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Marine heatwaves modulate the genotypic and physiological responses of reef‐building corals to subsequent heat stress

Abstract Back‐to‐back marine heatwaves in 2016 and 2017 resulted in severe coral bleaching and mortality across the Great Barrier Reef (GBR). Encouragingly, some corals that survived these events exhibit increased bleaching resistance and may represent thermally tolerant populations that can better cope with ocean warming. Using the GBR as a natural laboratory, we investigated whether a history of minimal (Heron Island) or severe (Lizard Island) coral bleaching in 2016 and 2017 equates to stress tolerance in a successive heatwave (2020). We examined the genetic diversity, physiological performance, and trophic plasticity of juvenile (25 cm) corals of two common genera (Pocillopora and Stylophora). Despite enduring greater cumulative heat stress (6.3°C week−1 vs. 5.6°C week−1), corals that experienced the third marine heatwave in 5 years (Lizard) exhibited twice as high survival and visual bleaching thresholds compared to corals that had not experienced significant bleaching in >10 years (Heron). Surprisingly, only one shared host–Symbiodiniaceae association was uncovered between locations (Stylophora pistillata–Cladocopium “C8 group”) and there was no genetic overlap in Pocillopora–Cladocopium partnerships, suggesting turnover in species composition from recent marine heatwaves. Corals within the species complex Pocillopora that survived the 2016 and 2017 marine heatwaves at Lizard Island were the most resilient, exhibiting three times greater calcification rates than conspecifics at Heron Island. Further, surviving corals (Lizard) had distinct isotopic niches, lower host carbon, and greater host protein, while conspecifics that had not experienced recent bleaching (Heron) had two times greater symbiont carbon content, suggesting divergent trophic strategies that influenced survival (i.e., greater reliance on heterotrophy vs. symbiont autotrophy, respectively). Ultimately, while corals may experience less bleaching and survive repeated thermal stress events, species‐specific trade‐offs do occur, leaving open many questions related to the long‐term health and recovery of coral reef ecosystems in the face of intensifying marine heatwaves

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. Methods We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study. Results The benchmark datasets focus on the two most widely used sequencing platforms: long read sequencing data from the Oxford Nanopore Technologies platform and short read sequencing data from the Illumina platform. There are six datasets: three were derived from recent publications; two were derived from data mining public databases to answer common questions not covered by published datasets; one unique dataset representing common sequence failures was obtained by rigorously scrutinizing data that did not pass quality checks. The dataset summary table, data mining script and quality control (QC) values for all sequence data are publicly available on GitHub: https://github.com/CDCgov/datasets-sars-cov-2. Discussion The datasets presented here were generated to help public health laboratories build sequencing and bioinformatics capacity, benchmark different workflows and pipelines, and calibrate QC thresholds to ensure sequencing quality. Together, improvements in these areas support accurate and timely outbreak investigation and surveillance, providing actionable data for pandemic management. Furthermore, these publicly available and standardized benchmark data will facilitate the development and adjudication of new pipelines