Impact of Integrated Omics Technologies for Identification of Key Genes and Enhanced Artemisinin Production in Artemisia annua L.
Tariq Aftab, M. Naeem, M. Masroor, A. Khan in Artemisia annua, 2017
Genomics is the systematic study of an organism’s genome with the help of molecular tools. Traditionally, genes have been analyzed individually, but microarray technology has advanced substantially in recent years. Various steps of genome analysis involve (1) genome sequencing, (2) identification of repetitive as well as unique sequences, (3) gene prediction, (4) identification of functional expressed sequence tags (ESTs) and complementary DNA (cDNA) sequences, and (5) genome annotation and gene location/gene mapping. Recently, DNA microarray techniques have evolved as a powerful tool, which has the potential to measure differences in DNA sequences between individuals and the expression of thousands of genes simultaneously.
Functional Omics and Big Data Analysis in Microalgae
Gokare A. Ravishankar, Ranga Rao Ambati in Handbook of Algal Technologies and Phytochemicals, 2019
The metabolism of a living organism is the complete set of chemical reactions required for life; numerous enzymes efficiently play the role of catalysts in these reactions. There are usually two main points to be considered while studying these reactions: first by kinetics, i.e., unknown for most of the reactions and other is through determination of stoichiometry (Baart and Martens 2012). Genome-scale metabolic models (GSMMs) can be constructed and modeled once, after gathering enough of the annotated algal genome or transcriptome data available and topology of the metabolic network is analyzed. Initial draft models are generated directly from the available genome annotation data and finalized simultaneously by adding various experimental datasets, literature review and gap-filling steps; the final model evolves with the inclusion of all the reactions alga performs and various associated genes and constraints (Reijnders et al. 2014).
Mycobacterium
Dongyou Liu in Laboratory Models for Foodborne Infections, 2017
This section provides a short description and also important information related to genome annotation and the whole genome comparison of some currently available sequenced strains of Mycobacterium spp., with special attention to MAP and MTBC. Table 12.1 shows Genbank information and basic features, such as the chromosome length, %GC, and total number of CDS of the genomes used in this analysis. M. tuberculosis H37Rv was included as an outgroup in the comparison, since it is closely related with M. bovis and M. avium spp. and, on the other hand, branched from the parent group before any other one in this set of genomes.
Advances, challenges and tools in characterizing bacterial serine, threonine and tyrosine kinases and phosphorylation target sites.
Published in Expert Review of Proteomics, 2019
Giovanni J. Pagano, Ryan J. Arsenault
It will also be necessary to explore the larger biological context for each of these target sites and the proteins and pathways they are a part of. Consideration should be given to the activating/inhibiting nature of the phosphorylation, the three-dimensional structure and the upstream and downstream pieces of the signaling pathway. Every one of these lines of research has its own challenges, but they can inform each other and provide new insights into bacterial phosphoproteomics when integrated together. High-throughput and low-throughput biochemistry or bioinformatics techniques will all be vital to this understanding, along with interdisciplinary collaborative efforts between researchers. Central to these collaboration efforts will be online databases that contain phosphosite data in a standard format that can be easily accessed by users. Several databases with these features were mentioned in the review, but a common weakness is the inability of scientists to add their own annotations and data to proteins of interest. Future iterations of these or other databases need to include avenues for community participation, in a manner accessible to people of all bioinformatics skill levels. As the continuing research of bacteriologists and biochemists on bacterial phosphorylation should be disseminated efficiently without the need for extensive bioinformatics training. Projects for genome annotation by a community already exist, so developing a similar pipeline for proteomic annotations is a feasible goal.
Mining for missed sORF-encoded peptides
Published in Expert Review of Proteomics, 2019
Xinqiang Yin, Yuanyuan Jing, Hanmei Xu
With the identification of some SEPs, researchers have shown more interests in this field. But there are many challenges in discovering sORFs and identifying the true coding sORFs. First of all, short coding sequences have been excluded from the initial genome annotation pipeline for a long time for the assumption that most of the coding genes are longer than 100 codons [37]. Secondly, it’s difficult to detect SEPs for their small size, low abundance, and even short life, in spite of great progress made in detection techniques. Thirdly, the usage of alternative start codons makes the identification process even more difficult [38]. Furthermore, several stop codon readthrough cases have been reported, which presents a challenge for the identification of stop codons and potential coding sORF [39–42]. Finally, although thousands of sORFs have been disclosed, how to distinguish between true coding sORFs and noncoding ones still is a big challenge. Here, we present an overview of the advances in the strategies that have been successfully implemented to identify novel SEPs. Both the advantages and disadvantages of all of the strategies are discussed. Furthermore, we described the techniques that are used to decipher the biological functions of micropeptides.
Identification of key biomolecules in rheumatoid arthritis through the reconstruction of comprehensive disease-specific biological networks
Published in Autoimmunity, 2020
Enrichment analyses were carried out through the ConsensusPathDB functional annotation tool [36] to find out crucial biological pathways significantly associated with DEGs. Kyoto Encyclopaedia of Genes and Genomes (KEGG) [37] and Reactome [38] was preferably employed as the pathway database and enrichment results with p-value < .01 were considered as statistically significant. Over-represented sets are searched at pathway-based sets. For each of the predefined sets, a p-value is calculated according to the hypergeometric test. Whole-genome annotation for the human genome was used as the background reference gene set.
Related Knowledge Centers
- Coding Region
- DNA Sequencing
- Genome
- Molecular Biology
- Open Reading Frame
- Sanger Sequencing
- Genetics
- Gene
- Sequence Assembly
- Maxam–Gilbert Sequencing