Damaged bone microarchitecture by Trabecular Bone Score (TBS) and low appendicular muscle mass: main risk factors for vertebral and non-vertebral fractures in women with long-standing rheumatoid arthritis

We ascertained the fracture risk factors stratified by vertebral and non-vertebral sites in rheumatoid arthritis (RA) females. Bone/muscle features, but not disease activity, were the main markers for fractures in this long-standing RA population: low trabecular bone score (TBS) for vertebral fracture and decreased appendicular muscle mass for non-vertebral fracture.

PURPOSE

To assess risk factors for fractures, including clinical, laboratory and dual energy X-ray absorptiometry (DXA) parameters (bone mass, trabecular bone score-TBS, muscle mass) in women with established rheumatoid arthritis (RA).

METHODS

Three hundred females with RA (ACR, 2010) were studied. Clinical data were obtained by questionnaire and disease activity by composite indices (DAS28, CDAI, SDAI), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). Bone mineral density (BMD), TBS, body composition and Vertebral Fracture Assessment (VFA) were performed by DXA. Logistic regression models were constructed to identify factors independently associated with vertebral (VF) and non-vertebral fractures (NVF), separately.

RESULTS

Through rigorous eligibility criteria, a total of 265 women were yielded for final data analysis (median age, 55 [22-86] years; mean disease duration, 16.2 years). Prevalence of VF and NVF were 30.6% and 17.4%, respectively. In multivariate analyzes, TBS (OR = 1.6, 95%CI = 1.09-2.36, p = 0.017), CRP (OR = 1.54, 95%CI = 1.15-2.08, p = 0.004), and parathormone (OR = 1.24, 95%CI = 1.05-1.45, p = 0.009) were risk factors for VF, whereas low appendicular muscle mass (OR = 2.71; 95%CI = 1.01-7,28; p = 0.048), body mass index (BMI) (OR = 0.90, 95%CI = 0.82-0.99; p = 0.025), ESR (OR = 1.18, 95%CI = 1.01-1,38, p = 0,038) and hip BMD (OR = 1.82, 95%CI = 1.10-3.03, p = 0.02) were associated with NVF.

CONCLUSION

In women with long-term RA, markers of fractures differed between distinct skeletal sites (vertebral and non-vertebral). The magnitude of association of bone/muscle parameters with fracture (TBS for VF and appendicular muscle mass for NVF) was greater than that of the association between RA activity and fracture. TBS seems to have greater discriminative power than BMD to identify subjects with VF in long-standing RA.

Healthcare-associated infections in high-risk neonates: Temporal trends in a national surveillance system

BACKGROUND

Increased survival of preterm neonates who require hospitalization at the Neonatal Intensive Care Unit has led to an increase in infections. This study aims to describe the temporal trend, risk factors, and outcome of healthcare-associated infections in a NICU of a high complexity hospital, with emphasis on the differences of incidence between bacterial and fungal infections.

METHODS

The study was carried out from January 2013 to December 2016, with daily follow-up of the newborns by the National Healthcare Safety Network.

RESULTS

The study included 881 newborns, of whom 214 had a bacterial infection, 19 had fungi infection, and 12 bacterial and fungal infections associated. The hospital infection rate was 12/1000 patient-days. SNAPPE>24, days of hospitalization and PICC days were independent risk factors for the development of fungal and bacterial infection, respectively, with statistical significance for bacterial and fungal infections. The mortality rate was 2.6 times higher in those who had fungal infection than in those who had a bacterial infection. The occurrence of invasive infections was higher in the years 2015 and 2016 and Gram-negative bacteria and yeasts were more frequent, impacting morbidity and mortality.

CONCLUSIONS

The use of invasive devices is a risk factor for the occurrence of HAI caused by bacteria and fungi. The frequency of deaths was higher in the group of neonates with fungal infection. These results point to the importance of constant epidemiological surveillance and measures of effective control of infections in NICU.

Exploring the use of residual variance for uniformity of body weight in meat quail lines using Bayesian inference

1. Uniformity in animal products is an important aspect of the production system. Several studies have reported estimates of genetics on residual variance in different species, indicating that it could be exploited to improve uniformity by selection. Nevertheless, there are no reports about the possibilities of such a selection strategy in meat quail.2. Records of hatching weight (HW) and body weight at 42 days (W42) of female and male birds from two meat quail lines (UFV1 and UFV2) were analysed. A three-step genetic evaluation was used to investigate the effect of genetic variation on residual variance of HW and W42 in both lines. In Step 1, a single-trait model was fitted to the data. In Step 2, log-transformed squared estimated residuals (ln(ê²)) were evaluated for these traits. In Step 3, a multi-trait analysis was performed to estimate the genetic correlation between the additive genetic effects for HW, W42, and their respective ln(ê²).3. The heritability estimates ranged from 0.12 to 0.23 for HW and from 0.22 to 0.35 for W42. The estimated heritabilities for the residual part were low and ranged from 0.0003 to 0.02 for both traits, and the genetic coefficient of variation residual variance estimates ranged from 0.31 to 0.42 for HW and from 0.09 to 0.25 for W42. Genetic correlations between the means (HW and W42) and ln(ê²) values were both positive and did not differ from zero, indicating no association between mean and ln(ê²).4. In conclusion, the uniformity of HW and W42 could be improved by selecting for lower residual variance in both meat quail lines, but the accuracy of selection may be low due to low heritability for uniformity, mainly for W42.

Genotype by environment interaction for Holstein cattle populations using autoregressive and within- and across-country multi-trait reaction norms test-day models

The progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G×E) within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm (RN) approach was used to investigate the presence of G×E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance for milk yield (MY) in Portugal was 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugal was 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR sire model were 0.78 (0.051) for MY and 0.75 (0.062) for SCS. In step 2, MY genetic correlations among HTD levels within countries were higher than 0.94 for Portugal and 0.98 for Brazil. Somatic cell score genetic correlations among HTD levels ranged from 0.70 to 0.99 for Portugal and from 0.84 to 0.99 for Brazil. The average (SD) of genetic correlation estimates between Portuguese and Brazilian HTD levels were 0.74 (0.009) for MY and 0.57 (0.060) for SCS. These results suggest the presence of G×E for MY and SCS of Holstein cattle between both countries. Although there was no indication of G×E between Brazilian herd environments, the low genetic correlation for SCS indicates potential re-ranking of bulls between extreme environmental gradient in Portugal. Overall, the results of this study evidence the importance of national and international genetic evaluation systems to assist dairy farmers in the selection of the best genotypes to obtain the expected returns from investments in imported semen and to realize genetic progress in dairy populations under local environmental conditions.

Foliar mycoendophytome of an endemic plant of the Mediterranean biome (Myrtus communis) reveals the dominance of basidiomycete woody saprotrophs

The true myrtle, Myrtus communis, is a small perennial evergreen tree that occurs in Europe, Africa, and Asia with a circum-Mediterranean geographic distribution. Unfortunately, the Mediterranean Forests, where M. communis occurs, are critically endangered and are currently restricted to small fragmented areas in protected conservation units. In the present work, we performed, for the first time, a metabarcoding study on the spatial variation of fungal community structure in the foliar endophytome of this endemic plant of the Mediterranean biome, using bipartite network analysis as a model. The local bipartite network of Myrtus communis individuals and their foliar endophytic fungi is very low connected, with low nestedness, and moderately high specialization and modularity. Similar network patterns were also retrieved in both culture-dependent and amplicon metagenomics of foliar endophytes in distinct arboreal hosts in varied biomes. Furthermore, the majority of putative fungal endophytes species were basidiomycete woody saprotrophs of the orders Polyporales, Agaricales, and Hymenochaetales. Altogether, these findings suggest a possible adaptation of these wood-decaying fungi to cope with moisture limitation and spatial scarcity of their primary substrate (dead wood), which are totally consistent with the predictions of the viaphytism hypothesis that wood-decomposing fungi inhabit the internal leaf tissue of forest trees in order to enhance dispersal to substrates on the forest floor, by using leaves as vectors and as refugia, during periods of environmental stress.

Predicting Rice Stem Stink Bug Population Dynamics Based on GAMLSS Models

The rice stem stink bug, Tibraca limbativentris Stål (Hemiptera: Pentatomidae), is one of the most harmful insects for Brazilian rice fields. Aiming to define the most appropriate time and place for pest management measures in commercial paddy fields, we adjusted regression models (Poisson, Zero Inflated Poisson, reparametrized Zero Inflated Poisson, Negative Binomial and Zero Inflated Negative Binomial) for modeling the population variation of T. limbativentris along the phenological cycle of the flooded rice cultivation. We hypothesize that the rice stem stink bug population's size is influenced by the rice cycle (time) and geographical positions within the crop. It was possible to predict the occurrence of the rice stem stink bug in the commercial flooded rice crop. The population of the rice stem stink bug increased significantly with the time or phenological evolution of rice. Our results indicated that the start of T. limbativentris monitoring should occur up to 45 d After Plant Emergence (DAE), from the regions along the edges of the rice paddies, which are the points of entry and higher concentration of the insect. In addition, 45 and 60 DAE were considered the crucial times for T. limbativentris control decision making in flooded rice paddies.

Recent Patents on the Industrial Application of Alpha-amylases

BACKGROUND

Alpha-amylases are enzymes capable of degrading polysaccharides, such as starch and glycogen. Found in various organisms, such as fungi and bacteria, these enzymes have great biotechnological potential due to their insertion in several industrial sectors ranging from food to biofuels.

OBJECTIVE

The aim of this study was to analyze patents deposited in intellectual property databases on alpha-amylases in the fields of food, beverages, detergents, animal feeds, biofuels, pharmaceuticals and textiles, with the search period being 5 years.

METHODS

This study targeted the use of alpha-amylases in various industrial sectors, so searches were carried out on the intellectual property database Espacenet website (European Patent Office - EPO) which contains more than 90 million patents deposited in its database.

RESULTS

During the search for patents filed in the last 5 years, 186 were found related to the use of alpha-amylases. These were disturbed as follows: 84 (biofuel), 41 (drinks), 16 (pharmaceuticals), 15 (detergents), 11 (food), 10 (animal feed), 9 (textiles). From the total number of patents found, we selected 6 from each area, except pharmaceutical products, to discuss and provide information on the application of this enzyme.

CONCLUSION

This study demonstrated that the sectors of beverages and animal feed have preferences for thermostable alpha-amylases while sectors such as food, biofuels and textiles only regarded the importance of enzymatic efficiency. The detergent sector presented the greatest use of alpha-amylases which had distinct biochemical characteristics as solvent resistance and thermostability. The pharmaceutical sector was the one that presented less patents related to the application of alpha amylases. In addition, this work showed that China is the country with the highest patent registration for the use of alpha-amylases in the analyzed period.

Short communication: Genetic parameter estimates for caprine arthritis encephalitis in dairy goats

Caprine arthritis encephalitis (CAE) is a chronic disease caused by a retrovirus from the Lentivirus genus. No effective vaccines or treatments exist, and therefore genetic selection for CAE resistance might be a feasible alternative. To our best knowledge, no other studies have investigated the genetic architecture of CAE resistance in dairy goats. In this context, this study was designed to estimate genetic parameters for CAE infection in Alpine and Saanen goats using a Bayesian threshold model. A total of 542 adult goats (and >3-generation pedigree), which were group-housed in a population with high CAE prevalence, were tested based on a serological infection assessment test (negative = 1 or positive = 2) and used for this study. Genetic parameters were estimated using the BLUPF90 family programs. There was considerable genetic variability for CAE resistance, and pedigree-based heritability was significantly different from zero (0.026 < heritability < 0.128). Our findings indicate that the prevalence of CAE in goat herds can be reduced or eliminated through direct genetic selection for CAE resistance in addition to proper management strategies.

Short communication: Time-dependent genetic parameters and single-step genome-wide association analyses for predicted milk fatty acid composition in Ayrshire and Jersey dairy cattle

Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemical-physical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (medium-chain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNP ranged from 0.71% (saturated FA) to 1.11% (long-chain FA) in Ayrshire, and from 0.70% (unsaturated FA) to 3.09% (medium-chain FA) in Jersey cattle. Important candidate genes and pathways were also identified, such as the PTK2 and TRAPPC9 genes, associated with milk fat percentage, and HMGCS, FGF10, and C6 genes, associated with fertility traits and immune response. Our findings on the genetic parameters and candidate genes contribute to a better understanding of the genetic architecture of milk FA composition in Ayrshire and Jersey dairy cattle.

Genetic evaluation for latent variables derived from factor analysis in broilers

1. The aim of this study was to investigate the associations between several carcass, performance and meat quality traits in broilers through factor analysis and use the latent variables (i.e. factors) as pseudo-phenotypes in genetic evaluations.2. Factors were extracted using the principal components method and varimax rotation algorithm. Genetic parameters were estimated via Bayesian inference under a multiple-trait animal model.3. All factors taken together explained 71% of the original variance of the data. The first factor, denominated as 'weight', was associated with carcass and body weight traits; and the second factor, defined as 'tenderness', represented traits related to water-holding capacity and shear force. The third factor, 'colour', was associated with traits related to meat colour, whereas the fourth, referenced as 'viscera', was related to heart, liver and abdominal fat.4. The four biological factors presented moderate to high heritability (ranging from 0.35 to 0.75), which may confer genetic gains in this population.5. In conclusion, it seems possible to reduce the number of traits in the genetic evaluation of broilers using latent variables derived from factor analysis.

Short communication: Molecular characterization and antimicrobial resistance of pathogenic Escherichia coli isolated from raw milk and Minas Frescal cheeses in Brazil

The aim of this study was to quantify, identify, evaluate antimicrobial resistance, and characterize the virulence factors of enteropathogenic (EPEC), Shiga-toxigenic (STEC), and enterohemorrhagic (EHEC) Escherichia coli in raw milk (RM) and legal (LMFC) and illegal (IMFC) Minas Frescal cheeses in southern and northeast Brazil. Illegal cheeses are those made without official inspection service or sanitary surveillance. We evaluated samples of RM produced in Paraná (southern) and Maranhão (northeast) States, LMFC produced using pasteurized milk in inspected industries, and IMFC potentially produced with raw milk. Mean total coliform counts were 8.4 × 10⁴ cfu/mL for RM, 1.4 × 10⁷ cfu/mL for LMFC, and 2.9 × 10⁷ cfu/mL for IMFC. Mean E. coli counts were 2.4 × 10³ cfu/mL for RM, 1.9 × 10² cfu/mL for LMFC, and 1.1 × 10⁵ cfu/mL for IMFC. Among the 205 E. coli isolates from RM, 9.75% were identified as EPEC, mainly (90%) in samples from Paraná. Of the total isolates from the cheese samples, 97.4% (n = 111) came from IMFC, of which 1.8 and 2.7% were identified as EPEC and STEC, respectively; no EHEC was detected. The phylogenetic group A (60%) and typical EPEC (68%) predominated, which confirms the possible human origin of pathogenic isolates in RM and IMFC. Of these, 50% were resistant to at least one antibiotic, and streptomycin was the antimicrobial with the highest number (8) of EPEC and STEC resistant isolates. This study reports the first isolation of serogroup O28ac in Brazilian milk. We found no predominance of a specific serogroup of EPEC or STEC in milk or cheese or clonal isolates in the same sample, indicating different origins of the contamination in these products, presumably mostly related to poor hygienic handling.

Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.

Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves. To identify important genomic regions related to the analyzed lactation stages, traits, parities and breeds, moving windows (SNP-by-SNP) of 20 adjacent SNP explaining more than 0.30% of total genetic variance were selected for further analyses of candidate genes. A lower number of genomic windows with a relatively higher proportion of the explained genetic variance was found in the Holstein breed compared with the Ayrshire and Jersey breeds. Genomic regions associated with the analyzed traits were located on 12, 8, and 15 chromosomes for the Ayrshire, Holstein, and Jersey breeds, respectively. Especially for the Holstein breed, many of the identified candidate genes supported previous reports in the literature. However, well-known genes with major effects on milk production traits (e.g., diacylglycerol O-acyltransferase 1) showed contrasting results among lactation stages, traits, and parities of different breeds. Therefore, our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the analyzed traits across breeds, parities, and lactation stages. Further functional studies are needed to validate our findings in independent populations.

Characterization of Candida species isolated from the hands of the healthcare workers in the neonatal intensive care unit

Colonization of health professional hands by potentially pathogenic microorganisms capable to expressing virulence factors, such as Candida spp., is worrisome because of the high contact between patients and professionals. The study aims to evaluate, in vitro, the following virulence factors: hemolytic activity, DNAse expression, biofilm formation, and susceptibility for antifungal agents of Candida species isolated from health professionals hands of a neonatal intensive care unit (NICU). The study includes 50 isolates of Candida spp.: 19 C. parapsilosis sensu stricto, three C. metapsilosis, one C. orthopsilosis, seven C. albicans, six C. famata, five C. lusitaniae, three C. krusei, two C. kefyr, two C. tropicalis, one C. glabrata, and one C. guilliermondii. The hemolytic activity and DNAse were investigated using blood agar and DNAse agar, respectively. Biofilm production was evaluated through XTT sodium salt reduction ability, and the susceptibility of the isolates to antifungals through the microdilution methodology. Forty-nine isolates presented at least one of the three virulence factors investigated. C. albicans showed more intense hemolytic activity. DNAse production was statistically significant between the C. parapsilosis complex and C. albicans, as well as between the C. parapsilosis complex and C. krusei, even as between C. famata and C. albicans, and between C. famata and C. krusei. Forty-three isolates produced biofilm. Seventy-eight percent of the isolates were sensitive to the three antifungals tested. This study demonstrated that Candida isolated from healthcare professionals' hands has virulence.

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits.

Genotype by feed interaction for feed efficiency and growth performance traits in pigs

A major objective of pork producers is to reduce production cost. Feeding may account for over 75% of pork production costs. Thus, selecting pigs for feed efficiency (FE) traits is a priority in pig breeding programs. While in the Americas, pigs are typically fed high-input diets, based on corn and soybean meal (CS); in Western Europe, pigs are commonly fed diets based on wheat and barley with high amounts of added protein-rich coproducts (WB), e.g., from milling and seed-oil industries. These two feeding scenarios provided a realistic setting for investigating a specific type of genotype by environment interaction; thus, we investigated the genotype by feed interaction (GxF). In the presence of a GxF, different feed compositions should be considered when selecting for FE. This study aimed to 1) verify the presence of a GxF for FE and growth performance traits in different growth phases (starter, grower, and finisher) of 3-way crossbred growing-finishing pigs fed either a CS (547 boars and 558 gilts) or WB (567 boars and 558 gilts) diet; and 2) to assess and compare the expected responses to direct selection under the 2 diets and the expected correlated responses for one diet to indirect selection under the other diet. We found that GxF did not interfere in the ranking of genotypes under both diets for growth, protein deposition, feed intake, energy intake, or feed conversion rate. Therefore, for these traits, we recommend changing the diet of growing-finishing pigs from high-input feed (i.e., CS) to feed with less valuable ingredients, as WB, to reduce production costs and the environmental impact, regardless of which diet is used in selection. We found that GxF interfered in the ranking of genotypes and caused heterogeneity of genetic variance under both diets for lipid deposition (LD), residual energy intake (REI), and residual feed intake (RFI). Thus, selecting pigs under a diet different from the diet used for growing-finishing performance could compromise the LD in all growth phases, compromise the REI and RFI during the starter phase, and severely compromise the REI during the grower phase. In particular, when pigs are required to consume a WB diet for growing-finishing performance, pigs should be selected for FE under the same diet. Breeding pigs for FE under lower-input diets should be considered, because FE traits will become more important and lower-input diets will become more widespread in the near future.

A note on transgenerational epigenetics affecting egg quality traits in meat-type quail

1. The aim of the following experiment was to estimate transgenerational epigenetic variance for egg quality traits using genealogical and phenotypic information in meat-type quail. Measured traits included egg length (EL) and width (EWD), albumen weight (AW), shell weight (SW), yolk weight (YW) and egg weight (EW). 2. A total of 391 birds were evaluated for egg quality by collecting a sample of one egg per bird, during three consecutive days, starting on the 14th d of production. Analyses were performed using mixed models including the random epigenetic effect. Variance components were estimated by the restricted maximum likelihood method. A grid-search for values for the auto-recursive parameter (λ) was used in the variance components estimation. This parameter is directly related to the reset (v) and epigenetic transmissibility (1 - v) coefficients. 3. The epigenetic effect was not significant for any of the egg quality traits evaluated. Direct heritability estimates for egg quality traits ranged in magnitude from 0.06 to 0.33, whereby the higher estimates were found for AW and SW. Epigenetic heritability estimates were low and close to zero (ranging from 0.00 to 0.07) for all evaluated traits. 4. The current breeding strategies accounting for additive genetic effect seem to be suitable for egg quality traits in meat-type quail.

Transgenerational epigenetic variance for body weight in meat quails

We aimed to estimate transgenerational epigenetic variance for body weight using genealogical and phenotypic information in meat quails. Animals were individually weighted from 1 week after hatching, with weight records at 7, 14, 21, 28, 35 and 42 days of age (BW7, BW14, BW21, BW28, BW35 and BW42, respectively). Single-trait genetic analyses were performed using mixed models with random epigenetic effects. Variance components were estimated by the restricted maximum likelihood method. A grid search for values of autorecursive parameter (λ) ranging from 0 to 0.5 was used in the variance component estimation. This parameter is directly related to the reset coefficient (ν) and the epigenetic coefficient of transmissibility (1-ν). The epigenetic effect was only significant for BW7. Direct heritability estimates for body weight ranged in magnitude (from 0.15 to 0.26), with the highest estimate for BW7. Epigenetic heritability was 0.10 for BW7, and close to zero for the other body weights. The inclusion of the epigenetic effect in the model helped to explain the residual and non-Mendelian variability of initial body weight in meat quails.

Genetic parameters for semen quality and quantity traits in five pig lines

We aimed to estimate genetic parameters for semen quality and quantity traits as well as for within-boar variation of these traits to evaluate their inclusion in breeding goals. Genetic parameters were estimated within line using a multiple-trait (4 × 4) repeatability animal model fitted for 5 pig lines, considering 4 semen traits: sperm motility (MOT), sperm progressive motility (PROMOT), log-transformed number of sperm cells per ejaculate (lnN), and total morphological abnormalities (ABN). The within-boar variation of these traits was analyzed based on a multiple-trait (2 × 2) approach for SD and average (AVG) and a single-trait analysis for CV. The average heritabilities across the 5 lines estimated by multiple-trait analysis were 0.18 ± 0.07 (MOT), 0.22 ± 0.08 (PROMOT), 0.16 ± 0.04 (lnN), and 0.20 ± 0.04 (ABN). The average genetic correlations were favorable between MOT and PROMOT (0.86 ± 0.10), between MOT and ABN (-0.66 ± 0.25), and between PROMOT and ABN (-0.65 ± 0.25). As determined by within-boar variation analysis, AVG exhibited the greatest heritabilities followed by SD and CV, respectively, for the traits MOT and ABN. For PROMOT, average SD heritability was lower than CV heritability, whereas for lnN, they were the same. The average genetic correlations between AVG and SD were favorable for MOT (-0.60 ± 0.13), PROMOT (-0.79 ± 0.14), and ABN (0.78 ± 0.17). The moderate heritabilities indicate the possibility of effective selection of boars based on semen traits. Average and SD are proposed as appropriate traits for selection regarding uniformity.

Genetic correlations between feed efficiency traits, and growth performance and carcass traits in purebred and crossbred pigs

Selection for feed efficiency (FE) is a strategy to reduce the production costs per unit of animal product, which is one of the major objectives of current animal breeding programs. In pig breeding, selection for FE and other traits traditionally takes place based on purebred pig (PB) performance at the nucleus level, while pork production typically makes use of crossbred animals (CB). The success of this selection, therefore, depends on the genetic correlation between the performance of PB and CB (rpc) and on the genetic correlation (rg) between FE and the other traits that are currently under selection. Different traits are being used to account for FE, but the rpc has been reported only for feed conversion rate. Therefore, this study aimed 1) to estimate the rpc for growth performance, carcass, and FE traits; 2) to estimate rg between traits within PB and CB populations; and 3) to compare three different traits representing FE: feed conversion rate, residual energy intake (REI), and residual feed intake (RFI). Phenotypes of 194,445 PB animals from 23 nucleus farms, and 46,328 CB animals from three farms where research is conducted under near commercial production conditions were available for this study. From these, 22,984 PB and 8,657 CB presented records for feed intake. The PB population consisted of five sire and four dam lines, and the CB population consisted of terminal cross-progeny generated by crossing sires from one of the five PB sire lines with commercially available two-way maternal sow crosses. Estimates of rpc ranged from 0.61 to 0.71 for growth performance traits, from 0.75 to 0.82 for carcass traits, and from 0.62 to 0.67 for FE traits. Estimates of rg between growth performance, carcass, and FE traits differed within PB and CB. REI and RFI showed substantial positive rg estimates in PB (0.84) and CB (0.90) populations. The magnitudes of rpc estimates indicate that genetic progress is being realized in CB at the production level from selection on PB performance at nucleus level. However, including CB phenotypes recorded on production farms, when predicting breeding values, has the potential to increase genetic progress for these traits in CB. Given the genetic correlations with growth performance traits and the genetic correlation between the performance of PB and CB, REI is an attractive FE parameter for a breeding program.

TRIENNIAL GROWTH AND DEVELOPMENT SYMPOSIUM: Dedifferentiated fat cells: Potential and perspectives for their use in clinical and animal science purpose

An increasing body of evidences has demonstrated the ability of the mature adipocyte to dedifferentiate into a population of proliferative-competent cells known as dedifferentiated fat (DFAT) cells. As early as the 1970s, in vitro studies showed that DFAT cells may be obtained by ceiling culture, which takes advantage of the buoyancy property of lipid-filled cells. It was documented that DFAT cells may acquire a phenotype similar to mesenchymal stem cells and yet may differentiate into multiple cell lineages, such as skeletal and smooth muscle cells, cardiomyocytes, osteoblasts, and adipocytes. Additionally, recent studies showed the ability of isolated mature adipocytes to dedifferentiate in vivo and the capacity of the progeny cells to redifferentiate into mature adipocytes, contributing to the increase of body fatness. These findings shed light on the potential for use of DFAT cells, not only for clinical purposes but also within the animal science field, because increasing intramuscular fat without excessive increase in other fat depots is a challenge in livestock production. Knowledge of the mechanisms underlying the dedifferentiation and redifferentiation of DFAT cells will allow the development of strategies for their use for clinical and animal science purposes. In this review, we highlight several aspects of DFAT cells, their potential for clinical purposes, and their contribution to adipose tissue mass in livestock.

Oviposition of fruit flies (Diptera: Tephritidae) and its relation with the pericarp of citrus fruits

Fruit flies (Diptera: Tephritidae) represent a threat to fruit growing worldwide, mainly the citrus culture, however, biological studies show that fruit flies are not perfectly adapted to this host. This study investigated oviposition of Anastrepha fraterculus (Wiedemann, 1830) and Ceratitis capitata (Wiedemann, 1824) and its relation with the pericarp of citrus fruits. We evaluated the relationship between depth of oviposition of A. fraterculus and C. capitata and epicarp thickness of orange [Citrus sinensis (L.) Osbeck)] 'Navelina' and tangerine [C. reticulata (L.)] 'Clemenules' and the influence of fruit mesocarp of tangerine 'Clemenules' on oviposition of these species. The study was conducted under controlled conditions of temperature (25 ± 2 °C), relative humidity (70 ± 10% RH) and photophase (12 h). A. fraterculus and C. capitata laid their eggs in the flavedo region of orange 'Navelina' and between the albedo and flavedo of tangerine 'Clemenules'. When fruits with mesocarp exposed were offered, there was no oviposition by both fruit fly species. The results show that epicarp thickness of citrus fruits did not influence oviposition of A. fraterculus and C. capitata as oviposition did not occur only in the presence of the mesocarp, suggesting that other factors are involved in oviposition of these species.

Regularized quantile regression for SNP marker estimation of pig growth curves

Background

Genomic growth curves are generally defined only in terms of population mean; an alternative approach that has not yet been exploited in genomic analyses of growth curves is the Quantile Regression (QR). This methodology allows for the estimation of marker effects at different levels of the variable of interest. We aimed to propose and evaluate a regularized quantile regression for SNP marker effect estimation of pig growth curves, as well as to identify the chromosome regions of the most relevant markers and to estimate the genetic individual weight trajectory over time (genomic growth curve) under different quantiles (levels).

Results

The regularized quantile regression (RQR) enabled the discovery, at different levels of interest (quantiles), of the most relevant markers allowing for the identification of QTL regions. We found the same relevant markers simultaneously affecting different growth curve parameters (mature weight and maturity rate): two (ALGA0096701 and ALGA0029483) for RQR(0.2), one (ALGA0096701) for RQR(0.5), and one (ALGA0003761) for RQR(0.8). Three average genomic growth curves were obtained and the behavior was explained by the curve in quantile 0.2, which differed from the others.

Conclusions

RQR allowed for the construction of genomic growth curves, which is the key to identifying and selecting the most desirable animals for breeding purposes. Furthermore, the proposed model enabled us to find, at different levels of interest (quantiles), the most relevant markers for each trait (growth curve parameter estimates) and their respective chromosomal positions (identification of new QTL regions for growth curves in pigs). These markers can be exploited under the context of marker assisted selection while aiming to change the shape of pig growth curves.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F₂ hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

After genome-wide association studies: Gene networks elucidating candidate genes divergences for number of teats across two pig populations

Number of teats (NT) is an important trait affecting both piglet's welfare and the production level of pig farms. Biologically, embryonic mammary gland development requires the coordination of many signaling pathways necessary for the proper development of teats. Several QTL for NT have been identified; however, further analysis is still lacking. Therefore, gene networks derived from genomewide association study (GWAS) results can be used to examine shared pathways and functions of putative candidate genes. Besides, such analyses may also be helpful to understand the genetic diversity between populations for the same trait or traits. In this study, we identified significant SNP for Landrace-based (line C) and Large White-based (line D) dam lines. Besides, gene-transcription factor (TF) networks were constructed aiming to obtain the most likely candidate genes for NT in each line followed by a comparative analysis between both lines to access similarities or dissimilarities at the marker and gene level. We identified 24 and 19 significant SNP (Bayes factor ≥ 100) for lines C and D, respectively. Only 1 significant SNP overlapped both lines. Network analysis illustrated gene interactions consistent with known mammal's breast biology and captured known TF. We observed different sets of putative candidate genes for NT in each line evaluated that may have common effects on the phenotype. Based on these results, we demonstrated the importance of post-GWAS analyses increasing the biological understanding of relevant genes for a complex trait. Moreover, we believe that this genomic diversity across lines should be taken into account, considering breed-specific reference populations for genomic selection.

Genomic prediction for additive and dominance effects of censored traits in pigs

Age at the time of slaughter is a commonly used trait in animal breeding programs. Since studying this trait involves incomplete observations (censoring), analysis can be performed using survival models or modified linear models, for example, by sampling censored data from truncated normal distributions. For genomic selection, the greatest genetic gains can be achieved by including non-additive genetic effects like dominance. Thus, censored traits with effects on both survival models have not yet been studied under a genomic selection approach. We aimed to predict genomic values using the Cox model with dominance effects and compare these results with the linear model with and without censoring. Linear models were fitted via the maximum likelihood method. For censored data, sampling through the truncated normal distribution was used, and the model was called the truncated normal linear via Gibbs sampling (TNL). We used an F₂ pig population; the response variable was time (days) from birth to slaughter. Data were previously adjusted for fixed effects of sex and contemporary group. The model predictive ability was calculated based on correlation of predicted genomic values with adjusted phenotypic values. The results showed that both with and without censoring, there was high agreement between Cox and linear models in selection of individuals and markers. Despite including the dominance effect, there was no increase in predictive ability. This study showed, for the first time, the possibility of performing genomic prediction of traits with censored records while using the Cox survival model with additive and dominance effects.

New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program

Genomic selection is the main force driving applied breeding programs and accuracy is the main measure for evaluating its efficiency. The traditional estimator (TE) of experimental accuracy is not fully adequate. This study proposes and evaluates the performance and efficiency of two new accuracy estimators, called regularized estimator (RE) and hybrid estimator (HE), which were applied to a practical cassava breeding program and also to simulated data. The simulation study considered two individual narrow sense heritability levels and two genetic architectures for traits. TE, RE, and HE were compared under four validation procedures: without validation (WV), independent validation, ten-fold validation through jacknife allowing different markers, and with the same markers selected in each cycle. RE presented accuracies closer to the parametric ones and less biased and more precise ones than TE. HE proved to be very effective in the WV procedure. The estimators were applied to five traits evaluated in a cassava experiment, including 358 clones genotyped for 390 SNPs. Accuracies ranged from 0.67 to 1.12 with TE and from 0.22 to 0.51 with RE. These results indicated that TE overestimated the accuracy and led to one accuracy estimate (1.12) higher than one, which is outside of the parameter space. Use of RE turned the accuracy into the parameter space. Cassava breeding programs can be more realistically implemented using the new estimators proposed in this study, providing less risky practical inferences.

Effects of using phenotypic means and genotypic values in GGE biplot analyses on genotype by environment studies on tropical maize (Zea mays)

The objective of this study was to examine the effects of the type and intensity of nutritional stress, and of the statistical treatment of the data, on the genotype x environment (G x E) interaction for tropical maize (Zea mays). For this purpose, 39 hybrid combinations were evaluated under low- and high-nitrogen and -phosphorus availability. The plants were harvested at the V6 stage, and the shoot dry mass was estimated. The variance components and genetic values were assessed using the restricted maximum likelihood/best linear unbiased prediction method, and subsequently analyzed using the GGE biplot method. We observed differences in the performances of the hybrids depending on both the type and intensity of nutritional stress. The results of relationship between environments depended on whether genotypic values or phenotypic means were used. The selection of tropical maize genotypes against nutritional stress should be performed for each nutrient availability level within each type of nutritional stress. The use of phenotypic means for this purpose provides greater reliability than do genotypic values for the analysis of the G x E interaction using GGE biplot.

Genetic progress resulting from forty-three years of breeding of the carioca common bean in Brazil

We aimed to evaluate 40 common bean cultivars recommended by various Brazilian research institutions between 1970 and 2013 and estimate the genetic progress obtained for grain yield and other agronomic traits. Additionally, we proposed a bi-segmented nonlinear regression model to infer the year in which breeding began to show significant gains in Brazil. The experiment was carried out in Viçosa/MG and Coimbra/MG, in the dry and winter seasons of 2013. For this, a randomized complete block design with three replications was employed. The following traits were evaluated: number of pods per plant (NPP); number of seeds per pod (NSP); 1000-seed weight (W1000); grain yield (Yield); plant architecture (Arch); and grain aspect (GA). Genotypic means were estimated over years using linear mixed models, and genetic gains were estimated using bi-segmented nonlinear regression models. In summary, the methodology proposed in the present study indicated that bean breeding programs in Brazil began to influence Yield beginning in 1990, resulting in a gain of 6.74% per year (68.15 kg/ha per year). The years from which estimated genetic progress for NPP (5.62% per year), NSP (4.59% per year), W1000 (2.08% per year), and GA (1.36% per year) began to increase were 1994, 1990, 1989, and 1986, respectively.

Technical note: Prediction of chemical rib section composition by dual energy X-ray absorptiometry in Zebu beef cattle

It is expensive and laborious to evaluate carcass composition in beef cattle. The objective of this study was to evaluate a method to predict the 9th to 11th rib section (rib) composition through empirical equations using dual energy X-ray absorptiometry (DXA). Dual energy X-ray absorptiometry is a validated method used to describe tissue composition in humans and other animals, but few studies have evaluated this technique in beef cattle, and especially in the Zebu genotype. A total of 116 rib were used to evaluate published prediction equations for rib composition and to develop new regression models using a cross-validation procedure. For the proposed models, 93 ribs were randomly selected to calculate the new regression equations, and 23 different ribs were randomly selected to validate the regressions. The rib from left carcasses were taken from Nellore and Nellore × Angus bulls from 3 different studies and scanned using DXA equipment (GE Healthcare, Madison, WI) in the Health Division at Universidade Federal de Viçosa (Viçosa, Brazil). The outputs of the DXA report were DXA lean (g), DXA fat free mass (g), DXA fat mass (g), and DXA bone mineral content (BMC; g). After being scanned, the rib were dissected, ground, and chemically analyzed for total ether extract (EE), CP, water, and ash content. The predictions of rib fat and protein from previous published equations were different ( < 0.01) from the observed composition. New equations were established through leave-one-out cross-validation using the REG procedure in SAS. The equations were as follows: lean (g) = 37.082 + 0.907× DXA lean ( = 0.95); fat free mass (g) = 103.224 + 0.869 × DXA fat free mass ( = 0.93); EE mass (g) = 122.404 + 1.119 × DXA fat mass ( = 0.86); and ash mass (g) = 18.722 + 1.016 × DXA BMC ( = 0.39). The equations were validated using Mayer's test, the concordance correlation coefficient, and the mean square error of prediction for decomposition. For both equations, Mayer's test indicated that if the intercept and the slope were equal to 0 and 1 ( > 0.05), respectively, then the equation correctly estimated the rib composition. Comparing observed and predicted values using the new equations, Mayer's test was not significant for lean mass ( = 0.26), fat free mass ( = 0.67), EE mass ( = 0.054), and ash mass ( = 0.14). We concluded that the rib composition of Nellore and Nellore × Angus bulls can be estimated from DXA using the proposed equations.

Multi-trait BLUP model indicates sorghum hybrids with genetic potential for agronomic and nutritional traits

The breeding of sorghum, Sorghum bicolor (L.) Moench, aimed at improving its nutritional quality, is of great interest, since it can be used as a highly nutritive alternative food source and can possibly be cultivated in regions with low rainfall. The objective of the present study was to evaluate the potential and genetic diversity of grain-sorghum hybrids for traits of agronomic and nutritional interest. To this end, the traits grain yield and flowering, and concentrations of protein, potassium, calcium, magnesium, sulfur, iron, manganese, and zinc in the grain were evaluated in 25 grain-sorghum hybrids, comprising 18 experimental hybrids of Embrapa Milho e Sorgo and seven commercial hybrids. The genetic potential was analyzed by a multi-trait best linear unbiased prediction (BLUP) model, and cluster analysis was accomplished by squared Mahalanobis distance using the predicted genotypic values. Hybrids 0306037 and 0306034 stood out in the agronomic evaluation. The hybrids with agronomic prominence, however, did not stand out for the traits related to the nutritional quality of the grain. Three clusters were formed from the dendrogram obtained with the unweighted pair group method with arithmetic mean method. From the results of the genotypic BLUP and the analysis of the dendrogram, hybrids 0577337, 0441347, 0307651, and 0306037 were identified as having the potential to establish a population that can aggregate alleles for all the evaluated traits of interest.

Accounting for genetic architecture in single- and multipopulation genomic prediction using weights from genomewide association studies in pigs

We studied the effect of including GWAS results on the accuracy of single- and multipopulation genomic predictions. Phenotypes (backfat thickness) and genotypes of animals from two sire lines (SL1, n = 1146 and SL3, n = 1264) were used in the analyses. First, GWAS were conducted for each line and for a combined data set (both lines together) to estimate the genetic variance explained by each SNP. These estimates were used to build matrices of weights (D), which was incorporated into a GBLUP method. Single population evaluated with traditional GBLUP had accuracies of 0.30 for SL1 and 0.31 for SL3. When weights were employed in GBLUP, the accuracies for both lines increased (0.32 for SL1 and 0.34 for SL3). When a multipopulation reference set was used in GBLUP, the accuracies were higher (0.36 for SL1 and 0.32 for SL3) than in single-population prediction. In addition, putting together the multipopulation reference set and the weights from the combined GWAS provided even higher accuracies (0.37 for SL1, and 0.34 for SL3). The use of multipopulation predictions and weights estimated from a combined GWAS increased the accuracy of genomic predictions.

Genomic selection for slaughter age in pigs using the Cox frailty model

The aim of this study was to compare genomic selection methodologies using a linear mixed model and the Cox survival model. We used data from an F2 population of pigs, in which the response variable was the time in days from birth to the culling of the animal and the covariates were 238 markers [237 single nucleotide polymorphism (SNP) plus the halothane gene]. The data were corrected for fixed effects, and the accuracy of the method was determined based on the correlation of the ranks of predicted genomic breeding values (GBVs) in both models with the corrected phenotypic values. The analysis was repeated with a subset of SNP markers with largest absolute effects. The results were in agreement with the GBV prediction and the estimation of marker effects for both models for uncensored data and for normality. However, when considering censored data, the Cox model with a normal random effect (S1) was more appropriate. Since there was no agreement between the linear mixed model and the imputed data (L2) for the prediction of genomic values and the estimation of marker effects, the model S1 was considered superior as it took into account the latent variable and the censored data. Marker selection increased correlations between the ranks of predicted GBVs by the linear and Cox frailty models and the corrected phenotypic values, and 120 markers were required to increase the predictive ability for the characteristic analyzed.

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required. Among these methods, independent component regression, principal component regression, partial least squares, and partial principal components stand out. Thus, the aim of this study was to propose an application of the methods of dimensionality reduction to GWS of carcass traits in an F2 (Piau x commercial line) pig population. The results show similarities between the principal and the independent component methods and provided the most accurate genomic breeding estimates for most carcass traits in pigs.

Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information

Knowledge of dominance effects should improve ge-netic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of het-erosis in crossbreeds. In this study, we combined genomic and pedi-gree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broad-sense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respec-tively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only for birth weight and weight at 21 days of age.

Genetic evaluation of milk yield in Alpine goats for the first four lactations using random regression models

Random regression models have been used in evaluating test-day milk yield, providing accurate estimates of genetic values in animals. However, herd evaluation with only information from the first lactation may not be the best option from an economic perspective. Other factors should be taken into account, particularly other lactations. Our objective in this study was to analyze the genetic divergence between the first four lactations of Alpine goats. The RENPED software was used to perform descriptive statistics, check for errors in pedigree, recode the data, and for Pearson's and Spearman's correlations. The WOMBAT software was used to estimate the variance components and predict the breeding values. The CALC software was adopted to calculate the percentage of coincidence between the ranking of the animals and the animals kept in common at each lactation evaluation. The results show that selection using only the first lactation in small herds with a low degree of technology can be employed as a palliative measure, in view of the difficulty in evaluating all lactations. However, the selection of breeding goats and the production of catalogues should not be based only on the first lactation, because the results demonstrate inversions in the classification of the best breeders when other lactations are analyzed.

A genome-wide association study reveals a novel candidate gene for sperm motility in pigs

Sperm motility is one of the most widely used parameters in order to evaluate boar semen quality. However, this trait can only be measured after puberty. Thus, the use of genomic information appears as an appealing alternative to evaluate and improve selection for boar fertility traits earlier in life. With this study we aimed to identify SNPs with significant association with sperm motility in two different commercial pig populations and to identify possible candidate genes within the identified QTL regions. We performed a single-SNP genome-wide association study using genotyped animals from a Landrace-based (L1) and a Large White-based (L2) pig populations. For L1, a total of 602 animals genotyped for 42,551 SNPs were used in the association analysis. For L2, a total of 525 animals genotyped for 40,890 SNPs were available. After the association analysis, a false discovery rate q-value ≤0.05 was used as the threshold for significant association. No SNPs were significantly associated with sperm motility in L1, while six SNPs on Sus scrofa chromosome 1 (position 117.26-119.56Mb) were significant in L2. The mitochondrial methionyl-tRNA formyltransferase (MTFMT) gene, which affects translation efficiency of proteins in sperm cells, was identified as a putative candidate gene. The significant markers identified in this study may be useful to enhance the genetic improvement of sperm motility by selection of boars at an earlier age under a marker assisted selection strategy.

Supervised independent component analysis as an alternative method for genomic selection in pigs

The objective of this work was to evaluate the efficiency of the supervised independent component regression (SICR) method for the estimation of genomic values and the SNP marker effects for boar taint and carcass traits in pigs. The methods were evaluated via the agreement between the predicted genetic values and the corrected phenotypes observed by cross-validation. These values were also compared with other methods generally used for the same purposes, such as RR-BLUP, SPCR, SPLS, ICR, PCR and PLS. The SICR method was found to have the most accurate prediction values.

Selection of sugar cane families by using BLUP and multi-diverse analyses for planting in the Brazilian savannah

This study evaluated different strategies to select sugar cane families and obtain clones adapted to the conditions of the Brazilian savannah. Specifically, 7 experiments were conducted, with 10 full sib families, and 2 witnesses in common to all experiments, in each experiment. The plants were grown in random blocks, with witnesses in common (incomplete blocks), and 6 repetitions of each experiment. The data were analyzed through the methodology of mixed patterns, in which the matrices of kinship between the families were identified by the method of restricted maximum likelihood. The characteristics that were evaluated included soluble solids content (BRIX), BRIX ton/ha, average mass of a culm, number of culms/m, and tons of culms/ha. A multi-diverse alternative based on the analysis of groupings by using the UPGMA method was used to identify the most viable families for selection, when considering the genotypic effects on all characteristics. This method appeared suitable for the selection of families, with 5 family groups being formed. The families that formed Group 2 appeared superior to all other families for all the evaluated characteristics. It is recommended that the families in Group 2 are preferentially used in sugar cane improvement programs to obtain varieties optimally adapted to the conditions of the Brazilian savannah.

Sire evaluation for total number born in pigs using a genomic reaction norms approach

In the era of genome-wide selection (GWS), genotype-by-environment (G×E) interactions can be studied using genomic information, thus enabling the estimation of SNP marker effects and the prediction of genomic estimated breeding values (GEBV) for young candidates for selection in different environments. Although G×E studies in pigs are scarce, the use of artificial insemination has enabled the distribution of genetic material from sires across multiple environments. Given the relevance of reproductive traits, such as the total number born (TNB) and the variation in environmental conditions encountered by commercial dams, understanding G×E interactions can be essential for choosing the best sires for different environments. The present work proposes a two-step reaction norm approach for G×E analysis using genomic information. The first step provided estimates of environmental effects (herd-year-season, HYS), and the second step provided estimates of the intercept and slope for the TNB across different HYS levels, obtained from the first step, using a random regression model. In both steps, pedigree ( A: ) and genomic ( G: ) relationship matrices were considered. The genetic parameters (variance components, h(2) and genetic correlations) were very similar when estimated using the A: and G: relationship matrices. The reaction norm graphs showed considerable differences in environmental sensitivity between sires, indicating a reranking of sires in terms of genetic merit across the HYS levels. Based on the G: matrix analysis, SNP by environment interactions were observed. For some SNP, the effects increased at increasing HYS levels, while for others, the effects decreased at increasing HYS levels or showed no changes between HYS levels. Cross-validation analysis demonstrated better performance of the genomic approach with respect to traditional pedigrees for both the G×E and standard models. The genomic reaction norm model resulted in an accuracy of GEBV for "juvenile" boars varying from 0.14 to 0.44 across different HYS levels, while the accuracy of the standard genomic prediction model, without reaction norms, varied from 0.09 to 0.28. These results show that it is important and feasible to consider G×E interactions in evaluations of sires using genomic prediction models and that genomic information can increase the accuracy of selection across environments.

Identification and validation of differentially expressed genes from pig skeletal muscle

Pig is an important animal for meat production; this is generally associated with characteristics determined prenatally during myogenesis. Expressed sequence tags (EST) can provide direct information on the transcriptome and indirect information on the relation between the genome and phenotype, giving information about differentially expressed genes (DEG). In this work, the identification and annotation of DEG from EST libraries of three pig breeds (Duroc, Large White and Local Breed Piau) were performed followed by real-time PCR analyses during pre- and postnatal stages (21, 40, 70 and 90 days of pregnancy and 107, 121 and 171 days postnatal) from commercial breed animals for analysis of genes expression levels. Therefore, 34 genes differentially expressed were identified, of which 21 grouped in a network related with muscle development. From this, the expression profile of 13 genes was measured, to confirm their relationship with myogenesis like ANKRD2, MYBPC1, NEB and MYL2. These genes showed a prenatal high expression in this study. Besides, novels candidates for muscle development (TP53 and DCTN1) were listed. These findings can contribute to better explaining gene function mechanism and are helpful in uncovering the pathways that mediate pre- and postnatal skeletal muscle development in vertebrates.

Transcript profiling of expressed sequence tags from semimembranosus muscle of commercial and naturalized pig breeds

In general, genetic differences across different breeds of pig lead to variation in mature body size and slaughter age. The Commercial breeds Duroc and Large White and the local Brazilian breed Piau are ostensibly distinct in terms of growth and muscularity, commercial breeds are much leaner while local breeds grow much slower and are fat type pigs. However, the genetic factors that underlie such distinctions remain unclear. We used expressed sequence tags (ESTs) to characterize and compare transcript profiles in the semimembranosus muscle of these pig breeds. Our aim was to identify differences in breed-related gene expression that might influence growth performance and meat quality. We constructed three non-normalized cDNA libraries from semimembranosus muscle, using two samples from each one, of these three breeds; 6902 high-quality ESTs were obtained. Cluster analysis was performed and these sequences were clustered into 3670 unique sequences; 24.7% of the sequences were categorized as contigs and 75.3% of the sequences were singletons. Based on homology searches against the SwissProt protein database, we were able to assign a putative protein identity to only 1050 unique sequences. Among these, 58.5% were full-length protein sequences and 17.2% were pig-specific sequences. Muscle structural and cytoskeletal proteins, such as actin, and myosin, were the most abundant transcripts (16.7%) followed by those related to mitochondrial function (12.9%), and ribosomal proteins (12.4%). Furthermore, ESTs generated in this study provide a rich source for identification of novel genes and for the comparative analysis of gene expression patterns in divergent pig breeds.

Genetic characterization of papaya plants (Carica papaya L.) derived from the first backcross generation

The limited number of papaya varieties available reflects the narrow genetic base of this species. The use of backcrossing as a breeding strategy can promote increases in variability, besides allowing targeted improvements. Procedures that combine the use of molecular markers and backcrossing permit a reduction of the time required for introgression of genes of interest and appropriate recovery of the recurrent genome. We used microsatellite markers to characterize the effect of first-generation backcrosses of three papaya progeny, by monitoring the level of homozygosity and the parental genomic ratio. The homozygosity level in the population ranged from 74 to 94%, with a mean of 85% for the three progenies (52-08, 52-29 and 52-34). The high level of inbreeding found among these genotypes increases the expectation of finding more than 95% fixed loci in the next generation of self-fertilization of superior genotypes. The mean proportion of the recurrent parent genome found in first-generation backcross progeny was 50.1%; 52-34 had a larger genomic region in common with the recurrent genitor and the lowest level of homozygosity. The progeny 52-08 was genetically closest to the donor genitor, and it also had the highest level of homozygosity. We found that linking conventional procedures and molecular markers contributed to an increase in the efficiency of the breeding program.

Novel vasopressin type 2 (AVPR2) gene mutations in Brazilian nephrogenic diabetes insipidus patients

Nephrogenic diabetes insipidus (NDI) is an inherited disorder characterized by renal resistance to the antidiuretic effect of arginine vasopressin (AVP), resulting in polyuria, polydipsia, and hypoosmolar urine. In the vast majority of cases, NDI is associated with germ-line mutations in the vasopressin receptor type 2 gene (AVPR2) and in about 8% of the cases with the water channel aquaporin-2 gene (AQP-2) mutations. To date, approximately 277 families with 185 germ-line mutations in the AVPR2 gene have been described worldwide. In the present study, the AVPR2 gene was genotyped in eight unrelated Brazilian kindred with NDI. In five of these NDI families, novel mutations were noted (S54R, I130L, S187R, 219delT, and R230P), whereas three seemingly unrelated probands were found to harbor previously described AVPR2 gene mutations (R106C, R137H, R337X). Additionally a novel polymorphism (V281V) was detected. In conclusion, although NDI is a rare disease, the findings of mutations scattered over the entire coding region of the AVPR2 gene are a valuable model to determine structure function relationship in G-protein-coupled receptor related diseases. Furthermore, our data indicate that in Brazil the spectrum of AVPR2 gene mutations is "family specific".

Follow-up of patients with vertically-acquired HIV infection who are more than 9 years old

The aim of this study was to assess the influence of biological markers of infection and antiretroviral therapy on the survival rate and quality of life in children with vertically-acquired HIV infection. This retrospective study was performed between August and October 2000. Outcome measures were presence of neurological disease, CD4 cell count, cranial computerized tomography (CT), electroencephalogram (EEG), use of antiretroviral agents, and mortality. The presence of neurological disease and of pathological findings in cranial computed tomography, and the lack of biological monitoring are associated with poor prognosis. Follow-up of this population should continue to allow long-term assessment of the social and biological impact of vertically-transmitted HIV.

[Prevalence of prenatal exposure to cocaine in a sample of newborns from a university teaching hospital]

OBJECTIVE: To assess the prevalence of prenatal exposure to cocaine in a sample of newborns using two methods: fluorescence polarization immunoassay and interview with the mother. METHODS: This cross-sectional study was carried out in a university teaching hospital. The population included all live births between March 23, 1999 and June 01, 1999 (n=847). Exposure was determined by a benzoylecgonine-positive meconium specimen and/or by a positive interview with the mother. RESULTS: The prevalence of prenatal exposure to cocaine in this sample was 2.4% (16 cases) according to the interviews, and 3.4% (25 cases) according to the meconium analysis. A rate of 4.6% (34 cases) was found when both methods were associated. CONCLUSIONS: We observed that the meconium test was more effective than the maternal interview for the diagnosis of prenatal exposure to cocaine. The meconium analysis enhanced diagnostic chances by 53.4%, compared to 26% in the case of maternal interview.