Next Article in Journal
Strawberry FaNAC2 Enhances Tolerance to Abiotic Stress by Regulating Proline Metabolism
Next Article in Special Issue
COR/LEA Proteins as Indicators of Frost Tolerance in Triticeae: A Comparison of Controlled versus Field Conditions
Previous Article in Journal
The Central Negative Regulator of Flooding Tolerance, the PROTEOLYSIS 6 Branch of the N-degron Pathway, Adversely Modulates Salinity Tolerance in Arabidopsis
Previous Article in Special Issue
Temperature and Light-Quality-Dependent Regulation of Freezing Tolerance in Barley
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 9
Issue 11
10.3390/plants9111416
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Carbohydrate Accumulation and Differential Transcript Expression in Winter Wheat Lines with Different Levels of Snow Mold and Freezing Tolerance after Cold Treatment

by
Erika B. Kruse
1,
Samuel Revolinski
1,
Jesse Aplin
2,
Daniel Z. Skinner
3,
Timothy D. Murray
4,
Charles G. Edwards
2 and
Arron H. Carter
1,*
1
Department of Crop and Soil Science, Washington State University, Pullman, WA 99164, USA
2
School of Food Science, Washington State University, Pullman, WA 99164, USA
3
Wheat Health, Genetics and Quality Research Unit, USDA-ARS, Pullman, WA 99164, USA
4
Department of Plant Pathology, Washington State University, Pullman, WA 99164, USA
*
Author to whom correspondence should be addressed.
Plants 2020, 9(11), 1416; https://doi.org/10.3390/plants9111416
Submission received: 27 August 2020 / Revised: 12 October 2020 / Accepted: 17 October 2020 / Published: 23 October 2020
(This article belongs to the Special Issue Plant and Microbe Adaptations to Cold)
Browse Figures
Versions Notes

Abstract

:
Winter wheat (Triticum aestivum L.) undergoes a period of cold acclimation in order to survive the ensuing winter, which can bring freezing temperatures and snow mold infection. Tolerance of these stresses is conferred in part by accumulation of carbohydrates in the crown region. This study investigates the contributions of carbohydrate accumulation during a cold treatment among wheat lines that differ in their snow mold tolerance (SMT) or susceptibility (SMS) and freezing tolerance (FrT) or susceptibility (FrS). Two parent varieties and eight recombinant inbred lines (RILs) were analyzed. The selected RILs represent four combinations of tolerance: SMT/FrT, SMT/FrS, SMS/FrT, and SMS/FrS. It is hypothesized that carbohydrate accumulation and transcript expression will differ between sets of RILs. Liquid chromatography with a refractive index detector was used to quantify carbohydrate content at eight time points over the cold treatment period. Polysaccharide and sucrose content differed between SMT and SMS RILs at various time points, although there were no significant differences in glucose or fructose content. Glucose and fructose content differed between FrT and FrS RILs in this study, but no significant differences in polysaccharide or sucrose content. RNAseq was used to investigate differential transcript expression, followed by modular enrichment analysis, to reveal potential candidates for other mechanisms of tolerance, which included expected pathways such as oxidative stress, chitinase activity, and unexpected transcriptional pathways. These differences in carbohydrate accumulation and differential transcript expression begin to give insight into the differences of wheat lines when exposed to cold temperatures.

Graphical Abstract

1. Introduction

Winter wheat (Triticum aestivum L.) plants require a period of cold temperatures to shift from vegetative growth to reproductive growth, a transition known as vernalization. Vernalization is primarily controlled by VRN1 genes, such that the recessive alleles result in a requirement for cold temperatures to initiate reproductive growth [1]. A typical greenhouse treatment to fulfill the vernalization requirement consists of approximately 6–8 weeks of growth at 4 °C under short day-length [2,3]. Natural winter conditions can be far more stressful to a wheat plant, however. Thus, in the autumn, winter wheat undergoes cold acclimation, which is a process involving many physiological, biochemical, and genetic changes that prepare a plant to survive the potentially freezing and snow-covered winter.
During winter, young wheat plants may be exposed to freezing temperatures when not insulated with snow cover. To avoid cell death associated with freezing temperatures, winter wheat accumulates simple carbohydrates, including sucrose, glucose, and fructose, in the crown region, thus lowering the freezing point of the cell and enabling the plant to survive [4,5]. These carbohydrates also serve as an energy source for the plant while photosynthesis is diminished due to cold temperatures and potential snow cover [4,6]. When there is snow cover, a diverse complex of fungal and fungal-like pathogens, referred to as ‘snow mold’ can also take advantage of a plant’s carbohydrate stores for energy. Persistent snow cover, which insulates plants from freezing ambient temperatures, provides a favorable environment for these psychrophilic, or “cold-loving”, pathogens [7]. To avoid infection by snow mold pathogens, winter wheat accumulates fructans, which are large carbohydrates consisting primarily of chains of fructose molecules [8]. These complex carbohydrates are thought to be unusable for snow mold pathogens but can be broken down by the plant for energy as needed [6,9]. Accumulation of any type of carbohydrate, whether simple or complex, can contribute to freezing tolerance, although only complex carbohydrates have been shown to contribute to snow mold tolerance [10,11,12,13].
Mohammad et al. [14] found that winter wheat varieties with moderate to high snow mold tolerance accumulated and maintained larger reserves of nonstructural carbohydrates than varieties with low to moderate snow mold tolerance. Of the non-structural polysaccharides accumulated in wheat, fructans have been shown to account for up to 30% of the dry weight of cold-acclimated seedlings [15]. In a study comparing carbohydrate levels among cultivars varying in freezing and snow mold tolerance, Yoshida et al. [8] observed that the most freezing-tolerant variety accumulated the most mono- and di-saccharides and the least polysaccharides. In direct contrast, the most snow mold tolerant variety accumulated the most polysaccharides and the least mono- and di-saccharides, although it had the greatest reserves of both poly- and simple saccharides remaining in the spring. Accordingly, a third variety with moderate tolerance to each snow mold and freezing accumulated intermediate amounts of both polysaccharides and simple saccharides. Come spring, the remaining reserves of simple sugars were similar between the moderately tolerant variety and the snow mold tolerant variety, but the reserves of polysaccharides in the moderately tolerant variety were nearly zero, as in the freezing tolerant variety. For both freezing tolerance and snow mold infection, it has been suggested that the primary difference between tolerant and susceptible wheat varieties is the amount of carbohydrates remaining at the end of winter [16]. Whatever the role of fructans, the amount accumulated and the rate of use is likely to determine the degree of snow mold tolerance [17]. The genes responsible for fructan synthesis encode for the following enzymes: 1-SST, 1-FFT, 6-SFT, and 6G-SFT [18]. All of these genes are under the control of the transcription factor MYB13. The enzymes involved in fructan metabolism are 1-FEH, 6-FEH, and 6-KEH [19,20].
VRN-1 interacts with the FR-2 locus and copy number and sequence variations at each of these loci account for much of the variation between freezing tolerant and susceptible lines [21]. In addition, copy number variation in the CBF (C-repeat binding factors) regulon at the FR-2 locus contributes to snow mold tolerance [22]. The CBF regulon consists of numerous COR (cold-responsive) genes and transcription factors including the well-characterized, temperature-induced genes, COR14b and Wcs120. These genes encode a chloroplast-protective peptide to prevent photodamage and a dehydrin suspected to prevent freezing-related dehydration [23]. Additional wheat dehydrin genes, Lea and Wdhn13, have also been correlated with protecting proteins and DNA from freezing damage [24,25]. Antioxidant enzymes and antifreeze proteins have also been indicated in defense against freezing damage [26,27,28,29,30]. The numerous genes involved in freezing tolerance reflect the variety of mechanisms involved in freezing tolerance.
Similarly, snow mold tolerance is a complex trait involving carbohydrate dynamics, pathogenesis-related proteins, and lipid transfer proteins. Chitinase and glucanase were induced in cold-acclimated wheat plants, as were the antipathogenic polypeptides resulting from expression of a novel defensin-like gene, Tad1 [4,31]. Several classes of lipid transfer proteins are also activated in response to cold temperatures and are suspected to strengthen structural barriers and arrest microbial growth [32]. No specific R genes for snow mold are known, and snow mold tolerance seems to be more of a general defense response [4].
Previous studies have verified the expression of snow mold and cold tolerance-related genes using semi-quantitative RT-PCR. VRN1-A in winter wheat was found to increase transcription when exposed to short daylight conditions compared to long daylight conditions [33]. COR14b was found to be expressed at higher levels in the cold-tolerant “maintained vegetative phase” mutant wheat [34] and for freezing conditions in the cultivar Yangmai 16 [35]. CS120 was also found to increase in Yangmai 16 when exposed to freezing conditions [35]. CS120 and wdhn13 transcription levels were found to be highly correlated with freezing tolerance [25]. Wdhn13 was found to increase transcription during drought conditions in a drought-tolerant wheat line and other members of the Triticeae genus [36]. TAD1 overexpression via a transgenic maize ubiquitin promoter has been shown increase tolerance to speckled snow mold and Fusarium head blight [37].
Analyzing the patterns of carbohydrate accumulation and use among recombinant inbred lines that vary in their tolerance to freezing stress and snow mold infection is expected to elucidate the connection between carbohydrate metabolism and both stresses. Past studies have focused on differences in carbohydrate storage between unrelated winter wheat varieties. In the present study, we analyze differences among recombinant inbred lines derived from parents that differ in their tolerance to both freezing stress and snow mold infection. It is hypothesized that carbohydrate dynamics differ between the tolerant and susceptible parents. The objectives of this study were to (1) demonstrate distinct patterns of carbohydrate accumulation in accordance with their different combinations of freezing and snow mold tolerance in a recombinant inbred line population, and (2) investigate differences in transcript expression during cold hardening to detect differences between tolerant and susceptible recombinant inbred lines (RILs).

2. Results

2.1. Carbohydrate Accumulation

Concentration of polysaccharides, sucrose, glucose, and fructose were compared between tolerance categories and time points to detect a relationship that could suggest a role in tolerance to snow mold and freezing. Analysis of variance of the polysaccharide content of each RIL at each time point showed no significant differences between the replicates (p = 0.68) or tolerance categories (p = 0.20), but significant differences existed between time points (p < 0.01) (Figure 1). Polysaccharide content increased in weeks 3 through 9 in RILs among all four tolerance categories and leveled off in later weeks. The maximum value of polysaccharide concentration was reached in week 9 amongst the RILs with both snow mold tolerance and freezing tolerance. By contrast, the minimum concentration of polysaccharides was reached in week 11 by the RILs with freezing tolerance and susceptibility to snow mold.
Analysis of variance of each of the polysaccharide, sucrose, glucose, and fructose contents, demonstrated no significant differences among the replicates. Polysaccharide content increased from week 3 to week 9, at which time the maximum polysaccharide content was reached in RILs across all tolerance categories, although it was greatest in RILs with SMT (Figure 1). Polysaccharide content only differed significantly between SMT and SMS RILs at week 9 (p = 0.04; Figure 2). At no time point did polysaccharide content differ significantly between FrT and FrS RILs. Sucrose content varied little between weeks 3 and 7 and reached its maximum in weeks 9 and 10 before decreasing toward initial levels in later weeks (Figure 1). Sucrose content differed between SMT and SMS RILs at weeks 5 (p = 0.01) and 13 (p = 0.03) (Figure 2), but it never differed significantly between FrT and FrS RILs. Glucose content peaked at week 5, decreased in all tolerance categories until week 9, and varied at succeeding time points (Figure 1). It differed between FrT and FrS RILs in weeks 10 (p = 0.01) and 12 (p = 0.04; Figure 2). Fructose content was steady in weeks 3 through 12 and peaked at the final time point, when both the polysaccharide and sucrose content decreased (Figure 1). Fructose content differed between FrT and FrS RILs at weeks 3 (p = 0.02), 7 (p = 0.02), and 10 (p = 0.02).

2.2. Transcript Expression of Genes of Interest

Transcripts of genes of interest from previous studies described in the introduction were tested for differential expression, and significant expression differences were detected for within-genotype time point comparisons and between-genotype comparisons at both 3 and 11 weeks of vernalization. VRN1-A is significantly upregulated in all the RILs in week 3 compared to week 11 (Figure 3). For the SMT/FrT RIL, 6-SFT, Chi 3, and MYB56 were upregulated significantly whereas cor14b, CS120, and Tad1 were downregulated from week 3 to week 11 during the cold treatment (Figure 3). In the SMS/FrT RIL, all of the carbohydrate-related genes were significantly upregulated whereas cor14b and both fungal defense genes were significantly downregulated (Figure 3). In the SMT/FrS RIL, the abiotic stress related genes, cor14b, CS120, and Wdhn 13, along with the fungal defense gene, Tad1, were significantly downregulated in week 11 compared to week 3 (Figure 3). The SMS/FrS RIL had significant up regulation of the SST-D1a, SST-A1, and 6-SFT carbohydrate modification-related genes and MYB56 between week 3 and week 11 of the cold treatment (Figure 3). The SMS/FrS RIL also had down regulation of cor14b, CS120, Wdhn 13, and Tad1 (Figure 3) between week 3 and week 11.
Genotype comparisons of transcript expression (Figure 4) were performed at week 3 in the cold treatment and revealed that only the SMT/FrT RIL had significant differences with other RILs. Genes related to carbohydrate modification and abiotic stress response were downregulated while Chi 3 was upregulated in the other RILs as compared to SMT/FrT. In week 3 the carbohydrate processing genes SST-D1a, SST-A1, and 6-FEH were downregulated and the Chi 3 gene was upregulated in the SMS/FrS RIL compared to the SMT/FrT RIL (Figure 4). After 3 weeks of cold treatment the SMS/FrT RIL had significantly lower transcript expression in SST-D1a, SST-A1, 1-FEHw1, 6-FEH, cor14b, CS120, and wdhn 13, while Chi 3 had significantly higher transcript expression, compared to the SMT/FrT RIL (Figure 4). The SMT/FrT against SMT/FrS comparison at week 3 showed only a significantly lower level of transcript expression for the CS120 and wdhn 13 genes (Figure 4).
Transcript expression levels of known genes were compared between genotypes after 11 weeks of cold treatment, revealing that the Chi 3 gene, genes related to carbohydrate modification, and genes involved with cold/drought tolerance were significantly differentially regulated between RILs (Figure 5). The SMT/FrT RIL had significantly higher transcript expression of the SST-D1a, SST-A1, 1-FEHw1, 6-FEH, CS120, Wdhn13, and Chi 3 genes compared to the SMS/FrS RIL. Compared to the SMS/FrT RIL, the SMT/FrT RIL had significantly higher transcript expression of Wdhn13 and Chi 3 genes (Figure 5). The SMT/FrT RIL had significantly higher transcript expression of SST-D1a, 6-FEH, cor14b, CS120, Wdhn13, and Chi 3 genes than the SMT/FrS RIL (Figure 5). After 11 weeks of cold treatment SST-D1a, SST-A1, 1-FEHw1, 6-FEH, and CS120 were significantly upregulated while Chi 3 was significantly downregulated in the SMS/FrT RIL compared to the SMS/FrS RIL. Transcript expression of SST-A1, 6-SFT, and VRN-1A genes was significantly higher while cor14b, Wdhn13, Tad1, Chi 3, and MYB56 were significantly lower in SMT/FrS compared to SMS/FrS (Figure 5). After 11 weeks of cold treatment SST-D1a, 1-FEHw2, 6-FEH, cor14b, CS120, Wdhn13, and MYB56 were significantly upregulated, while 6-SFT was significantly downregulated in the SMS/FrT RIL compared to the SMT/FrS RIL (Figure 5).

2.3. Modular Gene Enrichment

Modular enrichment analysis was used to identify other pathways contributing to tolerance. Comparisons were made between individual RILs at two different time points (Table 1) and between different RILs at each of the two time points (Table 2). The cross-time comparisons in Table 1 show that the SMS/FrS RIL had different expression levels only in the peroxisome and oxidative stress module, whereas the SMT/FrT RIL was the only RIL where the modified Fisher’s exact test for enrichment yielded non-significant enrichment in expression for gene ontology (GO) terms in that cluster. The metabolism and redox reactions and nuclear binding and protein modification modules only changed significantly in SMT RILs. The cell wall carbohydrates and chitin metabolism module had a significant enrichment score in the FrT RILs in the cross-time comparison. A beta-glucan synthesis module was only significant in the SMS/FrT RIL.
When comparing different RILs within the same time point, a module containing carbohydrate metabolism gene transcripts was significant only in the SMT/FrT and SMS/FrT comparison (Table 2). The module associated with cell wall and chitin metabolism was significant for at least one of the two time points in all comparisons between SMS and SMT except for the SMT/FrT and SMS/FrS comparison. However, the cell wall and chitin metabolism module also appeared significant for the SMS/FrS and SMS/FrT comparison. The most frequent significant module across the genotype comparisons contained genes with GO terms related to metabolism and redox reactions. The metabolism and redox module were significant in all comparisons except the SMT/FrT and SMT/FrS comparison, suggesting that response to oxidative stress is a component in both freezing and snow mold tolerance.

3. Discussion

The accumulation and maintenance of carbohydrates in the crown region has been shown, repeatedly, to correspond to tolerance of snow mold and freezing temperatures in winter wheat. Such studies, however, have been conducted using unrelated wheat varieties [8,16]. In this study, comparisons of carbohydrate dynamics between RILs with different combinations of tolerance suggested that carbohydrate dynamics did not vary along the divisions used to categorize the RILs. Making comparisons between SMT and SMS RILs and between FrT and FrS RILs showed significant differences for various carbohydrates at a few key time points, which varied for individual carbohydrates. Although the carbohydrate content differed significantly at several time points, the relationship between greater carbohydrate content and tolerance was inconsistent. This inconsistency may be due, in part, to the RILs chosen to represent the four tolerance categories, particularly for those RILs that were tolerant to only one of the traits. Because of the shared pathways involved in these tolerance traits, it is difficult to find plants that are fully tolerant to snow mold while also fully susceptible to freezing. Nevertheless, the tolerance scores of the tolerant RILs were significantly greater than those of the susceptible RILs, indicating that the categories were sufficiently distinct to potentially reveal the differences responsible for the variation in their tolerance levels. In addition, tolerance is likely conferred by traits other than carbohydrate accumulation, so the transcript expression of known genes related to snow mold and freezing tolerance was investigated, and modular enrichment analysis was performed to investigate potential mechanisms.
Modular enrichment analysis revealed expected mechanisms of tolerance to freezing and snow mold. However, modular enrichment analysis is limited by unidirectional results and was not able to entirely separate the mechanisms for freezing and snow mold tolerance due to the complexity of the underlying pathways and complications of trying to analyze the traits independently. For example, the appearance of a chitinase and cell wall metabolism cluster made sense where snow mold tolerance contrasted. However, the cell wall and chitin metabolism module were also significant for the SMS/FrS and SMS/FrT comparison suggesting that freezing tolerance is improved in lines with increased transcript expression of genes related to fungal defense, perhaps due to linkage between these genes and others contributing to freezing tolerance. The significant enrichment of metabolism and redox reaction pathways in most comparisons supports other results indicating redox responses in tolerance to abiotic stress [38,39,40] as well as a defense to fungal infections [41,42,43]. However, because modular enrichment uses the mean of values generated from unidirectional tests, it is not clear what lines expressed more or less transcripts for a given GO term or enrichment module. The carbohydrate metabolism module was significant only in SMT/FrT and SMS/FrT comparison after cold treatment, consistent with the hypothesis of differing carbohydrates for snow mold tolerance and increased fructan accumulation. Differences in carbohydrate metabolism were significant only after cold treatment, likely because the plants respond differently to changes in the environment.
To parse out the modular enrichment analysis further, differential transcript expression analysis of specific genes related to snow mold and freezing tolerance was performed. Comparing each RIL’s transcript expression at weeks 3 and 11 reveals three genes that are differentially expressed regardless of the tolerance category: VRN1-A, cor14b, and Tad1. The upregulation of VRN1-A is consistent with the expected vernalization response to the short day and cold temperature treatment. The down-regulation of cor14b and Tad1, both known to be cold-induced, likely reflects the decline in cold acclimation associated with the fulfillment of the vernalization requirement. Chi 3 was significantly upregulated in week 11 compared to week 3 for the SMT/FrT RIL, while being significantly downregulated in the SMS/FrT, suggesting Chi 3 has a role in snow mold tolerance. In the genotype comparisons, Chi 3 is upregulated in week 3 and down regulated in week 11 for SMT RIL compared to SMS RIL, suggesting that upregulation of chitinase producing genes early in the vernalization process contributes to tolerance to snow mold. The results of the Chi 3 in the cross-time comparisons showed that the cell wall carbohydrate and chitin metabolism module is likely upregulated in SMT/FrT while being downregulated in the SMS/FrT. This suggests that higher chitinase levels at week 11 compared to week 3 of vernalization play a part in tolerance to snow mold.
In winter rye, chitinase enzymes cor14b, CS120 and Wdhn13 were downregulated while FRA2 was upregulated during vernalization, suggesting cor14b, CS120, and Wdhn13 are activated by cold acclimation pathways [9]. In this study, at both 3 and 11 weeks of cold treatment the cor14b, CS120, and Wdhn13 genes tended to be more highly expressed in FrT RIL compared to FrS RIL, suggesting they are important to freezing tolerance. The similar profile of results in the freezing/drought tolerance genes suggest those genes are triggered by vernalization across RIL, although comparisons of genotypes at those times show differences of the levels between RIL of differing snow mold and cold tolerance.
Although our experiment measuring carbohydrate accumulation in the crown tissue was unable to identify conclusive differences between lines, the differentially expressed genes (DEGs) from the RNA-seq corroborate the results of Mohammad et al. [14]. In both week 3 and 11, the FrS RIL had significantly less transcript expression of the fructan synthesis genes SST-D1a and SST-A1, suggesting that fructan accumulation is related to cold tolerance, corroborating the results of Pollock and Jones [15]. At week 11 the SMT/FrT and SMS/FrT had significantly differentially expressed DEGs associated with drought/cold tolerance and Chi 3, but all of the carbohydrate modification/synthesis related genes had almost no difference between RIL, providing further evidence that non-structural carbohydrate accumulation is involved in freezing tolerance.
Sanderson et al. [44] examined genes regulated by a transcription factor involved in cold tolerance and found significant regulation differences in genes with GO terms relating to response to oxidative stress, response to fungal stress, and DNA binding. Sanderson et al. [44] also found dehydrin genes activated during cold acclimation. These results corroborate some of the pathways we found; however, molecular pathways such as metabolism, cellulose synthesis, and membrane transport/ion transport should be examined further to validate or understand the role of these pathways in freezing and snow mold tolerance in plants. The output of the modular enrichment analyses (Supplemental Materials, File 2) contains the differentially expressed genes associated with each FUNC-E cluster providing researchers with potential genes to characterize.
In conclusion, the hypothesis that patterns of carbohydrate accumulation would reflect patterns of tolerance, over time or at key time points, was not supported by the results of this study. This suggests that the observable differences in tolerance to snow mold and freezing in this population were not a direct result of differences in carbohydrate dynamics due to differences in other pathways contributing to these highly quantitative tolerance traits, or the carbohydrate experiment was not specific enough to detect differences. RNA-Seq was able to detect genes associated with fructan synthesis, even though the results of the fructan carbohydrate experiment showed little significant differences. RNA-Seq analysis was also able to detect many other genes and gene families (such as chitinase) that were up- or downregulated between tolerant and susceptible RIL. Further studies could examine shared pathways to determine how they contribute to each freezing and snow mold tolerance individually. Developing isogenic lines that represent all four tolerance combinations may also be useful, although challenging given the shared pathways that contribute to both phenotypes, instead of single genes controlling tolerance.

4. Materials and Methods

4.1. Plant Material and Growing Conditions

Eight recombinant inbred lines (RILs) were selected from a RIL population derived from a cross between soft white winter wheat cultivars, “Finch” (PI628640) [45] and “Eltan” (PI5369940) [46]. Finch and Eltan differ in their tolerance to snow mold and freezing stress, and segregation for these traits was observed among the RILs [47]. The eight lines chosen for this experiment represent four categories of snow mold tolerance (SMT) or susceptibility (SMS) and freezing tolerance (FrT) or susceptibility (FrS): SMT/FrT, SMT/FrS, SMS/FrT, SMS/FrS, based on preliminary data.
For the carbohydrate quantification experiment, the eight RILs and two parents were included in three randomized complete blocks in three trials. They were planted in seedling starter trays (East Jordan Plastics, Inc., East Jordan, MI, USA, A 8-06) and allowed to germinate and grow to the 3-leaf stage at 22 °C with 16 h day-length. Plants were then transferred to the cold treatment conditions, 4 oC with 12 h day-length. Samples were collected at eight time points as the 2 cm section of crown tissue directly above the roots [8,48]. The collections occurred at weeks 3, 5, 7, 9, 10, 11, 12, and 13 after treatment. For the transcript expression profile experiment, four RILs representing the four tolerance categories (Table 3) and the two parents were included in three randomized complete blocks in one trial that was grown under the same conditions for the same period of time as described previously. Samples were collected at weeks 3 and 11 as 1 cm (sample size based on expected yield of extracted total RNA) of crown tissue taken from the base of the crown, and pooled across five individual plants. All samples were immediately frozen in liquid nitrogen and stored at −80 °C until further processed.

4.2. Carbohydrate Extraction and Quantification

Carbohydrate extraction was carried out via a protocol slightly modified from Ekvall [49]. Samples were lyophilized, ground with steel beads using a Geno/Grinder 2010, and then weighed into 10 mg samples. To each 10 mg tissue sample, 2.0 mL of 50% ethanol was added. Samples were mixed via vortex and centrifuged, so the supernatant could be removed and retained. An additional 2.0 mL of 50% v v−1 ethanol was added to the first tube, mixed via vortex, and then shaken for 2 hrs at room temperature. Samples were centrifuged and the supernatant retained and pooled with previous for a total volume of approximately 4.0 mL. A 2.0 mL aliquot was taken from the pooled supernatant and added to 1.0 mL 90% v v−1 ethanol. The samples were then dried in a hot water bath at 60 °C with forced air over the top of each vial. Once re-eluted with 1.0 mL 18.0 mΩ H2O, the samples were shaken and filtered through micro syringe filters (PES 13 mm 0.45 μM) into vials. Samples were analyzed in an Agilent 1100 series HPLC (Agilent Technologies, Santa Clara, CA, USA) with an autosampler that injected 60 μL into the HPLC column, for separation using the Shodex KS 802 and Shodex KS 803 columns (Showa Denko K.K., Tokyo, Japan) in tandem [8]. Sucrose, fructose, and glucose were quantified using external standards. For polysaccharides, peak area comprising polysaccharide content (dp ≥ 3) was summed and compared to a standard solution of inulin (Sigma Chemical Co., St. Louis, MO, USA).

4.3. Statistical Analysis

Polysaccharide, sucrose, glucose, and fructose content were compared between SMT and SMS lines and between FrS and FrT lines at each time point using the lme function in the nlme package in R [50].

4.4. RNA Extraction, RNAseq, and Modular Enrichment Analysis

FERIL-20, FERIL-74, FERIL-94, and FERIL-128 were used with three biological replicates containing 5 crown tissue samples from each plant at each time point for RNA-seq analysis. Validation with qPCR was not performed because a number of studies have shown that using RNA-seq or qPCR will yield correlated results and the same conclusions [51,52,53,54]. Samples were ground with a mortar and pestle using liquid nitrogen to maintain freezing temperatures during grinding. RNA was extracted using the GeneJET Plant RNA Purification Mini Kit, following the associated protocol (Thermo Scientific). An aliquot of extracted RNA was sent to the Washington State University-Spokane Genomics Core Lab for library preparation, RNA-seq, and data analysis. Library construction and cDNA sequencing were performed on an Illumina platform. Reads were aligned to the T. aestivum reference genome (IWGSC RefSeq v1.0) using Bowtie2 [55] software. Differential transcript expression was estimated using Cufflinks [56]. Differentially expressed genes (DEGs) were identified as significant when the genes had a q-value from Cufflinks below 0.05 (Supplemental Materials, File 1). VRN1-A, cor14b, CS120, Wdhn13, Tad1, SST-D1a, SST-A1, 6-SFT, 6-GFFT, 1-FEHw1, 1-FEHw2, 6-FEH, MYB56, Tamyb7 genes and the Chi3 protein gene were examined separately from the modular enrichment analysis to develop a profile of the transcript expression of known and hypothetical genes. The genes tested separately were determined to be significant if the q-value was below 0.05. Gene ontology (GO) terms were extracted from the iwgsc_refseqv1.0 FunctionalAnnotation_v1__HCgenes_v1.0 gff3 file and the definitions for the terms were obtained by querying the GO database using the GO.db library [57] in R statistical programming language (Supplemental Materials, File 4). Gene set analysis and modular enrichment analysis were investigated using FUNC-E (Supplemental Materials, File 3) with default parameters [58]. FUNC-E performs the same methods for modular enrichment analysis as DAVID [59] but allows users to enter annotation for species not supported by DAVID. FUNC-E calculates a p-value for enrichment of each GO term present using a modified fisher’s exact test, then terms with significant kappa coefficients are clustered together and the negative log geometric mean of the p-values for terms in each cluster is reported as the enrichment score. Enrichment scores above 1 are considered significant when α = 0.01.

Supplementary Materials

The following are available online at https://www.mdpi.com/2223-7747/9/11/1416/s1. Supplemental File 1. Input RNA-Seq expression data of RIL varying for their tolerance/susceptibility to freezing temperatures and snow mold. Supplemental File 2. Output file of the FUNC-E analysis of RIL varying for their tolerance/susceptibility to freezing temperatures and snow mold. Supplemental File 3. Input file of the FUNC-E analysis of RIL varying for their tolerance/susceptibility to freezing temperatures and snow mold. Supplemental File 4. R code used to analyze RNA-Seq expression data of RIL varying for their tolerance/susceptibility to freezing temperatures and snow mold.

Author Contributions

Conceptualization, D.Z.S., T.D.M. and A.H.C.; formal analysis, E.B.K. and S.R.; funding acquisition, A.H.C.; investigation, E.B.K. and S.R.; methodology, J.A., D.Z.S., T.D.M. and C.G.E.; resources, J.A. and C.G.E.; supervision, A.H.C.; writing—original draft, E.B.K. and S.R.; writing—review and editing, T.D.M., C.G.E. and A.H.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institute of Food and Agriculture (NIFA) of the U.S. Department of Agriculture (Award number 2016-68004-24770) and Hatch project 1014919.

Conflicts of Interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Abbreviations

RILrecombinant inbred line
GOgene ontology
BLUPsbest linear unbiased predictions
FrTfreezing tolerant
FrSfreezing susceptible
SMTsnow mold tolerant
SMSsnow mold susceptible

References

  1. Stelmakh, A.F. Growth habit in common wheat (Triticum aestivum L. EM. Thell.). Euphytica 1987, 36, 513–519. [Google Scholar] [CrossRef]
  2. Sherman, J.D.; Talbert, L.E. Vernalization-induced changes of the DNA methylation pattern in winter wheat. Genome 2002, 45, 253–260. [Google Scholar] [CrossRef] [PubMed]
  3. Yan, L.; Loukoianov, A.; Blechl, A.; Tranquilli, G.; Ramakrishna, W.; SanMiguel, P.; Bennetzen, J.L.; Echenique, V.; Dubcovsky, J. The wheat VRN2 gene is a flowering repressor down-regulated by vernalization. Science 2004, 303, 1640–1644. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Ergon, Å.; Klemsdal, S.S.; Tronsmo, A.M. Interactions between cold hardening and Microdochium nivale infection on expression of pathogenesis-related genes in winter wheat. Physiol. Mol. Plant Pathol. 1998, 53, 301–310. [Google Scholar] [CrossRef]
  5. Trischuk, R.G.; Schilling, B.S.; Low, N.H.; Gray, G.R.; Gusta, L.V. Cold acclimation, de-acclimation and re-acclimation of spring canola, winter canola and winter wheat: The role of carbohydrates, cold-induced stress proteins and vernalization. Environ. Exp. Bot. 2014, 106, 156–163. [Google Scholar] [CrossRef]
  6. Gaudet, D.A.; Laroche, A.; Yoshida, M. Low temperature-wheat-fungal interactions: A carbohydrate connection. Physiol. Plant. 1999, 106, 437–444. [Google Scholar] [CrossRef]
  7. McBeath, J.H. Snow mold-plant-antagonist interactions: Survival of the fittest under the snow. Plant Health Instr. 2002, 1–4. [Google Scholar] [CrossRef]
  8. Yoshida, M.; Abe, J.; Moriyama, M.; Kuwabara, T. Carbohydrate levels among winter wheat cultivars varying in freezing tolerance and snow mold resistance during autumn and winter. Physiol. Plant. 1998, 103, 8–16. [Google Scholar] [CrossRef]
  9. Suzuki, M.; Nass, H.G. Fructan in winter wheat, triticale, and fall rye cultivars of varying cold hardiness. Can. J. Bot. 1988, 66, 1723–1728. [Google Scholar] [CrossRef]
  10. Tamura, K.I.; Sanada, Y.; Tase, K.; Yoshida, M. Fructan metabolism and expression of genes coding fructan metabolic enzymes during cold acclimation and overwintering in timothy (Phleum pratense). J. Plant Physiol. 2014, 171, 951–958. [Google Scholar] [CrossRef]
  11. Yukawa, T.; Kobayashi, M.; Watanabe, Y.; Yamamoto, S. Studies on Fructan Accumulation in Wheat (Triticum aestivum L.): IV. Fructan accumulation under cold treatments and its varietal difference in relation to the activities of sucrose-sucrose fructosyl transferase and fructan exohydrolase. Jpn. J. Crop Sci. 1995, 64, 801–806. [Google Scholar] [CrossRef] [Green Version]
  12. Snider, C.S.; Hsiang, T.; Zhao, G.; Griffith, M. Role of ice nucleation and antifreeze activities in pathogenesis and growth of snow molds. Phytopathology 2000, 90, 354–361. [Google Scholar] [CrossRef] [PubMed]
  13. Bruehl, G.W.; Cunfer, B. Physiologic and environmental factors that affect the severity of snow mold of wheat. Phytopathology 1971, 61, 792–799. [Google Scholar] [CrossRef]
  14. Mohammad, F.; Windes, J.M.; Souza, E. Total non-structural carbohydrates in winter wheat populations segregating for snow mold tolerance. Crop Sci. 1997, 37, 108–112. [Google Scholar] [CrossRef]
  15. Pollock, C.J.; Jones, T. Seasonal patterns of fructan metabolism in forage grasses. New Phytol. 1979, 83, 9–15. [Google Scholar] [CrossRef]
  16. Kiyomoto, R.K.; Bruehl, G.W. Carbohydrate accumulation and depletion by winter cereals differing in resistance to Typhula idahoensis. Phytopathology 1977, 67, 206–211. [Google Scholar] [CrossRef] [Green Version]
  17. Kawakami, A.; Yoshida, M. Graminan Breakdown by Fructan Exohydrolase Induced in Winter Wheat Inoculated with Snow Mold. J. Plant Physiol. 2012, 169, 294–302. [Google Scholar] [CrossRef]
  18. Hisano, H.; Kanazawa, A.; Kawakami, A.; Yoshida, M.; Shimamoto, Y.; Yamada, T. Transgenic Perennial Ryegrass Plants Expressing Wheat Fructosyltransferase Genes Accumulate Increased Amounts of Fructan and Acquire Increased Tolerance on a Cellular Level to Freezing. Plant Sci. 2004, 167, 861–868. [Google Scholar] [CrossRef] [Green Version]
  19. Ritsema, T.; Smeekens, S. Fructans: Beneficial for Plants and Humans. Curr. Opin. Plant Biol. 2003, 6, 223–230. [Google Scholar] [CrossRef]
  20. Van den Ende, W.; De Coninck, B.; Van Laere, A. Plant Fructan Exohydrolases: A Role in Signaling and Defense? Trends Plant Sci. 2004, 9, 523–528. [Google Scholar] [CrossRef]
  21. Zhu, J.; Pearce, S.; Burke, A.; Robert, D.; Daniel, S.; Dubcovsky, J.; Garland, K. Copy number and haplotype variation at the VRN—A1 and central FR—A2 loci are associated with frost tolerance in hexaploid wheat. Theor. Appl. Genet. 2014, 127, 1183–1197. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Kruse, E.B.; Carle, S.W.; Wen, N.; Skinner, D.Z.; Murray, T.D.; Garland-Campbell, K.A.; Carter, A.H. Genomic regions associated with tolerance to freezing stress and snow mold in winter wheat. G3-Genes Genom. Genet. 2017, 7, 775–780. [Google Scholar] [CrossRef] [Green Version]
  23. Galiba, G.; Vágújfalvi, A.; Li, C.; Soltész, A.; Dubcovsky, J. Regulatory genes involved in the determination of frost tolerance in temperate cereals. Plant Sci. 2009, 176, 12–19. [Google Scholar] [CrossRef] [Green Version]
  24. Sasaki, K.; Christov, N.K.; Tsuda, S.; Imai, R. Identification of a novel LEA protein involved in freezing tolerance in wheat. Plant Cell Physiol. 2014, 55, 136–147. [Google Scholar] [CrossRef] [Green Version]
  25. Holková, L.; Prášil, I.T.; Bradáčová, M.; Vítámvás, P.; Chloupek, O. Screening for frost tolerance in wheat using the expression of dehydrine genes Wcs120 and Wdhn13 at 17 °C. Plant Breed. 2009, 128, 420–422. [Google Scholar] [CrossRef]
  26. Baek, K.H.; Skinner, D.Z. Alteration of antioxidant enzyme gene expression during cold acclimation of near-isogenic wheat lines. Plant Sci. 2003, 165, 1221–1227. [Google Scholar] [CrossRef]
  27. Janda, T.; Szalai, G.; Leskó, K.; Yordanova, R.; Apostol, S.; Popova, L.P. Factors contributing to enhanced freezing tolerance in wheat during frost hardening in the light. Phytochemistry 2007, 68, 1674–1682. [Google Scholar] [CrossRef]
  28. Hiilovaara-Teijo, M.; Palva, E.T. Molecular responses in cold-adapted plants. In Cold-Adapted Organisms; Springer: Berlin/Heidelberg, Germany, 1999; pp. 349–384. [Google Scholar]
  29. Kosová, K.; Vítámvás, P.; Prášil, I.T. Wheat and barley dehydrins under cold, drought, and salinity–what can LEA-II proteins tell us about plant stress response. Front. Plant Sci. 2014, 5, 343. [Google Scholar] [CrossRef] [Green Version]
  30. Zhang, Y.; Zhang, H.; Wang, L.; Qian, H.; Qi, X. Extraction of oat (Avena sativa L.) antifreeze proteins and evaluation of their effects on frozen dough and steamed bread. Food Bioprocess Technol. 2015, 8, 2066–2075. [Google Scholar] [CrossRef]
  31. Koike, M.; Okamoto, T.; Tsuda, S.; Imai, R. A novel plant defensin-like gene of winter wheat is specifically induced during cold acclimation. Biochem. Biophys. Res. Commun. 2002, 298, 46–53. [Google Scholar] [CrossRef]
  32. Gaudet, D.A.; Laroche, A.; Frick, M.; Huel, R.; Puchalski, B. Cold induced expression of plant defensin and lipid transfer protein transcripts in winter wheat. Physiol. Plant 2003, 117, 195–205. [Google Scholar] [CrossRef]
  33. Shimada, S.; Ogawa, T.; Kitagawa, S.; Suzuki, T.; Ikari, C.; Shitsukawa, N.; Abe, T.; Kawahigashi, H.; Kikuchi, R.; Handa, H.; et al. A genetic network of flowering-time genes in wheat leaves, in which an APETALA1/FRUITFULL-like gene, VRN1, is upstream of FLOWERING LOCUS. Plant J. 2009, 58, 668–681. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Juhász, Z.; Boldizsár, Á.; Nagy, T.; Kocsy, G.; Marincs, F.; Galiba, G.; Bánfalvi, Z. Pleiotropic effect of chromosome 5A and the mvp mutation on the metabolite profile during cold acclimation and the vegetative/generative transition in wheat. BMC Plant Biol. 2015, 15, 57. [Google Scholar]
  35. Wang, W.; Wang, X.; Huang, M.; Cai, J.; Zhou, Q.; Dai, T.; Cao, W.; Jiang, D. Hydrogen Peroxide and Abscisic Acid Mediate Salicylic Acid-Induced Freezing Tolerance in Wheat. Front. Plant Sci. 2018, 9, 1137. [Google Scholar] [CrossRef]
  36. Pour-Benab, S.; Fabriki-Ourang, S.; Mehrabi, A. Expression of dehydrin and antioxidant genes and enzymatic antioxidant defense under drought stress in wild relatives of wheat. Biotechnol. Biotechnol. Equip. 2019, 33, 1063–1073. [Google Scholar] [CrossRef] [Green Version]
  37. Sasaki, K.; Kuwabara, C.; Umeki, N.; Fujioka, M.; Saburi, W.; Matsui, H.; Abe, F.; Imai, R. The cold-induced defensin TAD1 confers resistance against snow mold and Fusarium head blight in transgenic wheat. J. Biotechnol. 2016, 228, 3–7. [Google Scholar] [CrossRef]
  38. Hajheidari, M.; Eivazi, A.; Buchanan, B.B.; Wong, J.H.; Majidi, I.; Salekdeh, G.H. Proteomics uncovers a role for redox in drought tolerance in wheat. J. Proteome Res. 2007, 6, 1451–1460. [Google Scholar] [CrossRef]
  39. Soltész, A.; Tímár, I.; Vashegyi, I.; Tóth, B.; Kellős, T.; Szalai, G.; Vágújfalvi, A.; Kocsy, A.; Galiba, G. Redox changes during cold acclimation affect freezing tolerance but not the vegetative/reproductive transition of the shoot apex in wheat: Redox changes during cold acclimation in wheat. Plant Biol. 2011, 13, 757–766. [Google Scholar] [CrossRef]
  40. Suzuki, N.; Koussevitzky, S.; Mittler, R.; Miller, G. ROS and redox signalling in the response of plants to abiotic stress: ROS and redox signalling in plants. Plant Cell Environ. 2012, 35, 259–270. [Google Scholar] [CrossRef]
  41. Kim, J.H.; Chan, K.L.; Mahoney, N.; Campbell, B.C. Antifungal activity of redox-active benzaldehydes that target cellular antioxidation. Ann. Clin. Microbiol. Antimicrob. 2011, 10, 23. [Google Scholar] [CrossRef] [Green Version]
  42. Carter, C.; Thornburg, R.W. Is the nectar redox cycle a floral defense against microbial attack? Trends Plant Sci. 2004, 9, 320–324. [Google Scholar] [CrossRef] [PubMed]
  43. Vera-Estrella, R.; Blumwald, E. Plant Defense Response to Fungal Pathogens. Plant Physiol. 1994, 104, 209–215. [Google Scholar] [CrossRef] [PubMed]
  44. Sanderson, B.J.; Park, S.; Jameel, M.I.; Kraft, J.C.; Thomashow, M.F.; Schemske, D.W.; Oakley, C.G. Genetic and physiological mechanisms of freezing tolerance in locally adapted populations of a winter annual. Am. J. Bot. 2019, 102, 250–261. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Campbell, K.A.; Allan, R.E.; Anderson, J.; Pritchett, J.A.; Little, L.M.; Morris, C.F.; Line, R.F.; Chen, X.; Walker-Simmons, M.K.; Carter, B.P.; et al. Registration of ‘Finch’ wheat. Crop Sci. 2005, 45, 1656–1657. [Google Scholar] [CrossRef]
  46. Peterson, C.J.; Allan, R.E.; Rubenthaler, G.L.; Line, R.F. Registration of ‘Eltan’ wheat. Crop Sci. 1991, 31, 1704. [Google Scholar] [CrossRef]
  47. Balow, K.; Shelton, G.; Burke, A.; Hagemeyer, K.; Klarquist, E.F.; Froese, P.S.; Kruse, E.B.; Carle, S.W.; Roa, A.; Nielson, N.; et al. Registration of the Finch-Eltan winter wheat recombinant inbred line mapping population. J. Plant Reg. 2019, 13, 287–293. [Google Scholar] [CrossRef]
  48. Gaudet, D.A.; Laroche, A.; Puchalski, B. Seeding date alters carbohydrate accumulation in winter wheat. Crop Sci. 2001, 41, 728–738. [Google Scholar] [CrossRef]
  49. Ekvall, J.; Stegmark, R.; Nyman, M. Content of low molecular weight carbohydrates in vining peas (Pisum sativum) related to harvest time, size and brine grade. Food Chem. 2006, 94, 513–519. [Google Scholar] [CrossRef]
  50. nlme: Linear and Nonlinear Mixed Effects Models. Available online: https://cran.r-project.org/web/packages/nlme/nlme.pdf (accessed on 19 October 2020).
  51. Wu, A.; Neff, N.; Kalisky, T.; Dalerba, P.; Treutlein, B.; Rothenberg, M.; Mburu, F.; Mantalas, G.; Sim, S.; Clarke, S. Quantitative assessment of single-cell RNA-sequencing methods. Nat. Methods 2014, 11, 41–46. [Google Scholar] [CrossRef] [Green Version]
  52. Griffith, M.; Griffith, O.L.; Mwenifumbo, J.; Goya, R.; Morrissy, A.S.; Morin, R.D.; Corbett, R.; Tang, M.J.; Hou, Y.-C.; Pugh, T.J.; et al. Alternative Expression Analysis by RNA Sequencing. Nat. Methods 2010, 7, 843–847. [Google Scholar] [CrossRef]
  53. Asmann, Y.W.; Klee, E.W.; Thompson, E.A.; Perez, E.A.; Middha, S.; Oberg, A.L.; Therneau, T.M.; Smith, D.I.; Poland, G.A.; Wieben, E.D.; et al. 3′ Tag Digital Gene Expression Profiling of Human Brain and Universal Reference RNA Using Illumina Genome Analyzer. BMC Genom. 2009, 10, 531. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Shi, Y.; He, M. Differential Gene Expression Identified by RNA-Seq and QPCR in Two Sizes of Pearl Oyster (Pinctada Fucata). Gene 2014, 538, 313–322. [Google Scholar] [CrossRef] [PubMed]
  55. Langmead, B.; Salzberg, S. Fast gapped-read alignment with Bowtie 2. Nat. Methods 2012, 9, 357–359. [Google Scholar] [CrossRef] [Green Version]
  56. Trapnell, C.; Williams, B.A.; Pertea, G.; Mortazavi, A.; Kwan, G.; van Baren, M.J.; Salzberg, S.L.; Wold, B.J.; Pachter, L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 2010, 28, 511–515. [Google Scholar] [CrossRef] [Green Version]
  57. GO.db: A Set of Annotation Maps Describing the Entire Gene Ontology. Available online: https://bioconductor.org/packages/release/data/annotation/html/GO.db.html (accessed on 19 October 2020).
  58. SystemsGenetics/FUNC-E v1.0. Zenodo. Available online: https://zenodo.org/record/1246882#.X43pcO17mUk (accessed on 19 October 2020).
  59. Huang, D.; Sherman, B.T.; Tan, Q.; Collins, J.R.; Alvord, W.G.; Roayaei, J.; Stephens, R.; Baseler, M.W.; Lane, H.C.; Lempicki, R.A. The DAVID gene functional classification tool: A novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol. 2007, 8, R183. [Google Scholar] [CrossRef] [Green Version]
Plants 09 01416 g001 550
Figure 1. Changes in polysaccharide and simple carbohydrate content in wheat differing for snow mold and freezing tolerance after a cold treatment over 13 weeks at 4 °C.
Figure 1. Changes in polysaccharide and simple carbohydrate content in wheat differing for snow mold and freezing tolerance after a cold treatment over 13 weeks at 4 °C.
Plants 09 01416 g001
Plants 09 01416 g002 550
Figure 2. Time points at which significant differences in carbohydrate content exist between tolerant and susceptible recombinant inbred lines (RILs) of winter wheat.
Figure 2. Time points at which significant differences in carbohydrate content exist between tolerant and susceptible recombinant inbred lines (RILs) of winter wheat.
Plants 09 01416 g002
Plants 09 01416 g003 550
Figure 3. Fold change transcript expression between dates within RILs of different categories of freezing and snow mold tolerance. Genes were grouped and labeled by the hypothetical function categories; carbohydrate modification, drought/cold stress, vernalization, fungal defense, and transcription factor represented by the abbreviations CM, ABS, VRN, FD, and TF, respectively. “*” denotes genes with significant differences (q < 0.05) in transcript expression between week 3 and week 11 of the study.
Figure 3. Fold change transcript expression between dates within RILs of different categories of freezing and snow mold tolerance. Genes were grouped and labeled by the hypothetical function categories; carbohydrate modification, drought/cold stress, vernalization, fungal defense, and transcription factor represented by the abbreviations CM, ABS, VRN, FD, and TF, respectively. “*” denotes genes with significant differences (q < 0.05) in transcript expression between week 3 and week 11 of the study.
Plants 09 01416 g003
Plants 09 01416 g004 550
Figure 4. Fold change transcript expression between RILs of different classes of freezing and snow mold tolerance at week 3. Genes were grouped and labeled by the hypothetical function categories; carbohydrate modification, drought/cold stress, vernalization, fungal defense, and transcription factor represented by the abbreviations CM, ABS, VRN, FD, and TF, respectively. “*” denotes genes with significant differences (q < 0.05) in transcript expression between RILs at week 3 of the study.
Figure 4. Fold change transcript expression between RILs of different classes of freezing and snow mold tolerance at week 3. Genes were grouped and labeled by the hypothetical function categories; carbohydrate modification, drought/cold stress, vernalization, fungal defense, and transcription factor represented by the abbreviations CM, ABS, VRN, FD, and TF, respectively. “*” denotes genes with significant differences (q < 0.05) in transcript expression between RILs at week 3 of the study.
Plants 09 01416 g004
Plants 09 01416 g005 550
Figure 5. Fold change transcript expression between RILs of different classes of freezing and snow mold tolerance at week 11. Genes were grouped and labeled by the hypothetical function categories; carbohydrate modification, drought/cold stress, vernalization, fungal defense, and transcription factor represented by the abbreviations CM, ABS, VRN, FD, and TF, respectively. “*” denotes genes with significant differences (q < 0.05) in transcript expression between RILs at week 11 of the study.
Figure 5. Fold change transcript expression between RILs of different classes of freezing and snow mold tolerance at week 11. Genes were grouped and labeled by the hypothetical function categories; carbohydrate modification, drought/cold stress, vernalization, fungal defense, and transcription factor represented by the abbreviations CM, ABS, VRN, FD, and TF, respectively. “*” denotes genes with significant differences (q < 0.05) in transcript expression between RILs at week 11 of the study.
Plants 09 01416 g005
Table
Table 1. Group enrichment scores for modules differentially regulated for cross-time comparisons within the same RIL. (p-value significant at α = 0.05).
Table 1. Group enrichment scores for modules differentially regulated for cross-time comparisons within the same RIL. (p-value significant at α = 0.05).
ModuleSMT/FrTSMS/FrSSMT/FrSSMS/FrT
Peroxizome and oxidative stress 2.28892.62576.6852
Metabolism and redox reactions5.6142 4.2229
Nuclear binding and protein modification6.2492 4.8104
Cell wall carbohydrates and chitin metabolism2.6723 9.4938
Beta-glucan synthesis 2.0558
Table
Table 2. Group enrichment score for putative modules related to molecular pathways differentially regulated between wheat RILs with differing levels of snow mold and freezing tolerance at the same time point. (p-value significant at α = 0.05).
Table 2. Group enrichment score for putative modules related to molecular pathways differentially regulated between wheat RILs with differing levels of snow mold and freezing tolerance at the same time point. (p-value significant at α = 0.05).
ComparisonsSMT/FrT and SMS/FrSSMT/FrT and SMT/FrSSMT/FrT and SMS/FrTSMS/FrS and SMT/FrSSMS/FrS and SMS/FrTSMT/FrS and SMS/FrT
Module Week:311311311311311311
Acyl transferase activity3.44
Carbohydrate metabolism 2.62
Cell wall carbohydrates and chitin metabolism 8.383.36 4.357.78 6.60
Cellulose synthesis5.75
Membrane transport and ion channels2.99
Metabolism and redox reactions3.422.69 4.35 3.092.99 6.81
mRna modification2.69
Nuclear binding and protein modification 9.165.8737.67 2.88
Peroxisome and oxidative stress 5.21 4.57
Table
Table 3. Data (raw scores) used to determine representatives of the tolerance categories in comparison to the tolerant and susceptible parents. Bold RILs were used in the transcript expression experiment.
Table 3. Data (raw scores) used to determine representatives of the tolerance categories in comparison to the tolerant and susceptible parents. Bold RILs were used in the transcript expression experiment.
CategoryRILSMT Score aFrT % b
tolerant parentEltan6.3368
SMT/FrTFERIL-20781
FERIL-716.6785
SMT/FrSFERIL-94615
FERIL-10368
SMS/FrTFERIL-1283.3358
FERIL-132368
SMS/FrSFERIL-741.675
FERIL-10128
susceptible parentFinch4.331
a Snow mold tolerance was evaluated on a scale of 0 (severe susceptibility) to 10 (strong tolerance). b Freezing tolerance was recorded as percent survival, thus higher numbers indicate greater tolerance.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Kruse, E.B.; Revolinski, S.; Aplin, J.; Skinner, D.Z.; Murray, T.D.; Edwards, C.G.; Carter, A.H. Carbohydrate Accumulation and Differential Transcript Expression in Winter Wheat Lines with Different Levels of Snow Mold and Freezing Tolerance after Cold Treatment. Plants 2020, 9, 1416. https://doi.org/10.3390/plants9111416

AMA Style

Kruse EB, Revolinski S, Aplin J, Skinner DZ, Murray TD, Edwards CG, Carter AH. Carbohydrate Accumulation and Differential Transcript Expression in Winter Wheat Lines with Different Levels of Snow Mold and Freezing Tolerance after Cold Treatment. Plants. 2020; 9(11):1416. https://doi.org/10.3390/plants9111416

Chicago/Turabian Style

Kruse, Erika B., Samuel Revolinski, Jesse Aplin, Daniel Z. Skinner, Timothy D. Murray, Charles G. Edwards, and Arron H. Carter. 2020. "Carbohydrate Accumulation and Differential Transcript Expression in Winter Wheat Lines with Different Levels of Snow Mold and Freezing Tolerance after Cold Treatment" Plants 9, no. 11: 1416. https://doi.org/10.3390/plants9111416

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop