Pedro Revilla

Bio: Pedro Revilla is an academic researcher from Spanish National Research Council. The author has contributed to research in topics: Population & Sesamia nonagrioides. The author has an hindex of 25, co-authored 135 publications receiving 2524 citations.

Short-term effects of organic and inorganic fertilizers on soil microbial community structure and function

Abstract: A field study was carried out to analyze the short-term impacts of replacing mineral by organic fertilizers on the microbial and biochemical parameters relevant for soil fertility and crop yield. Three types of fertilization regimes were compared: (1) conventional fertilizer regime with inorganic fertilizer, and combined integrated fertilizer regimes in which 25 % of the nutrients were supplied by either (2) rabbit manure or (3) vermicompost. The effects on microbial community structure and function (phospholipid fatty acid [PLFA] profiles, bacterial growth, fungal growth, basal respiration, β-glucosidase, protease and phosphomonoesterase activities), soil biochemical properties (total C, dissolved organic carbon [DOC], N-NH4 +, N-NO3 −, PO4, total K) and crop yield were investigated in the samples collected from the experimental soil at harvest, 3 months after addition of fertilizer. The integrated fertilizer regimes stimulated microbial growth, altered the structure of soil microbial community and increased enzyme activity relative to inorganic fertilization. Bacterial growth was particularly influenced by the type of fertilizer regime supplied, while fungal growth only responded to the amount of fertilizer provided. The use of manure produced a fast increase in the abundance of PLFA biomarkers for Gram-negative bacteria as compared to inorganic fertilizer. Nutrient supply and crop yield with organic fertilizers were maintained at similar levels to those obtained with inorganic fertilizer. The effects of the organic amendments were observed even when they involved a small portion of the total amount of nutrients supplied; thereby confirming that some of the beneficial effects of integrated fertilizer strategies may occur in the short term.

Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds ( Zea mays L.)

Abstract: Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix–best linear unbiased predictions model (RA–BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.

Intraspecific variation of recombination rate in maize

Abstract: In sexually reproducing organisms, meiotic crossovers ensure the proper segregation of chromosomes and contribute to genetic diversity by shuffling allelic combinations. Such genetic reassortment is exploited in breeding to combine favorable alleles, and in genetic research to identify genetic factors underlying traits of interest via linkage or association-based approaches. Crossover numbers and distributions along chromosomes vary between species, but little is known about their intraspecies variation. Here, we report on the variation of recombination rates between 22 European maize inbred lines that belong to the Dent and Flint gene pools. We genotype 23 doubled-haploid populations derived from crosses between these lines with a 50 k-SNP array and construct high-density genetic maps, showing good correspondence with the maize B73 genome sequence assembly. By aligning each genetic map to the B73 sequence, we obtain the recombination rates along chromosomes specific to each population. We identify significant differences in recombination rates at the genome-wide, chromosome, and intrachromosomal levels between populations, as well as significant variation for genome-wide recombination rates among maize lines. Crossover interference analysis using a two-pathway modeling framework reveals a negative association between recombination rate and interference strength. To our knowledge, the present work provides the most comprehensive study on intraspecific variation of recombination rates and crossover interference strength in eukaryotes. Differences found in recombination rates will allow for selection of high or low recombining lines in crossing programs. Our methodology should pave the way for precise identification of genes controlling recombination rates in maize and other organisms.

Relationships among kernel weight, early vigor, and growth in maize

Abstract: Research supported by the Instituto Nacional de Investigation y Tecnologia Agraria y Alimentaria (INIA) of Spain (project Cod. SC93-098) and Excma. Diputacion Provincial de Pontevedra, Spain.

Yield and fruit quality of four sweet corn hybrids (Zea mays) under conventional and integrated fertilization with vermicompost

Abstract: BACKGROUND: Vermicompost has been proposed as a valuable fertilizer for sustainable agriculture. The effects of vermicompost on yield and quality of sweet corn were evaluated in this study. In two field trials, sweet corn plants were grown under (i) a conventional fertilization regime with inorganic fertilizer, and integrated fertilization regimes in which 75% of the nutrients were supplied by the inorganic fertilizer and 25% of the nutrients were supplied by either (ii) rabbit manure, or (iii) vermicompost. All three types of fertilization regime were supplied at two doses. Two pairs of nearly isogenic sweet corn hybrids homozygous for sugary1 and shrunken2 mutants were included in the trials to explore fertilizer × genotype interactions. Growth, yield and ear quality of the plants were evaluated in relation to the three fertilization regimes. RESULTS: In general, the integrated regimes yielded the same productivity levels as the conventional treatment. Moreover, both vermicompost and manure produced significant increases in plant growth and marketable yield, and also affected the chemical composition and quality of the marketable ear. Nevertheless, most of the observed effects of the organic fertilizers were genotype-dependent. CONCLUSION: The results confirm that the use of organic fertilizers such as vermicompost has a positive effect on crop yield and quality. Nevertheless, these effects were not general, indicating the complexity of the organic amendment-plant interactions and the importance of controlling genetic variation when studying the effects of vermicompost on plant growth.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

A User’s Guide

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GGE Biplot vs. AMMI Analysis of Genotype-by-Environment Data

Abstract: The use of genotype main effect (G) plus genotype-by-environment (GE) interaction (G+GE) biplot analysis by plant breeders and other agricultural researchers has increased dramatically during the past 5 yr for analyzing multi-environment trial (MET) data. Recently, however, its legitimacy was questioned by a proponent of Additive Main Effect and Multiplicative Interaction (AMMI) analysis. The objectives of this review are: (i) to compare GGE biplot analysis and AMMI analysis on three aspects of genotype-by-environment data (GED) analysis, namely mega-environment analysis, genotype evaluation, and test-environment evaluation; (ii) to discuss whether G and GE should be combined or separated in these three aspects of GED analysis; and (iii) to discuss the role and importance of model diagnosis in biplot analysis of GED. Our main conclusions are: (i) both GGE biplot analysis and AMMI analysis combine rather than separate G and GE in mega-environment analysis and genotype evaluation, (ii) the GGE biplot is superior to the AMMI1 graph in mega-environment analysis and genotype evaluation because it explains more G+GE and has the inner-product property of the biplot, (iii) the discriminating power vs. representativeness view of the GGE biplot is effective in evaluating test environments, which is not possible in AMMI analysis, and (iv) model diagnosis for each dataset is useful, but accuracy gain from model diagnosis should not be overstated.

Bacterial diversity in soils subjected to long-term chemical fertilization can be more stably maintained with the addition of livestock manure than wheat straw

Abstract: Addition of organic matter such as livestock manures and plant residues is a feasible practice to mitigate soil degradation caused by long-term application of chemical fertilizers, and the mitigation is largely mediated though activities of the soil-dwelling microorganisms. However, the roles of different kinds of organic matter in maintaining bacterial community structure have not been assessed in a comparative manner. In this study, 454 pyrosequencing of 16S rRNA gene was employed to compare the bacterial community structure among soils that had been subjected to 30 years of NPK fertilization under six treatment regimes: non-fertilization control, fertilization only, and fertilization combined with the use of pig manure, cow manure or low- and high-level of wheat straws. Consistent with expectation, long-term application of NPK chemical fertilizers caused a significant decrease of bacterial diversity in terms of species richness (i.e. number of unique operational taxonomic units (OTU)), Faith's index of phylogenetic diversity and Chao 1 index. Incorporation of wheat straw into soil produced little effects on bacterial community, whereas addition of either pig manure or cow manure restored bacterial diversity to levels that are comparable to that of the non-fertilization control. Moreover, bacterial abundance determined by quantitative PCR was positively correlated with the nutritional status of the soil (e.g., nitrate, total nitrogen, total carbon, available phosphorus); however, bacterial diversity was predominantly determined by soil pH. Together, our data implicate the role of livestock manures in preventing the loss of bacterial diversity during long-term chemical fertilization, and highlight pH as the major deterministic factor for soil bacterial community structure.