Alliance of Genome Resources Consortium (2019) Genetics "The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases."

Alliance of Genome Resources Consortium

[Genetics, 2019]

Model organisms are essential experimental platforms for discovering gene functions, defining protein and genetic networks, uncovering functional consequences of human genome variation, and for modeling human disease. For decades, researchers who use model organisms have relied on Model Organism Databases (MODs) and the Gene Ontology Consortium (GOC) for expertly curated annotations, and for access to integrated genomic and biological information obtained from the scientific literature and public data archives. Through the development and enforcement of data and semantic standards, these genome resources provide rapid access to the collected knowledge of model organisms in human readable and computation-ready formats that would otherwise require countless hours for individual researchers to assemble on their own. Since their inception, the MODs for the predominant biomedical model organisms [<i>Mus sp</i> (laboratory mouse), <i>Saccharomyces cerevisiae</i>, <i>Drosophila melanogaster</i>, <i>Caenorhabditis elegans</i>, <i>Danio rerio</i>, and <i>Rattus norvegicus</i>] along with the GOC have operated as a network of independent, highly collaborative genome resources. In 2016, these six MODs and the GOC joined forces as the Alliance of Genome Resources (the Alliance). By implementing shared programmatic access methods and data-specific web pages with a unified &quot;look and feel,&quot; the Alliance is tackling barriers that have limited the ability of researchers to easily compare common data types and annotations across model organisms. To adapt to the rapidly changing landscape for evaluating and funding core data resources, the Alliance is building a modern, extensible, and operationally efficient &quot;knowledge commons&quot; for model organisms using shared, modular infrastructure.

Muchnik L et al. (2007) Phys Rev E Stat Nonlin Soft Matter Phys "Self-emergence of knowledge trees: extraction of the Wikipedia hierarchies."

Itzhack R, Solomon S, Muchnik L, Louzoun Y

[Phys Rev E Stat Nonlin Soft Matter Phys, 2007]

The rapid accumulation of knowledge and the recent emergence of new dynamic and practically unmoderated information repositories have rendered the classical concept of the hierarchal knowledge structure irrelevant and impossible to impose manually. This led to modern methods of data location, such as browsing or searching, which conceal the underlying information structure. We here propose methods designed to automatically construct a hierarchy from a network of related terms. We apply these methods to Wikipedia and compare the hierarchy obtained from the article network to the complementary acyclic category layer of the Wikipedia and show an excellent fit. We verify our methods in two networks with no a priori hierarchy (the E. Coli genetic regulatory network and the C. Elegans neural network) and a network of function libraries of modern computer operating systems that are intrinsically hierarchical and reproduce a known functional order.

Kashyap L et al. (2006) Bioinformation "Comparative analysis of various gene finders specific to Caenorhabditis elegans genome."

Tabish M, KASHYAP L

[Bioinformation, 2006]

Computational gene prediction and identifying alternatively spliced isoforms have always been a challenging task. In this paper, we describe the performance of three gene/exon finding programmes namely Fex, Gen view2 and Gene builder capable of predicting open reading frames or exons for a given set of sequences from C. elegans genome. The predicted exons were compared with the 'sequencing consortium' identified exons and degree of consensus among them is discussed. We found that exon prediction by Fex was similar to the consortium prediction as compared to Gen view2 and Gene builder results. Interestingly, some exons (six exons in five genes) predicted positive only by Fex and not by the 'sequencing consortium' are found at the C. elegans EST database. This data is critical for further debate and discussion on gene finding in C. elegans.

Kudron MM et al. (2017) Genetics "The modERN Resource: Genome-Wide Binding Profiles for Hundreds of Drosophila and Caenorhabditis elegans Transcription Factors."

Samanta S, Waterston R, Seabrook-Sturgis S, Terrell R, Fisher WW, White KP, Yan KK, Gersch J, Hammonds AS, Ma L, Kirkey M, Han M, Kadaba M, Steffen D, Celniker SE, Gevirtzman L, Ammouri H, Hillier LW, Kudron MM, Wall ML, Gerstein M, Corson M, Szynkarek M, Moran J, Reinke V, Jameel N, Durham TJ, Xu J, Park S, Victorsen A, Patton J, Vafeados D

[Genetics, 2017]

In order to develop a catalog of regulatory sites in two major model organisms, Drosophilia melanogaster and Caenorhabditis elegans, the modERN consortium has systematically assayed the binding sites of transcription factors (TFs). Combined with data produced by our predecessor, modENCODE, we now have data for 262 TFs identifying 1.23M sites in the fly genome and 217 TFs identifying 0.67M sites in the worm genome. Because sites from different TFs are often overlapping and tightly clustered, they fall into 91,011 and 59,150 regions in the fly and worm, respectively, and these binding sites span as little as 8.7 Mb and 5.8 Mb in the two organisms. Clusters with large numbers of sites (so-called HOT regions) predominantly associate with broadly expressed genes, whereas clusters containing sites from just a few factors are associated with genes expressed in tissue specific patterns. All of the strains expressing GFP-tagged TFs are available at the stock centers and the ChIP-seq data are available through the ENCODE DCC, and also through a simple interface (http://epic.gs.washington.edu/modERN/) that facilitates rapid accessibility of processed datasets. These data will facilitate a vast number of scientific inquiries into the fuction of individual TFs in key developmental, metabolic, defense and homeostatic regulatory pathways, as well as provide a broader perspective on how individual TFs work together in local networks and globally across the lifespans of these two key model organisms.

West KH et al. (2016) Planta Med "Marine Biodiscovery Goes Deeper: Using In Vivo Bioassays Based on Model Organisms to Identify Biomedically Relevant Marine Metabolites."

West KH, Crawford AD

[Planta Med, 2016]

Secondary metabolites from marine organisms are structurally diverse small molecules with high levels of bioactivity, and represent an underutilized resource for modern drug discovery. To facilitate the identification of drug-like marine metabolites, the significant potential of in vivo models of human disease - in particular those suitable for medium-throughput screening and bioassay-guided fractionation - should be explored in future marine biodiscovery efforts. Here, we explore the advantages of Caenorhabditis elegans, Drosophila, and zebrafish bioassays for marine biodiscovery, and review recent progress in using these in vivo models to identify bioactive marine metabolites.

Lim CS et al. (2001) Curr Biol "C. elegans clk-2, a gene that limits life span, encodes a telomere length regulator similar to yeast telomere binding protein Tel2p."

Dernburg AF, Mian IS, Lim CS, Campisi J

[Curr Biol, 2001]

An important quest in modern biology is to identify genes involved in aging. Model organisms such as the nematode Caenorhabditis elegans are particularly useful in this regard. The C. elegans genome has been sequenced [1], and single gene mutations that extend adult life span have been identified [2]. Among these longevity-controlling loci are four apparently unrelated genes that belong to the clk family [3-5]. In mammals, telomere length and structure can influence cellular, and possibly organismal, aging [6]. Here, we show that clk-2 encodes a regulator of telomere length in C. elegans.

Monsalve GC et al. (2018) Genetics "A New Tool for Inducible Gene Expression in Caenorhabditis elegans."

Yamamoto KR, Ward JD, Monsalve GC

[Genetics, 2018]

Controlling protein activity and localization is a key tool in modern biology. Mammalian steroid receptor ligand-binding domains (LBDs) fusions have been used in a range of organisms and cell-types to inactivate proteins of interest until the cognate steroid ligand is applied. Here, we demonstrate that the glucocorticoid receptor LBD confers ligand-gated control of a heterologous gene expression system (Q system) and the DAF-16 transcription factor in <i>C. elegans</i> These experiments demonstrate provide a powerful tool for temporal control of protein activity, and will bolster existing tools used to modulate gene expression and protein activity in this animal.

Maddox PS et al. (2012) Methods Enzymol "Imaging the mitotic spindle."

Dorn J, Ladouceur AM, Ranjan R, Maddox AS, D'Amours D, Maddox PS, Ratsima H

[Methods Enzymol, 2012]

The mitotic spindle, due to its striking form, has been imaged for well over 100 years. Composed largely of microtubules and chromosomes, the spindle also contains numerous proteins whose roles include biochemical and biophysical regulation of mitosis. Given the transient, dynamic nature of the spindle, the light microscope continues to be the main tool employed to unlock its mysteries. In this chapter, we will discuss modern light microscopy techniques commonly used for imaging this intricate cellular machine as well as provide examples and protocols. We will also describe some biological preparations and experimental regimes for investigation of the mitotic spindle.

O'Halloran DM (2016) Invert Neurosci "NemaCount: quantification of nematode chemotaxis behavior in a browser."

O'Halloran DM

[Invert Neurosci, 2016]

Nematodes such as Caenorhabditis elegans offer a very effective and tractable system to probe the underlying mechanisms of diverse sensory behaviors. Numerous platforms exist for quantifying nematode behavior and often require separate dependencies or software. Here I describe a novel and simple tool called NemaCount that provides a versatile solution for the quantification of nematode chemotaxis behavior. The ease of installation and user-friendly interface makes NemaCount a practical tool for measuring diverse behaviors and image features of nematodes such as C. elegans. The main advantage of NemaCount is that it operates from within a modern browser such as Google Chrome or Apple Safari. Any features that change in total number, size, shape, or angular distance between control and experimental preparations are suited to NemaCount for image analysis, while commonly used chemotaxis assays can be quantified, and statistically analyzed using a suite of functions from within NemaCount. NemaCount also offers image filtering options that allow the user to improve object detection and measurements. NemaCount was validated by examining nematode chemotaxis behavior; angular distances of locomotory tracks in C. elegans; and body lengths of Heterorhabditis bacteriophora nematodes. Apart from a modern browser, no additional software is required to operate NemaCount, making NemaCount a cheap, simple option for the analysis of nematode images and chemotaxis behavior.

Hardin J et al. (2022) Methods Mol Biol "Imaging Epidermal Cell Rearrangement in the C. elegans Embryo."

Hardin J, King R, Walck-Shannon E, Reiner D, Serre J

[Methods Mol Biol, 2022]

The Caenorhabditis elegans embryo is well suited for analysis of directed cell rearrangement via modern microscopy, due to its simple organization, short generation time, transparency, invariant lineage, and the ability to generate engineered embryos expressing various fluorescent proteins. This chapter provides an overview of routine microscopy techniques for imaging dorsal intercalation, a convergent extension-like morphogenetic movement in the embryonic epidermis of C. elegans, including making agar mounts, low-cost four-dimensional (4D) Nomarski microscopy, laser microsurgery, and 4D fluorescence microscopy using actin and junctional fusion proteins, as well as tissue-specific promoters useful for studying dorsal intercalation.