Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary

Mao, Xizeng; Cai, Tao; Olyarchuk, John G.; Wei, Liping

doi:10.1093/bioinformatics/bti430

Cited by 3,051 publications

(1,975 citation statements)

References 28 publications

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“…Finally, we undertook a statistical step to identify enriched pathways from all the pathways that contain the remaining growth-related and immunity-related genes simultaneously. For each pathway, we calculated the P-value using a hypergeometric test (Mao et al, 2005): (1) if there are N background genes that are involved in all of the pig pathways, and among them there are n growthrelated and immunity-related QTL genes, and (2) if there are m genes that can be mapped to a certain pathway and this pathway includes M genes in total, then the P-value for this certain pathway can be calculated as follows:…”

Section: Methodsmentioning

confidence: 99%

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Zhang

Wang

Yang

et al. 2016

animal

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Both growth and immune capacity are important traits in animal breeding. The animal quantitative trait loci (QTL) database is a valuable resource and can be used for interpreting the genetic mechanisms that underlie growth and immune traits. However, QTL intervals often involve too many candidate genes to find the true causal genes. Therefore, the aim of this study was to provide an effective annotation pipeline that can make full use of the information of Gene Ontology terms annotation, linkage gene blocks and pathways to further identify pleiotropic genes and gene sets in the overlapping intervals of growth-related and immunity-related QTLs. In total, 55 non-redundant QTL overlapping intervals were identified, 1893 growth-related genes and 713 immunity-related genes were further classified into overlapping intervals and 405 pleiotropic genes shared by the two gene sets were determined. In addition, 19 pleiotropic gene linkage blocks and 67 pathways related to immunity and growth traits were discovered. A total of 343 growth-related genes and 144 immunity-related genes involved in pleiotropic pathways were also identified, respectively. We also sequenced and genotyped 284 individuals from Chinese Meishan pigs and European pigs and mapped the single nucleotide polymorphisms (SNPs) to the pleiotropic genes and gene sets that we identified. A total of 971 high-confidence SNPs were mapped to the pleiotropic genes and gene sets that we identified, and among them 743 SNPs were statistically significant in allele frequency between Meishan and European pigs. This study explores the relationship between growth and immunity traits from the view of QTL overlapping intervals and can be generalized to explore the relationships between other traits.

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Section: Methodsmentioning

confidence: 99%

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Zhang

Wang

Yang

et al. 2016

animal

View full text Add to dashboard Cite

show abstract

“…Identification of differentially regulated pathways was carried out using software KOBAS (for KEGG Orthology Based Annotation System) by setting cutoff values as e-values ≤1e-5, rank ≤10 and sequence identity ≥30% [31]. The fatty acid metabolism pathway was enriched by adding lipase, fatty acid elongase, desaturase and very long-chain fatty acid condensing enzymes.…”

Section: Image Acquisition Data Filtering and Processingmentioning

confidence: 99%

Gene expression and metabolite profiles of cotton fiber during cell elongation and secondary cell wall synthesis

et al. 2007

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Cotton fibers elongate rapidly after initiation of elongation, eventually leading to the deposit of a large amount of cellulose. To reveal features of cotton fiber cells at the fast elongation and the secondary cell wall synthesis stages, we compared the respective transcriptomes and metabolite profiles. Comparative analysis of transcriptomes by cDNA array identified 633 genes that were differentially regulated during fiber development. Principal component analysis (PCA) using expressed genes as variables divided fiber samples into four groups, which are diagnostic of developmental stages. Similar grouping results are also found if we use non-polar or polar metabolites as variables for PCA of developing fibers. Auxin signaling, wall-loosening and lipid metabolism are highly active during fiber elongation, whereas cellulose biosynthesis is predominant and many other metabolic pathways are downregulated at the secondary cell wall synthesis stage. Transcript and metabolite profiles and enzyme activities are consistent in demonstrating a specialization process of cotton fiber development toward cellulose synthesis. These data demonstrate that cotton fiber cell at a certain stage has its own unique feature, and developmental stages of cotton fiber cells can be distinguished by their transcript and metabolite profiles. During the secondary cell wall synthesis stage, metabolic pathways are streamed into cellulose synthesis.

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“…To further explore how the Yamanaka factors are involved in regulating signaling pathways in iPS cells, we used KOBAS [23,24] to clarify the pathways regulated by the four factors into subcategories of development, cancer, metabolism, and other signaling pathways ( Figure 5A). Consistent with the results from PANTHER analysis, the distributions of pathways regulated by Yamanaka factors between different subcategories in iPS cells also differ from those in ES cells.…”

Section: Defining a Signaling Network Controlling Pluripotency In Ipsmentioning

confidence: 99%

More synergetic cooperation of Yamanaka factors in induced pluripotent stem cells than in embryonic stem cells

et al. 2009

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Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary

Cited by 3,051 publications

References 28 publications

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Identification of pleiotropic genes and gene sets underlying growth and immunity traits: a case study on Meishan pigs

Gene expression and metabolite profiles of cotton fiber during cell elongation and secondary cell wall synthesis

More synergetic cooperation of Yamanaka factors in induced pluripotent stem cells than in embryonic stem cells

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