULT PLANT RESISTANCE BREEDING TECHNOLOGY

Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Ana Luisa Garcia-Oliveira Mahalingam Govindaraj Rodomiro Ortiz (2023, [Artículo])

Bioaccessibility and Absorption Biofortified Crop Cultivars Genes and Genetic Markers Nutrient Acquisition Transport and Storage CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOAVAILABILITY ABSORPTION CLIMATE CHANGE GENETIC MARKERS GENETIC ENGINEERING NUTRIENTS TRANSPORT STORAGE

Nitrogen fertilizer application alters the root endophyte bacterial microbiome in maize plants, but not in the stem or rhizosphere soil

Alejandra Miranda Carrazco Yendi Navarro-Noya Bram Govaerts Nele Verhulst Luc Dendooven (2022, [Artículo])

Plant-associated microorganisms that affect plant development, their composition, and their functionality are determined by the host, soil conditions, and agricultural practices. How agricultural practices affect the rhizosphere microbiome has been well studied, but less is known about how they might affect plant endophytes. In this study, the metagenomic DNA from the rhizosphere and endophyte communities of root and stem of maize plants was extracted and sequenced with the “diversity arrays technology sequencing,” while the bacterial community and functionality (organized by subsystems from general to specific functions) were investigated in crops cultivated with or without tillage and with or without N fertilizer application. Tillage had a small significant effect on the bacterial community in the rhizosphere, but N fertilizer had a highly significant effect on the roots, but not on the rhizosphere or stem. The relative abundance of many bacterial species was significantly different in the roots and stem of fertilized maize plants, but not in the unfertilized ones. The abundance of N cycle genes was affected by N fertilization application, most accentuated in the roots. How these changes in bacterial composition and N genes composition might affect plant development or crop yields has still to be unraveled.

Bacterial Community Structure DArT-Seq Bacterial Community Functionality Genes Involved in N Cycling CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRACTICES MAIZE RHIZOSPHERE STEMS NITROGEN FERTILIZERS

De Novo assembly and annotation of the Pacific calico scallop (Argopecten ventricosus) transcriptome for immune-related gene discovery

RUTH ESCAMILLA MONTES GENARO DIARTE PLATA GABRIELA BERENICE MENDOZA MALDONADO Aarón Barraza Celis Carlos Eliud Angulo Valadez Seyed Hossein Hoseinifar Jesús Arturo Fierro Coronado ANTONIO LUNA GONZALEZ (2022, [Artículo])

"Invertebrates' immune defense mechanisms play a critical role in pathogen recognition and elimination. De novo assembly and annotation of the Argopecten ventricosus transcriptome were performed for the immune-related gene identification. Scallops (height: 4.4 cm) were challenged with inactivated Vibrio parahaemolyticus IPNGS16. The RNA from different tissues was pooled for a single cDNA library construction sequenced by NextSeq 500 platform 2×75 paired‐end chemistry. Before de novo assembling with Trinity, reads were analyzed with FastQC, Trimmomatic, and Prinseq. Assembled sequences were analyzed by CD-HIT-EST and TransDecoder. The corresponding annotation was performed against NCBI-nr, RefSeq protein, and KAAS (KEGG) databases. The Trinity assembly yielded 107,516 contigs. TransDecoder yielded 25,285 sequences as CDSs of which, 16,123 were annotated against the NCBI-nr protein, most of them scored with Crassostrea gigas data. Gene ontology mapped sequences (15,262) were classified in molecular functions (~13,000), cellular components (~11,000), and biological processes (~13,000). The KAAS analysis showed biological categories for metabolism (13%), cellular processes (12%), genetic information processing (10%), organismal systems (19%), environmental information (13%), and human diseases (33 %). Within the organismal systems, 467 immune-related genes (KO) were identified. Sixty-four immune-related genes were annotated/blasted against the NCBI-nr and RefSeq protein databases. An RT-qPCR was performed to analyze the expression level of immune-related genes obtained in the transcriptome analysis in scallops (height 4.5 cm) treated with probiotic bacilli added to culture water. Bacilli significantly increased the expression of the HSP70 and PGRP genes. The gene transcripts analysis of A. ventricosus will better understand its immune response against pathogens in culture systems."

Argopecten ventricosus, calico scallop, transcriptome, bivalve, immune genes BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA BIOLOGÍA ANIMAL (ZOOLOGÍA) INMUNOLOGÍA INMUNOLOGÍA

Solanum tuberosum Microtuber Development under Darkness Unveiled through RNAseq Transcriptomic Analysis

ELIANA VALENCIA LOZANO LISSET HERRERA ISIDRON Osiel Salvador Recoder-Meléndez Aarón Barraza Celis JOSE LUIS CABRERA PONCE (2022, [Artículo])

"Potato microtuber (MT) development through in vitro techniques are ideal propagules for producing high quality potato plants. MT formation is influenced by several factors, i.e., photoperiod, sucrose, hormones, and osmotic stress. We have previously developed a protocol of MT induction in medium with sucrose (8% w/v), gelrite (6g/L), and 2iP as cytokinin under darkness. To understand the molecular mechanisms involved, we performed a transcriptome-wide analysis. Here we show that 1715 up- and 1624 down-regulated genes were involved in this biological process. Through the protein–protein interaction (PPI) network analyses performed in the STRING database (v11.5), we found 299 genes tightly associated in 14 clusters. Two major clusters of up-regulated proteins fundamental for life growth and development were found: 29 ribosomal proteins (RPs) interacting with 6 PEBP family members and 117 cell cycle (CC) proteins. The PPI network of up-regulated transcription factors (TFs) revealed that at least six TFs–MYB43, TSF, bZIP27, bZIP43, HAT4 and WOX9–may be involved during MTs development. The PPI network of down-regulated genes revealed a cluster of 83 proteins involved in light and photosynthesis, 110 in response to hormone, 74 in hormone mediate signaling pathway and 22 related to aging."

transcriptome-wide analysis, microtubers, potato, Solanum tuberosum, darkness, cell cycle, ribosomal proteins, PEBP family genes, cytokinin BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA GENÉTICA MOLECULAR DE PLANTAS GENÉTICA MOLECULAR DE PLANTAS

Control de sistemas usando aprendizaje de máquina

Systems control using machine learning

Jesús Martín Miguel Martínez (2023, [Tesis de maestría])

El aprendizaje por refuerzo es un paradigma del aprendizaje de máquina con un amplio desarrollo y una creciente demanda en aplicaciones que involucran toma de decisiones y control. Es un paradigma que permite el diseño de controladores que no dependen directamente del modelo que describe la dinámica del sistema. Esto es importante ya que en aplicaciones reales es frecuente que no se disponga de dichos modelos de manera precisa. Esta tesis tiene como objetivo implementar un controlador óptimo en tiempo discreto libre de modelo. La metodología elegida se basa en algoritmos de aprendizaje por refuerzo, enfocados en sistemas con espacios de estado y acción continuos a través de modelos discretos. Se utiliza el concepto de función de valor (Q-función y función V ) y la ecuación de Bellman para resolver el problema del regulador cuadrático lineal para un sistema mecánico masa-resorte-amortiguador, en casos donde se tiene conocimiento parcial y desconocimiento total del modelo. Para ambos casos las funciones de valor son definidas explícitamente por la estructura de un aproximador paramétrico, donde el vector de pesos del aproximador es sintonizado a través de un proceso iterativo de estimación de parámetros. Cuando se tiene conocimiento parcial de la dinámica se usa el método de aprendizaje por diferencias temporales en un entrenamiento episódico, que utiliza el esquema de mínimos cuadrados con mínimos cuadrados recursivos en la sintonización del crítico y descenso del gradiente en la sintonización del actor, el mejor resultado para este esquema es usando el algoritmo de iteración de valor para la solución de la ecuación de Bellman, con un resultado significativo en términos de precisión en comparación a los valores óptimos (función DLQR). Cuando se tiene desconocimiento de la dinámica se usa el algoritmo Q-learning en entrenamiento continuo, con el esquema de mínimos cuadrados con mínimos cuadrados recursivos y el esquema de mínimos cuadrados con descenso del gradiente. Ambos esquemas usan el algoritmo de iteración de política para la solución de la ecuación de Bellman, y se obtienen resultados de aproximadamente 0.001 en la medición del error cuadrático medio. Se realiza una prueba de adaptabilidad considerando variaciones que puedan suceder en los parámetros de la planta, siendo el esquema de mínimos cuadrados con mínimos cuadrados recursivos el que tiene los mejores resultados, reduciendo significativamente ...

Reinforcement learning is a machine learning paradigm with extensive development and growing demand in decision-making and control applications. This technique allows the design of controllers that do not directly depend on the model describing the system dynamics. It is useful in real-world applications, where accurate models are often unavailable. The objective of this work is to implement a modelfree discrete-time optimal controller. Through discrete models, we implemented reinforcement learning algorithms focused on systems with continuous state and action spaces. The concepts of value-function, Q-function, V -function, and the Bellman equation are employed to solve the linear quadratic regulator problem for a mass-spring-damper system in a partially known and utterly unknown model. For both cases, the value functions are explicitly defined by a parametric approximator’s structure, where the weight vector is tuned through an iterative parameter estimation process. When partial knowledge of the dynamics is available, the temporal difference learning method is used under episodic training, utilizing the least squares with a recursive least squares scheme for tuning the critic and gradient descent for the actor´s tuning. The best result for this scheme is achieved using the value iteration algorithm for solving the Bellman equation, yielding significant improvements in approximating the optimal values (DLQR function). When the dynamics are entirely unknown, the Q-learning algorithm is employed in continuous training, employing the least squares with recursive least squares and the gradient descent schemes. Both schemes use the policy iteration algorithm to solve the Bellman equation, and the system’s response using the obtained values was compared to the one using the theoretical optimal values, yielding approximately zero mean squared error between them. An adaptability test is conducted considering variations that may occur in plant parameters, with the least squares with recursive least squares scheme yielding the best results, significantly reducing the number of iterations required for convergence to optimal values.

aprendizaje por refuerzo, control óptimo, control adaptativo, sistemas mecánicos, libre de modelo, dinámica totalmente desconocida, aproximación paramétrica, Q-learning, iteración de política reinforcement learning, optimal control, adaptive control, mechanical systems, modelfree, utterly unknown dynamics, parametric approximation, Q-learning, policy iteration INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL