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Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

Whole-genome comparison between reference sequences and oyster Vibrio vulnificus C-genotype strains

CARLOS ABRAHAM GUERRERO RUIZ (2019, [Artículo])

Whole-genome sequences of Vibrio vulnificus clinical genotype (C-genotype) from the CICESE Culture Collection, isolated from oysters, were compared with reference sequences of CMCP6 and YJ016 V. vulnificus C-genotype strains of clinical origin. The RAST web server estimated the whole genome to be ~4.8 Mb in CICESE strain 316 and ~4.7 Mb in CICESE strain 325. No plasmids were detected in the CICESE strains. Based on a phylogenetic tree that was constructed with the whole-genome results, we observed high similarity between the reference sequences and oyster C-genotype isolates and a sharp contrast with environmental genotype (E-genotype) reference sequences, indicating that the differences between the C- and E-genotypes do not necessarily correspond to their isolation origin. The CICESE strains share 3488 genes (63.2%) with the YJ016 strain and 3500 genes (63.9%) with the CMCP6 strain. A total of 237 pathogenicity associated genes were selected from reference clinical strains, where—92 genes were from CMCP6, 126 genes from YJ016, and 19 from MO6-24/ O; the presence or absence of these genes was recorded for the CICESE strains. Of the 92 genes that were selected for CMCP6, 67 were present in both CICESE strains, as were as 86 of the 126 YJ016 genes and 13 of the 19 MO6-24/O genes. The detection of elements that are related to virulence in CICESE strains—such as the RTX gene cluster, vvhA and vvpE, the type IV pili cluster, the XII genomic island, and the viuB genes, suggests that environmental isolates with the C-genotype, have significant potential for infection. © 2019 Guerrero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Article, bacterial gene, bacterial strain, bacterial virulence, comparative study, controlled study, gene cluster, gene identification, genomic island, genotype, nonhuman, phylogenetic tree, sequence analysis, strain identification, Vibrio vulnificus BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA GENÉTICA

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Evaluación del acondicionamiento reproductivo del ostión japonés (Magallana gigas) en dos sistemas de recirculación con prevalencia de polidóridos mediante la expresión de genes

Evaluation of Japanese oyster (Magallana gigas) broodstock conditioning in two recirculating systems with the prevalence of Polidorids through gene expression

Adrián Andrés Morales Guadarrama (2024, [Tesis de maestría])

El ostión Magallana gigas es ampliamente cultivado a nivel mundial. En Baja California, México, los laboratorios de reproducción deben acondicionar ostiones para su maduración y producción de gametos, y abastecer de semilla a los productores. En nuestro laboratorio, Sistemas de Recirculación Acuícola (SRA), con control del sistema CO2-Carbonatos (SRA-R) o sin control (SRA-C), han permitido madurar ostiones M. gigas y M. sikamea. Recientemente, los ostiones M. gigas acondicionados en nuestros SRA no maduraron, y algunos presentaron prevalencia de polidóridos (PP), poliquetos parásitos excavadores de concha. Para comprender la condición de los ostiones, evaluamos el efecto del SRA y de la PP sobre la expresión relativa de ocho genes asociados a biomineralización (VpATP y Tyr), inmunidad innata (P38, PGRP-L y TLR2) y reproducción (GnRH-RI, Vasa-like y SP1b) de M. gigas en dos etapas del acondicionamiento, 18 °C y 24 °C. La PP se determinó por la presencia de ampollas en la concha. Mediante RT-qPCR se determinó la expresión de VpATP, Tyr, P38, PGRP-L y TLR2 en el manto, y de GnRH-RI, Vasa-like y SP1b en la gónada. La expresión relativa se evaluó con un enfoque estadístico basado en un análisis Bayesiano de dos vías y comparaciones múltiples, p-valor significativo < 0.05 y corrección de Bonferroni. En 18 °C, la expresión de VpATP, Tyr, TLR2 y P38 fue mayor en ostiones con PP (CPP) que sin PP (SPP). En contraste, la expresión de GnRH-RI, Vasa-like y SP1b fue menor CPP que SPP. Dentro del SRA-C, en los ostiones CPP hubo mayor expresión de Tyr y menor expresión de Vasa-like y SP1b, respecto a los ostiones SPP. Esto sugiere que la PP induce la reparación de la concha y las respuestas inmune e inflamatoria en el manto mientras que en la gónada reduce el desarrollo de las células germinales. En 24 °C, en el SRA-R hubo menor expresión de SP1b respecto del SRA-C y sugiere menor división celular en la gónada. En conclusión, el SRA-R y la PP afectaron el balance energético del ostión japonés, limitando la energía y reflejando menor esfuerzo reproductivo en los ostiones del SRA-R al final del acondicionamiento reproductivo.

The Japanese oyster (Magallana gigas) is highly cultured worldwide. In Baja California, Mexico, the reproduction laboratories must condition oysters to maturity and have gametes to supply oyster seeds to producers. In our laboratory, recirculating aquaculture systems (RAS), with control of the CO2-Carbonate system (RAS-R) and without this control (RAS-C), have allowed oysters M. gigas and M. sikamea to mature. Recently, the M. gigas oysters conditioned in our RAS did not mature, and some have the prevalence of Polidorids (PP), shell-boring polychaete parasites. To understand the oysters' condition, we evaluated the effect of RAS and the PP on the relative expression of eight genes associated with biomineralization (VpATP and Tyr), innate immunity (P38, PGRP-L, and TLR2), and reproduction (GnRH-RI, Vasa-like, and SP1b) of M. gigas at two phases of broodstock conditioning, 18 °C and 24 °C. The PP was determined by mud blisters at the inner oyster shell. RT-qPCR determined the expression of VpATP, Tyr, p38, PGRP-L, and TLR2 in the mantle tissue and GnRH-RI, Vasa-like, and SP1b in the gonad tissue. The relative gene expression was evaluated by a Bayesian statistics frame based on a two-way and multiple comparison analysis, with significant p-value < 0.05 and Bonferroni correction. At 18 °C, there was higher expression of VpATP, Tyr, TLR2, and P38 in oysters with PP (WPP) than without PP (WOPP). In contrast, the expression of GnRH-RI, Vasa-like, and SP1b was less WPP than WOPP. It suggests that the PP induces shell repair and immune and inflammatory responses in mantle tissue, while in gonad tissue, it reduces the development of germinal cells. At 24 °C, in RAS-R, there was less expression of SP1b respect RAS-C, and it suggests less cellular division in the gonad. In conclusion, the RAS-R and the PP affect the energetic balance of the Japanese oyster, limiting the energy and reflecting less reproduction effort in oysters from RAS-R at the end of broodstock conditioning.

SRA, biomineralización, Vasa-like, Tyr, ostión RAS, biomineralization, Vasa-like, Tyr, oyster BIOLOGÍA Y QUÍMICA CIENCIAS DE LA VIDA GENÉTICA CITOGENÉTICA ANIMAL CITOGENÉTICA ANIMAL