Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

Habitat quality,not habitat amount,drives mammalian habitat use in the Brazilian Pantanal

Landscape Ecology - An understanding of species-habitat relationships is required to assess the impacts of habitat fragmentation and degradation. To date, habitat modeling in fragmented landscapes...     

Contrasting edge and pasture matrix effects on ant diversity from fragmented landscapes across multiple spatial scales

Landscape Ecology - Harmful effects of habitat loss and fragmentation can be detected across multiple spatial scales, yet most studies that aim to characterize these effects take place at a single...     

Landscape composition is the major driver of the taxonomic and functional diversity of tropical frugivorous birds

Landscape Ecology - Anthropogenic land use and cover changes impact biodiversity worldwide. However, ecological groups are differently affected by landscape composition and configuration....     

Proximal sensor-enhanced soil mapping in complex soil-landscape areas of Brazil

Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO₂ contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.     

Inheritance of Aluminum Tolerance and its Effects on Grain Yield and Grain Quality in Oats (Avena Sativa L.)

Summary Aluminum toxicity due to the cation Al⁺³ is a major factor limiting yields in acid soils. Wide genetic variability to aluminum tolerance is found in oat genotypes. The objectives of this study were to determine the number of genes controlling aluminum tolerance in oats and to verify if any detrimental effects were present of the aluminum tolerance genes on grain yield and grain quality in Al⁺³free soils. Aluminum tolerance was estimated as the average regrowth of the main root after exposure to toxic levels of Al⁺³ in a hydroponic solution under controlled conditions. The number of genes controlling that trait was estimated from the distribution of the average root regrowth frequencies in a population of 333 recombinant inbred lines (RIL's) in generations F_5:6 and F_5:7. The effects on grain yield and grain quality were assessed in a subpopulation of 162 RIL's chosen based on their aluminum tolerance response. Aluminum tolerance in the evaluated population was controlled by one dominant major gene with the tolerant genotypes carying Al _a Al _a and the sensitive ones al _a al _a alleles. No detrimental effects of the Al _a allele on grain yield or grain quality were detected.Part of the Master of Science dissertation of the first author     

Genetic divergence among gerbera accessions evaluated by RAPD

Genetic diversity was evaluated by RAPD markers and morpho-agronomic characters for a total of 42 accessions of Barberton daisy (Gerbera jamesonii) consisting of 29 commercial and 13 wild accessions. A total of 74 polymorphic bands were obtained employing a set of 12 primer pairs. The average genetic similarity coefficient for the 42 accessions, evaluated by Jaccard index was 0.55 ranging from 0.28 to 1.00. The genetic structure found among Barberton daisy accessions was evaluated by hierarchic classification analyses and UPGMA modeling, revealing six clusters of genotypes where two of them include the wild accessions and the remaining four including commercial material, except for wild genotype number 9. Shannon (H′) index was calculated using the molecular markers to investigate the genetic variation among the Gerbera accessions and showed higher values for the commercial cluster in comparison to the values obtained for the individuals from the non-commercial cluster, namely 0.34 versus 0.27, respectively. Therefore, both calculated indices (Jaccard and Shannon) indicated the presence of higher genetic variation among commercial accessions in comparison to the cluster representing non-commercial accessions, suggesting that genetic breeding programs may focus on commercial accessions to recombine interesting genotypes with commercially important and marketing-desired characteristics.     

Nutrient Digestibility of Cereal Grain Products and By‐products in Extruded Diets for Nile Tilapia

Apparent digestibility coefficients (ADCs) provide estimates of nutrient availability in feedstuffs and can be used as a tool for selecting ingredients to compound cost‐effective diets for fish. Extrusion process is one factor that could influence ADC values. Thus, a digestibility trial was undertaken to evaluate ADC of protein, energy, and dry matter, and apparent amino acid availability (AAAA) in five cereal grain products/by‐products (corn, wheat middlings, broken rice, rice bran, and sorghum) in compounded diets for Nile tilapia. Chromic oxide was used as an external inert marker. The digestibility values of energy and dry matter in ingredients, in decreasing order, were highest for broken rice (95.34 and 96.45%), sorghum (82.37 and 87.29%), corn (67.34 and 82.21%), rice bran (57.58 and 55.59%), and wheat middlings (48.94 and 45.88%). Protein digestibility value was higher for corn (72.86%) and the lowest value was observed for sorghum (56.77%), while broken rice, wheat middlings, and rice bran presented values ranging from 63.01 to 66.88%. AAAA values were higher for corn (70.05%) and the lowest methionine and cystine availability values were recorded for wheat middlings and broken rice, respectively. Broken rice appears as one of the most indicated ingredient for using in Nile tilapia diets because of its highest values of nutrient digestibility when compared to the other energetic sources. The use of this information should aid more precise and economic diet formulation for Nile tilapia.     

Genetics and molecular mapping of the naked grains in hexaploid oat

Avena sativa L. subsp. nudisativa has the ability to produce naked grains. Genetic studies on the naked trait of oat began over a century ago, but the genetic and molecular factors associated with the expression of this trait have not been fully clarified. The objectives of this study were to evaluate the naked trait in two oat populations of recombinant inbred lines (RILs), to determine the number of genes, to estimate the heritability, and to map genomic regions associated with the naked trait in hexaploid oat. Parental lines and RILs of each population were screened for the naked trait from plants grown in the field over a 2 year period. Based on the phenotypic data, the oat RILs were classed as naked, partially naked, partially hulled and hulled. In both populations and years, a great number of RILs showed variable expressivity for the naked trait. The genetic analysis indicated the action of a major gene (N1) with the action of modifying genes controlling the formation of naked grains. The results of the estimate of heritability show that environmental conditions do not have a great influence in determining the naked trait. The quantitative trait loci analysis detected a genomic region with a large effect on the naked trait that explained more than 50% of the phenotypic variation. Further studies are needed to validate the use of these molecular markers to assist breeding programs to select high quality and stable naked oat cultivars.