RESUMO
Knowledge of genetic diversity is important to assist breeders in the selection of parental materials and in the design of breeding programs. In this study, we genotyped 348 inbred tomato lines, representing vintage and contemporary fresh-market varieties, by using 52 single nucleotide polymorphisms (SNPs); 45 of these were found to be polymorphic. The average minor allele frequency and unbiased expected heterozygosity were 0.315 and 0.356, respectively. Population structure analysis revealed that contemporary germplasm could be distinctly divided into six subpopulations representing three market classes and breeding programs (pink, green, and red). Vintage germplasm could be separated into at least two subpopulations, and more admixtures were found in vintage lines than in contemporary lines. These findings indicate that contemporary inbred lines are more diversified than vintage inbred lines. AMOVA of vintage and contemporary lines was performed. A significant difference was found (P < 0.01), which explained 17.4% of the total genetic variance. Subsequently, we constructed a core collection using 45 polymorphic SNP markers. The data showed that all alleles were captured by only 2% of lines, indicating that more alleles, as well as rare alleles, could enable more variation to be captured in the core collection. These data allow us to discard redundant inbred tomato lines and to select elite inbred lines, which will accelerate the breeding process.
Assuntos
Polimorfismo de Nucleotídeo Único , Sementes/genética , Solanum lycopersicum/genética , Frequência do Gene , Genes de Plantas , Estudos de Associação Genética , Marcadores Genéticos , Genótipo , Melhoramento Vegetal , Análise de Sequência de DNARESUMO
This study aims to investigate the association between ERCC1 codon C118T polymorphism and the response rate of platinum-based chemotherapy in patients with late-stage bladder cancer. A total of 41 eligible patients histologically confirmed as having stage IV muscle-invasive transitional cell carcinoma of the bladder were treated with platinum-based chemotherapy for 2-6 cycles. The genotypes of patients were determined by PCR amplification of genomic DNA followed by restriction enzyme digestion. Positive responses were categorized as complete and partial responses. In addition, progression-free survival (PFS) and overall survival (OS) were also determined as indicators of long-term outcomes. The genotype frequencies of C/C, C/T and T/T genotypes were 56.1, 34.1, and 9.8%, respectively. Positive response was observed in 14 patients (34.1%), while 27 patients (65.9%) were negative responders. As compared with individuals carrying the C/T and T/T genotypes, those with the C/C genotype had significantly improved short-term treatment responses (P = 0.018). The median PFS of patients carrying the C/C genotype was 6.3 months, while that of patients with C/T and T/T genotypes was 4.2 months (P = 0.023). Moreover, the median OS for patients carrying the C/C genotype was also longer as compared with that of patients carrying C/T and T/T (11.7 months vs 8.5 months, P = 0.040). Our results indicated that the ERCC1 codon 118 polymorphism may have predictive potential for chemotherapy treatment responses in late-stage bladder cancer patients.
Assuntos
Biomarcadores Tumorais/genética , Proteínas de Ligação a DNA/genética , Resistencia a Medicamentos Antineoplásicos/genética , Endonucleases/genética , Neoplasias da Bexiga Urinária/tratamento farmacológico , Adulto , Idoso , Cisplatino/administração & dosagem , Cisplatino/efeitos adversos , Intervalo Livre de Doença , Feminino , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Neoplasias da Bexiga Urinária/genética , Neoplasias da Bexiga Urinária/patologiaRESUMO
INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor of the pancreas with poor prognosis. The lack of understanding of the molecular mechanisms of PDAC and biomarkers for early diagnosis might be two of the reasons for the poor prognosis of PDAC. MATERIALS AND METHODS: ILK and ERP29 protein expressions in PDAC, peritumoral tissues, benign pancreatic lesions, and normal pancreatic tissues were measured by immunohistochemistry and the clinical and pathological significances of ILK and ERP29 in PDAC were analyzed. RESULTS: The percentages of positive ILK and negative ERP29 expressions were significantly higher in PDAC tumors than in peritumoral tissues, benign pancreatic tissues, and normal pancreatic tissues (P < 0.01). Benign pancreatic lesions with positive ILK and negative ERP29 expressions exhibited dysplasia or intraepithelial neoplasia. The percentage of cases with positive ILK and negative ERP29 expressions was significantly lower in PDAC patients without lymph node metastasis and invasion, and having TNM stage I/II disease than in patients with lymph node metastasis, invasion, and TNM stage III/IV disease (P < 0.05 or P < 0.01). Kaplan-Meier survival analysis showed that positive ILK and negative ERP29 expressions were significantly associated with survival in PDAC patients (P < 0.001). Cox multivariate analysis revealed that positive ILK and negative ERP29 expressions were independent poor prognosis factors in PDAC patients. CONCLUSIONS: Positive ILK and negative ERP29 expressions are associated with the progression of PDAC and poor prognosis in patients with PDAC.
Assuntos
Adenocarcinoma/secundário , Biomarcadores Tumorais/metabolismo , Carcinoma Ductal Pancreático/secundário , Proteínas de Choque Térmico/metabolismo , Neoplasias Pancreáticas/patologia , Proteínas Serina-Treonina Quinases/metabolismo , Adenocarcinoma/metabolismo , Carcinoma Ductal Pancreático/metabolismo , Progressão da Doença , Feminino , Seguimentos , Humanos , Técnicas Imunoenzimáticas , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica , Estadiamento de Neoplasias , Neoplasias Pancreáticas/metabolismo , Prognóstico , Taxa de Sobrevida , Neoplasias PancreáticasRESUMO
Immunoglobulin and cortisol levels are good indicators of well-being and living status in animals. In this study, the concentrations of fecal immunoglobulins A ([IgAF]), G ([IgGF]), and M ([IgMF]), and cortisol ([cortisolF]) were examined by enzyme-linked immunosorbent assay in reindeer of the Greater Khingan Mountains of Inner Mongolia, China. [IgAF] was significantly higher than [IgGF] and [IgMF], and [IgGF] was significantly higher than [IgMF] (P < 0.05). Both [IgAF] and [IgGF] were higher in the Adult group than in Aged or Infant groups, and higher in the Young than Infant group (P < 0.05). The four age group [IgMF]s were not significantly different (P > 0.05). [IgAF], [IgGF], and [IgMF] in each age group were higher in females than in males, with a significant difference in the Young group (P < 0.05). The Infant group had the highest [cortisolF], and the Adult group the lowest; [cortisolF] was significantly higher in the Infant group than in other age groups (P < 0.05). In each age group, [cortisolF] was higher in females than males, and there were significant differences among the Infant, Young, and Aged groups (P < 0.05). A significant negative correlation was observed between [cortisolF] and [IgAF] and [IgGF] (P > 0.05). Overall physical condition was better in the Adult and Young groups than in the Aged and Infant groups as determined by the comprehensive analysis of fecal Ig levels in the four age groups, with the Infant group the worst.
Assuntos
Hidrocortisona/análise , Imunidade Inata , Imunoglobulina A/análise , Imunoglobulina G/análise , Imunoglobulina M/análise , Rena/imunologia , Fatores Etários , Animais , China , Ensaio de Imunoadsorção Enzimática , Fezes/química , Feminino , Masculino , Fatores SexuaisRESUMO
Imbalances typically exist in bioinformatics and are also common in other areas. A drawback of traditional machine learning methods is the relatively little attention given to small sample classification. Thus, we developed imDC, which uses an ensemble learning concept in combination with weights and sample misclassification information to effectively classify imbalanced data. Our method showed better results when compared to other algorithms with UCI machine learning datasets and microRNA data.
Assuntos
Algoritmos , Aprendizado de Máquina , MicroRNAs/genética , Bases de Dados Genéticas , MicroRNAs/metabolismo , Curva ROC , Reprodutibilidade dos TestesRESUMO
PURPOSE: To identify biological markers related to the progression and prognosis of GBC. METHODS: The expressions of pyruvate kinase isoenzyme type M2 (PKM2) and activin A receptor type IC (ACVR 1C) in 46 squamous cell/adenosquamous carcinomas (SC/ASC) and 80 adenocarcinomas (AC) were examined using immunohistochemistry. RESULTS: Positive PKM2 and negative ACVR 1C expressions were significantly associated with lymph node metastasis, invasion and TNM stage of SC/ASCs and ACs. Univariate Kaplan-Meier analysis showed that either elevated PKM2 or loss of ACVR 1C expression significantly correlated with shorter average survival times in both SC/ASC and AC patients. Multivariate Cox regression analysis showed that positive PKM2 expression and loss of ACVR 1C expression were poor prognosis biomarkers in both SC/ASC and AC patients. CONCLUSIONS: Our study suggested that PKM2 overexpression is a marker of metastasis, invasion and poor prognosis of GBC. ACVR 1C is a tumor suppressor, and lowered ACVR 1C expression is an important marker for the metastasis, invasion, and prognosis of GBC.
Assuntos
Receptores de Ativinas Tipo I/fisiologia , Adenocarcinoma/diagnóstico , Biomarcadores Tumorais , Carcinoma Adenoescamoso/diagnóstico , Carcinoma de Células Escamosas/diagnóstico , Proteínas de Transporte/fisiologia , Neoplasias da Vesícula Biliar/diagnóstico , Proteínas de Membrana/fisiologia , Hormônios Tireóideos/fisiologia , Receptores de Ativinas Tipo I/metabolismo , Adenocarcinoma/metabolismo , Adenocarcinoma/mortalidade , Adenocarcinoma/patologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Biomarcadores Tumorais/metabolismo , Carcinoma Adenoescamoso/metabolismo , Carcinoma Adenoescamoso/mortalidade , Carcinoma Adenoescamoso/patologia , Carcinoma de Células Escamosas/metabolismo , Carcinoma de Células Escamosas/mortalidade , Carcinoma de Células Escamosas/patologia , Proteínas de Transporte/metabolismo , Feminino , Neoplasias da Vesícula Biliar/metabolismo , Neoplasias da Vesícula Biliar/mortalidade , Neoplasias da Vesícula Biliar/patologia , Humanos , Masculino , Proteínas de Membrana/metabolismo , Pessoa de Meia-Idade , Metástase Neoplásica , Prognóstico , Hormônios Tireóideos/metabolismo , Proteínas de Ligação a Hormônio da TireoideRESUMO
The oriental leafworm moth, Spodoptera litura, is a major agricultural pest in southeast Asia and nearby Pacific regions. Two distinct trehalases have been identified in insects: soluble trehalase (Treh1) and membrane-bound trehalase (Treh2), although there is currently no information on these genes in S. litura. To characterize the distribution and function of treh, cDNAs of Treh proteins were cloned from S. litura. SpoliTreh1 cDNA has an open reading frame of 1758 nucleotides, which encodes a protein of 585 amino acids, with a predicted mass of approximately 67.07 kDa and an isoelectric point of 4.86. SpoliTreh2 cDNA has an open reading frame of 2325 nucleotides, encoding a protein of 645 amino acids, a mass of approximately 73.62 kDa, and an isoelectric point of 5.90. Northern blotting analysis revealed that SpoliTreh1 transcripts are in the midgut, fat body, tracheae, and epidermis, but not in the brain and Malpighian tubules of S. litura larvae, whereas SpoliTreh2 transcripts were found in all 6 tissues. SpoliTreh1 transcripts were highly expressed in the fat body of the pre-pupal stage, and SpoliTreh2 transcripts were highly expressed in the fat body of 3-day-old larvae of the 6th instar and during the 1st 6 days of the pupal stage, except the 2nd day. Both SpoliTreh1 and SpoliTreh2 were highly expressed in third-instar larvae.
Assuntos
Clonagem Molecular , DNA Complementar , Spodoptera/enzimologia , Spodoptera/genética , Trealase/genética , Trealase/metabolismo , Sequência de Aminoácidos , Animais , Sequência de Bases , Regulação da Expressão Gênica , Dados de Sequência Molecular , Família Multigênica , Especificidade de Órgãos/genética , Filogenia , Alinhamento de Sequência , Análise de Sequência de DNA , Spodoptera/classificação , Trealase/químicaRESUMO
MicroRNAs (miRNAs) are short, non-coding RNA molecules that play an important role in the world of genes, especially in regulating the gene expression of target messenger RNAs through cleavage or translational repression of messenger RNA. Ab initio methods have become popular in computational miRNA detection. Most software tools are designed to distinguish miRNA precursors from pseudo-hairpins, but a few can mine miRNA from genome or expressed sequence tag sequences. We prepared novel testing datasets to measure and compare the performance of various software tools. Furthermore, we summarized the miRNA mining methods that study next-generation sequencing data for bioinformatics researchers who are analyzing these data. Because secondary structure is an important feature in the identification of miRNA, we analyzed the influence of various secondary structure prediction software tools on miRNA identification. MiPred was the most effective for classifying real-/pseudo-pre-miRNA sequences, and miRAbela performed relatively better for mining miRNA precursors from genome or expressed sequence tag sequences. RNA-fold performed better than m-fold for extracting secondary structure features of miRNA precursors.
Assuntos
MicroRNAs/genética , Software , Benchmarking , Simulação por Computador , Mineração de Dados , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Sequências Repetidas Invertidas , Conformação de Ácido Nucleico , Análise de Sequência de RNA , Máquina de Vetores de SuporteRESUMO
Protein folding is recognized as a critical problem in the field of biophysics in the 21st century. Predicting protein-folding patterns is challenging due to the complex structure of proteins. In an attempt to solve this problem, we employed ensemble classifiers to improve prediction accuracy. In our experiments, 188-dimensional features were extracted based on the composition and physical-chemical property of proteins and 20-dimensional features were selected using a coupled position-specific scoring matrix. Compared with traditional prediction methods, these methods were superior in terms of prediction accuracy. The 188-dimensional feature-based method achieved 71.2% accuracy in five cross-validations. The accuracy rose to 77% when we used a 20-dimensional feature vector. These methods were used on recent data, with 54.2% accuracy. Source codes and dataset, together with web server and software tools for prediction, are available at: http://datamining.xmu.edu.cn/main/~cwc/ProteinPredict.html.
Assuntos
Dobramento de Proteína , Estrutura Secundária de Proteína , Proteínas/química , Bases de Dados de Proteínas , Reconhecimento Automatizado de Padrão/métodos , Proteômica , Análise de Sequência de Proteína , SoftwareRESUMO
We propose a novel representation of RNA secondary structure for a quick comparison of different structures. Secondary structure was viewed as a set of stems and each stem was represented by two values according to its position. Using this representation, we improved the comparative sequence analysis method results and the minimum free-energy model. In the comparative sequence analysis method, a novel algorithm independent of multiple sequence alignment was developed to improve performance. When dealing with a single-RNA sequence, the minimum free-energy model is improved by combining it with RNA class information. Secondary structure prediction experiments were done on tRNA and RNAse P RNA; sensitivity and specificity were both improved. Furthermore, software programs were developed for non-commercial use.
Assuntos
Algoritmos , Conformação de Ácido Nucleico , RNA Arqueal/química , RNA Bacteriano/química , RNA de Protozoário/química , RNA de Transferência/química , Anaplasma marginale/genética , Sequência de Bases , Halobacterium/genética , Dados de Sequência Molecular , Plasmodium falciparum/genética , Alinhamento de Sequência , Análise de Sequência de RNA/métodos , TermodinâmicaRESUMO
Abundant single nucleotide polymorphisms (SNPs) provide the most complete information for genome-wide association studies. However, due to the bottleneck of manual discovery of putative SNPs and the inaccessibility of the original sequencing reads, it is essential to develop a more efficient and accurate computational method for automated SNP detection. We propose a novel computational method to rapidly find true SNPs in public-available EST (expressed sequence tag) databases; this method is implemented as SNPDigger. EST sequences are clustered and aligned. SNP candidates are then obtained according to a measure of redundant frequency. Several new informative biological features, such as the structural neighbor profiles and the physical position of the SNP, were extracted from EST sequences, and the effectiveness of these features was demonstrated. An ensemble classifier, which employs a carefully selected feature set, was included for the imbalanced training data. The sensitivity and specificity of our method both exceeded 80% for human genetic data in the cross validation. Our method enables detection of SNPs from the user's own EST dataset and can be used on species for which there is no genome data. Our tests showed that this method can effectively guide SNP discovery in ESTs and will be useful to avoid and save the cost of biological analyses.