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. 2017 Jan 4;45(D1):D650-D657.
doi: 10.1093/nar/gkw893. Epub 2016 Oct 3.

CeNDR, the Caenorhabditis Elegans Natural Diversity Resource

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Free PMC article

CeNDR, the Caenorhabditis Elegans Natural Diversity Resource

Daniel E Cook et al. Nucleic Acids Res. .
Free PMC article

Abstract

Studies in model organisms have yielded considerable insights into the etiology of disease and our understanding of evolutionary processes. Caenorhabditis elegans is among the most powerful model organisms used to understand biology. However, C. elegans is not used as extensively as other model organisms to investigate how natural variation shapes traits, especially through the use of genome-wide association (GWA) analyses. Here, we introduce a new platform, the C. elegans Natural Diversity Resource (CeNDR) to enable statistical genetics and genomics studies of C. elegans and to connect the results to human disease. CeNDR provides the research community with wild strains, genome-wide sequence and variant data for every strain, and a GWA mapping portal for studying natural variation in C. elegans Additionally, researchers outside of the C. elegans community can benefit from public mappings and integrated tools for comparative analyses. CeNDR uses several databases that are continually updated through the addition of new strains, sequencing data, and association mapping results. The CeNDR data are accessible through a freely available web portal located at http://www.elegansvariation.org or through an application programming interface.

Figures

Figure 1.
Figure 1.
Overview of the CeNDR focus areas.
Figure 2.
Figure 2.
Selected components of the CeNDR Resource. The following are screenshots of selected components of CeNDR. (A) A tool for interactive geographic exploration of wild isolates based on their isolation location (red markers). Additional information is displayed to the right of the map and is provided when hovering over isolation location. (B) A genome browser for examining genetic variation among wild isolates. Tracks for displaying genes, conservation, and the predicted effects of variants are also available. (C) The results from public statistically significant association mappings are added to a ‘cumulative’ Manhattan plot, which displays the positions of the most significant markers within a QTL confidence interval for each significant mapping.
Figure 3.
Figure 3.
The GWA mapping reports within CeNDR. (A) Manhattan plots provide visualization of significance values for all markers used in the statistical test of association. The y-axis is the negative base 10 log of the P-value obtained from the statistical test of association. The x-axis is the genomic position in millions of base pairs. Markers with a -log10 P-value greater than the Bonferroni-corrected significance threshold (gray line) are considered to be significantly correlated with the phenotype, indicating that linked genetic variation could be causing the observed phenotypic variation. (B) Linkage disequilibrium among the most significant markers from each associated region is displayed. (C) An interactive plot of the geographic location of strains harboring either the reference or alternative marker at the most significant marker within the QTL confidence interval is shown. (D) A summary table of genes and other attributes within the QTL confidence interval is output. The number of protein-coding genes with variants, genes with moderate-impact variants, and genes with high-impact variants are provided.

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