Biology subjects

Perez-Rodriguez, P.

Publications and source records attributed to Perez-Rodriguez, P..

3 recordsLinked to original sources

bioRxiv2020

Genomic Prediction with Genotype by Environment Interaction Analysis for Kernel Zinc Concentration in Tropical Maize Germplasm

Zinc (Zn) deficiency is a major risk factor for human health, affecting about 30% of the worlds population. To study the potential of genomic selection (GS) for maize with increased Zn concentration, an association panel and two doubled haploid (DH) populations were evaluated in three environments. Three genomic prediction models, M (M1: Environment + Line, M2: Environment + Line + Genomic, and M3: Environment + Line + Genomic + Genomic x Environment) incorporating main effects (lines and genomic) and the interaction between genomic and environment (G x E) were assessed to estimate the prediction ability (rMP) for each model. Two distinct cross-validation (CV) schemes simulating two genomic prediction breeding scenarios were used. CV1 predicts the performance of newly developed lines, whereas CV2 predicts the performance of lines tested in sparse multi-location trials. Predictions for Zn in CV1 ranged from -0.01 to 0.56 for DH1, 0.04 to 0.50 for DH2 and -0.001 to 0.47 for the association panel. For CV2, rMP values ranged from 0.67 to 0.71 for DH1, 0.40 to 0.56 for DH2 and 0.64 to 0.72 for the association panel. The genomic prediction model which included G x E had the highest average rMP for both CV1 (0.39 and 0.44) and CV2 (0.71 and 0.51) for the association panel and DH2 population, respectively. These results suggest that GS has potential to accelerate breeding for enhanced kernel Zn concentration by facilitating selection of superior genotypes.

genetics↗

bioRxiv2019

Pontoscolex corethrurus: a Homeless Invasive Tropical Earthworm?

The presence of earthworm species in crop fields is as old as agriculture itself. The earthworms Pontoscolex corethrurus (invasive) and Balanteodrilus pearsei (native) are associated with the emergence of agriculture and sedentism in the region Amazon and Maya, respectively. Both species have shifted their preference from their natural habitat to the cropland niche; however, they contrast in terms of intensification of agricultural land use (anthropic impact to the symbiotic soil microbiome). P. corethrurus inhabits conventional agroecosystems (pesticides, herbicides, and fertilizers are applied to soil), while B. pearsei thrives in traditional agroecosystems (biological management of soil); that is, P. corethrurus has not yet been recorded in soils where B. pearsei dwells. The demographic behavior of these two earthworm species was assessed in the laboratory over 100 days, according to their origin (OE; P. corethrurus and B. pearsei) food quality (FQ; soil only, maize stubble, and Mucuna pruriens), and soil moisture (SM; 25, 33, and 42%). The results showed that OE, FQ, SM, and the OE x FQ interaction were highly significant for the survival, growth, and reproduction of earthworms. P. corethrurus showed a lower survival rate (> mortality). P. corethrurus survivors fed a diet of low-to-intermediate nutritional quality (soil and corn stalks, respectively) showed a greater capacity to grow and reproduce; however, it was surpassed by the native earthworm when fed a high-quality diet (M. pruriens). Besides, P. corethrurus displayed a low cocoon hatching (emergence of juveniles). These results suggest that the presence of the invasive species was associated with the absence of natural mutualistic bacteria (gut, nephridia, and cocoons), and with a negative interaction with the soil microbiota where the native species dwells. These results are consistent with the absence of P. corethrurus in milpa and pasture-type agricultural niches managed by peasants (agroecologists) to grow food regularly a biological management of soil. The results reported here and the published information jointly (e.g., designation of the neotype and ambiguity of the place of origin) jointly suggest that P. corethrurus is an invasive species that is neither wild nor domesticated, that is, its eco-evolutionary phylogeny needs to be derived based on its symbionts.

ecology↗

bioRxiv2018

Use of Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

Hyperspectral reflectance phenotyping and genomic selection are two emerging technologies that have the potential to increase plant breeding efficiency by improving prediction accuracy for grain yield. Hyperspectral cameras quantify canopy reflectance across a wide range of wavelengths that are associated with numerous biophysical and biochemical processes in plants. Genomic selection models utilize genome-wide marker or pedigree information to predict the genetic values of breeding lines. In this study, we propose a multi-kernel GBLUP approach to genomic selection that uses genomic marker-, pedigree-, and hyperspectral reflectance-derived relationship matrices to model the genetic main effects and genotype x environment (G x E) interactions across environments within a bread wheat (Triticum aestivum L.) breeding program. We utilized an airplane equipped with a hyperspectral camera to phenotype five differentially managed treatments of the yield trials conducted by the Bread Wheat Improvement Program, International Maize and Wheat Improvement Center (CIMMYT) at Ciudad Obregon, Mexico over four breeding cycles. We observed that single-kernel models using hyperspectral reflectance-derived relationship matrices performed similarly or superior to marker-and pedigree-based genomic selection models when predicting within and across environments. Multi-kernel models combining marker/pedigree information with hyperspectral reflectance phentoypes had the highest prediction accuracies; however, improvements in accuracy over marker-and pedigree-based models were marginal when correcting for days to heading. Our results demonstrates the potential of hyperspectral imaging in predicting grain yield within a multi-environment context, it also supports further studies on integration of hyperspectral reflectance phenotyping in breeding programs.

genomics↗