Topological analysis and interactive visualization of biological networks and protein structures

Doncheva, Nadezhda T.; Assenov, Yassen; Domingues, Francisco S.; Albrecht, Mario

doi:10.1038/nprot.2012.004

Cited by 453 publications

(374 citation statements)

References 75 publications

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“…6). Various network statistics were calculated using NetworkAnalyzer 55 , including average number of neighbours (that is, protein interactions) and total number of isolated nodes (that is, without known interactors). Constructing a gene interaction network.…”

Section: Methodsmentioning

confidence: 99%

Single-molecule sequencing of the desiccation-tolerant grass Oropetium thomaeum

VanBuren

Bryant

Edger

et al. 2015

Nature

291

271

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Plant genomes, and eukaryotic genomes in general, are typically repetitive, polyploid and heterozygous, which complicates genome assembly 1 . The short read lengths of early Sanger and current next-generation sequencing platforms hinder assembly through complex repeat regions, and many draft and reference genomes are fragmented, lacking skewed GC and repetitive intergenic sequences, which are gaining importance due to projects like the Encyclopedia of DNA Elements (ENCODE) 2 . Here we report the whole-genome sequencing and assembly of the desiccationtolerant grass Oropetium thomaeum. Using only single-molecule real-time sequencing, which generates long (>16 kilobases) reads with random errors, we assembled 99% (244 megabases) of the Oropetium genome into 625 contigs with an N50 length of 2.4 megabases. Oropetium is an example of a 'near-complete' draft genome which includes gapless coverage over gene space as well as intergenic sequences such as centromeres, telomeres, transposable elements and rRNA clusters that are typically unassembled in draft genomes. Oropetium has 28,466 protein-coding genes and 43% repeat sequences, yet with 30% more compact euchromatic regions it is the smallest known grass genome. The Oropetium genome demonstrates the utility of single-molecule real-time sequencing for assembling high-quality plant and other eukaryotic genomes, and serves as a valuable resource for the plant comparative genomics community.The genomes of Arabidopsis 3 , rice 4 , poplar, grape and Sorghum 5 were first sequenced using high-quality and reiterative Sanger-based approaches producing a series of 'gold standard' reference genomes. The advent of next-generation sequencing (NGS) technologies reduced costs of sequencing substantially, which has enabled sequencing of over 100 plant genomes 1 . The quality of plant genome assemblies depends on genome size, ploidy, heterozygosity and sequence coverage, but most NGS-based genomes have on the order of tens of thousands of short contigs distributed in thousands of scaffolds. The short read lengths of NGS, inherent biases and non-random sequencing errors have resulted in highly fragmented draft genome assemblies that are not complete, which means they are missing biologically meaningful sequences including entire genes, regulatory regions, transposable elements, centromeres, telomeres and haplotype-specific structural variations. It is becoming clear from ENCODE projects that complete genomes are needed to better understand the importance of the non-coding regions of genomes 2 .More than 40% of calories consumed by humans are derived from grasses, and the grass family (Poaceae) is arguably the most important plant family with regard to global food security 6 . The size and complexity of most grass genomes has challenged progress in gene discovery and comparative genomics, although draft genomes are now available for most agriculturally important grasses 1 . The largest genome assemblies, such as maize (2,300 megabases (Mb)) 7 , barley (5,100 Mb) 8 and wheat (hexaploid, 1...

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Section: Methodsmentioning

confidence: 99%

Single-molecule sequencing of the desiccation-tolerant grass Oropetium thomaeum

VanBuren

Bryant

Edger

et al. 2015

Nature

291

271

View full text Add to dashboard Cite

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“…PPI networks were visualized and analyzed using the software platform Cytoscape 3.2.1 with the plugins MCODE for cluster analysis and BinGO for gene ontology analysis of protein clusters (37)(38)(39). Global network topological analysis, including clustering coefficients, average number of neighbors (degree), and network heterogeneity as well as local network analysis using betweenness centrality value calculation were carried out with NetworkAnalyzer and the Cytoscape plugin CytoNCA (40,41). The edges in all PPI networks were treated as undirected.…”

Section: Methodsmentioning

confidence: 99%

Biological Relevance and Therapeutic Potential of the Hypusine Modification System

Pällmann

Braig

Sievert

et al. 2015

Journal of Biological Chemistry

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Background: Hypusine modification of the eukaryotic initiation factor 5A (eIF-5A) represents a conserved post-translational modification that regulates translation. Results: Deletion of hypusine modification enzymes exerts strong phenotypes. eIF-5A2-deleted animals are viable and fertile. Conclusion: Both enzymatic steps of hypusine modification are essential for mammalian homeostasis, whereas the cancerrelated isoform eIF-5A2 is dispensable. Significance: eIF-5A2 might represent a safe therapeutic target.

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“…In prior studies, most biological networks had scalefree architectures that fit a power-law distribution (Barabási et al, 2004;Doncheva et al, 2012;Schaefer et al, 2014). For the three final maize networks constructed using optimized parameters, both neighborhood connectivity distribution (Supplemental Fig.…”

Section: Pcc and Scc-built Gcn Exhibits Identical Topological And Funmentioning

confidence: 99%

Construction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data

et al. 2017

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ORCID IDs: 0000-0002-6182-800X (J.H.); 0000-0001-6612-3570 (S.V.); 0000-0002-9564-8146 (K.M.M.).With the emergence of massively parallel sequencing, genomewide expression data production has reached an unprecedented level. This abundance of data has greatly facilitated maize research, but may not be amenable to traditional analysis techniques that were optimized for other data types. Using publicly available data, a gene coexpression network (GCN) can be constructed and used for gene function prediction, candidate gene selection, and improving understanding of regulatory pathways. Several GCN studies have been done in maize (Zea mays), mostly using microarray datasets. To build an optimal GCN from plant materials RNA-Seq data, parameters for expression data normalization and network inference were evaluated. A comprehensive evaluation of these two parameters and a ranked aggregation strategy on network performance, using libraries from 1266 maize samples, were conducted. Three normalization methods and 10 inference methods, including six correlation and four mutual information methods, were tested. The three normalization methods had very similar performance. For network inference, correlation methods performed better than mutual information methods at some genes. Increasing sample size also had a positive effect on GCN. Aggregating single networks together resulted in improved performance compared to single networks.Maize (Zea mays) is the most widely produced crop in United States, and U.S. agriculture accounted for 36% of world maize production in 2015 (USDA, 2016). Maize has also been in the center of genetics research for more than 100 years, including McClintock's pioneering work with transposable elements (reviewed by McClintock, 1983;Fedoroff, 2012). Due to recent technological advances in nucleic acid sequencing and the availability of the maize genome sequence (Schnable et al., 2009), maize genomics research has been greatly expedited.RNA-sequencing (RNA-Seq) has become the favored technique for detecting genomewide expression patterns. RNA-Seq has some advantages over microarray analysis of gene expression, including single base-pair resolution, detection of novel transcripts, and the ability to analyze transcript abundance without existing genome information (reviewed by Wang et al., 2009;Han et al., 2015;Conesa et al., 2016). RNA-Seq data provides information about single nucleotide polymorphisms, which facilitates genomewide association studies (Fu et al., 2013;Li et al., 2013a;Lonsdale et al., 2013;Fadista et al., 2014). Because of its widespread adaptability, greater than 5000 Illumina platform Maize RNA-Seq libraries (Fig. 1A) are available in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (Leinonen et al., 2010), adding to the body of data that can be used to study the maize genome.The maize genome is large and heterogeneous, and the genome annotation is still far from complete (Cigan et al., 2005;Ficklin and Feltus, 2011). Although recent work has...

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Topological analysis and interactive visualization of biological networks and protein structures

Cited by 453 publications

References 75 publications

Single-molecule sequencing of the desiccation-tolerant grass Oropetium thomaeum

Single-molecule sequencing of the desiccation-tolerant grass Oropetium thomaeum

Biological Relevance and Therapeutic Potential of the Hypusine Modification System

Construction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data

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