Investigating the persistence of accuracy of genomic predictions over time in broilers

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2; on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of data, and a decrease of ~7% was observed when the training population included only 1 year of data. Training sets including genomic information provided an increase in accuracy and persistence of genomic predictions compared with training sets without genomic data. The two most recent years of pedigree, phenotypic, and genomic data were sufficient to maintain prediction accuracies in selection candidates. Similar conclusions were obtained using validation populations per year.     

A selective, sensitive, and rapid in-field assay for soil catechin, an allelochemical of Centaurea maculosa

Centaurea maculosa is a plant species native to Eurasia and invasive in many regions of North America that secretes a phytotoxin from its roots, (+/−)-catechin, which is thought to serve an allelopathic role by reducing fitness of neighboring species. However, catechin is a relatively unstable compound, is often found at relatively low concentrations, interacts with soil cations to form insoluble complexes and/or degradation products, and exhibits extremely variable accumulation patterns in the soil. These factors, coupled with a lack of knowledge of the regulation of catechin production by C. maculosa, confound our understanding of the importance of catechin as an allelochemical. The time and cost of current sampling procedures effectively limit the observations made on catechin accumulation patterns, without which it is extremely difficult to conclusively attribute allelopathic significance to this compound. Thus, a highly sensitive, fast, inexpensive and reliable method for soil catechin analysis is needed. We report a novel method that utilizes the colorimetric reagent dimethylaminocinnamaldehyde (DMACA) in an acidic ethanol solution for detection of soil catechin. This method is selective and extremely sensitive and can be used in the field for qualitative, but not quantitative, analysis. This assay will allow for a greater understanding of the role of catechin as an allelochemical.     

Rhizobia phylogenetically related to common bean symbionts Rhizobium giardinii and Rhizobium tropici isolated from peanut nodules in Central Argentina

Our previous studies of the native rhizobial population associated with peanut nodules in the Córdoba soils of Argentina revealed that this population is highly diverse and includes slow- and fast-growing isolates. The native fast-growing isolates NCHA22 and NET30 were selected on the basis of their plant growth promoting properties and their chromosomal genotypes were determined by 16S rDNA sequencing. NCHA22 and NET30 16S rDNA alleles were found to cluster with those of Rhizobium tropici group IIB and Rhizobium giardinii bv. giardinii strain H152, respectively. We have now characterized these isolates by analyzing the glnA and nifH genes to clarify their taxonomic position. These studies confirmed that fast-growing isolates belonging to species earlier described as bean symbionts were obtained from nodules of a leguminous plant that has been described as efficiently nodulated exclusively by slow-growing rhizobial strains.     

An Approach to Air Pollution Source–Receptor Solution by Angular Distances

This study presents the analysis of two series of concentrations of airborne particulate matter (APM) collected in two exploratory campaigns aimed at elucidating the source–receptor problem (SRP) in the metropolitan area of Buenos Aires. Although several techniques have been previously applied to interpret these measurements, we have almost exclusively used here the method of angular distances among objects (ADO) to discuss its advantages as a tool in understanding environmental questions within the source–receptor framework. We present a simple method of calculating the ADO, explain its chemical interpretation and the information that is possible to get by classifying the angular distances. A comparison among ADO with principal component analysis and Kohonen artificial neural networks is also discussed.     

Interrelations of vegetal cover,silicophytolith content and pedogenesis of Typical Argiudolls of the Pampean Plain,Argentina

Knowledge of the origin, evolution and weathering of Pampean soils is still limited. There are few prior studies of silicophytoliths, even though they could be important pedogenetic indicators that provide information about the role of amorphous silica in the reestablishment of soil structure. The aim of this work is to determine the silicophytolith content in Typical Argiudolls of the Pampean Plain, Argentina, its relation with vegetal cover and its effect on pedogenesis. We worked in three plots with different vegetal cover: grasses and shelter-belt plantations of Acacia melanoxylon – Celtis tala and Eucalyptus globulus – Celtis tala. In the study area, morphological characterization and particle size distribution analysis of soils were completed, and pH and organic matter content were determined. The heavy liquid separation was realized with sodium polytungstate (δ = 2.3 g/cm³) and an average of around 500 mineral grains were counted under optical microscope for the quali-quantitative analysis. There were no differences between profiles with respect to their morphological properties, organic matter content and particle size distribution, except for the higher organic horizon development of the forest plots as compared with the grass plot. The silicophytolith content was higher in the forest plots than in the grass one; within each profile, this fraction content decreased from the surface (63–40%) to the subsurface levels (23–5%) of soils. This decrease parallels the pieces of amorphous silica (< 7.5 μm) distribution in all plots analyzed. Afforestation over the past 50 years does not affect either the morphological or the physico-chemical properties of soils. These forest species, through the organic horizons, preserve soil conditions, which insures a higher representativity of silicophytoliths in comparison with the grass plot.     

Classification of Peruvian highland maize races using plant traits

The maize of Latin America, with its enormous diversity, has played an important role in the development of modern maize cultivars of the American continent. Peruvian highland maize shows a high degree of variation stemming from its history of cultivation by Andean farmers. Multivariate statistical methods for classifying accessions have become powerful tools for classifying genetic resources conservation and the formation of core subsets. This study has two objectives: (1) to use a numerical classification strategy for classifying eight Peruvian highland races of maize based on six vegetative traits evaluated in two years and (2) to compare this classification with the existing racial classification. The numerical classification maintained the main structure of the eight races, but reclassified parts of the races into new groups (Gi). The new groups are more separated and well defined with a decreasing accession within group × environment interaction. Most of the accessions from G1 are from Cusco Gigante, all of the accessions from G3 (except one) are from Confite Morocho, and all of the accessions from G7 are from Chullpi. Group G2 has four accessions from Huayleño and four accessions from Paro, whereas G4 has four accessions from Huayleño and five accessions from San Geronimo. Group G5 has accessions from four races, and G6 and G8 formed small groups with two and one accession each, respectively. These groups can be used for forming core subsets for the purpose of germplasm enhancement and assembling gene pools for further breeding.     

Dietary Photoprotective Compounds Ameliorate UV Tolerance in Shrimp (Pleoticus muelleri) through Induction of Antioxidant Activity

The aim of this study was to determine the effects of ultraviolet radiation (UVR) on bioaccumulation of UV‐absorbing compounds acquired through the diet, in larvae and postlarvae of Pleoticus muelleri, and to assess tissue antioxidant activity, survival, and development. Mysis stage I were exposed to two artificial radiation treatments: M‐PAR (photosynthetically active radiation, range = 400–700 nm) and M‐PAR + UVR (280–700 nm). The experimental larvae received a mixed dietary treatment of Artemia persimilis and the microalga Pavlova lutheri, reared under two radiation regimes: PAR (D‐PAR) and PAR + UVR (D‐PAR + UVR). Shrimp from all treatments reached 8 d postlarval stage (PL8), except those under M‐PAR + UVR treatment fed the D‐PAR‐cultured algae, which had 0% survival. Larvae in M‐PAR + UVR and M‐PAR treatments fed with D‐PAR + UVR diet presented the highest survival rates (70 and 75%, respectively), with 37 and 41% increase in PL size. UV‐absorbing compounds were detected in microalgae and PL subject to PAR + UVR treatments. Antioxidant activity, quantified by measuring the free‐radical 1,1‐diphenyl‐2‐picrylhydrazyl in homogenates of PL8, decayed drastically under radiation treatment M‐PAR + UVR fed with algae of the D‐PAR + UVR treatment. It is concluded that the bioaccumulation of UV‐absorbing compounds and the highest antioxidant activity in PL could improve the biochemical and photophysiological responses of shrimp under UVR stress.