Journal Club presentations Prepare a 15'-20' presentation Prepare a 15'-20' journal club Spend ~5'- 10' setting the stage: what is the general question? • • • • • Why is it important? What was previously known? What were the outstanding questions? . Then state the specific question addressed in your paper. Next explain how they studied it General overview of techniques first, then specifics • • What were they trying to do? • how did they do it? • Then describe their results • General overview first Then specific experiments ■ Specific purpose of each experiment How they tested it Data they collected Controls!! How they analyzed it Conclusions they drew Your interpretation • Do you agree? How could they improve?/n Received: 23 October 2020 Revised: 15 May 2021 Accepted: 2 July 2021 DOI: 10.1111/ede.12388 RESEARCH Check for updates WILEY Inheritance of DNA methylation differences in the mangrove Rhizophora mangle 1,2 İD 1,5 Jeannie Mounger | M. Teresa Boquete¹ | Marc W. Schmid³ Renan Granado¹,4 ① Marta H. Robertson¹ ① | Sandy A. Voors¹ | Kristen L. Langanke¹ | Mariano Alvarez ¹5 ℗ | Cornelis A. M. Wagemaker | Aaron W. Schrey' İD | Gordon A. Fox¹ D | David B. Lewis¹ ① | Catarina Fonseca Lira⭑4 ① | Christina L. Richards¹,8 İD İD ¹Department of Integrative Biology, University of South Florida, Tampa, Florida, USA 2Department of Evolutionary Ecology, CSIC, Estación Biológica de Doñana, Sevilla, Spain 3MWSchmid GmbH, Zurich, Switzerland *Diretoria de Pesquisas, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de Janeiro/RJ, Brazil 5Avalo, Durham, NC, USA “Department of Experimental Plant Ecology, Radboud University, Nijmegen, The Netherlands Department of Biology, Georgia Southern University, Armstrong Campus, Savannah, Georgia, USA Plant Evolutionary Ecology, University of Tübingen, Institute of Evolution & Ecology, Tübingen, Germany Correspondence Christina L. Richards, Department of Integrative Biology, University of South Florida, 4202 E. Fowler Ave, Tampa, FL 33620, USA. Email: clr@usf.edu Funding information Ministerio de Ciencia e Innovación, Grant/Award Number: Juan de La Cierva incorporación IJC2018- 035018-I; Bundesministerium für Bildung und Forschung, Grant/Award Number: 306055; National Science Foundation, Grant/Award Numbers: DEB-1419960, IOS-1556820; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Grant/Award Number: 072/ 2014; H2020 Marie Sklodowska-Curie Actions, Grant/Award Number: 704141 Abstract The capacity to respond to environmental challenges ultimately relies on phenotypic variation which manifests from complex interactions of genetic and nongenetic mechanisms through development. While we know some- thing about genetic variation and structure of many species of conservation importance, we know very little about the nongenetic contributions to var- iation. Rhizophora mangle is a foundation species that occurs in coastal estuarine habitats throughout the neotropics where it provides critical eco- system functions and is potentially threatened by anthropogenic environ- mental changes. Several studies have documented landscape-level patterns of genetic variation in this species, but we know virtually nothing about the inheritance of nongenetic variation. To assess one type of nongenetic var- iation, we examined the patterns of DNA sequence and DNA methylation in maternal plants and offspring from natural populations of R. mangle from the Gulf Coast of Florida. We used a reduced representation bisulfite Jeannie Mounger, M. Teresa Boquete, and Marc W. Schmid shared first author. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. Evolution & Development published by Wiley Periodicals LLC. Evolution & Development. 2021;23:351-374. wileyonlinelibrary.com/journal/ede 351 352 MOUNGER ET AL. -WILEY- sequencing approach (epi-genotyping by sequencing; epiGBS) to address the following questions: (a) What are the levels of genetic and epigenetic di- versity in natural populations of R. mangle? (b) How are genetic and epi- genetic variation structured within and among populations? (c) How faithfully is epigenetic variation inherited? We found low genetic diversity but high epigenetic diversity from natural populations of maternal plants in the field. In addition, a large portion (up to ~25%) of epigenetic differences among offspring grown in common garden was explained by maternal fa- mily. Therefore, epigenetic variation could be an important source of response to challenging environments in the genetically depauperate popu- lations of this foundation species. KEYWORDS coastal ecosystems, conservation genomics, epigenetic inheritance, foundation species, mangrove 1525142x, 2021, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ede. 12388 by Eugene S. Farley Library, Wiley Online Library on [30/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 1 INTRODUCTION Preserving the ability of populations to respond to en- vironmental challenges is critical to conservation efforts. This ability ultimately depends on phenotypic variation (Björklund et al., 2009; Henn et al., 2018; Norberg et al., 2001). Conserving genetic variation has been championed by numerous researchers studying con- servation in recent decades to ultimately preserve these phenotypic options (Allendorf et al., 2012). However, the focus on genetic variation must be interpreted with caution (Hufford & Mazer, 2003) considering the mis- placed emphasis on the concept that only variation in DNA sequence matters (Bonduriansky & Day, 2018; Keller, 2002, 2014; Sultan, 2015). In fact, Sultan (2015) argued that as modern biologists our task is to restore the context dependence of gene expression and trait varia- tion. This task has become particularly relevant in the context of anthropogenic alterations to natural ecosys- tems. In the framework of re-evaluating the mapping of genotype to phenotype (Keller, 2014; Pigliucci, 2010), we can now use the concepts of Evo-Devo to explore phe- notypic plasticity and genetic and nongenetic structure within populations, as well as examine how these pro- cesses are impacted by climate change (Campbell et al., 2017). Natural epigenetic variation (e.g., alterations to DNA methylation, small RNAs, and chromatin remodeling) has been associated with phenotypic and functional di- versity in plants, emerging both as a molecular-level mechanism underlying phenotypic plasticity and as a potentially important nongenetic source of heritable variation (Balao et al., 2018; Banta & Richards, 2018; Cortijo et al., 2014; Medrano et al., 2014; Zhang et al., 2018). There is increasing evidence that suggests that environmentally-induced epigenetic variation can be heritable, particularly in plants (e.g., Herrera et al., 2017; Richards et al., 2012; Verhoeven et al., 2010) but this contention is not universally supported (reviewed in Richards & Pigliucci, 2020). This source of variation may be imperative for sessile organisms, and for organisms with limited dispersal ability, as they cope with a broad range of environmental conditions without the ability to migrate away from stressors (Balao et al., 2018; Dodd & Douhovnikoff, 2016). Further, rapid phenotypic altera- tions mediated by epigenetic mechanisms may be espe- cially important for persistence in dynamic ecosystems that face significant natural environmental variation as well as anthropogenic impacts, such as those in coastal and alpine regions (Burggren, 2016; Jueterbock et al., 2020; Neinavaie et al., 2021; Nicotra et al., 2015). Much of what is presently known about the func- tionality of epigenetic variation predominantly comes from studies of model organisms (Balao et al., 2018; Niederhuth & Schmitz, 2017; Richards et al., 2017). For instance, epigenetic differences in Arabidopsis thaliana have been linked to heritability in flowering time and primary root length (Cortijo et al., 2014), response to temperature (Kawakatsu et al., 2016), and biotic stressors (Dowen et al., 2012) reviewed in Zogli and Libault (2017). Additionally, inheritance of environmentally induced epigenetic variation has been observed in A. thaliana (Blevins et al., 2014; Lang-Mladek et al., 2010), as well as in several crop species (Bilichak et al., 2015; De Kort et al., 2020; Li et al., 2014) and dandelions (Verhoeven et al., 2010). However, our understanding of how 1525142x, 2021, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ede. 12388 by Eugene S. Farley Library, Wiley Online Library on [30/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License MOUNGER ET AL. epigenetic variation behaves in a variety of species and ecological contexts is growing (Mounger et al., 2021; Neinavaie et al., 2021; Richards & Pigliucci, 2020; Richards et al., 2017). Common garden studies of non-model plant species have elucidated changes in DNA methylation that are associated with community composition (van Moorsel et al., 2019), responses to temperature and nutrient stress (Nicotra et al., 2015; Verhoeven et al., 2010), and inheritance of induced re- sponses (aka transgenerational plasticity; Herman & Sultan, 2016; Puy, Carmona, et al., 2021; Puy, de Bello, et al., 2021; Shi et al., 2018). Moreover, methylation dif- ferences in natural plant populations have been asso- ciated with response to habitat (Foust et al., 2016; Gáspár et al., 2019; Jueterbock et al., 2020; Lira-Medeiros et al., 2010; Schulz et al., 2014; Xie et al., 2015), biotic interactions (e.g., herbivory; Herrera & Bazaga, 2011); reviewed in Alonso et al. (2019), hybridization and allopolyploidization (Mounger et al., 2021; Salmon et al., 2005; Sehrish et al., 2014) and domestication (Chen et al., 2020). However, other studies have shown that epigenetic changes could be explained by single genetic mutations, and several authors have argued that epige- netic variation is largely explained by genetic variation (Becker et al., 2011; Dubin et al., 2015; Sasaki et al., 2019). Understanding the mechanisms of response in foun- dation species has become increasingly important for conservation and management strategies. Work in foun- dation species supports the idea that these species dis- proportionately contribute to maintaining habitat integrity and ecosystem resilience (Ellison, 2019; Keith et al., 2017; Bertness 2020; Qiao et al., 2021). In coastal ecosystems, foundation species must cope with several anthropogenic impacts of habitat destruction and global climate change (Alongi, 2008; Osland et al., 2013; Osland, Day, et al., 2017; Osland, Griffith, et al., 2017). Worldwide, mangrove forests perform significant ecosystem services including buffering storm surges and tidal wave action, reducing erosion, sequestering an estimated 34.4 Tg of carbon per year (Mcleod et al., 2011), and providing habitat for economically important marine fauna (Alongi, 2008). These forests also play important roles in nutrient and sediment dynamics that are integral to the ecosystem processes of several marine systems, notably coral reefs and seagrass flats (Alongi, 2008; Polidoro et al., 2010). Despite their importance, the distribution and persistence of mangrove tree species are threatened by historic and current land-use change as well as by pollu- tion from agriculture and urban runoff, sewage effluents, hazardous materials spills, and other contaminants from human activities (Ellison et al., 2015). Evidence has sug- gested that populations of many mangrove species have -WILEY- 353 moved along the intertidal zone and poleward at pace with changes in sea level, reduced incidence of winter frost, and a variety of other abiotic conditions (Alongi, 2008; Osland, Day, et al., 2017). The mechanisms that allow for this migration are not well understood (Osland et al., 2013; Osland, Griffith, et al., 2017) and coastal development poses a significant barrier to the species' ability to colonize landward (Polidoro et al., 2010; Schuerch et al., 2018) (reviewed in Godoy & de Lacerda, 2015). To date, broad surveys of genetic diversity across the expansive ranges of mangrove species are lacking, and virtually no studies have directly addressed the im- portance of nongenetic variation for the persistence of coastal plant species (but see Foust et al., 2016; Lira- Medeiros et al., 2010; Robertson et al., 2017; Spens & Douhovnikoff, 2016). Genetic variation in the red man- grove, Rhizophora mangle L., has been investigated in various geographic regions to assess patterns of evolution (Duke et al., 2002), hybridization and introgression (Cerón-Souza et al., 2010), genetic population, and sub- population structure (Albrecht et al., 2013; Arbeláez- Cortes et al., 2007; Bruschi et al., 2014; Cerón-Souza et al., 2010; Chablé Iuit et al., 2020), and range expansion in response to climate change (Kennedy et al., 2017; Sandoval-Castro et al., 2012). R. mangle populations vary tremendously in genetic variation across their range. For example, populations along the Pacific Coast of the Americas have greater genetic diversity than those sampled elsewhere within their range (Arbeláez- Cortes et al., 2007; Bruschi et al., 2014; Cerón-Souza et al., 2012). Other studies also suggest that R. mangle populations are not well connected through gene flow (i.e., panmictic; Pil et al., 2011)). Instead, they tend to form somewhat isolated groups, particularly at range ends and in areas of limited tidal flow (Kennedy et al., 2017; Sandoval-Castro et al., 2012). In this study, we used the reduced representation bisulfite sequencing approach epigenotyping by sequen- cing (epiGBS; van Gurp et al., 2016)) to measure genetic and DNA methylation differentiation among red man- grove populations near the northern limit of this species in the Tampa Bay region. We took advantage of the unusual biology of R. mangle that allows for collecting viviparous propagules that are still attached to the ma- ternal plant. From six populations we collected leaves from maternal trees and their offspring propagules to answer the following questions: (a) What are the levels of genetic and epigenetic diversity in natural populations of R. mangle? (b) Are genetic and epigenetic variation structured among populations of this species in the wild? (c) To what extent does epigenetic variation in the off- spring correlate with the maternal plants? 354 -WILEY- MOUNGER ET AL. 1525142x, 2021, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ede. 12388 by Eugene S. Farley Library, Wiley Online Library on [30/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2 MATERIALS AND METHODS | 2.1 Study species The red mangrove, R. mangle L. 1753 (Malpighiales, Rhizophoraceae), is an estuarine tree species present along the tropical and subtropical coasts of the Americas, eastern Africa, Bermuda, and a handful of outlying is- lands in the South Pacific (DeYoe et al., 2020; Proffitt & Travis, 2014; Tomlinson, 2016). Rhizophora mangle typically grows in the intertidal regions of sheltered coastlines, but can also be found in estuaries, tidal creeks, and occasionally along the edges of hypersaline salt pans (DeYoe et al., 2020; Duke et al., 2002). It is a dominant mangrove species across its range, including along peninsular Florida (DeYoe et al., 2020). Like other mangrove species, R. mangle functions as a foundation species by altering environmental conditions, providing nursery grounds for numerous fish species, and serving as a crucial primary producer within tropical and sub- tropical estuarine environments (Ellison, 2019; Ellison et al., 2005; Proffitt & Travis, 2005). R. mangle is a monoecious, self-compatible species (Nadia & Machado, 2014). Pollination in this species is mediated by both insects and wind (ambophilous pollen dispersal), which has been shown to effectively promote outcrossing and long-distance gene flow, but these out- crossing events are thought to be rare (Cerón-Souza et al., 2012). R. mangle produces viviparous propagules that mature for up to 6 months on maternal trees to lengths of 15-20 cm (DeYoe et al., 2020; Goldberg & Heine, 2017). These propagules have considerable long- evity at sea, surviving up to 3-4 months in the water column allowing a great potential for long-distance dis- persal through ocean current transportation (Duke et al., 2002; Rabinowitz, 1978). However, propagules fre- quently recruit either directly underneath or within short distances of maternal trees (Goldberg & Heine, 2017; Sengupta et al., 2005; Sousa et al., 2007). Maximum tidal action via king tides and major weather events may be required to move propagules significant distances (Goldberg & Heine, 2017). (Figure 1). At each population, we collected leaf tissue and 20 propagules directly from each of 10 maternal trees separated by at least 10 m from each other to maximize the range of genetic variation sampled within each population (Albrecht et al., 2013). With this design, propagules from each maternal tree were at least half- siblings but they could be more closely related due to the reported high selfing rate of R. mangle in the study area (Proffitt & Travis, 2005). We maintained leaf tissue of maternal trees on ice until transported to the Richards laboratory at the University of South Florida and then stored samples at -80°C (N=60). We refrigerated the propagules at 4°C for up to 14 days until we planted them in the greenhouse at the University of South Florida Botanical Gardens. In the greenhouse, propagules from four of the maternal trees at AC and nine of the maternal trees at FD failed to establish, so we returned to sample propagules and maternal tissue from 8 new maternal trees at FD on August 12 and 29, and from the same original maternal trees at AC on October 17. We planted propagules in 0.5 L pots with a 50:50 mixture of sand and peat soil and grew them for 9 months in the greenhouse at 18-29°C as part of a large common garden experiment designed to assess propagule response to salinity (15 ppt and 45 ppt reflecting the Anclote Key Werner-Boyce Honeymoon Island Upper Tampa Bay Weedon Island 2.2 Field sampling We sampled six populations of R. mangle between June 9 and June 26, 2015, in the west coast of central Florida (USA) within the following county and state parks: An- clote Key Preserve State Park (AC), Fort De Soto Park (FD), Honeymoon Island State Park (HI), Upper Tampa Bay Conservation Park (UTB), Weedon Island Preserve (WI), and Werner-Boyce Salt Springs State Park (WB) 5 10km Fort De Soto FIGURE 1 Map of six collection sites (aka populations) within the greater Tampa Bay region (FL, USA) generated in ArcGIS. We collected Rhizophora mangle leaves and propagules from ten maternal trees in Werner-Boyce Salt Springs State Park (WB), Anclote Key Preserve State Park (AC), Honeymoon Island State Park (HI), Upper Tampa Bay Conservation Park (UTB), Weedon Island Preserve (WI), and Fort De Soto Park (FD) 1525142x, 2021, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ede. 12388 by Eugene S. Farley Library, Wiley Online Library on [30/10/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License MOUNGER ET AL. range of salinity measured in the field populations) and nitrogen (N) (no N amendment and high N, amended at approximately 3 mg N per pot each week, which is equivalent to a rate of 75 kg N per hectare per year; Langanke, 2017). The experiment was set up in five spatial blocks. Within each block we randomized the position of plants such that each block had one replicate of each family for each treatment combination (i.e., a full factorial randomized complete block design with N=6 populations x 10 maternal families × 4 treatment combi- nations × 5 blocks X-1 replicate/block = 1150 plants; Langanke, 2017; Richards et al., 2021). We watered all plants daily with tap water until propagules were planted and established for several weeks. In mid-October, we started applying treatments twice per week. Replicates of some families were not represented in all five blocks due to limitations in the number of viable propagules. We sampled one block of plants per day between 2 and 7 May 2016, storing leaf tissue from each plant in paper envelopes, which we dried in large glass containers with silica gel desiccant beads (N = 841 plants with leaves at the end of the experiment, ranging from 97 to 183 offspring per po- pulation). For the current study, we wanted to assess inheritance of epigenetic variation. Since epigenetic variation can be induced by environmental variation, we only used plants from the low salinity, no nitrogen amendment treatment for the epigenetic analysis (N = 158). 2.3 | Laboratory methods For genetic and epigenetic analyses, we isolated total genomic DNA from a total of 247 samples, including 60 maternal trees from the field and 187 offspring grown in the greenhouse. The 187 individuals represented 46 maternal families across the six populations (5-10 families per population). We increased replication of some families for genetic (not epigenetic) diversity ana- lyses with 29 plants that had received either high salt or high nitrogen treatments. By population, in the final group of samples that made it through the filtering pro- cess these 29 samples included AC (3 of 10 individuals), FD (5/47), HI (3/19), UTB (8/49), WB (4/24), WI (6/38) (Table S1). To prepare the epigenotyping-by-sequencing (epiGBS) libraries, we disrupted approximately 80 mg of leaf tissue using stainless steel beads in a Qiagen Tis- sueLyser II. Then, we extracted the DNA using the Qiagen Dneasy Plant Mini Kit following the manu- facturer instructions with slight modifications that in- cluded an extended lysis step, a post-extraction clean-up -WILEY- 355 with Buffer AW2, and elution in molecular grade water. The final concentration of DNA was quantified using the Qubit 3.0 Fluorometric dsDNA BR assay kit (Life Technologies). We prepared libraries for epiGBS following the methods outlined in van Gurp et al. (2016). In brief, we digested 400 ng of genomic DNA from each sample with the methylation-sensitive restriction enzyme PstI, and ligated methylated, non-phosphorylated barcoded adapters to the resulting fragments. The barcoded adaptors were designed so that we can identify forward ("Watson") and reverse ("Crick") strands for each fragment within each individual. Having the strand information allows for differentiating between C/T polymorphisms and methylation polymorph- isms because we can recreate when unmethylated cytosines were present in either strand before bisulfite treatment (for details see van Gurp et al., 2016). We concentrated the libraries (NucleoSpin™ Gel and PCR Clean-up Kit), and size selected the fragments using 0.8× SPRI beads (Agencourt AMPure XP; Beckman Coulter). We performed nick translation, bisulfite con- verted the fragments (EZ Lightning methylation kit; Zymo Research), and performed polymerase chain reac- tion amplification with the KAPA HIFI Uracil+ Hotstart Ready Mix (Roche). Finally, we quantified the libraries using the Qubit dsDNA assay kit, pooled them with equimolar concentrations (each sequenced library con- sisted of 96 multiplexed samples), and assessed their quality by analyzing 1 µl on a High Sensitivity DNA chip using an Agilent 2100 Bioanalyzer. We prepared libraries and sequenced paired-end reads of the 60 maternal plant samples and 36 randomly chosen offspring at the University of Florida Interdisciplinary Center for Bio- technology Research on one lane of the Illumina HiSeq. 3000 (2 × 150 bp) in February 2017. In August 2017, we prepared separate libraries for an additional 151 offspring and sequenced them at Novogene (HK) Company Lim- ited in Hong Kong on two lanes of the Illumina HiSeq X-Ten System (2×150 bp): one lane contained 96 off- spring samples, a second lane held 55 offspring samples along with 40 samples of another species prepared with the same protocol for another study (Ceratodon purpur- eus; Boquete et al., unpublished). 2.4 | Data processing We processed the raw sequencing files using the pipe- line provided by van Gurp et al. (2016) as in van Moorsel et al. (2019), available on https://github. Com/ thomasvangurp/epiGBS, with a bug-fix modification (i.e., described in Gawehns et al., 2020); https://github. com/MWSchmid/epiGBS_Nov_2017_fixed). Briefly, we