Navegando por Autor "Silva, Fabyano F."

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The diversification of begomovirus populations is predominantly driven by mutational dynamics
(Virus Evolution, 2017-03-02) Lima, Alison T. M.; Silva, Jose ́ C. F.; Silva, Fábio N.; Castillo-Urquiza, Gloria P.; Silva, Fabyano F.; Seah, Yee M.; Mizubuti, Eduardo S. G.; Duffy, Siobain; Zerbini, Murilo
Begomoviruses (single-stranded DNA plant viruses) are responsible for serious agricultural threats. Begomovirus populations exhibit a high degree of within-host genetic variation and evolve as quickly as RNA viruses. Although the recombination-prone nature of begomoviruses has been extensively demonstrated, the relative contribution of recombination and mutation to the genetic variation of begomovirus populations has not been assessed. We estimated the genetic variability of begomovirus datasets from around the world. An uneven distribution of genetic variation across the length of the cp and rep genes due to recombination was evident from our analyses. To estimate the relative contributions of recombination and mutation to the genetic variability of begomoviruses, we mapped all substitutions over maximum likelihood trees and counted the number of substitutions on branches which were associated with recombination (ηr) and mutation (ημ). In addition, we also estimated the per generation relative rates of both evolutionary mechanisms (r/μ) to express how frequently begomovirus genomes are affected by recombination relative to mutation. We observed that the composition of genetic variation in all begomovirus datasets was dominated by mutation. Additionally, the low correlation between the estimates indicated that the relative contributions of recombination and mutation are not necessarily a function of their relative rates. Our results show that, although a considerable fraction of the genetic variation levels could be assigned to recombination, it was always lower than that due to mutation, indicating that the diversification of begomovirus populations is predominantly driven by mutational dynamics.
Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
(BMC Genomics, 2018) Guimarães, Simone E. F.; Sevillano, Claudia A.; Napel, Jan ten; Silva, Fabyano F.; Calus, Mario P. L.
This study investigated if the allele effect of a given single nucleotide polymorphism (SNP) for crossbred performance in pigs estimated in a genomic prediction model differs depending on its breed-of-origin, and how these are related to estimated effects for purebred performance.SNP-allele substitution effects were estimated for a commonly used SNP panel using a genomic best linear unbiased prediction model with breed-specific partial relationship matrices. Estimated breeding values for purebred and crossbred performance were converted to SNP-allele effects by breed-of-origin. Differences between purebred and crossbred, and between breeds-of-origin were evaluated by comparing percentage of variance explained by genomic regions for back fat thickness (BF), average daily gain (ADG), and residual feed intake (RFI). From ten regions explaining most additive genetic variance for crossbred performance, 1 to 5 regions also appeared in the top ten for purebred performance. The proportion of genetic variance explained by a genomic region and the estimated effect of a haplotype in such a region were different depending upon the breed-of-origin. To illustrate underlying mechanisms, we evaluated the estimated effects across breeds-of-origin for haplotypes associated to the melanocortin 4 receptor (MC4R) gene, and for the MC4Rsnp itself which is a missense mutation with a known effect on BF and ADG. Although estimated allele substitution effects of the MC4Rsnp mutation were very similar across breeds, explained genetic variance of haplotypes associated to the MC4R gene using a SNP panel that does not include the mutation, was considerably lower in one of the breeds where the allele frequency of the mutation was the lowest.Similar regions explaining similar additive genetic variance were observed across purebred and crossbred performance. Moreover, there was some overlap across breeds-of-origin between regions that explained relatively large proportions of genetic variance for crossbred performance; albeit that the actual proportion of variance deviated across breeds-of-origin. Results based on a missense mutation in MC4R confirmed that even if a causal locus has similar effects across breeds-of-origin, estimated effects and explained variance in its region using a commonly used SNP panel can strongly depend on the allele frequency of the underlying causal mutation.
Fine mapping and single nucleotide polymorphism effects estimation on pig chromosomes 1, 4, 7, 8, 17 and X
(Genetics and Molecular Biology, 2013-11-08) Hidalgo, André M.; Lopes, Paulo S.; Paixão, Débora M.; Silva, Fabyano F.; Bastiaansen, John W.M.; Paiva, Samuel R.; Faria, Danielle A.; Guimarães, Simone E.F.
Fine mapping of quantitative trait loci (QTL) from previous linkage studies was performed on pig chromosomes 1, 4, 7, 8, 17, and X which were known to harbor QTL. Traits were divided into: growth performance, carcass, internal organs, cut yields, and meat quality. Fifty families were used of a F2 population produced by crossing local Brazilian Piau boars with commercial sows. The linkage map consisted of 237 SNP and 37 microsatellite markers covering 866 centimorgans. QTL were identified by regression interval mapping using GridQTL. Individual marker effects were estimated by Bayesian LASSO regression using R. In total, 32 QTL affecting the evaluated traits were detected along the chromosomes studied. Seven of the QTL were known from previous studies using our F2 population, and 25 novel QTL resulted from the increased marker coverage. Six of the seven QTL that were significant at the 5% genome-wide level had SNPs within their confidence interval whose effects were among the 5% largest effects. The combined use of microsatellites along with SNP markers increased the saturation of the genome map and led to smaller confidence intervals of the QTL. The results showed that the tested models yield similar improvements in QTL mapping accuracy.
Geminivirus data warehouse: a database enriched with machine learning approaches
(BioMed Central Bioinformatics, 2017-05-05) Silva, Jose Cleydson F.; Carvalho, Thales F. M.; Basso, Marcos F.; Deguchi, Michihito; Pereira, Welison A.; Vidigal, Pedro M. P.; Brustolini, Otávio J. B.; Silva, Fabyano F.; Dal-Bianco, Maximiller; Fontes, Renildes L. F.; Santos, Anésia A.; Zerbini, Francisco Murilo; Cerqueira, Fabio R.; Fontes, Elizabeth P. B.; R. Sobrinho, Roberto
The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics. Here, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes. The use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.
Genetic parameters of body weight and egg traits in meat-type quail
(Livestock Science, 2013-02-23) Silva, Luciano P.; Ribeiro, Jeferson C.; Crispim, Aline C.; Silva, Felipe G.; Bonafé, Cristina M.; Silva, Fabyano F.; Torres, Robledo A.
Data from two quail strains, UFV1 and UFV 2, measured weekly from hatch to sixth week in a total of seven live body weight traits were used aiming to estimate genetic correlations and heritabilities. After females were evaluated they were monitored in their egg-laying phase, in which the total egg number, the average weight of the eggs and the average specific gravity of eggs were measured. Multi-trait analysis was performed with the ten traits measured for estimation of heritabilities, genetic and residual correlations. For body weight traits, heritabilities varying from 0.25 to 0.53 for UFV1 and from 0.27 to 0.53 for UFV2 were estimated; genetic correlations increased as the interval between records was reduced. For egg number, the heritability estimate was of low magnitude (0.05 and 0.04), whereas for average egg weight (0.41 and 0.39) and egg specific gravity (0.31 and 0.18), they were of moderate magnitude for UFV1 and UFV2, respectively. The genetic correlations between body weights and egg number were negative in UFV1 and positive in UFV2; for average egg weight, they were positive, and for specific gravity, they were negative for both strains. It can be concluded, then, that selection based on body weight in the growth phase of meat quail must be done preferably at early ages such as weight at the third or fourth week of life, once they are positively correlated with weight at slaughter age and have few effects on the production and quality of eggs.
Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models
(Genetics Selection Evolution, 2016-01-14) Mota, Rodrigo R.; Tempelman, Robert J.; Lopes, Paulo S.; Aguilar, Ignacio; Silva, Fabyano F.; Cardoso, Fernando F.
The cattle tick is a parasite that adversely affects livestock performance in tropical areas. Although countries such as Australia and Brazil have developed genetic evaluations for tick resistance, these evaluations have not considered genotype by environment (G*E) interactions. Genetic gains could be adversely affected, since breedstock comparisons are environmentally dependent on the presence of G*E interactions, particularly if residual variability is also heterogeneous across environments. The objective of this study was to infer upon the existence of G*E interactions for tick resistance of cattle based on various models with different assumptions of genetic and residual variability. Data were collected by the Delta G Connection Improvement program and included 10,673 records of tick counts on 4363 animals. Twelve models, including three traditional animal models (AM) and nine different hierarchical Bayesian reaction norm models (HBRNM), were investigated. One-step models that jointly estimate environmental covariates and reaction norms and two-step models based on previously estimated environmental covariates were used to infer upon G*E interactions. Model choice was based on the deviance criterion information. The best-fitting model specified heterogeneous residual variances across 10 subclasses that were bounded by every decile of the contemporary group (CG) estimates of tick count effects. One-step models generally had the highest estimated genetic variances. Heritability estimates were normally higher for HBRNM than for AM. One-step models based on heterogeneous residual variances also usually led to higher heritability estimates. Estimates of repeatability varied along the environmental gradient (ranging from 0.18 to 0.45), which implies that the relative importance of additive and permanent environmental effects for tick resistance is influenced by the environment. Estimated genetic correlations decreased as the tick infestation level increased, with negative correlations between extreme environmental levels, i.e., between more favorable (low infestation) and harsh environments (high infestation). HBRNM can be used to describe the presence of G*E interactions for tick resistance in Hereford and Braford beef cattle. The preferred model for the genetic evaluation of this population for tick counts in Brazilian climates was a one-step model that considered heteroscedastic residual variance. Reaction norm models are a powerful tool to identify and quantify G*E interactions and represent a promising alternative for genetic evaluation of tick resistance, since they are expected to lead to greater selection efficiency and genetic progress.
Modelos de regressão não linear aplicados a grupos de acessos de alho
(Horticultura Brasileira, 2014-04-16) Puiatti, Mário; Reis, Renata M.; Cecon, Paulo R.; Finger, Fernando L.; Nascimento, Moysés; Silva, Fabyano F.; Carneiro, Antônio P. S.; Silva, Anderson R.
O principal objetivo deste estudo foi comparar modelos de regressão não linear aptos a descreverem o acúmulo de massa seca de diferentes partes da planta do alho ao longo do tempo (60, 90, 120 e 150 dias após plantio). Objetivou-se também identificar acessos semelhantes em relação às características avaliadas por meio de análises de agrupamento. Foram utilizados 20 acessos de alho pertencentes ao Banco de Germoplasma de Hortaliças da Universidade Federal de Viçosa (BGH/UFV). O teor de massa seca da folha, do pseudocaule, do bulbo e da raiz foram definidos como variáveis na análise de agrupamento (algoritmo de Ward utilizando como medida de dissimilaridade a distância quadrada generalizada de Mahalanobis), que resultou na indicação de um número ótimo (critério de Mojena) de três grupos de acessos, cujas médias de massa seca do bulbo, da raiz e total da planta em cada tempo de interesse foram utilizadas para o ajuste de cinco modelos de regressão não linear (Mitscherlich, Gompertz, Logístico, Brody e von Bertalanffy). A identificação do modelo que melhor se ajustou às três características de cada grupo foi realizada mediante coeficiente de determinação (R2), o quadrado médio do resíduo (QMR) e o desvio médio absoluto dos resíduos (DMA). Comparando os valores desses avaliadores observou-se que, para as três caraterísticas dos três grupos, o modelo que melhor se ajustou foi o Logístico.
Molecular factors underlying the deposition of intramuscular fat and collagen in skeletal muscle of nellore and angus cattle
(PLOS ONE, 2015-10-05) Martins, Taiane S.; Sanglard, Letícia M. P.; Silva, Walmir; Chizzotti, Mário L.; Rennó, Luciana N.; Serão, Nick V. L.; Silva, Fabyano F.; Guimarães, Simone E. F.; Ladeira, Márcio M.; Dodson, Michael V.; Du, Min; Duarte, Marcio S.
Studies have shown that intramuscular adipogenesis and fibrogenesis may concomitantly occur in skeletal muscle of beef cattle. Thus, we hypothesized that the discrepancy of intramuscular fat content in beef from Nellore and Angus was associated with differences in intramuscular adipogenesis and fibrogenesis during the finishing phase. To test our hypothesis, longissimus muscle samples of Nellore (n = 6; BW = 372.5 ± 37.3 kg) and Angus (n = 6; BW = 382.8 ± 23.9 kg) cattle were collected for analysis of gene and protein expression, and quantification of intramuscular fat and collagen. Least-squares means were estimated for the effect of Breed and differences were considered at P ≤ 0.05. A greater intramuscular fat content was observed in skeletal muscle of Angus compared to Nellore cattle (P≤0.05). No differences were observed for mRNA expression of lipogenic and lipolytic markers ACC, FAS, FABP4, SERBP–1, CPT–2, LPL, and ACOX (P > 0.05) in skeletal muscle of Nellore and Angus cattle. Similarly, no differences were observed in mRNA expression of adipogenic markers Zfp423, PPARγ, and C/EBPα (P>0.05) However, a greater PPARγ protein content was observed in skeletal muscle of Angus compared to Nellore cattle (P≤0.05). A greater abundance of adipo/fibrogenic cells, evaluated by the PDGFRα content, was observed in skeletal muscle of Angus than Nellore cattle (P≤0.05). No differences in fibrogenesis were observed in skeletal muscle of Angus and Nellore cattle, which is in accordance with the lack of differences in intramuscular collagen content in beef from both breeds (P>0.05). These findings demonstrate that difference in intramuscular fat content is associated with a slightly enhanced adipogenesis in skeletal muscle of Angus compared to Nellore cattle, while no difference in fibrogenesis.
NIK1-mediated translation suppression functions as a plant antiviral immunity mechanism
(Nature, 2015-04-30) Zorzatto, Cristiane; Machado, João Paulo B.; Lopes, Kênia V. G.; Nascimento, Kelly J. T.; Pereira, Welison A.; Brustolini, Otávio J. B.; Reis, Pedro A. B.; Calil, Iara P.; Deguchi, Michihito; Sachetto-Martins, Gilberto; Gouveia, Bianca C.; Loriato, Virgílio A. P.; Silva, Marcos A. C.; Silva, Fabyano F.; Santos, Anésia A.; Chory, Joanne; Fontes, Elizabeth P. B.
Plants and plant pathogens are subject to continuous co-evolutionary pressure for dominance, and the outcomes of these interactions can substantially impact agriculture and food security^ 1–3 . In virus– plant interactions, one of the major mechanisms for plant antiviral immunity relies on RNA silencing, which is often suppressed by co-evolving virus suppressors, thus enhancing viral pathogenicity in susceptible hosts^ 1 . In addition, plants use the nucleotide-binding and leucine-rich repeat (NB-LRR) domain-containing resistance proteins, which recognize viral effectors to activate effector-triggered immunity in a defence mechanism similar to that employed in non-viral infections^ 2,3 . Unlike most eukaryotic organisms, plants are not known to activate mechanisms of host global translation suppression to fight viruses^ 1,2 . Here we demonstrate in Arabidopsis that the constitutive activation of NIK1, a leucine-rich repeat receptor-like kinase (LRR-RLK) identified as a virulence target of the begomovirus nuclear shuttle protein (NSP)^ 4–6 , leads to global translation suppression and translocation of the downstream component RPL10 to the nucleus, where it interacts with a newly identified MYB-like protein, L10-INTERACTING MYB DOMAIN-CONTAINING PROTEIN (LIMYB), to downregulate translational machinery genes fully. LIMYB overexpression represses ribosomal protein genes at the transcriptional level, resulting in protein synthesis inhibition, decreased viral messenger RNA association with polysome fractions and enhanced tolerance to begomovirus. By contrast, the loss of LIMYB function releases the repression of translation-related genes and increases susceptibility to virus infection. Therefore, LIMYB links immune receptor LRR-RLK activation to global translation suppression as an antiviral immunity strategy in plants.
Revealing new candidate genes for reproductive traits in pigs: combining Bayesian GWAS and functional pathways
(Genetics Selection Evolution, 2016-02-01) Verardo, Lucas L.; Silva, Fabyano F.; Lopes, Marcos S.; Madsen, Ole; Bastiaansen, John W. M.; Knol, Egbert F.; Kelly, Mathew; Varona, Luis; Lopes, Paulo S.; Guimarães, Simone E. F.
Reproductive traits such as number of stillborn piglets (SB) and number of teats (NT) have been evaluated in many genome-wide association studies (GWAS). Most of these GWAS were performed under the assumption that these traits were normally distributed. However, both SB and NT are discrete (e.g. count) variables. Therefore, it is necessary to test for better fit of other appropriate statistical models based on discrete distributions. In addition, although many GWAS have been performed, the biological meaning of the identified candidate genes, as well as their functional relationships still need to be better understood. Here, we performed and tested a Bayesian treatment of a GWAS model assuming a Poisson distribution for SB and NT in a commercial pig line. To explore the biological role of the genes that underlie SB and NT and identify the most likely candidate genes, we used the most significant single nucleotide polymorphisms (SNPs), to collect related genes and generated gene-transcription factor (TF) networks. Comparisons of the Poisson and Gaussian distributions showed that the Poisson model was appropriate for SB, while the Gaussian was appropriate for NT. The fitted GWAS models indicated 18 and 65 significant SNPs with one and nine quantitative trait locus (QTL) regions within which 18 and 57 related genes were identified for SB and NT, respectively. Based on the related TF, we selected the most representative TF for each trait and constructed a gene-TF network of gene-gene interactions and identified new candidate genes. Our comparative analyses showed that the Poisson model presented the best fit for SB. Thus, to increase the accuracy of GWAS, counting models should be considered for this kind of trait. We identified multiple candidate genes (e.g. PTP4A2, NPHP1, and CYP24A1 for SB and YLPM1, SYNDIG1L, TGFB3, and VRTN for NT) and TF (e.g. NF-κB and KLF4 for SB and SOX9 and ELF5 for NT), which were consistent with known newborn survival traits (e.g. congenital heart disease in fetuses and kidney diseases and diabetes in the mother) and mammary gland biology (e.g. mammary gland development and body length).
Sustained NIK-mediated antiviral signalling confers broad-spectrum tolerance to begomoviruses in cultivated plants
(Plant Biotechnology Journal, 2015-01-06) Brustolini, Otávio J.B.; Machado, Joao Paulo B.; Condori-Apfata, Jorge A.; Coco, Daniela; Deguchi, Michihito; Loriato, Virgílio A.P.; Pereira, Welison A.; Alfenas-Zerbini, Poliane; Zerbini, Francisco M.; Inoue-Nagata, Alice K.; Santos, Anesia A.; Chory, Joanne; Silva, Fabyano F.; Fontes, Elizabeth P.B.
Begomovirus-associated epidemics currently threaten tomato production worldwide due to the emergence of highly pathogenic virus species and the proliferation of a whitefly B biotype vector that is adapted to tomato. To generate an efficient defence against begomovirus, we modulated the activity of the immune defence receptor nuclear shuttle protein (NSP)-interacting kinase (NIK) in tomato plants; NIK is a virulence target of the begomovirus NSP during infection. Mutation of T474 within the kinase activation loop promoted the constitutive activation of NIK-mediated defences, resulting in the down-regulation of translation-related genes and the suppression of global translation. Consistent with these findings, transgenic lines harbouring an activating mutation (T474D) were tolerant to the tomato-infecting begomoviruses ToYSV and ToSRV. This phenotype was associated with reduced loading of coat protein viral mRNA in actively translating polysomes, lower infection efficiency and reduced accumulation of viral DNA in systemic leaves. Our results also add some relevant insights into the mechanism underlying the NIK-mediated defence. We observed that the mock-inoculated T474D-overexpressing lines showed a constitutively infected wild-type transcriptome, indicating that the activation of the NIK- mediated signalling pathway triggers a typical response to begomovirus infection. In addition, the gain-of-function mutant T474D could sustain an activated NIK-mediated antiviral response in the absence of the virus, further confirming that phosphorylation of Thr-474 is the crucial event that leads to the activation of the kinase.
Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
(Genetics Selection Evolution, 2018) Marques, Daniele B. D.; Bastiaansen, John W. M.; Broekhuijse, Marleen L. W. J.; Lopes, Marcos S.; Knol, Egbert F.; Harlizius, Barbara; Guimarães, Simone E. F.; Silva, Fabyano F.; Lopes, Paulo S.
In recent years, there has been increased interest in the study of the molecular processes that affect semen traits. In this study, our aim was to identify quantitative trait loci (QTL) regions associated with four semen traits (motility, progressive motility, number of sperm cells per ejaculate and total morphological defects) in two commercial pig lines (L1: Large White type and L2: Landrace type). Since the number of animals with both phenotypes and genotypes was relatively small in our dataset, we conducted a weighted single-step genome-wide association study, which also allows unequal variances for single nucleotide polymorphisms. In addition, our aim was also to identify candidate genes within QTL regions that explained the highest proportions of genetic variance. Subsequently, we performed gene network analyses to investigate the biological processes shared by genes that were identified for the same semen traits across lines.We identified QTL regions that explained up to 10.8% of the genetic variance of the semen traits on 12 chromosomes in L1 and 11 chromosomes in L2. Sixteen QTL regions in L1 and six QTL regions in L2 were associated with two or more traits within the population. Candidate genes SCN8A, PTGS2, PLA2G4A, DNAI2, IQCG and LOC102167830 were identified in L1 and NME5, AZIN2, SPATA7, METTL3 and HPGDS in L2. No regions overlapped between these two lines. However, the gene network analysis for progressive motility revealed two genes in L1 (PLA2G4A and PTGS2) and one gene in L2 (HPGDS) that were involved in two biological processes i.e. eicosanoid biosynthesis and arachidonic acid metabolism. PTGS2 and HPGDS were also involved in the cyclooxygenase pathway.We identified several QTL regions associated with semen traits in two pig lines, which confirms the assumption of a complex genetic determinism for these traits. A large part of the genetic variance of the semen traits under study was explained by different genes in the two evaluated lines. Nevertheless, the gene network analysis revealed candidate genes that are involved in shared biological pathways that occur in mammalian testes, in both lines.