Table of Contents | Genet. Mol. Res. 2019 (4)
We examined the effect of lipid content in the diet on the transcriptome of the Longissimus dorsi muscle in pigs. Our objective was to examine changes at the molecular level affecting economically relevant meat quality characteristics such as intramuscular fat deposition and fatty acid profile. The treatments consisted of isoproteic and isoenergetic diets with differing lipid contents due to addition of rice bran. The control diet (T0) was a normal basic diet and the test diet (T15) had 15% rice bran. The final lipid content (ether extract) in the diets was 3.4 and 4.8% in T0 and T15, respectively. Three male piglets of the Uruguayan creole breed Pampa Rocha were used per treatment, which lasted from weaning at 42 days until 77 days of age. The animals were reared in confinement on deep bedding and were slaughtered at the end of the experiment, when muscle samples were collected. Intramuscular fat content (IMF) and fatty acid composition were analyzed to determine if diets had a phenotypic effect. Gene expression analysis was performed with RNA-seq methodology to carrying out a functional analysis of genes with differential expression between treatments. The added fat to the diet did not affect IMF or fatty acid composition. However, we identified 359 genes with differential expression between treatments. These genes participate in various metabolic pathways, some of them affecting meat quality. The most relevant genes identified in this regard were PDK4 (up-regulated with T15), which is associated with energy metabolism, FOS, ATF3, MYOD1 and MAFF (all down-regulated with T15), which are associated with skeletal muscle growth, and TNC (up-regulated with T15), which is associated with extracellular matrix-receptor interactions. This study of the skeletal muscle transcriptome in pigs can help understand the genetic basis of how diet affects important production traits.
The lima bean (Phaseolus lunatus) has been cultivated in Brazil since pre-colonization times and remains an important source of food and income for small farmers. Nevertheless, the species has not been extensively studied in this country. We assessed the genetic diversity of 183 lima bean landraces collected from different regions of Brazil, maintained by Embrapa, the Brazilian Government Agricultural Research Corporation. Twelve microsatellite markers were used, and seven morphological descriptors were applied. The genetic parameters suggested high diversity of the Brazilian collection of lima beans, with a mean gene diversity of 0.68 and number of alleles varying from 5 to 15 among sites. Based on a Bayesian model using molecular data, three sub-populations were identified in the sample: one predominantly from the Andean gene pool of the species (large seeds, mean 100-seed weight of 80g), and two predominantly from the Mesoamerican pool (both groups with a mean 100-seed weight of 34g). Another large group was composed of accessions classified as potential hybrids among the different sub-populations. All the accessions collected in the Krahô indigenous reserve were allocated in the Andean sub-population, and these indigenous accessions represented most of this Andean group. All the three sub-populations identified included accessions collected from far-apart sites in different geographic regions of Brazil. There was considerable introgression between the Andean and the Mesoamerican gene pools of cultivated P. lunatus.
Common beans are a key source of protein and are consumed daily by most of the Brazilian population. More than 70% of what is consumed in this country is classified as carioca beans, based on seed qualities and appearance. We evaluated progenies of carioca common beans of the Brazilian agriculture research agency (Embrapa) recurrent selection program. This recurrent selection program is based on resistance to common bean bacterial blight (CBB), seed yield, and other important agronomic traits. Selection also considers the genetic representativeness of the parents and the genetic diversity among phenotypically selected progenies. Initially, 60 superior progenies were selected based on resistance to CBB and on seed type, in two locations (Santo Antônio de Goiás, GO and Ponta Grossa, PR). These progenies were evaluated in the C0S0:2 generation in field trials in six locations during the rainy growing season. A randomized block experimental design was used with two replications, in plots of two 3-m rows spaced at 0.5 m. The most promising C0S0:3 progenies for combined agronomic performance in the different environments were selected and were then evaluated by means of 24 microsatellite molecular markers for the purpose of determining the genetic representativeness of their parents and the genetic diversity among them. The phenotypic data was subjected to analysis of variance for each trait in each of the environments, and then joint analyses were performed. To estimate genetic diversity among the progenies, the Rogers-W genetic distance was used, and a dissimilarity matrix was used to construct a dendrogram of genetic distances through the UPGMA method. Among the 60 C0S0:2 progenies that were evaluated, those that stood out for resistance to CBB also stood out for seed yield and for resistance to other diseases. Various progenies were superior, exhibiting large genetic distances between each other and in relation to the parents. This indicates a possibility of direct and indirect gains from the recurrent selection program. This molecular information will help direct selection of individuals for future recombination cycles.
Knowledge of the leaf characteristics of the coffee tree, such as leaf dimensions, is of great importance for management of this crop, since it directly impacts on plant development. We evaluated the genetic diversity of 43 Coffea canephora genotypes and developed and compared mathematical models for estimating the leaf area of distinct genotypes using linear characteristics. Leaves from 2½ year old trees were collected from the upper middle third of the plant and the length of the central vein and maximum width of the leaf were measured; the leaf area was subsequently measured to determine real leaf area (RLA). The variables leaf length (L), leaf width (W), RLA and length x width (LW) were subjected to Pearson correlation analysis and grouped by the Tocher optimization method. All combinations were tested by linear models according to the measured parameters, and for each model R2 was adjusted and Bayesian information criterion tested. After choosing the variable, equations were defined considering two parameters, which were subjected to cross-validation by comparing between observed x predicted areas. The 43 genotypes formed three groups according to the Tocher procedure, wherein one group was comprised of 41 genotypes. High Pearson linear correlations were found between LW x RLA (0.99), followed by W x RLA (0.95), and as such, LW best estimated the coffee leaf area; but the variable width can also be adopted, with greater ease of field measurement. The equations designed including both variables were significant at 1% and 0.1% according to the F test, and cross-validation analysis confirmed the adjustment of the equations, with equal or very similar values.
We compared two techniques of machine learning for the identification of cows that will be good producers of milk based on their genome-wide information. Data from a genome-wide genotyping panel, consisting of 164312 single nucleotide polymorphism markers (SNPs), within the 29 autosomal chromosomes, from 1092 Holstein cow samples were used for this study. Sample cows were divided as high-milk producers and low-milk producers based on their estimated breeding value of the 305 day average milk yield. Seven data sets were generated that grouped chromosomes with the highest number of SNPs related to milk production for prediction. Decision trees and artificial neural network algorithms were trained and tested, and the performance of prediction was computed. The mean prediction accuracy obtained with the decision tree algorithm was 92.44%, with a maximum of 94.5%, while the mean prediction accuracy obtained with the artificial neural network algorithm was 82.19%, with a maximum of 87.3%. Also, the decision tree algorithm permitted the identification of the most dominant single nucleotide polymorphism for prediction, which is situated within a milk-related quantitative trait locus in chromosome 14. Finally, our results add new evidence to support that machine learning algorithms may be used for managing genome-wide SNP markers, for implementing classification and prediction tools in the cattle industry.
Vimentin is a cytoskeletal protein belonging to a family of intermediate filaments whose expression has been studied in human cancers due to its association with the mesenchymal epithelial transition, a cancer reactivation event that results in complex alterations in the expression of genes involved in the invasion and metastasis processes. Studies on the prognostic value of vimentin, using immunohistochemistry are scarce, with conflicting results. Our evaluation was performed based on 111 cases of cervical cancer, including different clinical stages and histological types. Our objective was to evaluate the vimentin expression in cervical cancers, investigating a possible prognostic role of this biomarker. The evaluation was performed by immunohistochemistry in cases of cervical cancer and the marking index was evaluated with regards to clinical and pathological aspects, and to survival. Vimentin expression was observed in 100% of the tumor specimens. Hyperexpression of this biomarker in tumor cells (> 40%) was observed in 25% of the cases; however, it was not associated with clinical and pathological, or prognostic aspects of cervical cancer. Five-year survival for this group of patients was 66%; it was influenced by age, tumor size, presence of lymph node metastases, presence of distant metastases, and clinical stage. Hyperexpression of vimentin was not found to be a prognostic factor for cervical cancer.
Disordered anthropic action causes relevant impacts on different ecosystems. This may endanger key species and the compounds they produce, which have potential for commercial development. We collected environmental samples from the Bela Vista Biological Refuge, belonging to ITAIPU/Brazil, over a period of three years. A total of 181 fungal species were isolated and evaluated for cellulases and xylanases, 74% of which were classified as good enzymatic producers, with a production of up to 50 U/mL of xylanase and 7 U/mL for cellulase. A total of 34 isolates were selected and identified by amplification of internal transcribed spacer regions and then analyzed in BLASTn with 89-99% similarity/identity with others deposited in GenBank; the genera found were Aspergillus, Penicillium, Chaetomium, Clonostachys, Fusarium, Hypocrea, Paecilomyces, Thermoascus, Thermomyces, and Trichoderma. The enzymatic data reveals details of the roles of this biological community. The ability of these fungal species to utilize plant cell wall compounds discovered based on bioprospecting analysis of this biome is a pioneering study for this purpose in this region and points out important microorganisms that have potential for enzymatic production in biological biomass depolymerization, resulting in biotechnologically useful products.
Cowpea (Vigna unguiculata) is of great importance for human consumption due to its high nutritional value. The crop is grown in tropical and subtropical regions of the world; however, grain productivity is severely affected by water restriction imposed by long periods of drought in semiarid regions. We compared two contrasting cowpea genotypes for drought tolerance through proteomic analyses by identifying differentially expressed proteins responsive to water deficit and associating them with physiological responses. Water stress-tolerant (Pingo de Ouro 1,2) and sensitive (Santo Inácio) cowpea genotypes were submitted to moderate (Ypd = -1.0 MPa) and severe (Ypd = -1.5 MPa) water deficit conditions, re-irrigation after severe water deficit, and a full irrigation regime as a control. Physiological responses and expressed proteins in response to water stress were assessed. Pingo de Ouro 1,2 showed drought tolerance by delaying dehydration, being efficient in stomatal control, increasing photosynthesis and reducing transpiration rates. Based on proteomic analysis, 108 differentially expressed proteins were identified that may be associated with drought response in both tolerant and sensitive genotypes. Drought stress-response peptides, including glutamine synthetase, CPN60-2 chaperonin, malate dehydrogenase, heat-shock proteins, and rubisco were expressed differentially in both genotypes. The changes in the proteome in cowpea leaves in response to drought can help us understand the mechanisms and specific metabolic pathways involved in drought tolerant and drought sensitive cowpea genotypes.
We compared two statistical methodologies applied to genetic and genomic analyses of categorical traits. The first one consists of a Bayesian approach to the Bayesian Linear Mixed Model (BLMM), which addresses the statistical problems of genomic prediction. The second methodology, called Bayesian Generalized Linear Mixed Model (BGLMM) is similar, but it is used when the distribution of the response variable is not Gaussian, as in the case of disease resistance phenotype categories. These models were compared according to predictive ability, bias, computational time and cross validation error rate (CVER). Additionally, an alternative classification method for the BLMM was proposed, which allowed us to obtain the CVER for this model. Estimates of the genetic parameters were obtained using BLASSO (Bayesian Least Absolute Shrinkage and Selection Operator) and Bayesian G-BLUP (Genomic Best Linear Unbiased Prediction) estimation methods applied to BLMM and BGLMM. The models were applied in two scenarios, with two and four classes for the phenotype of resistance to rust disease caused by the pathogen Puccinia psidii and classified as reaction types (two classes) and infection levels (four classes) recorded for 559 trees of Eucalyptus urophylla with 24,806 SNP markers. Modeling this trait through SNPs allow the next generation of plants to be selected early, reducing time and costs. We found the same predictive ability for both models and a bias value closer to the ideal for BLMM (GBLUP). The BGLMM had the best CVER (0.29 against 0.32 and 0.47 against 0.51 for 2 and 4 categories, respectively), BLMM had a three times shorter computational time, and though BLMM is not the most appropriate model for handling categorical data, this model presented similar responses to BGLMM. Thus, we consider it as an appropriate alternative for categorical data modeling.
Genetic polymorphism of cytokine genes has been shown to be associated with susceptibility to diseases. We investigated the frequency of the IL-7 receptor-α +510 CT SNP in relation to pain and other symptoms among HIV and AIDS patients attended at various South African hospitals for treatment. Demographic as well as clinical data was obtained through structured interviews and patient files were consulted. A total of 107 mouth wash samples were obtained from volunteers, and DNA was extracted from these samples using the Qiagen protocol. Genotyping of the IL-7 receptor +510 CT SNP was conducted using sequence specific PCR. The CC and TC genotypes were the most common, while the TT genotype was rare (47.7, 45.8 and 6.5% respectively). The CC genotype was more common among patients who had body pain at the time they went for testing (χ2 = 4.75; P = 0.029) while the TC genotype was more common among those that did not have pain (χ2 = 6.86; P = 0.009). The TC genotype was also more common among patients who did not have genital sores (χ2 = 4.663; P = 0.031). The TT genotype was more common among patients whose infection state had improved as well as among those who had tuberculosis, although the differences were not significant. We concluded that the CC genotype is associated with pain while the TC genotype is protective of pain and genital sores. Further studies will be needed to confirm these hypotheses in larger populations.
Cerebral ischemia is one of the main causes of death in Brazil, according to a survey by the Brazilian Society of Neurology in 2000, being the third cause of death after cardiovascular diseases and cancer; it is also one of the major causes of permanent sequels that can result in disability. In the last decades, experimental studies have shown beneficial effects of physical exercise associated with cerebral ischemia. Several molecular mechanisms are involved in the pathophysiology of cerebral ischemia, including changes in neurotransmitter expression profiles. Current research has highlighted the role of microRNAs both in the process of cerebral ischemia and in the regulation of neurotransmitters. Therefore, analyzing the expression of neurotransmitters and microRNAs associated with cerebral ischemia, as well as the role of the benefits promoted by physical exercise may contribute to the elucidation of possible molecular pathways with neuroprotective effect. Forty-eight rats were divided into four experimental groups: control, cerebral ischemia through middle cerebral artery occlusion, physical exercise and physical exercise associated with cerebral ischemia. Real-time PCR methodology was used to analyze miRNA expression of miR15b, miR-29b, miR-219 and miR-222. We did not observe significant differences in miRNA expression in brain tissue in rats submitted to cerebral ischemia, physical exercise and both treatments when compared with the control group. However, miR-222 expression increased in the cerebral ischemia group submitted to physical exercise, which may help promote cerebrovascular regeneration.
Schizophrenia is considered one of the most severe and complex mental disorders; it affects both the quality of life of the patient and his family. The dopamine hypothesis is the main concept concerning antipsychotic activity. Patients with treatment-refractory schizophrenia have a lower capacity for dopamine synthesis than those with a good response to first-generation antipsychotics. The polymorphisms rs1800497, rs1799732 and rs6280were chosen for evaluation because they are associated with decreased dopamine receptor expression and occur in genes encoding these receptors, namely, ANKK1, DRD2 and DRD3, respectively. This effect caused by these polymorphisms enhances refractoriness to treatment. We investigated the frequency of these polymorphisms and evaluated their association with refractory schizophrenia. This was a case-control molecular genetic study, with patients who were divided into three groups of 72 participants each: patients with refractory schizophrenia, with schizophrenia and controls with no diagnosis of any type of mental disorder. All participants of the research were from the extended Midwest region of Minas Gerais. Polymorphisms were evaluated by PCR followed by RFLP. The allele and genotype frequencies were determined, the association tests performed using Pearson's Chi Square, and Odds Ratio values were estimated. Genotypic models of dominance and heterosis were constructed. An association of the Del C allele of rs1799732 polymorphism and schizophrenia (P = 0.03) was found. Further research on this subject is merited, since response to treatment is of utmost importance to the patient's quality of life.
Phosphorus is one of the most vital macronutrients required for growth and development of plants. A large number of microorganisms in the rhizosphere are known to solubilize and make available insoluble phosphorus, transforming it into phosphorus available to plants. We evaluated the phosphate solubilizing activity of native microbiota and phosphate solubilizing bacteria in rhizospheric soil with or without added rock dust (mainly granite dust) for enhancing growth of Jatropha curcas, an important plant for biodiesel production. The experiments were performed in a greenhouse with a random statistical design with 14 replicates. The soil received varying dosages of rock dust. Resident microorganism concentrations were measured, along with phosphorus content and enzymatic activity with focus on phosphatase, for 240 days. The highest content of phosphorus, 2.49, and dry biomass occurred in the presence of only soil-resident microbiota until 120 days, 70.45 in leaves; 73,98, in roots, and 105.44, in stalks. Soil samples under the influence of only resident microbiota had the highest enzymatic activity. The highest values were observed for acid phosphatase activity. Phosphatases showed values of 130.69 µg at 30 days, 155 µg, at 120 days, and 122.62 µg of p-nitrophenol.g-1soil.h- 1, at 210 days. Added rock dust and phosphate solubilizing bacteria did not improve plant growth.
In medicine, the 20th century was marked by one of the most important revolutions in infectious-disease management, the discovery and increasing use of antibiotics. However, their indiscriminate use has led to the emergence of multidrug-resistant (MDR) bacteria. Drug resistance and other factors, such as the production of bacterial biofilms, have resulted in high recurrence rates of bacterial diseases. Bacterial vaginosis (BV) syndrome is the most prevalent vaginal condition in women of reproductive age, leading to considerable discomfort. BV can be a consequence of gynecological and obstetric complications, as well as sexually transmitted diseases. Given the decrease in efficiency of antibiotic therapy and high rates of recurrence, probiotics have become promising alternatives for both prevention and treatment of BV, or as an adjuvant to conventional therapy. Currently, Lactobacillus species are the most extensively studied for use as probiotics. Probiotics act through stimulation of the host immune system, competitive exclusion and antimicrobial activity; the latter involves production of substances such as lactic acid, hydrogen peroxide and bacteriocins. Lactobacillus crispatus is considered to be a biomarker of a healthy vaginal tract and is indicated for a probiotic approach to maintaining and restoring of a healthy vaginal ecosystem. Some L. crispatus probiotic strains are already commercially available with encouraging results; however, control of BV syndrome still presents many challenges.
Glioblastoma is considered incurable, even with a combination of therapies (chemo and radiotherapy), and surgical resection. New therapeutic approaches are needed to improve the prognosis of patients with glioblastoma. In recent decades, research has focused on molecular biology of brain tumors. We examined the role of programmed cell death, apoptosis, through two microRNAs that act as possible pro and anti-apoptotic gene regulators. We evaluated the expression of the genes CASPASE-8 and C-FLIP and microRNAs miR-126-5p and miR-873-5p in adhered cells (AC) and neurospheres (NS) from cell line U343, which were submitted to temozolomide (TMZ) and ionizing radiation (IR), isolated and associated (TMZ + IR). We concluded that microRNA-126 and 873 were differentially expressed as as a function of treatment regime in glioblastomas. The higher expression of the caspase-8 gene in adhered cells in the group treated with IR when compared to the other groups at time 48 h suggests that the ionizing radiation in the adhered cells of the glioblastoma cell line culture has apoptosis-inducing properties.