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SERGIO GARCIA LAYNES VIRGINIA AURORA HERRERA VALENCIA Lilia Guadalupe Tamayo Torres VERONICA LIMONES BRIONES FELIPE ALONSO BARREDO POOL FRAY MARTIN BAAS ESPINOLA Ángel Gabriel Alpuche Solís CARLOS ALBERTO PUCH HAU SANTY PERAZA ECHEVERRIA (2022, [Artículo])
"WRKY transcription factors (TFs) play key roles in plant defense responses through phytohormone signaling pathways. However, their functions in tropical fruit crops, especially in banana, remain largely unknown. Several WRKY genes from the model plants rice (OsWRKY45) and Arabidopsis (AtWRKY18, AtWRKY60, AtWRKY70) have shown to be attractive TFs for engineering disease resistance. In this study, we isolated four banana cDNAs (MaWRKY18, MaWRKY45, MaWRKY60, and MaWRKY70) with homology to these rice and Arabidopsis WRKY genes. The MaWRKY cDNAs were isolated from the wild banana Musa acuminata ssp. malaccensis, which is resistant to several diseases of this crop and is a progenitor of most banana cultivars. The deduced amino acid sequences of the four MaWRKY cDNAs revealed the presence of the conserved WRKY domain of ~60 amino acids and a zinc-finger motif at the N-terminus. Based on the number of WRKY repeats and the structure of the zinc-finger motif, MaWRKY18 and MaWRKY60 belong to group II of WRKY TFs, while MaWRKY45 and MaWRKY70 are members of group III. Their corresponding proteins were located in the nuclei of onion epidermal cells and were shown to be functional TFs in yeast cells. Moreover, expression analyses revealed that the majority of these MaWRKY genes were upregulated by salicylic acid (SA) or methyl jasmonate (MeJA) phytohormones, although the expression levels were relatively higher with MeJA treatment. The fact that most of these banana WRKY genes were upregulated by SA or MeJA, which are involved in systemic acquired resistance (SAR) or induced systemic resistance (ISR), respectively, make them interesting candidates for bioengineering broad-spectrum resistance in this crop."
Banana Transcription factor WRKY Defense phytohormones Salicylic acid Methyl jasmonate SAR ISR Broad-spectrum resistance BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA GENÉTICA
Maraeva Gianella Daniele Dondi Andreas Börner Anca Macovei Andrea Pagano Filippo Guzzon Alma Balestrazzi (2022, [Artículo])
Thermogravimetry CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CARBOHYDRATES PROLINE TOCOPHEROLS GENETICS PHYSIOLOGY PEAS SEEDS SUGARS DIFFERENTIAL SCANNING CALORIMETRY SEED LONGEVITY THERMOGRAVIMETRIC ANALYSIS
Genome-based predictions of sub-genome genetic interactions effects in wheat populations
David González-Diéguez (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOMES WHEAT GENETICS MARKER-ASSISTED SELECTION GENETIC VARIANCE HYBRIDS
Genomic prediction of hybrid crops accounting for non additive genetic effects
David González-Diéguez (2022, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MARKER-ASSISTED SELECTION HYBRIDS MAIZE GENOMES GENETICS GENETIC VARIANCE CROPS
Vijay Gahlaut Vandana Jaiswal Pushpendra Kumar Gupta (2019, [Artículo])
Genome-Wide Association Study Marker-Trait Associations CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC LINKAGE GENETICS PROCEDURES QUANTITATIVE TRAIT LOCI WHEAT CHROMOSOME MAPPING
Genomic regions associated with resistance to three rusts in CIMMYT wheat line “Mokue#1”
Naeela Qureshi Ravi Singh sridhar bhavani (2023, [Artículo])
Genetic Analysis Leaf Rust CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETICS RUSTS QUANTITATIVE TRAIT LOCI MAPPING DISEASE RESISTANCE STRIPE RUST STEM RUST
Hari Sankar Nayak C.M. Parihar Shankar Lal Jat ML JAT Ahmed Abdallah (2022, [Artículo])
Non-Linear Growth Model Nitrogen Remobilization Right Placement Precision Nitrogen Management CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GROWTH MODELS NITROGEN NUTRIENT MANAGEMENT
Algorithmic differentiation of linear mixed models with variance-covariance structures
Fernando Henrique Toledo Jose Crossa Juan Burgueño Keith Gardner Rosa Angela Pacheco Gil (2023, [Objeto de congreso])
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MATHEMATICAL MODELS ALGORITHMS LINEAR MODELS
Timothy Joseph Krupnik Jeroen Groot (2024, [Artículo])
We investigated alternative cropping and feeding options for large (>10 cows), medium (5–10 cows) and small (≤4 cows) mixed crop – livestock farm types, to enhance economic and environmental performance in Jhenaidha and Meherpur districts – locations with increasing dairy production – in south western Bangladesh. Following focus group discussions with farmers on constraints and opportunities, we collected baseline data from one representative farm from each farm size class per district (six in total) to parameterize the whole-farm model FarmDESIGN. The six modelled farms were subjected to Pareto-based multi-objective (differential evolution algorithm) optimization to generate alternative dairy farm and fodder configurations. The objectives were to maximize farm profit, soil organic matter balance, and feed self-reliance, in addition to minimizing feed costs and soil nitrogen losses as indicators of sustainability. The cropped areas of the six baseline farms ranged from 0.6 to 4.0 ha and milk production per cow was between 1,640 and 3,560 kg year−1. Feed self-reliance was low (17%–57%) and soil N losses were high (74–342 kg ha−1 year−1). Subsequent trade-off analysis showed that increasing profit and soil organic matter balance was associated with higher risks of N losses. However, we found opportunities to improve economic and environmental performance simultaneously. Feed self-reliance could be increased by intensifying cropping and substituting fallow periods with appropriate fodder crops. For the farm type with the largest opportunity space and room to manoeuvre, we identified four strategies. Three strategies could be economically and environmentally benign, showing different opportunities for farm development with locally available resources.
Ruminant Feed Pareto-Based Optimization Farm Bioeconomic Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUMINANT FEEDING BIOECONOMIC MODELS MIXED CROPPING FARMS LIVESTOCK