Gerbera hybrida is one of the top five cut flowers across the world, it is host for the root rot causing parasite called Phytophthora cryptogea. In this study, plantlets of healthy and root-rot pathogen-infected G. hybrida were used as plant materials for transcriptome analyis using high-throughput Illumina sequencing technique. A total 108,135 unigenes were generated with an average length of 727 nt and N50 equal to 1274 nt out of which 611 genes were identified as DEGs by DESeq analyses. Among DEGs, 228 genes were up-regulated and 383 were down-regulated. Through this annotated data and Kyoto encyclopedia of genes and genomes (KEGG), molecular interaction network, transcripts accompanying with tyrosine metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, phenylpropanoid and flavonoid biosynthesis, and plant hormone signal transduction pathways were thoroughly observed considering expression pattern. The involvement of DEGs in tyrosine metabolism pathway was validated by real-time qPCR. We found that genes related with tyrosine metabolism were activated and up-regulated against stress response. The expression of GhTAT, GhAAT, GhHPD, GhHGD and GhFAH genes was significantly increased in the leaves and petioles at four and six dpi (days post inoculation) as compared with control. The study predicts the gene sequences responsible for the tyrosine metabolism pathway and its responses against root-rot resistance in gerbera plant. In future, identification of such genes is necessary for the better understanding of rot resistance mechanism and to develop a root rot resistance strategy for ornamental plants.
Gerbera hybrida (2n = 2x = 50) is a perennial herbaceous flower planted as cut flower, pot flower and garden plants [[
Due to distinctive capitulum inflorescence and floral stem, gerbera has a great aesthetic value. Unlike other species having solitary inflorescences such as roses, it has three different types of florets that are compacted at the same receptacle [[
To study of floral growth and development in Asteraceae flowers, gerbera has proved a model plant. Its variation in disc and ray florets pattering, flower color and high levels of secondary metabolites make it putative model flower for biosynthetic research [[
The biochemical mechanism of root rot in plants is very complex. The genomics and proteomics proved helpful in revealing the mechanisms and root cause of many diseases and controlling these infestations. However, the genomic resources are rarely available for ornamental crops; the transcriptome RNA sequencing provides an excellent opportunity to study the ornamental plants. Considering the large genome size of Gerbera, the use of sequencing is helpful that reduces the cost and decreases the processing time, significantly. It also helps to focus on specific genes for the establishment of genomic resources. Transcriptome RNA sequencing (RNA-Seq) has recently emerged as a wide and accurate tool for expression pattern analysis of genes, because of its extensive genomic range, higher reproducibility and the superior evaluation for expression levels, particularly under the situations where genomic means are not common and the chance of heterozygosity exists [[
This study focus on the identification and characterization of differentially expressed genes of healthy and diseased plants using utilizing NGS sequencing. Through the configuration of reads, assembled by de novo assembly, we identified the genes that can be utilized for further genetic investigations. The overall goal of this study was the identification of defense-related genes that are differentially expressed in various pathways when gerbera plants are exposed to Phytophthora cryptogea. For the validation of DEGs, real-time quantitative PCR was performed for the genes involved in tyrosine metabolism pathway. This helps to recognize the role of these genes in defense mechanism against pathogen infection in gerbera plants. Transcriptomes are examined by gene annotation and anticipated the candidate genes that are involved in disease resistance pathways particularly for root rot. Identification of DEGs involved in disease defense-related pathways helps study the role of gene in gerbera against root rot. These DEGs provide evidence and can be utilized in gerbera crop improvement program for root rot resistance.
A total of 113,980,180 reads were produced by means of Illumina high-throughput sequencing TM 2000. Subsequent to the separation of low-quality reads, 110,371,574 clean reads were selected. Among these, 57,026,700 and 53,344874 clean reads of healthy and diseased gerbera plant sample were obtained, respectively (Table 1). Among all reads, the Q
Graph
Table 1 Summary of G. hybrida sequence analysis.
Sample Raw Reads Clean Reads Clean Bases Error (%) Q20 (%) C 59001654 57026700 8.55 Gb 0.01 97.38 Dis. 54978526 53344874 8 Gb 0.01 97.81 Total 113980180 110371574 16.55 Gb
1 C: Control; Dis: root-rot disease
Graph
Table 2 Summary of transcriptome of G. hybrida.
Sample Total number Total nucleotides mean length N50 Total number of unigenes 108135 65063492 602 937 Total number of transcripts 141972 103194053 727 1274
Subsequently excluding repetitive and short size sequences, 38,922 unigenes (35.99% of all cleaned unigenes) were annotated by BLASTX against Nr through cut-off E-value 1e
Graph: Fig 1 Nr categorization of gerbera Unigenes.(a) E-value distribution (b) Similarity distribution (c) Species classification.
In addition, unigenes were exposed to NR, NT, KO, Swiss Port, Pfam, GO and KOG databases using BLAST analysis (E-value <0.00001). In addition to this, 27,314 unigenes (25.25% of all prepared unigenes) were annotated using BLASTN in contrast with Nt under indistinguishable parameters. Unigenes were likewise adjusted to further databases comprising 32,062 genes (29.64% of all cleaned unigenes) in Swiss-Prot database, 28,964 genes (26.78% of all cleaned unigenes) in Pfam, 29,451 genes (27.23% of all cleaned unigenes) in GO and 15,528 genes (47.89% of all cleaned unigenes) were annotated in KOG database. In total 51,796 (47.89% of all cleaned unigenes) unigenes were effectively annotated from atleast one of the Nr, Nt, KO, SwissProt, GO, COG, KEGG and Pfam databases (Fig 2 and S1 Table).
Graph: Fig 2 Summary of gene annotation against seven databases in gerbera.
The distribution of gene functions in GO (Gene Ontology) was grouped into biological processes, cellular component and molecular function. Total annotated genes were 29,451, among each term cellular (16,369 genes), metabolic (15,485 genes) and single–organism process (11,891 genes); cell (8,489 genes), cell part (8,482 genes), organelle (5,588 genes)"; binding (15,516 genes), catalytic activity (12,600 genes) and transporter activity (1,922 genes)" were dominant subcategories (S2 Fig).
Similarly, 15,528 putative proteins marked by COG were categorized into 25 molecular families, and the uppermost classification was General function prediction (2,769 genes) followed by post-translation modification, protein turnover, chaperones (1,992 genes), translation, ribosomal structure and biogenesis (1,433 genes), and signal transduction mechanisms (1,394 genes) (S3 Fig).
Unigenes were also annotated against KEGG database for understanding advanced-level utilities and functions of the biological structure. In this way, 14,335 unigenes were assigned to 19 pathways. By representing the enzyme commission (EC) numbers in contrast to the KEGG database, numerous transcripts were discovered that are involved in metabolism and signal transduction pathways. Metabolism was the most significant category, a substantial number of genes were related to carbohydrate metabolism (1,422 genes) and amino acid metabolism (852 gens) (S4 Fig).
We found 611 unigenes differentially expressed amongst two samples by comparing the expression levels. A total of 228 genes were up-regulated and 383 genes were down-regulated in gerbera in response to the infection of Phytophothora cryptogea (Fig 3). For instance, the GO terms single organism metabolic process (GO: 0044710), carbohydrate metabolic process (GO: 0005975), catalytic activity (GO: 0003824), and cell wall (GO: 0005618), were enriched in analysis of DEGs. Interesting, among these DEGs, there were several up-and down-regulated genes that are involved in metabolic and catalytic activities. The functional distribution of up-and down-regulated DEGs with corrected p-value < 0.05 are provoided in S2 Table.
Graph: Fig 3 Volcano plot demonstrating differential expressed genes among the Dis (disease) and C (control) gerbera samples.The x-axis is the genes expression change of different sample in a different experiment, and the y-axis is the p-value after normalized. The bigger -log10 (q-value) represents more significant differences.
Functional annotation demonstrated that root rot disease apprantly (corrected p value < 0.05) influenced 15 biological process, 15 molecular functions and 5 cell component metabolic pathways. The root rot disease largely influenced the following biological process in gerbera: single-organism metabolic process, oxidation-reduction process and carbohydrate metabolic process; the affected molecular function includes catalytic activity and oxidoreductase activity; the affected cellular component includes cell wall and cell periphery (S5 Fig). The up and down regulated DEGs that involved in resistance against root-rot disease with their functional annotation, Log
Graph
Table 3 Differentially expressed genes in gerbera plant that are involved in disease resistance against root-rot disease.
Gene ID Dis read-count Ck read-count FC Functional annotation c54071_g1 56.825651 6.0599569 3.2292 7.75E-12 1.22E-09 Tyrosine aminotransferace c55425_g1 110.14922 39.302357 1.4868 2.55E-09 3.09E-07 Homogentisate 1,2-dioxygenase c52742_g1 0.4184647 107.30028 -8.0023 3.75E-24 1.39E-21 Polyphenol oxidase c49788_g1 0.8369295 24.426437 -4.8672 4.19E-07 3.84E-05 Polyphenol oxidase c52132_g1 269.44479 99.070106 1.4435 7.61E-20 2.15E-17 4-hydroxyphenylpyruvate dioxygenase c93557_g1 175.6157 36.705672 2.2583 2.05E-23 7.23E-21 Aspartate aminotransferase c39452_g1 343.55955 162.44681 1.0806 1.85E-16 4.20E-14 Phospho-2-dehydro-3-deoxyheptonate aldolase, c53077_g2 13.065399 58.975541 -2.1744 2.35E-08 2.50E-06 Arogenate /prephenate dehydratase c52184_g1 77.741448 28.123411 1.4669 7.18E-07 6.27E-05 phenylalanine ammonia-lyase 3 c52203_g1 16.785085 68.394023 -2.0267 9.02E-09 1.03E-06 Peroxidase c48612_g1 1.9063393 56.862984 -4.8986 1.09E-14 2.15E-12 Peroxidase c54004_g1 44.682734 14.215746 1.6522 4.23E-05 0.0026664 Peroxidase c51559_g1 2.1853158 115.3544 -5.7221 7.00E-29 3.69E-26 Caffeic acid 3O methyl transferase c44146_g1 72.301407 27.463237 1.3965 4.06E-06 0.0003196 caffeoylshikimate esterase c41936_g1 726.31529 2840.6405 -1.9675 2.30E-289 4.27E-285 chalcone Synthase c56396_g2 133.16478 47.488514 1.4876 5.60E-11 8.31E-09 ABF c67578_g1 16.459613 119.27143 -2.8572 1.65E-20 4.91E-18 auxin-responsive protein IAA c50421_g1 11.902997 45.99212 -1.9501 4.33E-06 0.000338 MYC2 c52417_g1 18.598433 56.334845 -1.5988 9.63E-06 0.0007055 Indole-3-acetic acid-amido synthetase GH3.5, c1401_g2 391.35752 50.789384 2.9459 2.06E-66 3.71E-63 PP2C c21743_g1 36.499424 2.7727307 3.7185 6.66E-09 7.74E-07 PP2C c57241_g1 98.618189 30.059921 1.714 4.32E-10 5.80E-08 PP2C c57287_g1 60.491402 3.3008698 4.1958 9.01E-15 1.79E-12 PP2C c52897_g1 282.13822 56.598915 2.3176 1.04E-37 7.93E-35 PP2C c53505_g1 340.63029 144.49008 1.2372 7.50E-20 2.12E-17 PP2C c55258_g1 15.111226 141.62932 -3.2284 7.93E-27 3.65E-24 Pectinesterase c54418_g1 48.309429 102.98714 -1.0921 8.72E-06 0.0006438 Pectinesterase c48524_g1 13.716344 145.63438 -3.4084 9.01E-29 4.70E-26 Pectinesterase c45767_g2 1.8598433 23.326147 -3.6487 4.77E-06 0.0003695 Pectinesterase c67308_g1 11.345044 38.994276 -1.7812 6.98E-05 0.0041518 Pectinesterase c46138_g1 12.135477 65.357222 -2.4291 3.23E-10 4.40E-08 Pectinesterase c52600_g1 4.7426003 56.510891 -3.5748 1.60E-12 2.69E-10 Pectinesterase
To understand the functional classification of DEGs, 14,335 unigenes belonging to 130 pathways were observed in Kyoto encyclopedia of genes and genomes (KEGG). KEGGs analysis indicated that maximum genes were differentially expressed for amino acid metabolism, carbohydrate metabolism, lipid metabolism, metabolism of cofactors and vitamins and metabolism of terpenoids and polyketides. These pathways are involved in tyrosine metabolism, tryptophan metabolism, phenylalanine metabolism, styrene degradation, phenylpropanoid biosynthesis, flavonoid biosynthesis and plant hormone signal transduction. Moreover, these pathways are interconnected with each other, genes involved in these pathways are highly enriched in diseased vs healthy plant samples and each was involved in different pathways in a different manner. The rich factor determins the ratio among the portion of pathway genes in the tested set and portion of pathway genes in the data set. It was observed that the q-value was higher for tyrosine metabolism followed by photosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis, and isoquinoline alkaloid biosynthesis (Fig 4). The top 17 KEGG pathways, and differently expressed genes involved in these pathways with least p-value are provoided in S3 Table.
Graph: Fig 4 KEGG pathway of differentially expressed genes distinguished in Dis Vs Ck of gerbera.The pathway names are given in the vertical axis, rich factor in the horizontal axis, size of the point represents the number of DEGs and the shade of the dot represent the q value.
Synthesis of aromatic amino acids, phenylalanine (Phe), tyrosine (Tyr) and tryptophan (Trp) starts with the alteration of phosphoenol pyruvate and erythrose 4-phosphate into chorismate by shikimate pathway. Four key enzymes involved in this pathway are 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase (DAHP, EC: 2.5.1.54), aspartate aminotransferase (AAT, EC: 2.6.1.1), tyrosine aminotransferase (TAT, EC: 2.6.1.5), and arogenate dehydratase (ADT, E.C:4.21.91). Condensation of ethrose-4-phosphate with phosphoenolpyruvate is catalyzed through the enzyme DAHP. Gene annotated as DAHP was up-regulated. DAHP is a fundamental enzyme regulating flux through the shikimate pathway. Phenylalanine and tyrosine both are regulated from prephenate. Prephenate synthesizes the phenylalanine in two steps: one through phenylpyruvate as a metabolic intermediary and another is arogenate. Dehydration forming phenylpyruvate is catalyzed by ADT. DEG annotated as ADT was down-regulated with a log2fold change value of -2.20. DEGs involved in this pathway are presented in Fig 5. In Phe, Tyr, and Trp biosynthesis we also found genes that were annotated as TAT and AAT, these genes were up-regulated with a log2fold change value of 3.20 and 2.30, respectively in root rot-infected plants. DEGs related with this pathway, their identity, gene length, regulation, and q-value are presented in Table 4.
Graph: Fig 5 Schematic diagram of key genes and metabolites of phenylalanine, tyrosine and tryptophan biosynthesis in gerbera; Colored boxes represent the DEGs in this KEGG pathway.Red color represents the up-regulation of DEGs; Green color represents the down-regulation of DEGs.
Graph
Table 4 KEGG annotation of enriched pathways in response to root-rot disease in gerbera.
KO ID EC number Gene-ID Gene length FC q-value Functional Annotation Gene Regulation Tyrosine Metabolism KI4454 2.6.1.1 c93557_g1 1661 2.2583 7.23E-21 Aspartate aminotransferase Up-regulated K00815 2.6.1.5 c54071_g1 1537 3.2292 1.22E-09 Tyrosine aminotransferase Up-regulated K00451 1.13.115 c55425_g1 1777 1.4868 3.09E-07 Homogentisate 1,2-dioxygenase Up-regulated K00422 1.10.3.1 c52742_g1 2096 -8.0023 1.39E-21 Polyphenol oxidase Down-regulated K01555 3.7.1.2 c53159_g1 1738 1.3843 1.15E-15 Fumarylacetoacetase Up-regulated K00457 1.13.11.27 c52132_g1 1717 1.4435 2.15E-17 4-hydroxyphenylpyruvate dioxygenase Up-regulated K00422 1.10.3.1 c49788_g1 2010 -4.8672 3.84E-05 Polyphenol oxidase Down-regulated Phenylalanine, tyrosine and tryptophan biosynthesis K01626 2.5.1.54 c39452_g1 1917 1.0806 4.20E-14 Phospho-2-dehydro-3-deoxyheptonate aldolase, Up-regulated K14454 2.6.1.1 c93557_g1 1661 2.2583 7.23E-21 Aspartate aminotransferase Up-regulated K00815 2.6.1.5 c54071_g1 1537 3.2292 1.22E-09 Tyrosine aminotransferase Up-regulated K05359 4.21.91 c53077_g2 1795 -2.1744 2.50E-06 Arogenate /prephenate dehydratase Down-regulated Phenylpropanoid biosynthesis K10775 4.3.1.24 c52184_g1 1085 1.4669 6.27E-05 Phenylalanine ammonia-lyase 3 Up-regulated K10775 4.3.1.24 c52203_g1 1597 -2.0267 1.03E-06 Phenylalanine ammonia-lyase Down-regulated K01188 3.2.1.21 c54615_g3 1436 1.6777 2.95E-19 Hypothetical protein PHAV Up-regulated K00430 1.11.1.7 c48612_g1 1308 -4.8986 2.15E-12 peroxidase Down-regulated K00430 1.11.1.7 c17117_g2 1563 -3.4041 6.45E-205 peroxidase Down-regulated K00430 1.11.1.7 c57922_g3 1646 -3.4336 0.001789 peroxidase Down-regulated K00430 1.11.1.7 c54004_g1 1307 1.6522 0.002666 peroxidase Up-regulated K13066 2.1.1.68 c51559_g1 1344 -5.7221 3.69E-26 Caffeic acid 3O methyl transferase Down-regulated K18368 3.1.1. c44146_g1 1517 1.3965 0.00032 Caffeoylshikimate esterase Up-regulated Flavonoid biosynthesis K00660 2.3.1.74 c41936_g1 1669 -1.9675 4.27E-285 Chalcone Synthase Down-regulated Plant hormones and signal transduction K14432 c56396_g2 2385 1.4876 8.31E-09 ABF Up-regulated K14484 c67578_g1 1122 -2.8572 4.91E-18 Auxin-responsive protein IAA Down-regulated K13422 c50421_g1 1777 -1.9501 0.000338 MYC2 Down-regulated K14506 c52417_g1 1047 -1.5988 0.000705 Indole-3-acetic acid-amido synthetase GH3.5, Down-regulated K14497 c1401_g2 1748 2.9459 3.71E-63 Highly ABA induced PP2C gene Up-regulated K14497 c21743_g1 523 3.7185 7.74E-07 Protein phosphatase 2C Up-regulated K14497 c57241_g1 1773 1.714 5.80E-08 Protein phosphatase 2C Up-regulated K14497 c57287_g1 977 4.1958 1.79E-12 Protein phosphatase 2C Up-regulated K14497 c52897_g1 1506 2.3176 7.93E-35 Protein phosphatase 2C Up-regulated K14497 c53505_g1 1654 1.2372 2.12E-17 Protein phosphatase 2C Up-regulated
Considering the EC of annotated sequences the enzymes associated with tyrosine metabolism were observed in response to disease infection. The pathways identified from KEGG incorporated all enzymes and metabolite, however, Tyr pathway was well characterized (Fig 6). Generally, six enzymes related with Tyr metabolism in plants are reported including Tyr aminotransferase (TAT, EC: 2.6.1.5), aspartate aminotransferase (AAT, EC: 2.6.1.1), 4-hydroxy-phenypyruvate dioxygenase (HPPD, EC: 1.13.11.27), homogentisate dioxygenase (HGD, EC: 1.13.115), fumeryl acetoacetate hydroxylase (FAH, EC: 3.7.1.2) and polyphenol oxidase (PPO, EC: 1.10.3.1).
Graph: Fig 6 Schematic diagram of key genes and metabolites of tyrosine metabolism pathway in gerbera; Colored boxes represent the DEGs in this KEGG pathway.Red color represents the up-regulation of DEGs; Green color represents the down-regulation of DEGs.
Tyrosine aminotransferase and aspartate aminotransferase catalyze the conversion of Tyr into 4-hydroxyphenylpyruvate (4-OH-PhPyr). TAT and AAT genes were up-regulated with a log2fold change value of 3.20 and 2.20, respectively. 4-hydroxyphenylpyruvate then changed into homogentisate by enzyme HPPD (EC: 1.13.11.27). The gene annotated as HPPD was up-regulated with a log2fold change value of 1.40. Homogentisate acts as a center of the pathway, homogentisate is converted to 4-maleylacetoacetate by enzyme HGD (EC: 1.13.115) that is further converted to 4-fumarylacetoacetase by maleyl acetoacetate isomerase. HGD gene was up-regulated with a log2fold change of 1.50, and then 4-fumarylacetoacetate is hydrolyzed into two compounds acetoacetate and fumarate by enzyme FAH (EC: 3.7.1.2). These two compounds are the main product of amino acid metabolism. FAH gene was up-regulated with a log2fold change value of 1.40. Two PPO genes were down-regulated with log2fold change value of -8.00, -4.80 and q-value of 1.39e
The five important enzymes in phenylpropanoid biosynthesis are phenylalanine ammonia-lyase (PAL, EC: 4.3.1.24), Beta-glucosidase (EC: 3.2.1.21), caffeic acid-3-methyl transferase (EC: 2.1.1.68), peroxidase (EC: 1.11.1.7) and caffeoylshikimate esterase (CSE, EC: 3.1.1). Phenylpropanoid pathway produces the compounds such as lignin and phytoalexins. PAL catalyzes the transformation of phenylalanine into cinnamic acid. In this pathway PAL, C4H and 4CL are indispensable enzymes, playing an important role in biosynthesis and affect the accumulation of phenylpropanoids in plants. PAL gene was up-regulated with a log2fold change value of 1.50 and another gene was down-regulated with a log2fold change value of 2.02. DEGs annotated as Beta-glucosidase and caffeoyl-o-shikimate and peroxidase were up-regulated with log2fold change values of 1.70, 1.40 and 1.70, respectively. Caffeic acid-3-methyl transferase was down-regulated with a log2fold change value of -5.70. Similarly, three peroxidase genes were also down-regulated with log2fold change values of -4.90, -3.50 and -3.50, respectively in response to rootrot disease infection.
Flavonoid biosynthesis includes iso-flavonoid biosynthesis, anthocyanin biosynthesis, and flavone and flavonol biosynthesis. Flavonoids are generated from phenylpropanoid pathway that converts phenylalanine into 4-coumaroyl-CoA which is primary branch point in phenylpropanoid pathway. Either it is utilized in flavonoids biosynthesis (CHS catalyze the flavonoid skeleton and leads to the synthesis of flavonol, cyaniding, and anthocyanin) or produces methoxylated guaiacy (G), syringyl (S) monolignols and lignins. The first enzyme for this pathway is chalcone synthase (CHS, EC: 2.3.1.74) that makes chalcone scaffolds and all flavonoids are derived from it. In flavonoid biosynthesis, one DEG annotated as chalcone synthase was down-regulated with a log2fold change value of 2.00, in response to disease infection (Fig 7). The genes in both pathways have very low (or zero) E-value. Genes in these pathways, their description and their expression are shown in Table 4.
Graph: Fig 7 Schematic diagram of key genes and metabolites of phenylpropanoid biosynthesis & flavonoid biosynthesis pathway; Colored boxes represent the DEGs in KEGG pathways.Red color represents the up-regulation of DEGs; Green color represents the down-regulation of DEGs; Yellow color represents the up-and down regulation of DEGs.
Plants produce a lot of hormones such as auxins, cytokinins (CK), gibberellins, abscisic acid (ABA), ethylene (ET), salicylic acid (SA), jasmonate (JA), and brassinosteriodes (BR). The five key regulatory enzymes in this pathway were ABF (c56396_g2); IAA (c67578_g1); MYC2 (c50421_g1); JAR1 (c52417_g1); PP2C (c1401_g2, c21743_g1, c57241_g1, c57287_g1, c52897_g1, c53505_g1) (Fig 8). Gerbera transcriptome data contains multiple contigs encoding these enzymes. These genes are involved in senescence, the stress responses in gerbera plant is related to jasmonic acid and α-linolenic acid metabolism. DEGs in plant hormone signal transduction pathway annotated as JAR1, MYC2, and IAA were down-regulated with log2fold change values of -1.60, -2.00 and -2.90, respectively. Six DEGs, annotated as PP2Cs, were up-regulated with log2fold change value of 3.00, 3.70, 1.70, 4.20, 2.30 and 1.00 in response to root rot disease (Table 4).
Graph: Fig 8 Schematic diagram of key genes and metabolites of plant hormones and signal transduction pathway in gerbera upon root-rot infection.Colored boxes represent the DEGs in KEGG pathway. Red color repreents up-regulation of DEGs; Green color representsdown-regulation of DEGs.
To indorse the RNA-Seq expression profiles of gerbera DEGs obtained by RNA-Seq, the expression pattern of six identified responsive genes was estimated by qRT-PCR utilizing gene-specific primers. The expression comparisons were performed between healthy (leaf, petiole and root) plant samples and phytophothora cryptogea inoculated (leaf, petiole and root) plant samples after two, four and six days of inoculation. The results showed that the genes were significantly affected by disease infection by different days after pathogen inoculation compared with control. We compared the expression of genes from tyrosine metabolism pathway that are GhTAT, GhAAT, GhHPPD, GhHGD, GhFAH and GhPPO after 2, 4 and 6 days of inoculation with phytophothora cryptogea in leaf, petiole and root tissues. GhTAT, GhAAT, GhHPPD, GhHGD, and GhFAH gene expression was relatively higher after 6 dpi in leaf tissues. The expression was highly significant (p < 0.01) in all genes compared with control. GhHPPD, GhHGD and GhFAH gene expression were higher at 6 dpi in the leaf and petiole tissues. In petiole tissues, GhHPPD, GhHGD, and GhFAH showed higher relative expression after six dpi. The expression of GhHPPD, and GhFAH was highly significant (p < 0.01) at 6 dpi compared with control. While GhTAT and GhAAT gene expression were highly significant at 4 dpi and 2 dpi, respectively. We observed that for most of the genes the expression was increased with the time of infection. In root tissues, GhTAT, GhAAT, GhHPPD, GhHGD and GhFAH gene expression was high after 2 dpi. GhPPO gene expression was high at 2 dpi in (leaf, petiole and root) tissues and continuously decreased later on. The qRT-PCR expression summaries of these six gerbera genes was similar with RNA-seq information. Overall, the enrichment in expression level and defense reaction revealed by RNA-Seq results in response to be pathogenic contamination were similar with qRT-PCR, affirming the consistency of sequencing data and our results (Fig 9).
Graph: Fig 9 Expression analysis of various genes in tyrosine metabolism pathway in combination of root-rot pathogen inoculation and without inoculation in leaf, petiole and root tissues of gerbera plant.Control (C) untreated; two, four, six days of post-inoculation of the pathogen in leaf, petiole and root tissues in GhTAT, GhAAT, GhHPPD, GhHGD, GhFAH and GhPPO genes. Relative expression was investigated using the mean of CT values that were standardized to the mean CT estimation of the housekeeping gene 18S. The expression standards were determined using equation 2-ΔΔct. Data are presented as Mean ± SD of autonomous biological replicates (n = 3 biological replicates) (LSD test p < 0.05). Asterisks show substantial changes between non-pathogenic and pathogen-inoculated means within the identical time of specimen, as per one-way ANOVA (** represents significant variance at p < 0.01 and * represents significant variance at p < 0.05).
In order to improve the understanding of transcriptomic responses of healthy and diseased gerbera plants to Phytophothora cryptogea, we performed RNA-Seq investigation to look at the genome-wide expression pattern of gerbera plants with pathogenic and non-pathogenic separates. Our study provides the first prominent evidence regarding the gene expression pattern when gerbera plants are infected with Phytophothora cryptogea (root rot causing agent).
In this investigation, we established transcriptome response (leaf and root tissues) of Gerbera hybrida cv. Daxueju for healthy and diseased plants. A total of about 114 million reads were generated from healthy (59 million) and diseased (55 million) plant samples respectively, constituting approximately 8.55 Gb and 8 Gb of cDNA sequence data. After de novo association, we produced 141,972 transcripts, with an average size of 727 bp and N50 length of 1,274. The highest numbers of homologs were found for Vitis vinifera (grapevine). Remarkably, the grapevine is a alos known to produce high amount of secondary metabolites and its association with p. cryptogea. Numerous studies have been performed on this crop-pathogen from different perspectives [[
Plant metabolism and pathogen contamination are firmly interconnected. Pathogens require nourishment from the host for colonization and in this manner accessibility of nutrition can be influenced by plant metabolism [[
It is considered that some natural secondary metabolites play an important role in plant defense mechanism [[
In plants, biotic and abiotic stresses lead to the production of reactive oxygen species (ROS). Fortunately, plants possess different enzymatic and non-enzymatic oxidative defense system that helps protect plants by scavenging ROS. Tyr is an aromatic amino acid that is a prerequisite for protein synthesis in almost all organisms particularly plants and microorganisms. It is the originator of several secondary metabolites such as alkaloids, phenylquinones, cyanogenic glycosides and other amino acids such as methionine that have different physiological roles as antioxidants, attractants, electron carriers, and defense compounds [[
Graph: Fig 10 Biosynthesis and metabolism of tyrosine in plants.Shikimate pathway gives the originator for Tyr as well as other AAA; trp and phe. Tyr can be assimilated into a protein that catabolized into TCA cycle; metabolized into vitamin E and plastoquinone; or various plant natural products. Synthesis of tyrosine shown by black arrows. Genes are shown in red color; regulation of genes in tyrosine metabolism are shown with red arrows. Abbreviations Trp, tryptophan; Phe, phenylalanine; Tyr, tyrosine; HPP, hydroxyphenylpyruvate; HGA, Homogentisate; TAT, tyrosine aminotransferase; AAT, aspartate aminotransferase; HPPD hydroxyphenylpyruvate dioxygenase; HGD, homogentisate dioxygenase; FAH, fumaryl acetoacetate hydroxylase; PPO, polyphenol oxidase.
The activity of Tyr-AT has been identified in many plant species comprising Psium sativum and Anchusa officinalis. Genes encoding Tyr-AT enzymes have been identified recognized for numerous plants [[
Aspartate aminotransferase is involved in plant carbon and nitrogen dissemination that catalyzes the reversible response of transmembrane among aspartate and 2-oxoglutarate to yield oxaloacetate and glutamate. AAT's contain additional prephanate dehydratase/prephenate dehydrogenase domains in N-ends that are exceptional to oomycetes. AAT gene is engaged with pathogen pathogenicity and nitrogen utilization during contamination. Asparagine levels were associated with early defense responses. However, alteration of aspartate to asparagine can modulate plant defense [[
Gene expression analysis revealed that the aspartate aminotransferase encoding genes were differentially expressed when exposed to biotic stress such as infection with Phytophthora infestans, Botrytis cinerea, Pseudomonas syringae and abiotic strains [[
4-hydroxyphenylpyruvate dioxygenase and homogentisate are involved in biosynthetic pathway of tocopherol in plants that leads to the production of plastoquinone and vitamin E. In plants, the product of HPPD response is a key forerunner for biosynthesis of photosynthetic pigments such as plastoquinones and vitamin E (tocotrienol and tocopherols products) [[
Fumaryl acetoacetate hydrolase (FAH) hydrolyzes fumaryl acetoacetate to fumarate and acetoacetate that is the last step in tyrosine degradation pathway and is necessary in animals and plants metabolism [[
Polyphenol oxidase is an oxidoreductase that catalyzes the oxidation of moniphenols, it assumes a crucial role in the biosynthesis of secondary metabolites such as aurones and betalins. PPO has a precise role in plant protection against insects and pathogens. It performs different functions in plants. In transgenic tomato plants, PPO overexpression greatly increases resistance to Peudomonas syringae [[
PPO is a significant supporter in plant fundamental resistance against pathogens that contributes to catalyzing phenolic oxidation to restrict disease movement. Subsequently it can be associated with systemic resistance stimulation against plant infection [[
The expression of GhTAT, GhAAT, GhHPPD, GhFAH in root was different. The expression was high at an early stage and decreased at later stages that is similar with a previous study in which root expression of defense-related genes was observed in wheat in response to F. culmorum infection. The F. culmorum infection was greater at 24 hpi but somewhat low at 48 and 96 hpi [[
The Gerbera hybrida cv. Daxueju seedlings grown in Sanming Modern Agriculture Sci-tech Demonstration Garden, Sanming, Fujian was utilized as plant material for transcriptome analyses. In this study, the samples of healthy and root-rot infected plants were harvested for transcriptome analyses. Leaves and roots of healthy and diseased plants were collected in three biological replicates. Samples were prepared as healthy gerbera plantlets and diseased gerbera plantlets and Illumina sequencing were performed for both samples.
The Gerbera hybrida cv. Daxueju seedlings grown in Sanming Modern Agriculture Sci-tech Demonstration Garden, Sanming, Fujian were used for cDNA sequencing. Healthy and root rot diseased plant samples were gathered. The leaves and roots of healthy and infected plants were taken and temporarily stored at -80°C prior to RNA-Seq analysis (Fig 11). Frozen tissues were crushed in liquid nitrogen with mortar and pestle. Total RNA of the samples was extracted using Trizol reagent and afterward purified with the RNA cleanup procedure according to manufacturer's instruction. Total RNA of the leaves and roots (three replicates) was mixed in equivalent quantities. RNA quality and quantity were determined using a Nanodrop 2000 and checked by RNase free agarose gel electrophoresis. Additionally, the total RNA of the samples were evaluated for quality using an Alignment 2100 Bioanalyzer TM. RNA-Seq libraries were prepared by Illumina HiSeq technology.
Graph: Fig 11 (a) Healthy and (b) root-rot diseased gerbera plant.
The cDNA libraries of both samples (healthy and root-rot diseased plant) were sequenced by 2×100 bp paired-end sequencing on an Illumine HiSeq platform according to manufactures instructions. The primary base setup and quality separation of the image statistics were refined by means of default parameters in the Illumine data processing pipeline. The adaptors, any anonymous nucleotides greater than 10% and low quality reads containing more than 50% bases with Q-values ≤ 20 were executed after sequencing. Processed reads with an identity of 95% and coverage length of 200 bp were accumulated using Trinity software [[
The unigenes were submitted to protein databases for annotation and homolog correlation by BLASTX algorithm (e-value ≤1e-5) comprising Nr, Nt, Swiss-prot, GO and KEGG database. The Blast2GO v 2.5 [[
The GO enhancement investigation of differentially expressed genes was prepared by GOseq R package, in which the gene length was balanced. GO terms with adjusted p-value < 0.05 were considered differentially expressed genes. KEGG is a database for understanding high-level utilities and elements of the biological system such as cell, organism, and ecosystem from molecular dimension data, mainly large-scale datasets are produced by genome sequencing and other high-throughput experimental technologies. We used KOBAS software for the statistical improvement of differentially expressed genes in KEGG pathways.
To achieve information with respect to metabolism and signal transduction of phyto-hormones, the transcripts that are involved in these pathways were generally filtered by relating annotation of KEGG and KO ID in KEGG maps. Though, the annotations of a solitary transcript from Nr, Swiss-Prot and KEGG databases were not constantly dependable with another. Hence, additional stringent screening conditions were set up to guarantee that the annotation were consistent in at least two distinct databases. A few sequences with uncertain annotation were established online by Nr association using BLASTX. To compare the homologs with the other species in the Asteraceae, we executed screening parameters as E-value ≤ -5 using local BLASTX.
As the transcriptome was the pooled information with the various libraries, qRT-PCR was performed to identify the expression of particular genes at particular stages. This was accomplished for certain gerbera genes that were up and down-regulated in healthy and diseased samples. Gerbera plants were grown in growth chamber in Fujian Agriculture and Forestry University, in full-strength Murashige and Skoog solution. The plants were inoculated with Phytophothora cryptogea a root-rot pathogen. Leaf, petiole and root samples of healthy plant and diseased plants were collected. After the pathogen inoculation, leaf, petiole and root samples were collected after two days, four days and six days of infection. These healthy and diseased (leaf, petiole, and root) samples were used for qRT-PCR analyses. Total RNA of three biological replicates of root, petiole, and leaf samples from control plants and Phytophothora cryptogea infected plants were extracted using the same method as mentioned before. A 2-μg sample of entire RNA after DNase action was used for cDNA synthesis by using cDNA synthesis kit. The relative quantitative study was accomplished under the following conditions: 95°C for 30 s and 40 cycles at 95°C 30 s, 60°C 25 s. A melting curve analysis extending from 60 to 95°C was used to distinguish different amplicons. Three specialized replicates inside each biological replicate were used for individually tested sample and template free negative controls. The candidate genes with length more than 500 bp were primarily screened for designing primers. The gene specific primer sets in the particular sequences were designed using DNAMAN 6.0 software (S4 Table). The 18S was used as housekeeping gene for standardization. Three biological replicates were analyzed for each gene. The average threshold cycle (Ct) was calculated and relative gene expression was determined using the 2
RNA-Seq analysis uncovered the genes and network involved in gerbera disease resistance. We analyzed the expression summaries of Gerbera hybrida inoculated with root rot pathogenic/non-pathogenic fungal isolates. A noticeable differential responsive expression pattern in host-pathogen combination was observed. Progressively, active, and drastic responses were observed in response to root-rot pathogen infection. These responses include a stronger activation of several well-known defense related genes and genes involved in Tyr metabolism, plant hormone signal transduction and catalytic activity. GO and KEGG pathway analysis identified various molecular mechanisms that intricate in disease resistance and corresponding infection related pathways. This information is valuable for further genomic studies in Asteraceae and this can be utilized as a reference for other closely related species having ornamental importance. The outcomes of this research are useful to understand the molecular basis of gerbera root rot associations and new resistance mechanisms in gerbera against Phytophothora cryptogea.
S1 Fig. Length distribution of transcript and unigenes in gerbera.
(TIF)
S2 Fig. GO classification of 294521 unigenes in gerbera.
(TIF)
S3 Fig. KOG classification of 15528 unigenes in gerbera.
(TIF)
S4 Fig. KEGG classification of 14335 unigenes in gerbera.
(TIF)
S5 Fig. Most enriched up and down regulated DEGs in Dis vs Ck in gerbera.
(TIF)
S1 Table. Annotation summary of unigenes in gerbera.
(XLSX)
S2 Table. Up and down regulated DEGs related to healthy and root-rot disease gerbera plant.
(XLSX)
S3 Table. Top 17 KEGG pathways of DEGs in healthy and diseased gerbera plant.
(XLSX)
S4 Table. List of primers used in this research.
(XLSX)
By Nigarish Munir; Chunzhen Cheng; Chaoshui Xia; Xuming Xu; Muhammad Azher Nawaz; Junaid Iftikhar; Yukun Chen; Yuling Lin and Zhongxiong Lai
Reported by Author; Author; Author; Author; Author; Author; Author; Author; Author