Search USGSSearch

USGS · 70237185

Millennia-old coral holobiont DNA provides insight into future adaptive trajectories

Abstract

Ancient DNA (aDNA) has been applied to evolutionary questions across a wide variety of taxa. Here, for the first time, we leverage aDNA from millennia-old fossil coral fragments to gain new insights into a rapidly declining western Atlantic reef ecosystem. We sampled four Acropora palmata fragments (dated 4215 BCE - 1099 CE) obtained from two Florida Keys reef cores. From these samples, we established that it is possible both to sequence ancient DNA from reef cores and place the data in the context of modern-day genetic variation. We recovered varying amounts of nuclear DNA exhibiting the characteristic signatures of aDNA from the A. palmata fragments. To describe the holobiont sensu lato, which plays a crucial role in reef health, we utilized metagenome-assembled genomes as a reference to identify a large additional proportion of ancient microbial DNA from the samples. The samples shared many common microbes with modern-day coral holobionts from the same region, suggesting remarkable holobiont stability over time. Despite efforts, we were unable to recover ancient Symbiodiniaceae reads from the samples. Comparing the ancient A. palmata data to whole-genome sequencing data from living acroporids, we found that while slightly distinct, ancient samples were most closely related to individuals of their own species. Together, these results provide a proof-of-principle showing that it is possible to carry out direct analysis of coral holobiont change over time, which lays a foundation for studying the impacts of environmental stress and evolutionary constraints.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Carly B. Scott, Anny Cardenas, Matthew Mah, Vagheesh Narasimhan, Nadin Rohland, Lauren T. Toth, Christian Voostra, David Reich, Mikhail V Matz. 2022-08-18. Millennia-old coral holobiont DNA provides insight into future adaptive trajectories. https://doi.org/10.1111/mec.16642

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Evaluating the central–marginal hypothesis: Introgression and genetic variation at the trailing edge of Quercus bicolor

The central–marginal hypothesis (CMH) predicts reduced genetic diversity and increased differentiation in range-edge populations due to ecological marginality and limited gene flow. Deviations from this pattern, however, can result from historical demographic processes, variation in reproductive strategies or interspecific hybridization. The genus Quercus , known for hybridization and long-distance pollination, offers an excellent model to examine the spatial patterns of genetic diversity, structure and introgression across species distributions. Here, we investigate these dynamics in Quercus bicolor Willd., a widespread eastern North American oak. Using RADseq, we genotyped 142 individuals from 12 sites at the fragmented trailing range edge and nine sites from the range core. To detect introgression, we incorporated reference data from six sympatric white oak species. We reveal extensive introgression, particularly from Q. lyrata Walt., in nearly all southern edge populations, but none in core populations despite sympatry with closely related congeners. Southern populations also showed increased genetic structure and differentiation, but not reduced diversity or increased inbreeding, even when only examining non-admixed individuals. Regression analyses reveal relationships between introgressed ancestry and heterozygosity, inbreeding and differentiation, indicating that introgression may buffer range-edge populations against genetic erosion by introducing novel alleles. Hindcast, current and forecast ecological niche models demonstrate temporally changing degrees of overlap between the geographic range of Q. lyrata and Q. bicolor and suggest higher hybridization potential in the future. These findings offer mixed support for the CMH while underscoring the evolutionary relevance of introgression in shaping genetic landscapes at range margins with significant implications for conservation.

Molecular Ecology

Metabarcoding analysis of arthropod pollinator diversity: A methodological comparison of eDNA derived from flowers and DNA derived from bulk samples of insects

Limitations of traditional insect sampling methods have motivated the development and optimisation of new non-lethal methods capable of quantifying diverse arthropod communities. Environmental DNA (eDNA) metabarcoding using arthropod-specific primers has recently been investigated as a novel way to characterise arthropod communities from the DNA they deposit on the surface of plants. This sampling method has had demonstrated success, but pollinators—especially bees—are oddly underrepresented in these studies. To evaluate this inconsistency, we investigated the limitations of eDNA metabarcoding for bees and other pollinators. We compared pollinator diversity derived from eDNA extracted from flowers and DNA extracted from pulverised bulk samples of insects collected from vane traps deployed at the same sites using three metabarcoding primers, two of which target arthropods generally (COI-Jusino and 16S-Marquina) and one that targets bumblebees ( Bombus spp., COI-Milam). Across methods, we detected 77 insect families from 9 orders. The COI-Jusino marker amplified the highest taxonomic diversity compared to 16S-Marquina and COI-Milam. More amplicon sequence variants (ASVs) were recovered from vane traps (blue: 1357, yellow: 1542) than flowers (245), but only 23% of families and 13% of genera were shared among methods, indicating that flowers and blue and yellow vane traps may each sample different parts of the available arthropod community. Of 29 flower samples with known bee visitations, only 10 samples had bee detections from eDNA, and incomplete reference databases hindered assignment to species. Although our study provides additional evidence for the usefulness of eDNA metabarcoding for characterising arthropod communities, significant challenges remain when using eDNA metabarcoding methods to identify and quantify pollinator communities, especially bees.

Molecular Ecology