Chakraborty et al. AMB Expr (2016) 6:12
DOI 10.1186/s13568-016-0182-3
Deep RNA-Seq prole revealsbiodiversity, plantmicrobe interactions anda large family ofNBS-LRR resistance genes inwalnut (Juglans regia) tissues
Sandeep Chakraborty1, Monica Britton2, P. J. MartnezGarca1 and Abhaya M. Dandekar1*
Introduction
Rapid detection of pathogens in plants is becoming increasingly necessary to prevent loss of productivity and quality (Dandekar etal. 2010; Fletcher etal. 2006). The wide variety of diseases and pathogens necessitates a broad detection system (Asiatic citrus canker: Xanthomonas axonopodis, sudden oak death: Phytophthora
ramorum, Pierces disease of grapevine: Xylella fastidiosa, etc.). Traditionally, real-time PCR has been used extensively for plant disease diagnostics (Schaad and Frederick 2002). However, these diagnostic tools are biased, and can only detect pathogens with a known nucleic acid template. RNA-Seq, a high-throughput DNA sequencing method, has revolutionized the eld of gene discovery (Wang et al. 2009; Flintoft 2008). RNA-Seq can detect transcripts with very low expression levels, in contrast to other traditional methods like RNA:DNA hybridization (Clark et al. 2002) and short sequence-based approaches (Kodzius et al. 2006). The
*Correspondence: [email protected]
1 Plant Sciences Department, University of California, Davis, CA 95616, USAFull list of author information is available at the end of the article
2016 Chakraborty et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/
Web End =http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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RNA-Seq derived transcriptome with a selection protocol for polyadenylated mRNA from an organism with known genome enables detection of mRNA from extraneous eukaryotes like fungi and pests. Certain RNASeq protocols ensure that only polyadenylated mRNA is being analyzed, yet some bacterial mRNA does leak through in the analysis. Thus, this presents an unbiased method of diagnosing the presence of wide range of prokaryotic and eukaryotic organisms (Moretti etal. 2007; Janse 2010). Such a study can also guide downstream PCR diagnostics to determine the exact species/ strain of a pathogen. We have recently used a RNA-Seq methodology to derive the transcriptome of walnut (Juglans regia) from twenty dierent tissues types with selection for polyadenylated mRNA in the course of obtaining the walnut genome sequence (WGS) (manuscript submitted). Firstly, we excluded transcripts that aligned to WGS and the E. coli genome. Expression counts enabled the determination of the localization, although the residual nature of the transcripts being analyzed did not provide sufficient information to identify the exact species/ strain. Thus, inferences made were constrained to the genus. These counts were not normalized, since there were no comparisons of absolute or relative expression levels. Some non-polyadenylated bacterial mRNA leaked through the RNA-Seq analysis. We detected several well-known pathogens, fungi, endophytic bacteria, and pests. The detection of these pathogenic agents in an otherwise healthy plant can be ascribed to the presence and activity of resistance (R) genes that specically recognize pathogens, which contain complementary avirulence genes (Staskawicz 2001).
The oomycete Phytophthora, a pathogen responsible for destructive diseases in a wide variety of crop plants, was found localized in the root (Fletcher et al. 2006; Belisario et al. 2012; Nowicki et al. 2012). Although sequence homology indicated the presence of several species of Phytophthora (nicotianae, infestans, parasitica), the similarity among these strains did not allow for an exact enumeration of the individual species. For example, a glyceraldehyde-3-phosphate dehydrogenase with 97% identity to a GAPDH from P. parasitica and P. infestans is an enzyme detected from this pathogen. Cryptococcosis in human and animals is caused by Cryptococcus neoformans and C. gattii, which has been exacerbated in recent times in immuno-compromised individuals (Mitchell and Perfect 1995). The plant surface is a conducive environment for the sexual cycle of Cryptococcus (Xue et al. 2007). Here, we detect prolyl-isomerases and ADP/ATP translocases from Cryptococcus present in catkins and in vegetative buds, corroborating these ndings. Endophytic Actino-bacteria are present extensively in the inner tissues of
living plants, and are a source of important secondary metabolites related to the defense response, growth and environmental stress (Ventura etal. 2007). Based on the top BLAST score, we detected several species in the Actinobacteria phyla spread out across all tissues. Methylibium petroleiphilum, which is capable of using methyl tert-butyl ether as a sole source of carbon, was also found in the root (Nakatsu etal. 2006). The ribosomal L37 protein from the pest pea aphid was found in the leaves and vegetative buds. Interestingly, a serine pro-tease from the mosquito (Kelleher and Markow 2009) with signicant homology to a female reproductive tract protease from Drosophila mojavensis (Isoe etal. 2009) in the vegetative bud suggested egg-laying activities by these pests.
Materials andmethods
RNASeq
Fifteen samples of walnut tissue (Table 1) were gathered from Chandler trees in the UC Davis eld facilities located in Davis, California. Three additional samples were taken from Chandler plant material maintained in tissue culture. The root sample was taken from potted Chandler trees in the greenhouse/lath house. Several grams of leaf and root tissue from each plant were frozen in liquid nitrogen immediately after harvest and then transferred to a 80 C freezer. RNA was isolated from each sample using the hot borate method (Wilkins and Smart 1996) followed by purication and DNAse treatment using an RNA/DNA Mini Kit (Qiagen, Valencia, CA) per the manufacturers protocol. High quality RNA was conrmed by running an aliquot of each sample on an Experion Automated Electrophoresis System (Bio-Rad Laboratories, Hercules, CA). The cDNA libraries were constructed following the Illumina mRNA-sequencing sample preparation protocol (Illumina Inc., San Diego, CA). Final elution was performed with 16L RNase-free water. The quality of each library was determined using a BioRad Experion (BioRad, Hercules, CA). Each library was run as an independent lane on a Genome Analyzer II (Illumina, San Diego, CA) to generate paired-end sequences of 85bp in length from each cDNA library. In total, over a billion reads were obtained. Prior to assembly, all reads underwent quality control for paired-end reads and trimming using Sickle (Joshi and Fass 2011). The minimum read length was 45bp with a minimum Sanger quality score of 35. The quality controlled reads were de novo assembled with Trinity v2.0.6 (Grabherr et al. 2011). Standard parameters were used and the minimum contig length was 300bp. Individual assemblies for each library and a combined assembly of all tissues were performed (Chakraborty etal. 2015).
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Table 1 Walnut tissue sources used forRNAseq analysis
Code Tissue source Sequence read archive
Source No ofreads x106
VB Vegetative bud SRS523592 Chandler Vegetative Orchard 39.9 LY Leafyoung SRS523594 Chandler Vegetative Orchard 63.3 RT Root SRS523799 Chandler Vegetative Greenhouse 38.8 CI Callus interior SRS523805 Chandler Vegetative In Vitro 59.3 CE Callus exterior SRS523808 Chandler Vegetative In Vitro 29.8 FL Pistillate ower SRS523810 Chandler Vegetative Orchard 69.8 CK Catkins SRS523917 Chandler Immature Orchard 56.4 SE Somatic embryo SRS523919 Chandler Immature In Vitro 27.8 LM Leafmature SRS523921 Chandler Vegetative Orchard 50.4 LE Leaves SRS523922 Chandler Vegetative Orchard 60.1 IF Fruit immature SRS523923 Mixed Immature Orchard 57.0 HL Hull immature SRS523924 Chandler Immature Orchard 115.8 PT Packing tissue SRS523925 Chandler Immature Orchard 62.8 HP Hull peel SRS523926 Chandler Mature Orchard 43.3 HC Hull cortex SRS523927 Chandler Mature Orchard 62.8 PK Packing tissue SRS523928 Chandler Mature Orchard 56.7 PL Pellicle SRS523929 Chandler Mature Orchard 42.7 EM Embryo SRS523930 Mixed Mature Orchard 35.5 HU Hulldehiscing SRS523931 Chandler Senescent Orchard 59.5 TZ Transition wood SRS523933 J.nigra Transition zone Orchard 48.4
Total number of reads: 1080.0
Walnut genotype
Developmental stage
In silico analysis
The NCBI database (http://www.ncbi.nlm.nih.gov/taxonomy
Web End =http://www.ncbi.nlm.nih.gov/ http://www.ncbi.nlm.nih.gov/taxonomy
Web End =taxonomy ) provides several resources for the curated classication and nomenclature of all of organisms in the public sequence databases. This currently represents about 10% of the described species of life on the planet. There were ~111k transcripts. ~5k did not align to the walnut genome, and were removed (Chakraborty et al. 2015). Of these, ~4 k transcripts had signicant homology to E. coli genomes. The remaining ~1k transcripts were the subject of analysis in the current manuscript, under the assumption that they were derived from extraneous organisms, pathogens or commensal, inhabiting the twenty dierent tissues. The species names were derived from the best BLAST match to the nt database. A bitscore (BLASTSCORE) cuto of 150 was used (~E-value=1E33). The numerical identier was obtained from the species name using the site http://www.ncbi.nlm.nih.gov/Taxonomy/TaxIdentifier/tax
Web End =http://www.ncbi.nlm.nih.gov/Taxonomy/TaxIdentier/ http://www.ncbi.nlm.nih.gov/Taxonomy/TaxIdentifier/tax
Web End =tax identier.cgi. For example, Arthrobacter has the tax ID 1663. These numerical IDs were then used to obtain the complete lineage. The rst classication of all organisms was into Eukaryota or Bacteria. We used the second classication eld to cluster the organisms discussed here. The expression counts are not normalized since we
do not make any inferences on the absolute or relative abundance of the transcripts.
The iterative gene nding method described in YeATS (Chakraborty etal. 2015) was used to identify the homologous set of nucleotide-binding site (NBS)-leucine-rich repeat (LRR) class of genes. A BLAST bitscore of 100 (E value~1E20), with an increment of 20 for each iteration, was used as the homology threshold. The increment in each of the iterations ensures that the resultant proteins do not diverge far from the initially chosen protein. We have used 600 as a lower threshold for the length of NBS-LRR proteins. Additionally, we exclude transcripts with % of leucine less than the 10% frequency of leucine residues seen in plant proteomes. These transcripts are probably fragments which have not been assembled by Trinity (Chakraborty etal. 2015).
Results
As a result of the analysis of ~1 k transcripts obtained from 20 dierent tissues of walnut, dierent extraneous organisms, pathogens or commensal, were detected (Fig. 1). Several transcripts (N = 260) were associated with Phytophthora, mostly localized in the root (Fig.2a). A sample of transcripts, and the putative proteins they encode, identied C43181_G1_I1 encoding
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a 293 nt long ORF with a predicted protein (molecular weight=30kDa) homologous to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Tables 2, 3a). This
GAPDH has 97% identity to a GAPDH from P. parasitica and P. infestans, and a 96% identity to the GAPDH from P. sojae (Fig.3a). The 3D structure of PhyGAPDH1 was modeled using SWISSMODEL (Arnold etal. 2006). The structural superimposition of the PhyGAPDH1 to the structure of the human placental GAPDH (PDBid:1U8F, chain O) reveals the structural conservation of this gene across dierent species (Fig.3b). In this study, the presence of Cryptococcus was also conrmed in the catkins and the vegetative buds (Table3b). We identied a cyclophilin A (peptidyl-prolyl cistrans isomerase) (Table4a) associated with Cryptococcus. In addition, we detected several transcripts associated with the endophytic Actinobacteria (EndAct) in several tissues of walnut (Fig.2b, Table 5). Most putative proteins from these transcripts have signicant homologs in the BLASTnr database, although most of them are uncharacterized. Other interesting results are the presence of Methylibium petroleiphilum in the roots (3442 cumulative counts, Fig.2c), Acyrthosiphon pisum (or the pea aphid) with 1256 cumulative counts in the leaves (Fig.2d) and Aedes aegypti (yellow fewer mosquito) in the vegetative bud of walnut, with a total of 428 cumulative counts of transcripts (Fig.2e).
Discussion
High-throughput mRNA sequencing (RNA-Seq) has revolutionized the view of the prole of the transcriptome, enhancing gene discovery. Although some
protocols are designed to view exclusively polyadenylated eukaryotic mRNA, prokaryotic mRNA can be surreptitiously included in the analysis, especially highly abundant transcripts like ribosomal proteins. This presents an opportunity to identify extraneous transcripts residing in various tissues, provided the genome of the organism is known. Expression counts are low due to the residual nature of the analysis. Yet, as we observed for pea aphid, very low counts were able to accurately identify the L37 ribosomal protein, which shares 88% identity with the L37 protein from Drosophila Melanogaster (Anger etal. 2013).
Phytophthora: causal agent ofpotato blight
The oomycete Phytophthora is a pathogen responsible for destructive diseases in a wide variety of crop plants, including tomato, potato (Nowicki etal. 2012) and walnut (Belisario etal. 2012) (Fig.1). Although the presence of a pathogen from the Phytophthora genus is almost certain, it is not possible to determine the exact strain of this pathogen. GAPDH is involved in gycolysis, and other non-metabolic processes (Tarze et al. 2007), and is a well-known housekeeping gene (Eisenberg and Lev-anon 2013). The Phytophthora GAPDH also shares a 70% identity with the GAPDH in human placenta (Jenkins and Tanner 2006).
Fungi
Cryptococcus: Causal agent ofcryptococcosis inhuman
These fungi are mostly localized in the catkins and the vegetative bud in walnut, corroborating previous results about their sexual cycle (Xue etal. 2007). Cryptococcosis is a disease of the respiratory system in human and animals, caused by Cryptococcus neoformans and C. gattii, and exacerbated in patients infected with the AIDS virus (Mitchell and Perfect 1995). Plants are known to host a large number of commensal fungi (Schmit and Mueller 2007). An interesting ecological experiment demonstrated that the plant surface is a conducive environment, stimulating the sexual cycle of Cryptococcus (Xue et al. 2007). Myo-inositol and the plant growth hormone IAA synergistically were proved as strong aphrodisiacs (Xue etal. 2007). Two homologous cyclophilin A genes (KGB74193 and KGB74187) have been shown to inuence cell growth, mating and virulence (Wang etal. 2001). A peptidyl-prolyl cistrans isomerase from Cryptococcus (Ess1), non-homologous to the above two genes, is required only for virulence (Ren et al. 2005). Another pathogenic fungus, Pyrenophora (teres/triticirepentis), and the causal agent of the disease tan spot (Liu etal. 2011) have been identied in several tissues (Tables3c, 4b).
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Table 2 Proteins fromPhytophthora
Transcript Description Evalue
C43181_G1_I1 XM_ 008893048.1 P. parasitica INRA310 glyceraldehyde3phosphate dehydrogenase 0 C30378_G1_I1 XM_ 008895058.1 P. parasitica INRA310 guanine nucleotidebinding protein 0 C7548_G1_I1 DQ057354.1 P. nicotianae manganese superoxide dismutase (MnSOD1a) 0 C26754_G1_I1 FJ493002.1 P. cinnamomi clone PC02 Ric1 protein mRNA, complete 1.00E 78
C49955_G2_I1 XM_ 002997461.1 P. infestans T304 1433 protein epsilon (PITG 19017) 0 C62634_G1_I1 XM_ 002903199.1 P. infestans T304 transcription factor BTF3like protein 0
Transcripts from the pathogenic oomycete Phytophthora with ORFs that have signicant matches in the BLAST nr database. There are several strains of P. (nicotianae, cinnamomi, infestans) that have the best matches to these transcripts. It is difficult to ascertain the exact species from these transcripts since some of these proteins have high conservation across many species
Actinobacteria: nitrogen xing bacterial diazotrophs
Bacterial mRNA is non-polyadenylated, and most should be excluded by the RNA-Seq library preparation method, but some mRNA invariably leaks through. EndAct are
present extensively in the inner tissues of living plants, and are a source of important secondary metabolites related to the defense response, growth and environmental stress (Qin et al. 2011; Palaniyandi et al. 2013). The
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Table 3 Expression counts ofselected transcripts
Transcript CE CI CK EM FL HC HL HP HU IF LE LM LY PK PL PT RT SE TZ VB
a
C30378 _G1_I1 104C7548 _G1_I1 497 2 C26754 _G1_I1 28C43181 _G1_I1 326C49955_G2_I1 1 2 1 1 3 2 1 2 1 4 185C62634 _G1_I1 123C442 G2 I1 24 C03 _G1_I1 2 8 C28542 _G1_I1 18 2 14 bC9244 _G1_I1 8 C87 _G1_I1 2 3C61284 _G1_I1 12 14 C498 _G1_I1 2 12 C6553 _G1_I1 8 C35196 _G1_I1 2 2 14 2 10 C50331 G1 I4 2 1 2 11 1 2 37 C34393 _G1_I1 4 1 4 1 16 3 9 4 2 2 45 12 68 4 2 21 1 2 15 cC50331_G1_I5 2 13 14 8 2 2 26 C58663 _G1_I1 2 2 10 C29801 _G1_I1 4 2 16 C30295 _G1_I1 8 29 C16207 _G1_I1 54 C50331 G1 I2 2 1 4 3 2 2 14
These are raw counts, and are not normalized
a Phytophthora is the pathogen responsible for potato blight, which caused the Great Irish Famine (18451849). C30378_G1_I1 encodes a glyceraldehyde 3-phosphate dehydrogenase, an enzyme involved in glycolysis. Most transcripts from this oomycete are found localized in the root (Fig.2a). b Cryptococcus is the causal agent of cryptococcosis, aecting immuno-compromised individuals. These fungi are mostly localized in the catkins and the vegetative buds. It was previously shown that the plant surface provides a conducive environment for the sexual cycle of these pathogens. c Pyrenophora: These fungi, responsible for the `tan spot disease in barley, are spread out throughout dierent tissues. d Acyrthosiphon: The pea aphid pest. C58762_G1_I1 encodes a 91 long ORF that has a 99% identity match to the ribosomal protein L37 (Accession:NP 001129424.1). The low counts of this transcript are testimony to the ability of the RNAseq technology to accurately determine the sequence and localization of transcripts
signicant homology of the putative proteins from these transcripts after BLAST results highlights the ability of the current methodology to detect a genus with fair precision. A clear example is the transcript C54818_G4_I1 that encodes a 68bp long ORF, and matches to a MULTISPECIES: hypothetical protein from Streptomyces with 82% identity. The nitrogen xing diazotroph, Paenibacillus polymyxa P2b-2R, was found to enhance the growth of the important oilseed crop canola (Puri etal. 2016). EndAct obtained from healthy wheat tissue was shown to prime the systemic acquired resistance (SAR) and the jasmonate/ethylene (JA/ET) pathways in Arabidopsis thaliana JA/ET pathways when infected with bacterial pathogen Erwinia carotovora subsp. carotovora or the fungal pathogen Fusarium oxysporum, respectively (Conn etal. 2008). The importance of EndAct in biodiversity was established in a tropical rainforest native
plant, which identied a total of 312 Actinobacteria associated with the order Actinomycetales (Qin etal. 2012). Recently, the genome sequence of Arthrobacter koreensis 5J12A, a desiccation-tolerant strain, was obtained (Manzanera et al. 2015). Teicoplanin, an antibiotic working against Gram positive bacteria like methicillin-resistant Staphylococcus aureus and Enterococcus faecalis, was obtained from the fermentation broth of a strain of Actinoplanes teichomyceticus (Jung etal. 2008). Another EndAct (Streptomyces) was shown to produce lipase, -1-3-glucanase and chitinase (defence related enzymes), and aid plant growth (Gopalakrishnan etal. 2013). Micrococcus sp NII-0909 isolated from the Western ghat forest soil in India had demonstrable ability to enhance soil fertility and promote plant growth (Dastager etal. 2010). EndAct, for example Corynebacteria, can be associated with plant pathogenicity (Vidaver 1982). Also, juglone has been
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Table 4 Transcripts fromfungi
Transcript Description Evalue
a
C44240_G2_I1 KGB78973.1 ADP/ATP translocase [Cryptococcus gattii R265] 3e91 C8003_G1_I1 XM_571019.1 C. neoformans var. neoformans JEC21 60 s ribosomal protein 3e98 C28542_G1_I1 XP 003191240.1 40 s ribosomal protein s3aea (s1a) [Cryptococcus gattii WM276] 3e91 C9244_G1_I1 XM_569612.1 C. neoformans var. neoformans JEC21 40S ribosomal protein 3e119 C8207_G1_I1 KGB74187.1 cyclophilin A, peptidylprolyl isomerase [Cryptococcus gattii R265] 5e82 C61284_G1_I1 KGB74302.1 60S ribosomal protein L10 [Cryptococcus gattii R265] 1e76 C60498_G1_I1 AFR92589.1 glutamine synthetase [Cryptococcus neoformans var. grubii H99] 9e51 bC6553_G1_I1 XM_001932117.1 P. triticirepentis Pt1CBFP subtilasetype proteinase 6e130 C35196_G1_I1 XM_001932926.1 P. triticirepentis Pt1CBFP 60S ribosomal protein 0.0 C50331_G1_I4 XM_001930633.1 P. triticirepentis Pt1CBFP hypothetical protein 9e125 C34393 _G1_I1 XM_003296940.1 P. teres f. teres 01 ubiquitin40S ribosomal protein 1e101 C50331_G1_I5 XM_001930633.1 P. triticirepentis Pt1CBFP hypothetical protein 1e133 C58663_G1_I1 XM_001937272.1 P. triticirepentis Pt1CBFP opsin1, mRNA 3e69 C29801_G1_I1 XM_001936103.1 P. triticirepentis Pt1CBFP conserved hypothetical 1e57 C30295_G1_I1 XM_003306030.1 P. teres f. teres 01 hypothetical protein, mRNA 2e70 C16207_G1_I1 XM_001935967.1 P. triticirepentis Pt1CBFP conserved hypothetical 7e97 C50331_G1_I2 XM_001930633.1 P. triticirepentis Pt1CBFP hypothetical protein 1e122
a Cryptococcus is the causal agent of the human/animal respiratory disease cryptococcosis. These fungi are mostly localized in the catkins and the vegetative bud in walnut, corroborating previous results indicating that the plant surface provides a conducive environment for their sexual cycle. Here, we see two dierent species: C. neoformans var. neoformans and C. gattii. b The tan spot causing pathogenic fungi Pyrenophora had two dierent strainspresent: P. tritici-repentis and P. teres f. teres
Table 5 Species fromActinobacteria
Taxonomy name ID Lineage
Arthrobacter 1663 Bacteria; Actinobacteria; Actinobacteria; Micrococcales; Micrococcaceae Modestobacter 88138 Bacteria; Actinobacteria; Actinobacteria; Geodermatophilales; Geodermatophilaceae Microlunatus 29404 Bacteria; Actinobacteria; Actinobacteria; Propionibacteriales; Propionibacteriaceae Actinoplanes 1865 Bacteria; Actinobacteria; Actinobacteria; Micromonosporales; Micromonosporaceae Nakamurella 53460 Bacteria; Actinobacteria; Actinobacteria; Nakamurellales; Nakamurellaceae Streptomyces 1883 Bacteria; Actinobacteria; Actinobacteria; Streptomycetales; Streptomycetaceae Propionibacterium 1743 Bacteria; Actinobacteria; Actinobacteria; Propionibacteriales; Propionibacteriaceae Corynebacterium 1716 Bacteria; Actinobacteria; Actinobacteria; Corynebacteriales; Corynebacteriaceae Micrococcus 1269 Bacteria; Actinobacteria; Actinobacteria; Micrococcales; Micrococcaceae
We obtain the taxonomy ID from http://www.ncbi.nlm.nih.gov/Taxonomy/TaxIdentier/tax_identifer.cgi
Web End =http://www.ncbi.nlm.nih.gov/Taxonomy/TaxIdentier/tax_identifer.cgi using the taxonomy name, which is then used to get the lineage. The taxonomy names were obtained from best entry in a BLAST search to the nt database
found to have inhibitory eects on some of these nitrogen xing bacteria (Dawson etal. Dawson and Seymour 1983).
Methylibium petroleiphilum: involved inaerobic biodegradation ofmethyl tertbutyl ether
Methylibium petroleiphilum is capable of using methyl tert-butyl ether as a sole source of carbon in the root (Fig. 2c) (Nakatsu et al. 2006). Unlike Phytophthora, there are only two transcripts for Methylibium. One transcript is 461 nt long and has a 92 % identity to the M.
petroleiphilum PM1 genome (Accession: CP000555.1). The ORF from this transcript has a 79% identity to part of a protein (Accession: ABM53545.1) from uncultured beta proteobacterium CBNPD1 BAC clone 578, which was obtained in a metagenomic analysis of a freshwater toxic cyanobacteria bloom (Pope and Patel 2008). Although the PCR-generated 75-clone, 16S rRNA gene library had conrmed the presence of Proteobacteria, data here associates this protein with M. petroleiphilum. Interestingly, this transcript or ORF has no match in the new draft sequence of the Methylibium sp. strain T29, a
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fuel oxygenate-degrading bacterial isolate from Hungary (Szab et al. 2015). This is explained by the dierences observed: unlike M. petroleiphilum PM1 our isolate does not harbor the mega plasmid which carries the genes for MTBE-degradation (Szab etal. 2015).
Acyrthosiphon pisum: the pea aphid pest
While both Methylibium and Phytophthora are mostly localized in the root, thepeaaphid A. pisum, which is a pest of importance in agriculture (Van Emden and Harrington 2007), was found in the leaves (Fig. 2d). One transcript of Acyrthosiphon (C58762 _G1_I1) encodes a 91 amino acid long ORF having a 99 % match to the ribosomal L37 protein (Accession: NP 001129424.1). The low count of this transcript demonstrates the accuracy of the RNA-Seq technology (Table3d).
Aedes aegypti: yellow fever mosquito
The presence of yellow fever mosquito in the vegetative bud was not expected (Fig. 2e) and was not previously reported in Northern California. The proteins found there include proteases (both serine and metallo), ribosomal RNA and an elongation factor (Table 6). Among the serine proteases, C40984_G1_I1 encodes a trypsin that has a signicant similarity to a female reproductive tract protease from Drosophila mojavensis (Uniprot id: C5IB51) (Kelleher and Markow 2009), suggesting that the mosquito had been using the vegetative buds for reproductive purposes. The importance of the serine proteases in egg-formation abilities of mosquitoes were established using a RNAi knockdown method (Isoe et al. 2009). Another interesting development has been the recent monitoring of Aedes aegypti and Aedes albopictus by the California Department of Public Health.
Their detection sites are updated regularly. (https://www.cdph.ca.gov/HEALTHINFO/DISCOND/Pages/Aedes-albopictus-and-Aedes-aegypti-Mosquitoes.aspx
Web End =https:// https://www.cdph.ca.gov/HEALTHINFO/DISCOND/Pages/Aedes-albopictus-and-Aedes-aegypti-Mosquitoes.aspx
Web End =www.cdph.ca.gov/HEALTHINFO/DISCOND/Pages/
https://www.cdph.ca.gov/HEALTHINFO/DISCOND/Pages/Aedes-albopictus-and-Aedes-aegypti-Mosquitoes.aspx
Web End =Aedes-albopictus-and-Aedes-aegypti-Mosquitoes.aspx ). However, their detection method is not known to us.
Nucleotidebinding site (NBS) andleucinerich repeats (LRR) inwalnut
The detection of several well-characterized plant pathogens in the current study raises the question of what innate resistance mechanism in walnut could provide resistance to these virulent agents. While it is possible that these strains of these pathogens are non-virulent, it is equally likely that this plant encodes and transcribes the desired resistance genes and transcripts needed to combat a virulent response from any one of these pathogens. Plants possess two distinct kinds of defence mechanismsthe pathogen-associated molecular patterns (PAMP) mediated immunity (PTI) and eector-triggered immunity encoded by resistance (R) genes (ETI). PTI is analogous to the rst line of defense (innate immunity) in vertebrates, which is bypassed or disrupted by pathogen eector molecules that are used to downregu-late PTI, making the cell vulnerable to pathogen attack (Nicaise etal. 2009). R genes have evolved in this ensuing evolutionary warfare in plants, akin to the mammalian adaptive immunity, to recognize pathogens which contain complementary avirulence genes (DeYoung and Innes 2006). However, unlike the mammalian adaptive immune system which is enforced through specialized cells, R genes are active in all plant cells. The majority of R genes encode proteins comprise of a nucleotide-binding site (NBS) and leucine-rich repeats (LRRs). NBS-LRR proteins recognize and neutralize specialized pathogen avirulence (Avr) proteins, leading to the upregulation of PTI, thus, providing plants with resistance to the attack (Hayashi etal. 2010; Ernst etal. 2002; Borhan etal. 2004; Zhang et al. 2010). It has been hypothesized that the distribution and diversity of NBS-LRR sequences is a direct consequence of extensive duplication and random
Table 6 Transcripts fromAedes aegypti, the yellow fever mosquito
Transcript Description Evalue
C40984 _G1_I1 XM_ 001652893.1 Aedes aegypti trypsin partial mRNA 0.0 C56263 _G1_I1 AY432478.1 Aedes aegypti ASAP ID: 35053 metalloendopeptidase mRNA sequence 3e152 C58453 _G1_I1 AY432463.1 Aedes aegypti ASAP ID: 35049 serine protease mRNA sequence 0.0 C62133 _G1_I1 U65375.1 AAU65375 Aedes aegypti 18S ribosomal RNA gene 0.0 C24216 _G1_I1 U65375.1 AAU65375 Aedes aegypti 18S ribosomal RNA gene 8e148 C5389 _G1_I1 L22060.1 Aedes albopictus 8S, 5.8S, and 28S ribosomal RNA genes 0.0 C58751 _G1_I1 AY433205.1 Aedes aegypti solate A20 28S ribosomal RNA gene 9e163 C59860 _G1_I1 AY736001.1 Aedes aegypti elongation factor 1 alpha mRNA, partial cds 4e152
These match with high signicance to the yellow fever mosquito BLAST nt database, and are mostly found in the vegetative bud (Fig.2e). C40984_G1_I1 encodes an ORF with a 99% identity to the Aedes aegypti trypsin. Interestingly, this protein also has a signicant similarity to a female reproductive tract protease from Drosophila mojavensis, suggesting that the walnut vegetative bud has been used for egg-laying purposes by the female mosquito
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rearrangements, endowing plants with the ability to recognize diverse molecules arising from dynamically changing biotic challenges (Meyers etal. 2003). Here, we
briey describe the transcripts and expression levels of the NBS-LRRs genes in walnut. Two specic examples of such NBS-LRRs genes conferring resistance to plants are
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Table 7 Expression counts often highly expressed transcripts fromthe NBS-LRR family
Transcript CE CI CK EM FL HC HL HP HU IF LE LM LY PK PL PT RT SE TZ VB L
C54426_G7_I1 9.9 19.7 1.2 0 2.8 26.2 3.5 23 0.2 1.2 0.9 0.7 3.2 2.8 0.5 1.4 4.5 0.2 1.2 1 745 C50016_G1_I3 0.9 2.2 2.6 1.3 8 2.3 18.9 1.5 1.5 9 8.1 0.4 7.6 0.6 0.7 8.6 2.4 1.9 0.2 3.3 1026 C52820_G1_I1 1.7 4.6 3.8 2.4 14.3 2.5 1 0 2.8 0.6 7.9 2.6 0.4 3.1 2.4 1.4 12.3 1.4 4.5 1.1 3.1 1010 C8180_G1_I1 1.3 2.8 0.8 0.4 8.1 3 25.2 1.5 5 13.9 2.4 0 3.8 0.1 0.3 17.2 1.6 0.5 0 2 668 C55004_G7_I2 2 4.4 2.2 2.5 9.2 3.9 11.9 3.3 3.1 5.6 7.3 3.1 8.3 3.2 1.5 6.2 3.6 2 1.7 3.9 767 C49942_G2_I1 2.7 6.7 2.2 3 1.3 14.8 7 4.8 7.4 2.9 1.3 2.7 1.3 6.5 5.1 4.2 3.2 2.8 5.5 0.8 669 C47067_G1_I2 1.1 2.6 1.1 0.3 8.2 2 7.5 1.3 1.4 5.9 6.4 1 9 4.4 7 11.2 2.4 1.3 1.4 3.6 677 C44186_G1_I3 1.7 2.5 4.5 0.5 5.7 2 15.2 1.2 6 6.4 7.9 2.1 7.2 1 0.7 9.3 5.9 0.9 0.1 4.3 1034 C44186_G1_I1 1.9 2.6 4.6 0.6 5.4 2.1 14.8 1.5 6.8 6.6 8.1 2.2 7.3 1.2 0.8 9.1 5.4 0.9 0.1 4.1 659 C51189_G5_I1 5 10.3 4.1 3.5 16.5 3.6 19.1 3 21.3 10.6 9.5 1.5 10.8 6.5 2.7 14.9 5.9 6.5 2.7 6 1017
These are raw counts in K (103 ), and are not normalized. Some NBS-LRRs (like C54426_G7 _I1, a Strubbelig receptor kinase) are signicantly overexpressed in specic tissues
the blast-resistance gene Pb1 NBS-LRR from rice (Uniprot: E3WF10) (Hayashi etal. 2010) and the cyst nematode resistance gene from tomato (Uniprot: Q8GT46) (Ernst et al. 2002). In addition to being leucine rich, these two proteins are also abundant with the negatively charged glutamic acid (Fig.4a). Although these specic NBS-LRRs are ~1300 amino acid long, the typical length of NBS-LRR varies from a few hundred to <2K (McHale etal. 2006). Using these proteins as initial search entities, we have identied ~400 NBS-LRR transcripts (excluding splice variants denoted by transcripts having the same prex) in walnut through the ndgene algorithm described earlier by us (Chakraborty etal. 2015) (Fig.4b). This is in excellent agreement with the 374 NBS-LRR genes that were identied in a genome wide study of Chinese chestnut (Castanea mollissima) resistant to Chestnut Blight Disease (Zhong etal. 2015). The tissue-specic expression pattern allows the discrimination of the truly critical genes in this large family (Table7). The tissue-specic nature of certain genes is exemplied by C54426_G7_I1, which has signicantly higher expression in the catkins and hull, and shares 78% identity with a Strubbelig-receptor family (SRF) from Malus domestica. SRFs are receptor-like kinases (Eyboglu etal. 2007), and are involved in tissue morphogenesis (Vaddepalli et al. 2011) and immune response (Alczar etal. 2010). As corroboration, we chose one NBS-LRR protein from each of the two major domains of NBS-LRR (McHale et al. 2006)TIR-NBS-LRR (Uniprot:Q6QX58 (Borhan et al. 2004)) and CC-NBS-LRR Uniprot:Q56YM8 (Meyers etal. 2003), and obtained the same number of transcripts encoded by NBS-LRR genes. Thus, we demonstrate that transcriptomic data that has revealed the biodiversity in dierent tissues of walnut simultaneously provides insights into the ability of the plant to negate the threat posed by some of these potentially destructive pathogens.
In summary, high conservation of some proteins within a genus does not allow the proper characterization of the species. Thus, although we can state with a great degree of certainty the presence of the genus Phytophthora, it is not possible to identify the exact species/strain. No viruses have been detected using the current methodology. Also, since the root samples were derived from a sterile sample, we did not detect root lesion nematodes (Pratylenchus vulnus), a major source of concern for the California walnut industry (Walawage et al. 2013). The detection of specic proteins from pathogens can serve as a target for therapeutics. The methodology described here presents an unbiased rapid tool to extract the metagenome from an RNA-Seq prole that can be used to develop diagnostics. In this study, the prole represented twenty dierent tissues from walnut, and the extracted metagenome from all of these tissue types presents a vivid picture of the biodiversity in its surroundings in California.
Authors contributions
Dandekar and Britton were involved in the design of the RNAseq, Dandekar and Chakraborty designed the metagenome extraction, Chakraborty did the in silico analysis that revealed the metagenome, MartnezGarca was involved in the validation with the walnut genome sequence. Chakraborty wrote the rst draft and the rest of the authors were involved in subsequent modications.
Author details
1 Plant Sciences Department, University of California, Davis, CA 95616, USA.
2 UC Davis Genome Center Bioinformatics Core Facility, Davis, CA 95616, USA.
Acknowledgements
Grant information: The authors wish to acknowledge support from the Califor nia Walnut Board and UC Discovery program.
Accesion number: Sequence data from this article can be found in the NCBI Sequence Read Archive under BioProject PRJNA232394.
Competing interests
The authors declare that they have no competing interests.
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Received: 18 November 2015 Accepted: 29 January 2016
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The Author(s) 2016
Abstract
Deep RNA-Seq profiling, a revolutionary method used for quantifying transcriptional levels, often includes non-specific transcripts from other co-existing organisms in spite of stringent protocols. Using the recently published walnut genome sequence as a filter, we present a broad analysis of the RNA-Seq derived transcriptome profiles obtained from twenty different tissues to extract the biodiversity and possible plant-microbe interactions in the walnut ecosystem in California. Since the residual nature of the transcripts being analyzed does not provide sufficient information to identify the exact strain, inferences made are constrained to the genus level. The presence of the pathogenic oomycete Phytophthora was detected in the root through the presence of a glyceraldehyde-3-phosphate dehydrogenase. Cryptococcus, the causal agent of cryptococcosis, was found in the catkins and vegetative buds, corroborating previous work indicating that the plant surface supported the sexual cycle of this human pathogen. The RNA-Seq profile revealed several species of the endophytic nitrogen fixing Actinobacteria. Another bacterial species implicated in aerobic biodegradation of methyl tert-butyl ether (Methylibium petroleiphilum) is also found in the root. RNA encoding proteins from the pea aphid were found in the leaves and vegetative buds, while a serine protease from mosquito with significant homology to a female reproductive tract protease from Drosophila mojavensis in the vegetative bud suggests egg-laying activities. The comprehensive analysis of RNA-seq data present also unraveled detailed, tissue-specific information of ~400 transcripts encoded by the largest family of resistance (R) genes (NBS-LRR), which possibly rationalizes the resistance of the specific walnut plant to the pathogens detected. Thus, we elucidate the biodiversity and possible plant-microbe interactions in several walnut (Juglans regia) tissues in California using deep RNA-Seq profiling.
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