Hawaiʻi Coral Disease database (HICORDIS):species-specific coral health data from across the Hawaiian archipelago

AbstractThe Hawaiʻi Coral Disease database (HICORDIS) houses data on colony-level coral health condition observed across the Hawaiian archipelago, providing information to conduct future analyses on coral reef health in an era of changing environmental conditions. Colonies were identified to the lowest taxonomic classification possible (species or genera), measured and assessed for visual signs of health condition. Data were recorded for 286,071 coral colonies surveyed on 1819 transects at 660 sites between 2005 and 2015. The database contains observations for 60 species from 22 genera with 21 different health conditions. The goals of the HICORDIS database are to: i) provide open access, quality controlled and validated coral health data assembled from disparate surveys conducted across Hawaiʻi; ii) facilitate appropriate crediting of data; and iii) encourage future analyses of coral reef health. In this article, we describe and provide data from the HICORDIS database. The data presented in this paper were used in the research article “Satellite SST-based Coral Disease Outbreak Predictions for the Hawaiian Archipelago” (Caldwell et al., 2016) [1]

Data for spatial analysis of growth anomaly lesions on Montipora capitata coral colonies using 3D reconstruction techniques

Ten annotated 3D reconstructions of Montipora capitata coral colonies contain x,y,z coordinates for all growth anomaly (GA) lesions affecting these corals. The 3D reconstructions are available as Virtual Reality Modeling Language (VRML) files, and the GA lesions coordinates are in accompanying text files. The VRML models and GA lesion coordinates can be spatially analyzed using Matlab. Matlab scripts are provided for three spatial statistical procedures in order to assess clustering of the GA lesions across the coral colony surfaces in a 3D framework: Ripley׳s K, Moran׳s I, and the Kolmogorov–Smirnov test. Please see the research article, “Investigating the spatial distribution of Growth Anomalies affecting Montipora capitata corals in a 3-dimensional framework” (J.H.R. Burns, T. Alexandrov, E. Ovchinnikova, R.D. Gates, M. Takabayashi, 2016) [1], for further interpretation and discussion of the data

Whole-genome sequencing of a sporadic primary immunodeficiency cohort

Primary immunodeficiency (PID) is characterized by recurrent and often life-threatening infections, autoimmunity and cancer, and it poses major diagnostic and therapeutic challenges. Although the most severe forms of PID are identified in early childhood, most patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent and up to 10% develop lymphoid malignancies1-3. Consequently, in sporadic (or non-familial) PID genetic diagnosis is difficult and the role of genetics is not well defined. Here we address these challenges by performing whole-genome sequencing in a large PID cohort of 1,318 participants. An analysis of the coding regions of the genome in 886 index cases of PID found that disease-causing mutations in known genes that are implicated in monogenic PID occurred in 10.3% of these patients, and a Bayesian approach (BeviMed4) identified multiple new candidate PID-associated genes, including IVNS1ABP. We also examined the noncoding genome, and found deletions in regulatory regions that contribute to disease causation. In addition, we used a genome-wide association study to identify loci that are associated with PID, and found evidence for the colocalization of-and interplay between-novel high-penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to the variable penetrance and phenotypic complexity that are observed in PID. Thus, using a cohort-based whole-genome-sequencing approach in the diagnosis of PID can increase diagnostic yield and further our understanding of the key pathways that influence immune responsiveness in humans

Publisher Correction: Whole-genome sequencing of a sporadic primary immunodeficiency cohort (Nature, (2020), 583, 7814, (90-95), 10.1038/s41586-020-2265-1)

An amendment to this paper has been published and can be accessed via a link at the top of the paper