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“Omics” Technologies in Vaccine Research
Published in Mesut Karahan, Synthetic Peptide Vaccine Models, 2021
In order to identify candidate antigens from Ctenocephalides felis for vaccine development against cat flea, transcriptomics data were evaluated from unfed adult fleas. RNA-seq analysis produced 59,558 transcripts and 11,627 unigenes, of which 1620 unigenes were predicted in the exoproteome, 177 of them encoding proteins with transmembrane regions or signal peptides. The gene ontology (GO) analysis of these unigenes showed that 96% of the proteins belonged to cell membrane or extracellular space. Among them, six proteins were selected as candidate antigens, combining with proteomics data (Contreras et al. 2018).
Gene Expression Profiling to Detect New Treatment Targets in Leukemia and Lymphoma: A Future Perspective
Published in Gertjan J. L. Kaspers, Bertrand Coiffier, Michael C. Heinrich, Elihu Estey, Innovative Leukemia and Lymphoma Therapy, 2019
Torsten Haferlach, Wolfgang Kern, Alexander Kohlmann
In addition to all the sequences represented on the HG-U133A and HG-U133B two-array set, the HG-U133 Plus 2.0 microarray also covers 9921 new probe sets representing approximately 6500 new genes. These gene sequences were selected from GenBank, dbEST, and RefSeq. Sequence clusters were created from the UniGene database (Build 159, January 25, 2003) and refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the NCBI human genome assembly Build 31 (www.affymetrix.com). Thus, in using this comprehensive whole human genome expression array, an extensive coverage of the human genome is reached. HG-U133 Plus 2.0 microarrays are manufactured as standard format arrays with more than 54,000 probe sets of a feature size of 11 µm and use 11 probe pairs per sequence. The oligonucleotide length is 25 mer.
Molecular biology
Published in Maxine Lintern, Laboratory Skills for Science and Medicine, 2018
There are many web-based resources to help you prepare for your experiments. In fact a lot can be achieved in silico before you even put on a lab coat. Since the completion of the human and other genomes there is an increasing need to be computer savvy and make use of web-based programs and databases. The National Center for Biotechnology Information (NCBI) website7 supports the GenBank DNA sequence database. Using the Entrez tool,8 you’ll be able to search and retrieve RNA, DNA and protein sequences from various organisms. In addition NCBI supports databases such as Online Mendelian Inheritance in Man (OMIM),9 Unique Human Gene Sequence Collection (UniGene),10 and The Cancer Genome Anatomy Project (CGAP).11 Useful programs available on the NCBI website include BLAST,12 which is a powerful sequence similarity searching tool for nucleotide and protein sequences, and Open Reading Frame Finder (ORF Finder).13 For those important literature searches there’s PubMed,14 which provides access to MEDLINE,15 and will allow you to peruse over 11 million citations.
The gut microbiome and metabolome in kidney transplant recipients with normal and moderately decreased kidney function
Published in Renal Failure, 2023
Yang Lan, Duo Wang, Jiayang He, Hongji Yang, Yifu Hou, Wenjia Di, Hailian Wang, Xiangwei Luo, Liang Wei
Analysis of the Microbiota. Krona analysis, the exhibition of generation situation of relative abundance, the exhibition of abundance cluster heat map, principal coordinate analysis (PCoA) [19] (R ade4 package, Version 2.15.3) and non-metric multidimensional scaling (NMDS) [20] (R vegan. package, Version 2.15.3) decrease-dimension analysis are based on the abundance table of each taxonomic hierarchy. The difference between groups is tested by Anosim analysis. Metastats and LEfSe analysis are used to look for the different species between groups. LEfSe analysis is conducted by LEfSe software (the default LDA score is 3) [21]. Random forest (RandoForest) (R pROC and randomForest packages, Version 2.15.3) was used to construct a random forest model. A heat map reveals the function difference between microbial communities of CKD G1-2T and CKD G-3T. (Zscore method is applied to the preprocessing of original data.). Screen out important species by MeanDecreaseAccuracy and MeanDecreaseGin, 24 CKD G1-2T and 22 CKD G3T samples were randomly divided into the training set, and the remaining participants were incorporated into the testing set. Then cross-validate each model (default 10 times) and plot the ROC curve. Adopt DIAMOND software (V0.9.9) to blast Unigenes to functional database. Statistic of the relative abundance of different functional hierarchy.
Comparative transcriptome analysis reveals the impact of the daily rhythm on the hemolymph of the Chinese mitten crab (Eriocheir sinensis)
Published in Chronobiology International, 2022
Changyue Yu, Baoli Zhang, Zhiyuan Zhang, Simiao Wang, Tingyu Wei, Lisong Li, Yingying Zhao, Hua Wei, Yingdong Li
Once the original FASTQ data had filtered the reads with connectors, length less than 50 bp, and average sequence quality less than Q20 were removed. The high-quality sequences were spliced from scratch to obtain transcripts. The transcripts were clustered, and the longest transcripts were selected as unigenes. The gene function of each unigene was annotated. The databases used for gene function annotation included Non-Redundant Protein Sequence Database (NR) (https://ftp.ncbi.nlm.nih.gov/blast/db/FASTA/), Gene Ontology (GO) (http://geneontology.org/), Kyoto Encyclopedia of Genes and Genome (KEGG) (https://www.kegg.jp/), evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG) (http://eggnog5.embl.de/), Swiss-Prot (http://www.gpmaw.com/html/swiss-prot.html), and Pfam (http://pfam.xfam.org/).
YjbH mediates the oxidative stress response and infection by regulating SpxA1 and the phosphoenolpyruvate-carbohydrate phosphotransferase system (PTS) in Listeria monocytogenes
Published in Gut Microbes, 2021
Changyong Cheng, Xiao Han, Jiali Xu, Jing Sun, Kang Li, Yue Han, Mianmian Chen, Houhui Song
RSEM (RNA-Seq by Expectation-Maximization)65 was used to quantify gene and isoform abundance. EdgeR (Empirical analysis of digital gene expression data in R)66 was utilized for differential expression analysis. Mapped read count normalization was applied to the data based on the number of reads per kilobase of coding sequence per million mapped reads (RPKM).67 The TMM (trimmed mean of M-values) method was selected to compute normalization factors and differentially expressed genes (DEGs) between two samples selected using the following criteria: (i) logarithmic of fold change greater than 1.0 and (ii) FDR (false discovery rate) less than 0.05. To determine the functions of the differentially expressed genes, the unigenes were aligned by BLASTx against the NCBI non-redundant, Swiss-Prot, KEGG, and Cluster of Orthologous Groups (COG) protein databases. GO functional enrichment analyses were carried out using Goatools and KOBAS.68 DEGs were significantly enriched in GO terms and metabolic pathways at Bonferroni-corrected P-values of less than 0.05.