{"doi":"10.1111/nph.17816","title":"Transcriptional acclimation and spatial differentiation characterize drought response by the ectomycorrhizal fungus <i>Suillus pungens</i>","abstract":"Increasing temperature and decreasing precipitation has led to more frequent and extreme drought events in many regions throughout the world. In the western United States, multi-year drought events have led to widespread plant mortality and extreme wildfires (Asner et al., 2016; Pickrell & Pennisi, 2020). Communities of ectomycorrhizal fungi (EMF) – root symbionts which play a critical role in forest health – are also thought to be threatened by these climatic changes (Fernandez et al., 2017; Steidinger et al., 2019). However, altered soil moisture conditions have complex direct and indirect effects on both fungi and ecosystem processes, such as nutrient availability (Schimel, 2018), making it difficult to elucidate the primary drivers of community composition based on field observations or experiments (Pena & Polle, 2014). As a result, efforts to identify the genes or traits involved in response to drought events are critical for accurate prediction of future EMF composition and function (Allison & Treseder, 2008; Romero-Olivares et al., 2019). Despite this fact, we are not aware of any studies that have used gene expression analyses to measure the response of individual EMF to drought events or other climatic stressors. In this study, we used RNA-sequencing (RNA-Seq) to measure transcriptional changes in the fungus Suillus pungens (SP) exposed to experimental drought. We grew SP in symbiosis with Pinus muricata (PM) in a growth chamber where we manipulated both long-term (chronic) and short-term (acute) soil moisture and sequenced messenger RNA (mRNA) extracted from both ectomycorrhizal roots and extraradical mycelium (ERM). Our primary aims were to: (1) demonstrate the utility of RNA-Seq to quantify response to global change stressors for EMF; (2) identify biological functions involved in drought response by comparing gene expression across moisture treatments and in different organs of EMF; and (3) estimate the potential for fungal acclimation by comparing gene expression between chronic and acute drought stress treatments. In the first experiment, 2-month-old SP colonized seedlings were subjected to two watering regimes (drought, control) for 10 wk. The amount of water added (4 or 10 ml, biweekly) was chosen to maintain distinct but field-relevant soil moisture levels (Kennedy & Peay, 2007), while mimicking longer-term, climatic trends expected in California, USA, where SP and PM are native. In the second experiment, seedlings from the control treatment were exposed to dry down (i.e. no additional watering) for periods of 5, 7, 9, 11, 14 and 15 d. This treatment was intended to simulate the onset of acute short-term drought events that occur regularly in California. After each experiment, we measured plant biomass, scored SP root colonization, conducted soil chemical analyses, and removed a subset of colonized roots and soil containing ERM for mRNA extraction. Complementary DNA (cDNA) libraries were sequenced on an Illumina HiSeq 4000 2 × 150 bp, with 228 × 106 reads obtained from 15 root and 22 soil samples (Supporting Information Table S1). Fungal transcripts were mapped against the annotated transcriptome of SP strain FC27 (JGI GOLD Project ID Gp0251823) using Kallisto (Bray et al., 2016). Analyses of variance was used to compare plant biomass and SP root colonization and DESeq2 (Love et al., 2014) to compare fungal gene expression across drought and control treatments, respectively. Additional details on the experiment, molecular methods, bioinformatics and statistics can be found in Methods S1. At a transcriptional level, SP responded very differently to acute and chronic drought. The acute drought treatment caused major changes in gene expression (Fig. 1). After 5–15 d of dry down, 21% of all genes (2069) were downregulated and 20% (1968) upregulated in ERM (adjusted P < 0.1; Fig. 1a; Dataset S1). A sizable but somewhat modified pattern was seen in ectomycorrhizal roots, with 12% of genes downregulated (1209) and 16","journal":"New Phytologist","year":2021,"id":192368,"datarank":0.6785268159886664,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"self_citation_contribution":0.38474240361923057,"citation_network_contribution":0.29378441236943587,"self_endowment_contribution":0.38474240361923057,"citer_contribution":0.29378441236943587,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":8,"citers_with_citation_signal":8,"citers_with_endowment":8,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9604,"is_data_producer":true,"deposit_databanks":{"Dryad":["10.5061/dryad.qnk98sfht"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":759409,"name":"Rogério Margis","orcid":"0000-0002-2871-4473","position":1,"is_corresponding":false},{"id":759410,"name":"Andrea Ramirez","orcid":"0000-0003-3986-5792","position":2,"is_corresponding":false},{"id":296143,"name":"Nhu Nguyen","orcid":"0000-0001-8276-7042","position":3,"is_corresponding":false},{"id":296142,"name":"Lotus Lofgren","orcid":"0000-0002-0632-102X","position":4,"is_corresponding":false},{"id":296146,"name":"Hui‐ling Liao","orcid":"0000-0002-1648-3444","position":5,"is_corresponding":false},{"id":296144,"name":"Rytas Vilgalys","orcid":"0000-0001-8299-3605","position":6,"is_corresponding":false},{"id":296153,"name":"Peter G. Kennedy","orcid":"0000-0003-2615-3892","position":7,"is_corresponding":false},{"id":759411,"name":"Kabir Peay","orcid":"0000-0002-7998-7412","position":8,"is_corresponding":false},{"id":759408,"name":"Sonya Erlandson","orcid":"0000-0002-8032-2602","position":0,"is_corresponding":true}],"reference_count":23,"raw_metadata":null,"created_at":"2026-07-18T23:49:43.496702Z","pmid":"34668199","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}