Using WormBase: A Genome Biology Resource for Caenorhabditis elegans and Related Nematodes

Grove, Christian A.; Cain, Scott; Chen, Wen J.; Davis, Paul A.; Harris, Todd W.; Howe, Kevin; Kishore, Ranjana; Lee, Raymond; Paulini, Michael; Raciti, Daniela; Tuli, Mary Ann; Auken, Kimberly Van; Williams, Gary W.

doi:10.1007/978-1-4939-7737-6_14

Cited by 26 publications

(23 citation statements)

References 56 publications

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“…Blastx performed against the 43,718 M. incognita predicted proteins [ 25 ] found significant hits for 27,340 sequences (62%) of the Mg_v2 transcriptome, including 8111 sequences having no homologies with any of the M. graminicola genomic sequences produced by Somvanchi et al [ 24 ], thus probably pointing to genes lacking in the M. graminicola draft genome sequence. Finally, taking into account of Blastx results against Meloidogyne hapla [ 27 ], Caenorhabditis elegans [ 28 ], and the Uniprot databases, we determined that the Mg_v2 transcriptome contains 7095 sequences (16%) with no homology at all.…”

Section: Resultsmentioning

confidence: 99%

“…Neuropeptides can modulate nematode behavior, including locomotion and chemo-attraction [ 29 ]. In C. elegans , 31 genes encode flp (FMRFamide-like peptides) and 75 genes encode nlp (neuropeptides-like proteins) [ 28 ]. The M. incognita neuropeptide complement is reduced compared to that of C. elegans with only 19 flp genes and 21 nlp genes readily identifiable [ 26 ].…”

Section: Resultsmentioning

confidence: 99%

“…In addition, Blastx alignments were performed on the M. hapla and C. elegans protein databases and the UniProt database, and PFAM and Interproscan domains were determined for M. graminicola predicted proteins [ 10 ]. To retrieve putative homologs of functional genes, PFAM and Interproscan accession numbers, C. elegans gene class names, as described in WormBase [ 28 ], or keywords were used.…”

Section: Methodsmentioning

confidence: 99%

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Analyses of the Root-Knot Nematode (Meloidogyne graminicola) Transcriptome during Host Infection Highlight Specific Gene Expression Profiling in Resistant Rice Plants

et al. 2020

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The plant-parasitic nematode Meloidogyne graminicola causes considerable damages to rice (Oryza sativa) culture. Resistance to M. graminicola in the related species Oryza glaberrima reduces root penetration by juveniles and stops further nematode development. M. graminicola genes expressed during O. sativa infection were previously characterized but no information is available about the molecular dialogue established with a resistant plant. We compared the M. graminicola transcriptomes of stage-two juveniles (J2s) before and during infection of susceptible or resistant rice. Among 36,121 M. graminicola genes surveyed, 367 were differentially expressed during infection of resistant or susceptible plants. Genes encoding cell wall-degrading enzymes, peptidases and neuropeptides were expressed for a longer time in resistant plants compared to susceptible plants. Conversely, genes related to nematode development were not activated in the resistant host. The majority of M. graminicola effector genes had similar expression patterns, whatever the host genotype. However, two venom allergen-like protein (VAP)-encoding genes were specifically induced in resistant plants and Mg-VAP1 silencing in J2s reduced their ability to colonize roots. This study highlighted that M. graminicola adapts its gene expression to the host susceptibility. Further investigation is required to assess the role of Mg-VAPs in the rice–nematode interaction.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Analyses of the Root-Knot Nematode (Meloidogyne graminicola) Transcriptome during Host Infection Highlight Specific Gene Expression Profiling in Resistant Rice Plants

et al. 2020

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“…From literature, we know this is actually the case, as the underlying gene is npr-1 , for which a variant (215V in N2) has a neomorphic gain-of-function mutation, making it responsive to both FLP-21 and FLP-18 (reviewed by (1)). There are many other databases that can be consulted similarly for further investigation, such as WormNet (97), WormBase (98), MODENCODE (99)/MODERN (100), Genemania (101), and StringDB (102).…”

Section: Resultsmentioning

confidence: 99%

WormQTL2: an interactive platform for systems genetics inCaenorhabditis elegans

Snoek

Sterken

Hartanto

et al. 2019

Preprint

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18Quantitative genetics provides the tools for linking polymorphic loci (QTLs) to trait 19 variation. Linkage analysis of gene expression is an established and widely applied 20 method, leading to the identification of expression quantitative trait loci (eQTLs). (e)QTL 21 detection facilitates the identification and understanding of the underlying molecular 22 components and pathways, yet (e)QTL data access and mining often is a bottleneck. Here 23 we present WormQTL2 (www.bioinformatics.nl/WormQTL2/), a database and platform 24 for comparative investigations and meta-analyses of published (e)QTL datasets in the 25 model nematode worm C. elegans. WormQTL2 integrates six eQTL studies spanning 11 26 conditions as-well-as over 1000 traits from 32 studies and allows experimental results to 27 be compared, reused, and extended upon to guide further experiments and conduct 28 systems-genetic analyses. For example, one can easily screen a locus for specific cis-eQTLs 29 that could be linked to variation in other traits, detect gene-by-environment interactions 30 by comparing eQTLs under different conditions, or find correlations between QTL 31 profiles of classical traits and gene expression.32 100 (2,3,13,23,30,34,41,47,49,(53)(54)(55)(56)(57)(58)(59)61,76,(80)(81)(82)(83)(84)(85)(86)(87)(88)(89)(90) (Table 2). In this paper, we present WormQTL2 101 and showcase its use by presenting short research scenarios. 102 Results 103 104 eQTL studies in WormQTL2 105WormQTL2 is a browser-based interactive platform and database for investigating expression 106 and other Quantitative Trait Locus (QTL) studies conducted in C. elegans (Figure 1). It enables 107 access to the mapping data of six previously published eQTL studies (Table 1) (28,50,(76)(77)(78)(79). 108Together, these studies cover over 700 samples, including expression measurements of 109 approximately 20,000 different genes across different life stages and environmental conditions. 110The effect of genetic variation on gene expression is presented in 11 genome-wide sets of 111 eQTLs from three different RIL populations. The three populations consist of two different 112 CB4856 x N2 populations, recombinant inbred lines (RILs) (28) and recombinant inbred 113 advanced intercross lines (RIAILs) (91,92) and a mutation introgressed RIL population 114 resulting from a cross between a let-60 gain-of-function mutant in an N2 background, MT2124, 115 with CB4856 (11,50). For the Li et al. 2006, Viñuela & Snoek et al. 2010 and Li et al. 2010 116 Figure 1: WormQTL2 Homepage. On the top of the page the navigation bar can be found. This includes the WormQTL2 logo, which functions as a home button. It also includes a fast link to the Correlation and Locus overviews as well as links for help, data download, and visual examples. The search box is located in the centre, in which genes, phenotypes and GO terms can be entered. Shown in the blue middle square are the buttons for the investigations of single traits, correlating QTL profiles, QTLs at a specific locus, all eQTLs of an expe...

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“…BLAST searches were performed using default settings [41]. To identify putative GATA factors in a species, BLASTP searches were performed using the NCBI BLAST server [42]), Wormbase [43], the Caenorhabditis Genomes Project [44], and Command Line BLAST+ 2.7.1 and 2.10.1 executables running in Windows PowerShell (PC) or Terminal (Apple Macintosh), from https://ftp.ncbi.nlm.nih. gov/blast/executables/blast+/LATEST/.…”

Section: Identification Of Gata Factors In Nematode Speciesmentioning

confidence: 99%

Evolution of Developmental GATA Factors in Nematodes

Eurmsirilerd

Maduro

2020

JDB

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GATA transcription factors are found in animals, plants, and fungi. In animals, they have important developmental roles in controlling specification of cell identities and executing tissue-specific differentiation. The Phylum Nematoda is a diverse group of vermiform animals that inhabit ecological niches all over the world. Both free-living and parasitic species are known, including those that cause human infectious disease. To date, GATA factors in nematodes have been studied almost exclusively in the model system C. elegans and its close relatives. In this study, we use newly available sequences to identify GATA factors across the nematode phylum. We find that most species have fewer than six GATA factors, but some species have 10 or more. Comparisons of gene and protein structure suggest that there were at most two GATA factors at the base of the phylum, which expanded by duplication and modification to result in a core set of four factors. The high degree of structural similarity with the corresponding orthologues in C. elegans suggests that the nematode GATA factors share similar functions in development.

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Using WormBase: A Genome Biology Resource for Caenorhabditis elegans and Related Nematodes

Cited by 26 publications

References 56 publications

Analyses of the Root-Knot Nematode (Meloidogyne graminicola) Transcriptome during Host Infection Highlight Specific Gene Expression Profiling in Resistant Rice Plants

Analyses of the Root-Knot Nematode (Meloidogyne graminicola) Transcriptome during Host Infection Highlight Specific Gene Expression Profiling in Resistant Rice Plants

WormQTL2: an interactive platform for systems genetics inCaenorhabditis elegans

Evolution of Developmental GATA Factors in Nematodes

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