Insect and plant material

Diuraphis noxia biotype 1 aphids were collected from wheat fields near Hays, KS (38.8794° N, 99.3222° W). Schizaphis graminum biotype I originated from a field population on the Kansas State University campus in Manhattan, KS (39.188307° N, -96.605864° W). Neither field collection involved endangered or protected species. No specific permissions were required for these collections, as they were activities agreed upon by USDA-ARS scientists and scientists at Colorado State University and Kansas State University as a part of the Areawide Pest Management for Wheat: Management of Greenbug and Russian Wheat Aphid. The identity of each aphid was confirmed by PCR amplification of DNA from whole bodies and sequencing of a region of mitochondrial cytochrome c oxidase I (COI) from the PCR product. Partial COI sequences of the S. graminum I colonies used in these studies have been deposited at GenBank under MT011383. Partial COI sequences for D. noxia biotype 1 used in these studies have been deposited at GenBank under accessions MN994435. COI has been used effectively to identify both Diuraphis noxia and Schizaphis graminum [25]. Fresh DNA samples of three additional aphid species (Sitobion avenae, Rhopalosiphum padi, Melanaphis sacchari), were also amplified, along with archived and fresh DNA of D. noxia from Hungary, Spain, and North America (biotypes 1, 2, 4, 6, and 8). After COI identification, biotype identification and validation were independently performed for both D. noxia and S. graminum by plant differential diagnoses [26,27,28] at Stillwater, OK, and Manhattan, KS. Each aphid species was maintained in separate growth chambers at Kansas State University on the susceptible wheat cultivar ‘Jagger.’ Specimen samples (S. graminum biotype I voucher specimen #155, D. noxia biotype 1 voucher specimen #176) are deposited at the Museum of Entomological and Prairie Arthropod Research at Kansas State University.

The wheat varieties Yuma, containing no resistance genes (Dn0); the D. noxia biotype 1-resistant variety Yumar, containing the Dn4 resistance gene [29]; and the variety 94M370, containing the Dn7 gene for resistance to D. noxia biotype 2 [30] were used in experiments to compare the transcriptomes of S. graminum biotype I and D. noxia biotype 1. Yuma was developed from crosses between the D. noxia-susceptible wheat varieties NS14, NS25 and Vona. Yumar wheat was selected from a cross between Yuma and wheat plant introduction (PI) 372129, the source of Dn4 [31]. The Dn7 gene originates from the terminal region of the short arm of chromosome 1 (1RS) of rye, Secale cereale L., variety Turkey 77. Dn7 resistance was transferred to Gamtoos wheat by a translocation of the rye 1RS segment into the short arm of wheat chromosome 1B [30,32], resulting in the breeding line 94M370 [33].

Plants of each variety were grown in 16.5-cm-diameter-plastic pots containing Pro-Mix-Bx potting mix (Premier ProMix, Lansing, MI USA) and covered with fine screen mesh cages. Plants were grown and maintained at greenhouse conditions described previously [34,35]. Groups of 200 apterous adult aphids of each species were starved for 12h before infestation and released onto pots of 30 plants of each of the three wheat cultivars. There were three replicate pots for each cultivar. At 24-, 48-, 72- and 96h post-infestation, 30–40 aphids were collected from each of the three replicate pots of plants of each of the three wheat cultivars. Aphid samples from the four time points were pooled within each of the three biological replicates collected for each of the three feeding treatments and stored in RNAlater (Qiagen, GmbH, Hilden, Germany) according to the manufacturer’s recommendations.

Plant response to feeding by S. graminum biotype I

The responses of D. noxia to the three wheat lines used in this study have been previously assessed [28]; however, the ability of S. graminum to establish on these lines are unknown and bioassays were conducted to determine assess virulence. Assays were conducted in Manhattan, KS, using three cylindrical (10 cm diam x 9 cm tall) pots of variety tested, with each pot containing three seeds each of Yumar wheat (containing the Dn4 D. noxia resistance gene); 94M370 (containing the Dn7 D. noxia resistance gene); the D. noxia susceptible variety Yuma (Dn0); or a S. graminum resistant control TAM110. After germination, seedlings were thinned to one per pot, and randomly placed and grown in a growth chamber (Percival Scientific, Perry, Iowa USA) at 26:18C^o day / night and a photoperiod of 14:10 [L:D] h. When plants reached the two-leaf stage at 10 d post-planting, five aged-synchronized 3 d old greenbug nymphs reared on susceptible Jagger wheat plants were placed on each test plant. Infested plants were caged in 8.5 cm diam x 51 cm tall plastic cylindrical cages with two side openings (5 cm diam) and one top opening (8.5 cm diam) covered with mite-proof mesh to reduce humidity inside the cage. The base of each cage was pressed ~ 0.5 cm below the soil to hold it in place. Two un-infested two-leaf stage plants of each variety were caged similarly and served as controls for plant dry weight change. This protocol allowed measurement of both the antibiosis and tolerance categories of resistance to S. graminum.

Antibiosis was determined by counting the mean total number of aphids on plants of each wheat genotype. Tolerance was measured as the per cent mean proportional dry weight change in leaves of each genotype. Mean proportional per cent dry weight changes (% DWT) were calculated as: [(mean dry weight of uninfested plants–mean dry weight of infested plants/mean dry weight of uninfested plants) x 100] [36]. An additional measure of tolerance was made by calculation of a tolerance index [37], which removes the potential bias of aphid population differences in tolerance measurements. Mean plant tolerance indices were calculated as (% DWT/total # aphids).

Reaction of plants of the three wheat genotypes to S. graminum feeding was assessed by measuring plant chlorosis, damage and dry weight; and the total number of S. graminum on each plant at 21 d post-infestation [38]. Plant chlorosis and damage scores were rated visually, using a scale of 1 = no chlorosis; 2 = >10% to 25% chlorosis; 3 = >25% to 50% chlorosis; 4 = >50% to 75% chlorosis; 5 = >76% to 100% chlorosis. After assessment, plants were cut at the soil level and placed on top of a piece of gridded cardstock (10 cm wide x 28 cm tall) coated with adhesive to trap aphids as plants dried at room temperature for 3 d. Dried plants were then removed from cards, bagged in aluminum pouches (11 cm wide x 12 cm tall) and placed in an oven (Precision, ThermoFisher Scientific, Waltham, MA USA) at 60°C for 10 d. Dry weights were measured using a digital balance. The total number of aphids per sticky-card were counted using a stereoscope (Nikon SMZ645, Tokyo, Japan).

Total numbers of aphids and plant dry weight change data followed assumptions of normality and homogeneity of variances based on Kolmogorov-Smirnov, Levene, and Brown and Forsythe tests [39–41]. These data were analyzed using a normal distribution and PROC GLIMMIX [42], where plant variety was considered a fixed effect. Plant damage scores were analyzed using an approximate normal distribution to estimate treatment differences between varieties. Plant chlorosis and plant tolerance index data did not follow assumptions of normality and homogeneity of variances. These data were analyzed using negative binomial distribution and Poisson distribution with log-link function, respectively, after verification of control of overdispersion with a Pearson Chi-square/DF test [43]. Degrees of freedom were estimated using the Kenward-Rogers method [44] when data failed to follow assumptions of normality and homogeneity of variances. When the F-test for type III effects was significant at P < 0.05, pairwise comparisons were conducted using Tukey’s honestly significant difference at α = 0.05 significance level [45].

D. noxia and S. graminum RNA isolation, library preparation, and sequencing

Total RNA was isolated from the three biological replications collected from each of the three feeding treatments using the RNeasy Plus Kit (Qiagen, GmbH, Hilden, Germany) and treated with DNase. RNA was quality-checked using three different methods, including absorbance at 230, 260 and 280 nm on a NanoDrop spectrophotometer (Thermoscientific, Wilmington, DE USA), 1% agarose (RNase-free grade) gel electrophoresis using GelGreen staining (Biotium Inc., Hayward, CA USA) and by capillary electrophoresis using an RNA Nano Lab-Chip (Agilent, Santa Clara, CA USA) and an Agilent 2100 Bioanalyzer system. Overall, RNA was collected from 18 different samples (two aphid species x three feeding treatments x three biological replicates). These included D. noxia and S. graminum each fed plants of wheat genotypes that contained either the Dn0, Dn4, or Dn7 genes. Approximately 1 μg of total RNA (100ng/μl) from each sample was used for library preparation with the Illumina TruSeq RNA sample preparation kit (Illumina Inc., San Diego, CA USA) per the manufacturer's recommendations. These libraries were validated, and a portion of each was diluted to a 10 nM concentration. Samples were separately barcoded for multiplexing, and libraries from all 18 samples were combined into two pools (each loaded in 1 lane) for a total of nine libraries per pool. A 1 x 100 bp single-end sequencing run was performed using an Illumina TruSeq single-read clustering Kit v3 and Illumina TruSeq SBS-HS v3 sequencing chemistry on an Illumina Hiseq 2500 sequencer. Library preparation and sequencing were conducted at the University of Kansas Medical Center, Kansas City, KS USA. Raw sequencing reads from D. noxia and S. graminum have been deposited in NCBI’s Sequence Read Archive (SRA) under Bioproject PRJNA306025. SRA experiments SRX1494436 to SRX1494443 and SRX1494451 are derived from S. graminum and SRX1494444 to SRX1494451, SRX1494434, and SRX1494435 are derived from D. noxia.

Primary sequence processing

Low quality sequences with mean quality scores <25 (min_qual_mean 25, trim_qual_type mean, Trim_qual_rule lt), reads consisting of more than 1% ambiguous bases (ns_max_p 1), and exact duplicates (derep 1), were removed using PRINSEQ [46] prior to transcriptome assembly for S. graminum and prior to read mapping for D. noxia. Further, low quality bases with PHRED scores <20 (trim_qual_left 20, trim_qual_right 20, trim_qual_window 2, trim_qual_step1), Illumina sequencing adapters, polyA/T tails (lc_method entropy and lc_threshold 70), and poly N tails containing five or more ambiguous bases (trim_ns_left 5 and trim_ns_left 5) were stripped from the reads. Reads shorter than 35 nt after quality trimming were also discarded. FastQC was used to validate the improved quality of the reads after quality filtering (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

Schizaphis graminum transcriptome assembly and abundance estimation

Quality filtered reads from all nine S. graminum samples were pooled and a de novo transcriptome assembly was performed using Trinity v.2.3.2 (50) with a kmer length of 25 (default), minimum contig length of 200 nt (default) and in silico normalization. After assembly, reads were pooled from each of the nine samples and mapped back to the transcriptome assembly using the align_and_estimate_ abundance.pl script with the RSEM method for abundance estimation [47] and Bowtie for read mapping [48]. Transcripts with <0.5 transcripts per million mapped reads (TPM) or transcripts representing < 10% of the expression value of the dominant isoform for each unigene, were removed from the transcriptome assembly. Protein coding regions of at least 100 amino acids in length were then identified using Transdecoder v.3.0.1 (https://transdecoder.github.io/) and the single highest scoring ORF for each transcript was retained using the single_best_orf option. Finally, transcripts containing no open reading frames were removed from the assembly. Functional annotations were then predicted for protein coding transcripts using Trinotate v.3.0.2 (https://trinotate.github.io/), which incorporated results from blastp/x (ncbi-blast v.2.6.0+) searches against the Swiss-Prot database (version 32 as of March 10, 2017), hmmer searches against the PFAM-A database, signalP searches, and TMHMM searches.

In addition, predicted ORFs were searched against the non-redundant protein database (downloaded on February 8, 2017) using blastp to identify any potential plant or bacterial transcripts in the assembly. In brief, the top five blastp matches with e-values ≤0.00001 were retained for each predicted coding region and taxonomic classifications were carried out using MEGAN's least common ancestor algorithm [49].

After removing non-coding transcripts, transcripts derived from microbes and 15,688 low abundance transcripts from the assembly as described above (which represented approximately 18% of the total number of assembled transcripts), reads from the nine libraries were re-aligned to the filtered transcriptome assembly individually using the same methods described previously. RSEM counts from each of the nine samples were concatenated into a single count matrix for differential expression analysis, which was conducted using edgeR [50]. Only transcripts with counts per million (CPM) values greater than one in at least two samples were tested for differential expression. Read counts were normalized using trimmed mean of M-values (TMM) and variances were estimated using tagwise dispersions. Pairwise comparisons between all possible sample combinations were used to identify genes that were differentially expressed in at least one sample using Fisher's Exact test. Differential expression analysis was performed at the unigene level. For the purposes of this study, unigenes were defined as Trinity transcripts that shared significant sequence similarity (≥97%) but had different structures and likely represented transcript isoforms derived from the same gene or locus. Unigenes with False-Discovery-Rate (FDR) corrected p-values ≤0.05 were considered differentially expressed.

Gene ontology (GO) enrichments were performed using GoSeq [51] and k-means analysis [52] was performed to identify groups of aphid genes with similar expression patterns across the three plant gene treatments. For GoSeq, the entire list of genes with CPM> = 1 in at least two samples were used as a reference to determine enrichment and nodes containing less than five genes were excluded from the analysis to control false discovery rate. Enrichment was determined using the Wallenius approximation (‘pwf’) option and categories with Benjamini-Hochberg adjusted p-values <0.05 were considered enriched. Enriched terms were dereplicated using REViGO [53] using medium similarity (0.7) and SimRel for semantic similarity measure. For k-means, the number of clusters that best represented the dominant expression profiles in the dataset was selected using the ‘factoextra’ [54] and the ‘NbClust’ packages [55] implemented in the R statistical environment (version 3.3.1) [56]. The elbow, silhouette and gap statistic methods, and the majority rule of the ‘fviz_nbclus’ function from the NbClust package were consulted to select the number of clusters for k-means. Finally, KEGG pathway analysis was performed to determine the impact of the different feeding treatments on unigenes assigned to various core metabolic pathways. In brief, protein coding sequences were assigned to pathways using the KAAS server [57] with blastp searches (single-directional best hit method) against a database consisting of annotated A. pisum and D. noxia enzymes. Impacts to differentially expressed unigenes were visualized using the KEGG pathway mapper tool available at https://www.genome.jp/kegg/mapper.html. All transcripts containing protein coding genes have been submitted to NCBI’s Transcriptome Shotgun Assembly database (GIML00000000). The entire transcriptome assembly containing both coding and non-coding genes has been deposited in USDA’s Ag Data Commons at https://data.nal.usda.gov/dataset/de-novo-transcriptome-assembly-schizaphis-gramium-biotype-i-feeding-wheat and an annotated assembly of the transcripts that code for proteins is available at NCBI’s Transcriptome Shotgun Assembly (TSA) database under the accession GIML00000000.

Diuraphis noxia transcriptome assembly and abundance estimation

Reads derived from D. noxia biotype 1 were quality filtered using the same approach as described above for S. graminum and mapped to the D. noxia biotype 2 genome assembly version WGS Accession JOTR00000000.1 [3] using Hisat2 v.2.0.5 [58]. The number of reads mapped to each locus were summed using the FeatureCounts command in the Subread v.1.5.1 package [59]. The annotation files are available at ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/001/186/385/GCF_001186385.1_Dnoxia_1.0/. Differentially expressed genes were identified using edgeR and GO terms, KEGG pathways, and k-means analyses were performed using the same protocols as described above for S. graminum.

Insect identities

Sequencing results of aphid amplification products confirmed that D. noxia U. S. biotype 1 samples were correctly identified and also revealed that the nine samples reported as D. noxia U. S. biotype 2 in Sinha et al. [2] were Schizaphis graminum, as indicated by trace chromatograph files (data not shown). The COI sequences from the transcriptome assembly also confirmed that the samples previously labeled D. noxia biotype 2 were S. graminum (99–100% identity). The identity of S. graminum biotype I was confirmed via a diagnostic assay using sorghum breeding line TX2783, which is resistant to biotype I and susceptible to biotype E [60,61] (data not shown).

Plant and aphid responses to aphid feeding on plants of three wheat lines containing either Dn0, Dn4 or Dn7

Plants of breeding line 94M370 exhibit resistance to S. graminum biotype I.

Mean percent plant chlorosis (F_{3, 36} = 16.45, P < 0.0001) and mean plant damage scores (F_{3, 36} = 3.76, P = 0.02) were significantly lower on TAM110 resistant control plants than on plants containing Dn0, Dn4 or Dn7 (Table 1). The mean damage of 94M370 plants was also significantly lower than that of Dn4 plants and mean percent dry weight change (% DWT) in 94M370 plants was significantly less than that in Dn0 plants (F_{3, 36} = 12.34, P < 0.0001), but there were no other significant differences in % DWT between varieties. There were no significant differences in total aphid number between varieties (F_{3, 36} = 1.76, P = 0.17). As a result, there were no significant differences between the tolerance index (% DWT/ # aphids) values of any varieties (F_{3, 36} = 0.28, P = 0.83). Overall, 94M370 plants were more resistant to S. graminum biotype I than plants containing Dn0 or Dn4 as shown by significantly decreased foliar damage (Table 1). 94M370 plants appear to be resistant to both D. noxia biotype 1 and S. graminum biotype I, there are differences in the mechanisms of resistance to each aphid. Foliar damage is significantly reduced in 94M370 plants in response to feeding by each species, but the reduction in S. graminum biotype I populations does not differ significantly at (P < 0.05), while numbers of D. noxia biotype 1 on 94M370 plants are significantly less than those on Dn0 plants.

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Table 1. Mean (lower, upper CI) % chlorosis, damage score, number of S. graminum biotype I, % proportional dry weight change and tolerance index in plants containing Dn4- or Dn7 genes, susceptible control Dn0 plants and resistant control TAM110 plants infested by S. graminum at 21 d post infestation.

https://doi.org/10.1371/journal.pone.0233077.t001

S. graminum assembly metrics

The final S. graminum transcriptome assembly contained 23,982 transcripts derived from 13,534 protein coding unigenes with an average number of isoforms per unigene of 1.8 and an average GC content of 38.48%. Median transcript length was 1,032 nt and the total assembly length was 33.02 Mb (Table 2). When including only the single longest isoform per unigene, the median transcript length dropped to 942 nt and the total assembly size was reduced to 17.54 Mb. In addition, approximately 75% of the transcripts containing ORFs (18,075 transcripts), representing 71% of the protein coding unigenes (9,641 unigenes), had a significant blastp match to at least one Swiss-Prot protein (Table 2). Of the protein coding transcripts lacking BLASTP matches to Swiss-Prot, 1.4% (331 transcripts derived from 246 unigenes) had a significant BLASTX match to Swiss-Prot and 5.4% contained at least one PFAM domain (1,299 transcripts derived from 954 unigenes). Approximately 500 unigenes derived from Buchnera (2.5%) were also detected in the assembly, with a N50 contig size of 945 bp, total assembly length of approximately 401 kb, and an estimated GC content of 27.82%. In addition, 0.15% of the unigenes in the assembly were derived from plants, 0.38% were derived from other bacteria, and 0.05% were derived from fungi. Similar to the metabolic capacity of other Buchnera sp., unigenes coding for the metabolic pathways detected in this transcriptome assembly included genes coding for enzymes involved in folate biosynthesis (5 unigenes), phenylalanine, tyrosine, and tryptophan biosynthesis (10 unigenes), lysine biosynthesis (9 unigenes), valine, leucine, and isoleucine biosynthesis (4 unigenes), and arginine biosynthesis (6 unigenes). Unigenes derived from partial 16S and 23S rRNAs assigned to the genus Buchnera were also recovered, which showed 95% and 100% nucleotide identity to Buchnera aphidicola strains associated with S. graminum, respectively.

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Table 2. Assembly statistics for S. graminum transcriptome assembly.

https://doi.org/10.1371/journal.pone.0233077.t002

94M370 plants had a more pronounced impact on global gene expression in S. graminum than Dn4 plants

An average of 84.1% of the reads derived from each S. graminum sample were successfully mapped back to the transcriptome assembly and no major differences in mapping metrics were detected among any of the three aphid-plant diet treatment groups. The three replicates of the 94M370 treatment were highly correlated with one another (R² ≥0.90) based on global expression profiles and the Dn4 treatment was more similar to the Dn0 treatment than it was to the Dn7 treatment (Figs 1 and 2). Overall, 2,063 S. graminum unigenes were differentially expressed in at least one treatment with an FDR corrected p-value of ≤0.05 (Fig 3).

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Fig 1. EdgeR correlation matrix for DEGs expressed by greenbug, Schizaphis graminum, biotype I, fed plants containing no resistance genes (Dn0); the Diuraphis noxia biotype 1-resistant plants containing the Dn4 resistance gene from wheat; or plants of 94M370 containing the Dn7 gene from rye resistant to D. noxia and S. graminum.

https://doi.org/10.1371/journal.pone.0233077.g001

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Fig 2. S. graminum DEGs associated with feeding on wheat plants containing the Dn7 resistance gene from 94M370 plants relative to plants containing the Dn4 resistance gene or susceptible Dn0 plants.

https://doi.org/10.1371/journal.pone.0233077.g002

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Fig 3.

Clusters of co-expressed unigenes in S. graminum fed wheat plants containing the Dn7 resistance gene from rye in 94M370 plants (blue bar); the Dn4 resistance gene from wheat (green bar); or no resistance gene (Dn0) (orange bar).

https://doi.org/10.1371/journal.pone.0233077.g003

Consistent with the resistance of 94M370 to S. graminum, the majority of the differentially expressed genes that were identified were either up- or down-regulated in insects feeding on 94M370 plants. Lending support to this observation, K-means analysis led to the identification of two major gene clusters that each contained unigenes with similar expression patterns across the three feeding treatments (Fig 4). Although various statistical methods detected the presence of from two to 10 clusters of co-expressed genes in the data, the most frequently predicted number of clusters among the different methods used to detect co-expression was two clusters. Cluster 1 contained 1,175 unigenes expressed at lower levels in S. graminum fed 94M370 plants relative to those fed Dn4 and Dn0 plants (Fig 4A and 4C), while cluster 2 contained 888 unigenes more highly expressed in S. graminum fed 94M370 plants than those relative those fed Dn4 and Dn0 plants (Fig 4B and 4D). No other clusters of co-expressed unigenes could be identified through k-means, indicating that 94M370 plants containing the Dn7 gene from rye had stronger effects on the global transcriptional profiles of S. graminum relative to those fed Dn4 plants. However, a closer inspection of the clusters led to the identification of 159 unigenes within cluster 1 that were more highly downregulated and had more substantial log fold changes in S. graminum fed 94M370 plants compared to the other unigenes assigned to that cluster (Fig 5A; average log-fold change (LFC) = -2); as well as 78 unigenes within cluster 2 that were more highly upregulated in S. graminum fed 94M370 plants compared to the other unigenes assigned to that cluster (Fig 5B; average LFC = 3).

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Fig 4. K-means analysis of two major clusters of unigenes sharing common expression in S. graminum biotype I fed wheat plants containing the Dn4 D. noxia resistance or the Dn7 D. noxia resistance gene in 94M370 plants and susceptible (Dn0) plants.

A. Cluster 1–1,175 unigenes. B. Cluster 2–888 unigenes. C. Number of cluster 1 unigenes downregulated in Dn7 relative to Dn0 and Dn4. D. Number of cluster 2 unigenes upregulated in Dn7 relative to Dn0 and Dn4.

https://doi.org/10.1371/journal.pone.0233077.g004

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Fig 5. K-means analysis of two major clusters of highly differentially expressed (2–8 fold) unigenes in S. graminum biotype I fed wheat plants containing the D. noxia Dn7 resistance gene in 94M370 plants compared to other unigenes assigned to each cluster.

A. Cluster 1–159 highly downregulated unigenes. B. Cluster 2–78 highly upregulated unigenes.

https://doi.org/10.1371/journal.pone.0233077.g005

GO enrichments for signal transduction and nucleic acid metabolism in S. graminum were associated with feeding on 94M370 plants

Of the cluster 1 unigenes in Fig 4, 284 were exclusively downregulated in S. graminum fed 94M370 plants relative to those fed Dn0 plants, 862 were exclusively downregulated in S. graminum fed 94M370 plants relative to those fed Dn4 plants and 29 were downregulated in S. graminum fed 94M370 plants relative to those fed Dn4 and Dn0 plants (Fig 4C). Of the cluster 2 unigenes, 46 were exclusively upregulated in S. graminum fed 94M370 plants relative to those fed Dn0 plants, 648 were exclusively upregulated relative to those fed Dn4 plants, and 194 were upregulated relative to those fed Dn4 and Dn0 plants (Fig 4D).

Overall, unigenes with lower expression levels in S. graminum fed 94M370 plants relative to those fed Dn4 and Dn0 plants (cluster 1) were enriched for GO categories linked to regulation of developmental process, cell migration, regulation of nucleic acid specific binding, cholesterol transporter activity, receptor activity, and signal transduction. Specific enriched terms included signal transduction activity (GO:0004871), signaling receptor activity (GO:0038023), oxidoreductase, acting on diphenols (GO:0016882), steroid transporting ATPase activity (GO:0034041), and regulatory region nucleic acid binding (GO:0001067) (Table 3). Other enriched terms included anatomical structure development (GO:004886), regulation of cell development (GO:0060284), regulation of neurogenesis (GO:0050767), morphogenesis of an epithelium (GO:0048513), regulation of response to stimulus (GO:0048585), biological adhesion (GO:0022610), axon guidance (GO:0042659), intrinsic component of membrane (GO:0031226), and negative regulation of serine/threonine kinase activity (GO:0071901) (S1 Table).

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Table 3. Enriched gene ontology (GO) molecular function terms for cluster 1 unigenes expressed at lower levels in S. graminum fed 94M370 plants compared to those fed either Dn0 or Dn4 plants.

https://doi.org/10.1371/journal.pone.0233077.t003

The upregulated unigenes in cluster 2 from S. graminum fed 94M370 plants were enriched for GO terms linked to nucleic acid metabolic process (GO:0090304), cellular nitrogen compound metabolic process (GO:0034641), double-strand break repair via homologous recombination (GO:0000724), DNA replication (GO:0006260), cell division (GO:0051301), ribosomal large subunit biogenesis (GO:0042273), and ribonucleoprotein complex biogenesis (GO:0022613) (Table 4). Other enriched GO terms included protein complex (GO:0043234), rRNA metabolic process (GO:0016072), Ada2/Gcn5/Ada3 transcription activator complex (GO:0005671), macromolecular complex (GO:0032991), ncRNA processing (GO:0034470), nucleolus (GO:0005730), and acetyltransferase complex (GO:1902493) (S2 Table).

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Table 4. Enriched gene ontology (GO) biological process terms for cluster 2 unigenes expressed at higher levels in S. graminum fed 94M370 plants compared to those fed either Dn0 or Dn4 plants.

https://doi.org/10.1371/journal.pone.0233077.t004

Although not enriched, other GO categories that contained large numbers of unigenes impacted by feeding on 94M370 plants included cholesterol transport (GO:0030301; 9 of 26 annotated unigenes assigned to this category), melanin biosynthetic process (GO:0006469; 6 of 15 unigenes), and sensory organ development (GO:0007423; 37 of 169 unigenes), all of which were associated with differentially expressed genes (DEGs) (Table 5). Additionally, unigenes coding for enzymes linked to mitotic cell cycle process (GO:1903047; 53 of 453 unigenes) and microtubule organization center (GO:0031023; 15 of 80 unigenes) were associated with DEGs upregulated in S. graminum fed 94M370 plants (Table 5).

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Table 5. Additional GO terms associated with unigenes differentially expressed in S. graminum.

https://doi.org/10.1371/journal.pone.0233077.t005

Expression of genes linked to actin cytoskeleton regulation and proteolysis were also impacted in S. graminum fed 94M370 plants

Pathway level analysis using KEGG assignments largely mirrored the results of the GO enrichments and identified additional impacts of the feeding treatments on gene expression in S. graminum. Cluster 1 downregulated unigenes were largely assigned to KEGG pathways for focal adhesion, several different signaling pathways, axon guidance, purine metabolism, actin cytoskeleton regulation, amino acid biosynthesis, lysine degradation, starch and sucrose metabolism, autophagy, apoptosis, endocytosis, protein digestion and absorption, glycerosphingolipid metabolism, cell cycle, galactose metabolism, lysosome, and melanogenesis (Table 6). Interestingly, in the amino acid biosynthesis pathway, unigenes coding for all enzymes linked to the synthesis of proline from glutamine, a unigene coding for cystathoine-γ lyase (cysteine biosynthesis), and serine/threonine ammonia-lyase (serine and/or threonine metabolism) were expressed at lower levels in S. graminum fed 94M370 plants compared to both plants containing Dn0 or Dn4 (Table 6).

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Table 6. KEGG pathway assignments for cluster 1 unigenes from S. graminum.

https://doi.org/10.1371/journal.pone.0233077.t006

Four unigenes coding for different portions of the lysine degradation pathway were also expressed at lower levels in S. graminum fed 94M370 plants while unigenes coding for enzymes linked to the degradation of sucrose and/or maltose (maltase-glucoamylase), gluconeogenesis (glycogen synthase), UDP-glucose metabolism (UDP-glucose pyrophoshorylase), and metabolism of chitin (chitinase) were also expressed at low levels in this treatment (Table 6). Additionally, unigenes coding for four different glycosidases associated with lysosomal activity were also downregulated in S. graminum fed 94M370 plants compared to those fed plants containing Dn0 or Dn4 (Table 6). In contrast, upregulated unigenes associated with cluster 2 were assigned to pathways linked to ubiquitin mediated proteolysis, cell cycle, pyrimidine and purine metabolism, ribosome biogenesis, nucleotide excision repair, amino acyl tRNA biosynthesis, RNA degradation, endocytosis, and peroxisome (Table 7).

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Table 7. KEGG pathway assignments for cluster 2 unigenes from S. graminum.

https://doi.org/10.1371/journal.pone.0233077.t007

Genes coding for detoxification enzymes were downregulated in in S. graminum fed 94M370 plants

Beyond these GO categories and KEGG pathways, S. graminum feeding on 94M370 plants expressed unigenes coding for proteins broadly linked to detoxification, digestion and growth or development (S3 and S4 Tables). Most of these unigenes were actually downregulated when compared to S. graminum fed plants containing either Dn4 or Dn0 (S3 Table). Those most strongly downregulated included a detoxification acyl transferase homologous to nose resistant to fluoxetine 6 protein (-8.6 log-fold change (LFC)), platelet-activating factor acetylhydrolase IB (-5.3 LFC), and a WD domain, G-beta repeat protein involved in tRNA binding (-6.5 LFC). Several developmental proteins were highly downregulated, including platelet-activating factor acetylhydrolase IB (-5.3 LFC), Dscam2 cell adhesion molecule-like protein (-7.4 LFC), a GCM motif protein (-6.2 LFC), and a DHHC palmitoyltransferase (-4.2 LFC) (S3 Table). A unigene coding for phosphate acetyltransferase involved in the metabolism of pyruvic acid was also highly downregulated (-6.6 LFC).

Four unigenes coding for glycoside hydrolase (GH) family 1 proteins were also downregulated in this comparison. All four GH family 1 unigenes have highest scoring blastp matches to myrosinases. Few GH family 1 genes have been functionally characterized in any aphid or insect species. However, many of these enzymes have known roles in digestive or detoxification processes in other organisms, such as degrading β-1,4-linked disaccharide sugars or metabolizing nitrogen- and sulfur-containing compounds. Unigenes coding for the most strongly upregulated proteins (S4 Table), included those for energy production (NADH-quinone oxidoreductase, 7.5 LFC); lipid homeostasis (glycerol-3-phosphate acyltransferase 1, 4.5 LFC); molting (zinc finger protein 862, 6.8 LFC); and DNA repair (DNA-directed RNA polymerase III subunit RPC5, 8.4 LFC). Several proteins related to DNA replication, gene expression, and chromatin structure were also highly upregulated. These included dUTP diphosphatase (7.9 LFC), leucine-tRNA ligase (7.2 LFC), and polycomb protein eed (6.2 LFC). Unigenes coding for proteins linked to growth/development and fatty acid biosynthesis and were also upregulated including protein inturned (6.4 LFC) and malonyl coA acyl carrier protein transacylase (6.9 LFC), respectively.

Dn4 plants had minimal impacts on gene expression in S. graminum

Although Dn4 appeared to be susceptible to S. graminum, the expression levels of a few S. graminum unigenes were impacted by feeding on Dn4 plants compared to Dn0, which included four up- and eight downregulated unigenes. Due to the low numbers of DEGs identified in S. graminum fed Dn4, no GO terms were enriched for any unigenes in this comparison (Fig 4). However, upregulated unigenes included a cytochrome P450 (CYP450; detoxification); glutamate dehydrogenase (an important branch point between carbon and nitrogen metabolism) and a zinc finger protein (transcriptional regulation) (S5 Table), while downregulated unigenes included one gene each for coding for GDSL lipase (neurotransmitter), acyltransferase (detoxification), RNA-dependent DNA polymerase (transposase) major facilitator transporter (transmembrane transport), and a cleavage stimulation factor (polyadenylation) (S6 Table). The rest were hypothetical proteins that could not be annotated. In addition, four of the eight down-regulated DEGs in S. graminum fed Dn4 plants were also downregulated in aphids fed 94M370 plants compared to those fed Dn0 plants (S3 and S6 Tables), while only one, a zinc-finger protein, was upregulated in S. graminum fed both Dn4 and 94M370 plants compared to those fed Dn0 plants (S4 and S5 Tables). The four commonly downregulated unigenes coded for an acyltransferase, a lipase, a transporter, and a hypothetical protein.

94M370 plants had the most pronounced impacts on DEGs produced in D. noxia

Greater than 85% of the RNA-Seq reads derived from D. noxia biotype 1 successfully mapped to the biotype 2 reference genome, indicating the biotype 2 genome assembly to be a suitable reference for read mapping. No major differences in mapping metrics were detected among any of the three D. noxia treatment groups (feeding on Dn0, Dn4, or 94M370 plants) and the three biological replicates within each treatment were highly correlated with one another (R² ≥0.90) (Fig 6). The 420 differentially expressed D. noxia unigenes in at least one treatment with an FDR corrected p-value of ≤0.05 formed 6 clusters (Fig 7). As in S. graminum, the global gene expression profiles of D. noxia fed Dn0 and Dn4 plants were more similar to one another in comparison to those fed 94M370 plants. A total of 376 DEGs were present in D. noxia biotype 1 fed wheat plants containing at least one of the three different plant Dn genes compared to D. noxia fed only Dn0 plants (Fig 8). Of these differentially expressed unigenes, 204 were exclusively upregulated in D. noxia fed 94M370 plants relative to those fed Dn0 plants and 30 were exclusively upregulated in D. noxia fed Dn4 plants relative to those fed Dn0 plants (Fig 8A). Among downregulated DEGs, 138 were exclusively downregulated in D. noxia fed 94M370 plants relative to those fed Dn0 plants and 4 were exclusively downregulated relative to those fed Dn4 plants (Fig 8B). In contrast to the expression data in Fig 7, K-means analysis indicated the presence of one to 10 clusters of co-expressed genes in D. noxia fed the three plant diets. However, among the statistical methods used for k-means optimization, five was the most frequently predicted number of clusters, as shown in Fig 9.

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Fig 6. EdgeR correlation matrix for DEGs expressed by Russian wheat aphid, Diuraphis noxia, biotype 1 fed plants containing no resistance genes (Dn0); the D. noxia Dn4 resistance gene from wheat; or the D. noxia Dn7 gene from rye.

https://doi.org/10.1371/journal.pone.0233077.g006

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Fig 7. Clusters of co-expressed unigenes in D. noxia biotype 1 fed wheat plants containing the Dn7 resistance gene from rye (blue bar); the Dn4 resistance gene (green bar); or no resistance gene (Dn0) (orange bar).

https://doi.org/10.1371/journal.pone.0233077.g007

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Fig 8. D. noxia DEGs associated with feeding on wheat plants containing the Dn7 or Dn4 resistance genes relative to feeding on susceptible Dn0 plants.

https://doi.org/10.1371/journal.pone.0233077.g008

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Fig 9. K-means analysis of five major clusters of unigenes sharing common expression in D. noxia biotype 1 fed wheat plants containing the Dn4 and Dn7 D. noxia resistance genes and susceptible (Dn0) plants.

A. Cluster 1–33 unigenes; B. Cluster 2–179 unigenes; C. Cluster 3–49 unigenes; D. Cluster 4–110 unigenes; E. Cluster 5–46 unigenes. Cluster 6 (2 unigenes) was omitted due to the low number of unigenes assigned to this group.

https://doi.org/10.1371/journal.pone.0233077.g009

GO enrichments for fatty acid synthase and glucosidase activity were detected in D. noxia fed 94M370 plants

Among the five clusters shown in Fig 9, D. noxia fed 94M370 plants consistently upregulated 212 unigenes at levels higher than in those fed Dn0 and Dn4 plants (cluster 1–33 unigenes, cluster 2–179 unigenes) (Fig 9A and 9B). Cluster 3 contained 49 unigenes differentially expressed in D. noxia fed both 94M370 and Dn4 plants, relative to those fed Dn0 plants (Fig 9C). Additionally, 159 unigenes (cluster 4–110 unigenes, cluster 5–46 unigenes) were strongly downregulated in D. noxia fed 94M370 plants relative to those fed Dn0 plants and Dn4 plants (Fig 9D and 9E).

Due to the low numbers of unigenes assigned to each of the six clusters of co-expressed genes, few GO terms were enriched. However, unigenes that were downregulated in D. noxia fed 94M370 plants were enriched for fatty acid synthase (GO:0004312; cluster 4); glucosidase activity (GO:0015926; cluster 4); oxidoreductase activity, acting on CH-CH group of donors (GO:0016628; cluster 4); cell cycle process (GO:0022402; cluster 5); and microtubule binding (GO:0008017; cluster 5) (Table 8). Unigenes that were upregulated in D. noxia fed 94M370 plants relative to D. noxia fed either Dn4 plants or Dn0 plants were enriched with GO terms linked to actin filament polymerization (GO:0030838; cluster 3) and protein K63-linked ubiquitination (GO:0070534; cluster 3). No other GO categories were enriched or highly abundant among the unigenes that were upregulated in D. noxia fed 94M370 plants (clusters 1 and 2) or cluster 6.

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Table 8. Enriched gene ontology (GO) terms for unigenes differentially expressed in D. noxia fed 94M370 plants compared to those fed either Dn0 or Dn4 plants.

https://doi.org/10.1371/journal.pone.0233077.t008

Genes coding for lysosomal enzymes and purine metabolism were similarly impacted in D. noxia and S. graminum fed 94M370 plants

Additionally, KEGG pathway analysis identified unigenes associated with several metabolic pathways were impacted, particularly in D. noxia fed 94M370 plants relative to those fed either Dn0 or Dn4 plants. These included unigenes coding for enzymatic components of lysosomes and unigenes associated with thiamine absorption, autophagy, and signaling pathways, which were associated with upregulated unigenes (Table 9).

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Table 9. KEGG pathway assignments for genes upregulated in D. noxia fed 94M370 plants relative to D. noxia fed Dn0 plants.

https://doi.org/10.1371/journal.pone.0233077.t009

In contrast, downregulated unigenes in this comparison were associated with purine metabolism (primarily inosine monophosphate biosynthesis and ribonucleotide reductase associated with the formation of deoxyribonucleotides from ribonucleotides). Genes linked to purine metabolism were also downregulated in S. graminum (Tables 6 and 7). Others unigenes downregulated in D. noxia in this comparison included those involved in protein processing in the endoplasmic reticulum, glutathione metabolism, and two enzymes associated with oxidative phosphorylation (Table 10). Due to the lower number of DEGs in the Dn4 versus Dn0 comparison, few metabolic pathways were impacted.

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Table 10. KEGG pathway assignments for genes downregulated in D. noxia fed 94M370 plants relative to D. noxia fed Dn0 plants.

https://doi.org/10.1371/journal.pone.0233077.t010

Expression levels of detoxification genes exhibited divergent expression patterns in D. noxia and S. graminum on 94M370 plants

D. noxia fed 94M370 plants upregulated between twice as many unigenes coding for proteins linked to detoxification and 5x more unigenes coding for proteins linked to nucleic acid processing or signaling than unigenes than D. noxia fed Dn4 or Dn0 plants (S7 Table). In contrast, S. graminum fed 94M370 plants downregulated most of the unigenes coding for proteins linked to detoxification (S3 Table). Unigenes associated with stress response and detoxification in D. noxia included two lipases, four CYP450 proteins, three phosophlipases, two glucose dehydrogenases, a multicopper oxidase, a cysteine proteinase inhibitor, two trypsins, a serpin, and a Kazal-type serine protease inhibitor were upregulated in this treatment (S7 Table). However, the fold change levels of all of these unigenes were much lower (0.75 LFC to 1.25 LF) than fold change levels of unigenes expressed by S. graminum (S4 Table). In addition, several unigenes linked to nutrient acquisition/transport and general metabolism were also upregulated, coding for proteins linked to transport of folates (2), sugar (2), acetyl-coA (2); fatty acid desaturase (1), gluconeogenesis, and vitamin A metabolism (1) (S7 Table).

Unigenes coding for detoxification and digestion were also predominant among the genes that were downregulated in D. noxia fed 94M370 plants relative to those fed Dn0 plants, but again at lower expression levels than in S. graminum. Strongly downregulated detoxification unigenes included those coding for γ-glutamyltranspeptidase (-1.2 fold); heat shock protein (HSP) 70 (-2.2 and -0.35 fold); HSP90 (1); HSP60 (1); lipocalin (1); papain family cysteine protease (2); trypsin (1); ubiquitin (1), and UGT (3) (S8 Table). Additionally, unigenes coding for several key digestive enzymes and nutrient transporters were also downregulated in this treatment, including those coding for α-amylase (3), fatty acid synthase (3); lysosomal α-mannosidase (1); GH family 1 protein (1); reduced folate carrier (1); sugar (and other) transporters (3); and sulfate permease (1) (S8 Table). Unigenes coding to mitochondrial activities were also downregulated in D. noxia fed 94M370 plants, including those coding for cytochrome c oxidase proteins (1), cytochrome b561, as were unigenes associated with cell cycle activities, including cyclin (2); cell division protein (1); and Chromo (CHRomatin Organizaton MOdifer) domain protein (1 (S8 Table)). More unigenes coding for structural proteins were downregulated in D. noxia fed 94M370 plants compared to those that were upregulated (S7 and S8 Tables). These unigenes were annotated as cadherin (1); insect cuticle protein (1); laminin (1); kinesin motor domain (1); and microtubule binding proteins (4).

Impacts of Dn4 plants had stronger effects on global gene expression in D. noxia than in S. graminum

Consistent with the antibiosis effects of Dn4 plants on D. noxia, ingestion of phloem sap from Dn4 plants had a much higher impact on unigene expression relative to S. graminum. Upregulated unigenes were predominantly linked to stress response and coded for ABC transporter (1); CYP450 (2); glucose dehydrogenase (1); lipase (1); multicopper oxidase (1); serpin protease inhibitor, and protein Spaetzle (1; ligand for Toll receptor) (S9 Table). The same unigenes coding for multicopper oxidase, lipase, and Spaetzle were also upregulated in D. noxia fed 94M370 plants when compared to those fed Dn0 plants (S7 and S9 Tables). Several unigenes whose products were linked to growth and development were also upregulated, including two unigenes coding for peritrophin A proteins (2), one unigene coding for a GH 18 chitinase linked to chitin remodeling, one unigene coding for a JHBP, and three unigenes coding for insect cuticle proteins (S9 Table). Unigenes coding for reduced folate carriers (2; also upregulated in D. noxia fed 94M370 plants) and general odorant binding proteins (PBP/GOBP) were also upregulated (S9 Table). Interestingly, nine of the 13 unigenes that were downregulated in D. noxia fed Dn4 plants were also downregulated in D. noxia fed 94M370 plants, which included unigenes coding for α-amylase (2), HSP70 (1); insect cuticle protein (1); papain family cysteine protease (1); and major facilitator superfamily transporters (2) (S8 and S10 Tables). The remaining four unigenes that were downregulated exclusively in D. noxia fed Dn4 plants coded for hypothetical proteins (3) and a second insect cuticle protein (1) (S10 Table).