Assisted gene flow using cryopreserved sperm in critically endangered coral.

Assisted gene flow (AGF) is a conservation intervention to accelerate species adaptation to climate change by importing genetic diversity into at-risk populations. Corals exemplify both the need for AGF and its technical challenges; corals have declined in abundance, suffered pervasive reproductive failures, and struggled to adapt to climate change, yet mature corals cannot be easily moved for breeding, and coral gametes lose viability within hours. Here, we report the successful demonstration of AGF in corals using cryopreserved sperm that was frozen for 2 to 10 y. We fertilized Acropora palmata eggs from the western Caribbean (Curaçao) with cryopreserved sperm from genetically distinct populations in the eastern and central Caribbean (Florida and Puerto Rico, respectively). We then confirmed interpopulation parentage in the Curaçao-Florida offspring using 19,696 single-nucleotide polymorphism markers. Thus, we provide evidence of reproductive compatibility of a Caribbean coral across a recognized barrier to gene flow. The 6-mo survival of AGF offspring was 42%, the highest ever achieved in this species, yielding the largest wildlife population ever raised from cryopreserved material. By breeding a critically endangered coral across its range without moving adults, we show that AGF using cryopreservation is a viable conservation tool to increase genetic diversity in threatened marine populations.

Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate.

Studying the genetics of adaptation to new environments in ecologically and industrially important tree species is currently a major research line in the fields of plant science and genetic improvement for tolerance to abiotic stress. Specifically, exploring the genomic basis of local adaptation is imperative for assessing the conditions under which trees will successfully adapt in situ to global climate change. However, this knowledge has scarcely been used in conservation and forest tree improvement because woody perennials face major research limitations such as their outcrossing reproductive systems, long juvenile phase, and huge genome sizes. Therefore, in this review we discuss predictive genomic approaches that promise increasing adaptive selection accuracy and shortening generation intervals. They may also assist the detection of novel allelic variants from tree germplasm, and disclose the genomic potential of adaptation to different environments. For instance, natural populations of tree species invite using tools from the population genomics field to study the signatures of local adaptation. Conventional genetic markers and whole genome sequencing both help identifying genes and markers that diverge between local populations more than expected under neutrality, and that exhibit unique signatures of diversity indicative of "selective sweeps." Ultimately, these efforts inform the conservation and breeding status capable of pivoting forest health, ecosystem services, and sustainable production. Key long-term perspectives include understanding how trees' phylogeographic history may affect the adaptive relevant genetic variation available for adaptation to environmental change. Encouraging "big data" approaches (machine learning-ML) capable of comprehensively merging heterogeneous genomic and ecological datasets is becoming imperative, too.

Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa.

Local adaptation is a critical evolutionary process that allows plants to grow better in their local compared to non-native habitat and results in species-wide geographic patterns of adaptive genetic variation. For forest tree species with a long generation time, this spatial genetic heterogeneity can shape the ability of trees to respond to rapid climate change. Here, we identify genomic variation that may confer local environmental adaptations and then predict the extent of adaptive mismatch under future climate as a tool for forest restoration or management of the widely distributed high-elevation oak species Quercus rugosa in Mexico. Using genotyping by sequencing, we identified 5,354 single nucleotide polymorphisms (SNPs) genotyped from 103 individuals across 17 sites in the Trans-Mexican Volcanic Belt, and, after controlling for neutral genetic structure, we detected 74 F ST outlier SNPs and 97 SNPs associated with climate variation. Then, we deployed a nonlinear multivariate model, Gradient Forests, to map turnover in allele frequencies along environmental gradients and predict areas most sensitive to climate change. We found that spatial patterns of genetic variation were most strongly associated with precipitation seasonality and geographic distance. We identified regions of contemporary genetic and climatic similarities and predicted regions where future populations of Q. rugosa might be at risk due to high expected rate of climate change. Our findings provide preliminary details for future management strategies of Q. rugosa in Mexico and also illustrate how a landscape genomic approach can provide a useful tool for conservation and resource management strategies.