DOI: 10.5061/dryad.8717pg9
title: Data from: Evidence for local adaptation to extreme heat across populations of a widespread tree from quantitative proteomics

description: 1. Heat waves are increasing in frequency and intensity globally with
 negative consequences for biological function. Assessing the effect of
 extreme heat on species requires an understanding of their adaptive
 capacity for mitigating physiological damage. Where long-term exposure to
 hot conditions in natural populations provides sufficient selection
 pressure, populations should exhibit signals of adaptive thermotolerance
 to temperature extremes. 2. Using quantitative proteomics, we tested this
 idea in the widespread and commercially-important tree species Eucalyptus
 grandis (Flooded Gum). Seedlings from six natural populations of E.
 grandis spanning a 2000 km gradient were exposed to a four-day extreme
 heat treatment (42-24°C day-night cycle) in experimental growth chambers.
 Populations differed in their long-term exposure to extreme heat
 conditions, defined both as the number of days annually ≥15°C above mean
 annual temperature (MAT), and average number of days annually with
 temperature maxima ≥ 35°C between 1960-1990. 3. Long-term exposure to
 extreme heat conditions in the field predicted the protein-level response
 of E. grandis to experimental heat waves. Relationships between long-term
 extreme heat exposure and protein increases were positive and linear for
 all combinations of extreme heat (days ≥15°C above MAT, mean days with
 temperature maxima ≥35°C annually) and expression (all differentially
 expressed proteins, isolated heat shock proteins, proteins involved in
 molecular stress responses). 4. Although extreme climate events are
 typically rare (e.g. 1 day 15° ≥ MAT per 5 years in some populations in
 our study), E. grandis populations sampled from across a 2000km range
 exhibit a clear capacity to increase expression of proteins involved in
 heat stress in response to simulated heat wave exposure. Presumably they
 respond similarly under natural heat wave conditions. 5. We show that a
 long-lived species with a broad environmental niche exhibits adaptive
 variation in protein response to temperature extremes at the population
 level. This implies that restoration, translocation and silvicultural
 programs should consider the molecular response of source populations to
 climatic extremes to maximise success under future climates. 6. Tree
 populations with low exposure to extreme heat conditions may be limited in
 their ability to respond to heat wave events, potentially limiting their
 adaptive capacity to withstand novel climate conditions.
description: Protein expression under
 heat wave conditionsProtein ratios from
 quantitative proteomics of leaf samples collected after a four-day heat
 wave (42 degree) and control (28 degree) treatment for Eucalyptus grandis.
 Protein identity and quantity were determined using Proteome Discoverer
 V1.3 software (Thermo Scientific, United States) run from a local MASCOT
 server (Matrix Science, London, U.K.). The E. grandis protein sequences
 available through UniProt (http://www.uniprot.org, n = 44,150 proteins;
 October 2016) were used as a reference search database. The following
 parameters were used for peptide to spectrum matching in MASCOT: MS
 tolerance, ±10 ppm; enzyme, trypsin with one missed cleavage; fragment
 mass error, 0.1 Da; static modifications, carbamidomethylation of cysteine
 and 10-plex TMT tags on lysine residues and peptide N-termini; variable
 modifications, oxidation of methionine and deamidation of asparagine and
 glutamine. Spectra were also searched against a reversed-sequenced decoy
 database to determine false discovery rates (FDR) and filtered at a
 maximum FDR cut-off of 1% at the protein level. Only peptides below the
 MASCOT significance threshold filter of p = 0.05 were included in the
 final dataset, and proteins with at least two unique peptides were
 regarded as confident identifications. Relative quantification of proteins
 was achieved by pairwise comparison of TMT intensities, using the ratio of
 the labels for each of the treatment replicates (numerator) versus the
 labels of their corresponding pooled control reference
 (denominator).Appendix_s2.xlsx