01. Universidade Federal Rural de Pernambuco - UFRPE (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/1
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Resultados da Pesquisa
Item Levantamento e análise da variabilidade genética do gênero Siderastrea Blainville, 1830(2024-10-04) Lira, Jean Tácio Tôrres de; Amaral, Fernanda Maria Duarte do; http://lattes.cnpq.br/7026011892824176; http://lattes.cnpq.br/0569107903225207This study aimed to fill gaps in knowledge about the genetic and phylogenetic diversity of the genus Siderastrea (Blainville, 1830), important coral reef-building organisms, with a greater focus on the species Siderastrea stellata (Verrill, 1868). Partially bleached colonies of the species S. stellata were collected on Gaibu beach, from November 2022 to January 2023 and the genomic DNA of the colonies was extracted using the Wizard Genomic DNA Purification Kit. A specific primer pair was designed to confirm the species S. stellata and the identification of the colonies was performed by the conventional PCR technique. The analysis of the variability between the colonies was performed by the RAPD technique using 06 random ITS primers. Furthermore, to analyze whether there was genetic variability among the S. stellata samples in the Genbank genomic database, we downloaded all sequences and performed sequence alignment. Subsequently, phylogenetic analyses were performed among the deposited samples using the Mega platform. Finally, in silico restriction enzyme analyses were performed to search for restriction enzymes that could be used to differentiate between the isolates. The results obtained with the RAPD technique did not provide sufficient data to identify genetic variability among the samples analyzed in the present study. On the other hand, regarding the data from the phylogenetic analysis, it was possible to find differences between the sequences of isolates from different regions. There was greater genetic proximity between S. stellata isolates from Panama and Brazil and less proximity to the isolate from Mexico. Siderastrea savigneana stood out as the most distant ancestor within the genus. In addition, it was possible to detect preliminary genetic variations among the populations evaluated, using data from the in silico restriction analysis. Thus, this study provides a first approach to genetic analysis of variability within the species of S. stellata. However, more in-depth studies are needed and may help to clarify the complexity of the genetic variability of the genus, in addition to assisting in management and conservation strategies for these organisms and the marine ecosystems they support.Item Predição por análise in silico da consequência de mutação missense no gene IGF2 humano(2023-09-04) Costa, Karla Roberta Lemos Maul de Souza; Maia, Maria de Mascena Diniz; http://lattes.cnpq.br/7051998554981575; http://lattes.cnpq.br/8727605240852776Item Métodos computacionais para a análise de dados de expressão gênica provenientes de uma análise de microarray utilizada para teste farmacológico(2023-04-28) Costa, Allan Mesquita da; Melo, Jeane Cecília Bezerra de; Costa, Luciana Amaral de Mascena; http://lattes.cnpq.br/2352032088330896; http://lattes.cnpq.br/8499459630583005; http://lattes.cnpq.br/2703136397519338The advent of the Human Genome Project (HGP), completed in October 2003, propelled the development of techniques for obtaining and analyzing biological data. The need to manage the vast amount of digital genome data was a decisive factor in the growth of a multidisciplinary area of knowledge, Computational Biology. In the two decades following the completion of the HGP, genomes of different organisms were obtained. Regarding mammals, projects such as the 1000 Genomes Project and the Cancer Genome Atlas (TCGA) illustrated the advancement of knowledge in the analysis of complex data. Among the newest techniques, we highlight Microarrays. They provide a significant amount of data in a single experiment, allowing the comparison of complete genomes. The analysis of Microarray data is relatively complex and requires protocols that make this analysis simpler, producing more understandable information. The present study involves the use of computational methods to analyze gene expression data obtained from a Microarray experiment used for pharmacological testing related to breast cancer. To process the raw data, obtained from a spreadsheet containing more than 3216 genes resulting from a Microarray analysis, a script was developed to facilitate the extraction of information from this data and subsequent selection of genes of interest. The program allowed the search for genes involved in the processes of cell death (apoptosis, necrosis, and autophagy), which are determining factors in the success analysis of the tested drug. To categorize the genes involved in the apoptotic, necrotic, and autophagic death cascade, heatmaps were constructed from fold-change values (difference in gene expression for values before and after treatment of cancerous cells with the mesoionic compound), using k-means clustering and hierarchical clustering techniques provided in the Heatmapper program. Results of the study include the development of a script in the R program that resulted in the separation of 20 genes involved in the apoptotic death cascade, six involved in the autophagic death, and seven involved in the necrotic death cascade, as well as the development of three heatmaps, contributing to the biological analysis of data, in addition to making Microarray data processing more accessible.Item Análise in silico de Polimorfismo de Nucleotídeo Único (SNP) de variantes missense do gene IL17A(2022-10-06) Silva, João Gabriel da; Maia, Maria de Mascena Diniz; http://lattes.cnpq.br/7051998554981575Item Desenvolvimento e validação de marcadores moleculares tipo microssatélites a partir do transcriptoma de Vigna unguiculata (L.) Walp.(2019-07-17) Oliveira, Wilson Dias de; Iseppon, Ana Maria Benko; Araújo, Flávia Czekalski de; http://lattes.cnpq.br/1888011932745430; http://lattes.cnpq.br/7796654028353519; http://lattes.cnpq.br/3544882037972617Genetic improvement of plants has potentiated continuous gains in the productivity of several crops. In this context, molecular markers stand out as a promising tool, which allows direct access to the genotype of the individual, thus differentiating it self from the morphological markers. Microsatellites (SSR) are codominant markers and are among the most used for this purpose. Thus, the present work aimed to develop and validate SSR markers for use in genetic improvement programs of cowpea [Vigna unguiculata (L.) Walp.]. For this, three transcripts of the species, from experiments by CPSMV (Cowpea Severe Mosaic Virus), CABMV (Cowpea Aphid-born Mosaic Virus) and root dehydration were analyzed. A computational pipeline was used to identify and annotate SSRs. The selection of the candidates for the development of the markers was performed considering the polymorphism of size between the motifs, followed for the design of the primers using the SnapGene tool. 45,776 sequences containing SSRs were identified, among which the di- and trinucleotide motifs prevailed, together representing a total of 60% of the sequences identified. Of these, 3,493 sequences were present in the three transcripts analyzed, where 160 were selected based on the most significant difference in size (12-42) among the motifs, followed by the design of 30 SSRs. In the conventional PCR step, it was observed that 73% of the markers confirmed polymorphism between the BR 14-Mulato and IT85F-2687 accessions, while 57% were polymorphic between Pingo de Ouro and Santo Inácio. A total of 23 markers were transferable to V. unguiculata subsp. sesquipedalis and 16 for V. radiata (L.). Finally, the analysis allowed the identification of SSRs in the transcriptomes of cowpea, submitted to biotic and abiotic stresses, revealing polymorphisms between different accessions. The data identified, analyzed and validated will contribute to studies of genetic diversity and pre-breeding, aiming to broaden the available genetic base of cowpea.