research article transcriptome analysis of gelatin seed...

Research ArticleTranscriptome Analysis of Gelatin Seed Treatment asa Biostimulant of Cucumber Plant Growth

H T Wilson K Xu and A G Taylor

Cornell University School of Integrated Plant Science New York State Agriculture Experimental Station Geneva NY 24456 USA

Correspondence should be addressed to H T Wilson hiromiwilsonsyngentacom

Received 29 May 2015 Accepted 8 July 2015

Academic Editor Zhoufei Wang

Copyright copy 2015 H T Wilson et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The beneficial effects of gelatin capsule seed treatment on enhanced plant growth and tolerance to abiotic stress have been reportedin a number of crops but the molecular mechanisms underlying such effects are poorly understood Using mRNA sequencingbased approach transcriptomes of one- and two-week-old cucumber plants from gelatin capsule treated and nontreated seedswere characterizedThe gelatin treated plants had greater total leaf area fresh weight frozen weight and nitrogen content Pairwisecomparisons of the RNA-seq data identified 620 differentially expressed genes between treated and control two-week-old plantsconsistent with the timing when the growth related measurements also showed the largest differences Using weighted genecoexpression network analysis significant coexpression gene network module of 208 of the 620 differentially expressed genes wasidentified which included 16 hub genes in the blue module a NAC transcription factor a MYB transcription factor an aminoacid transporter an ammonium transporter a xenobiotic detoxifier-glutathione S-transferase and others Based on the putativefunctions of these genes the identification of the significant WGCNAmodule and the hub genes provided important insights intothe molecular mechanisms of gelatin seed treatment as a biostimulant to enhance plant growth

1 Introduction

Seed gelatin encapsulation is a technology developed byAlliance Seed Capsule a consortiumbetweenCoating Supplyand Sakata Seed in which raw andor processed seeds areencapsulated in gelatin capsule (Supplementary Figure 1AB in Supplementary Material available online at httpdxdoiorg1011552015391234)The encapsulation provides severaladvantages such as improved handling and sowing fasterplant growth precision planting and precise seed quantitiesper sowing unit and also provides the capability of combiningseed enhancement technologies and other chemicals or bio-logical additives such as pesticides fertilizers and Rhizobium[1]

Plant biostimulants are a broad class of substances andmicroorganisms that enhance plant growth Biostimulantshave been gaining interest in sustainable agriculture becausethey stimulate physiological process in plants that enhancesplant development and nutrient use efficiency which reducesfertilizer consumption [2 3] Many biostimulants have beenreported to counteract the effect of biotic and abiotic stresses

enhancing quality and crop yield [3 4] The EuropeanBiostimulants Industry Council (EBIC) has defined plantbiostimulants as substance(s) andor microorganisms whosefunction when applied to plants or the rhizosphere is to stim-ulate natural processes to enhancebenefit nutrient uptakenutrient efficiency tolerance to abiotic stress and cropquality Biostimulants have no direct action against pestsand therefore do not fall within the regulatory frameworkof pesticides [5 6] Thus the application of gelatin as a seedtreatment falls under the category of plant biostimulants as ituses animal based protein hydrolysate a hydrolyzed form ofprotein as the main component

Protein hydrolysate and other protein-based productapplications were reported to enhance plant growth andyield in field tomato [7] greenhouse tomato [8] papaya [9]maize seedlings [10 11] spinach [2] carrot [12] and lettuce[13 14] A positive effect of protein hydrolysate on abioticstress also was reported and cucumber plants subjected tosuboptimal pH level and temperature performed better withthe application of humic acid containing substance LACTO-FOL with notable increase in leaf area shoot and root

Hindawi Publishing Corporatione Scientific World JournalVolume 2015 Article ID 391234 14 pageshttpdxdoiorg1011552015391234

2 The Scientific World Journal

mass [15 16] Atonik a synthetic biostimulant composed ofnitrophenolates have been shown to increase leaf area androot system development Plants treatedwith nitrophenolateshave been characterized as having greater inhibition of IAAoxidase which ensures a higher activity of naturally synthe-sized auxins [17] MEGAFOL a biostimulant composed ofa complex of vitamins amino acids proteins and betainespositively increased crop yield in sweet yellow pepper [18]The biostimulant also provided drought stress resistance intomato and MEGAFOL treated plants were able to recovermore quickly from drought stress Analyzing the expres-sion levels of drought-stress marker genes in tomato plantstreated with MEGAFOL demonstrated a lower expression ofdrought-related genes [19] An alfalfa plant-derived biostim-ulant increased maize plant biomass under salinity conditionand enhanced Na+ accumulation and reduced K+ accumu-lation in roots and leaves [10] Perennial ryegrass treatedwith an animal membrane hydrolysate Macro-Sorb Foliar(FOLIAR) when subjected to high air temperature stressexhibited increased photochemical efficiency and membranethermostability compared to plants without the treatment[20] Seed priming with BABA (120573-amino butyric acid) anonprotein amino acid reduced the abiotic stress in Vignaradiate by enhancing photosynthesis and proline accumula-tion and antioxidant enzyme activities in seedlings subjectedto NaClPEG [21]

Protein hydrolysate was shown to stimulate carbon andnitrogen metabolism and increase nitrogen assimilation inplants [22 23] A biostimulant containing amino acid Ami-noplant enhanced the nitrate reductase activity in spinach[2] NAD-dependent glutamate dehydrogenase nitrate re-ductase and malate dehydrogenase in maize had higheractivities following application of animal epithelial hydrol-ysate [24] Alfalfa protein hydrolysate applied to hydro-ponically grown maize increased the activity of malatedehydrogenase isocitrate dehydrogenase and citrate syn-thase which are enzymes found in the TCA cycle as wellas nitrogen metabolism enzymes nitrate reductase nitritereductase glutamine glutamine synthetase (GS) glutaminesynthase and aspartate aminotransferase [22] Ertani et al[23] reported that both alfalfa protein hydrolysate and animalconnective tissue hydrolysate stimulated plant growth andalso increased nitrate conversion into organic nitrogen byinducing nitrate reductase and GS activities The treatmentsespecially enhanced theGS2 isoform which is responsible forassimilation of ammonia produced by nitrate reduction thusconfirming that protein hydrolysate enhances plant growthby upregulating nitrate assimilation [23 25] Similarly Vac-caro et al [26] demonstrated that low concentration of humicacid positively influenced nitrate metabolism by increasingthe content of soluble protein and amino acid synthesiswhich was stimulated by significant increase in activity andtranscription of enzymes functioning in N assimilation andKrebs cycle

Seed encapsulation using gelatin capsules is a novelapproach as a seed treatment to enhance plant growth [1]The effect of gelatin applied at time of sowing on cucumberplant increased leaf surface area and fresh and dry weightas compared to the nontreated control and increased salinity

tolerance in plants treated with gelatin capsules (Wilson andTaylor unpublished) However the underlying molecularmechanisms of the plant growth promotion by proteinhydrolysate are unknown The objective of this study wasto characterize the effect of gelatin capsules on cucumbergrowth and development at the transcriptome level usingmRNA sequencing (RNA-seq) based genome-wide geneexpression profiling approach

2 Materials and Methods

21 Plant Materials and Evaluation of Growth and NitrogenContent Cucumber seeds ldquoVlaspikrdquo (Seminis Oxnard CA)were planted in a controlled greenhouse maintained at24∘C21∘C temperature with 1410-hour photoperiod at NewYork State Agricultural Experiment Station in Geneva NewYork in the winter of 2013 Two size 3 gelatin capsules(Capsule Line Pompano Beach FL) were placed adjacentto each seed in a 4-inch pot (Supplementary Figure 1A)these are referred to as treated plants Capsules were placedadjacent to the seeds to prevent decrease in germinationrate and for controlling the amount of gelatin used in thetreatment Total weight of two gelatin capsules was 937mgwith a nitrogen content of 142mg and protein contentof 800mg The nontreated control plants did not receivegelatin capsule treatment Thirty-two plants (16 control and16 treated plants) were placed in the greenhouse followinga completely randomized design First (L1) and second (L2)true leaves from 8 plants in each treatment group weresampled at each of two different time points one (T1) andtwo (T2) weeks after emergence Total leaf area wasmeasuredusing a CI-202 Leaf Area Meter (CID Bio-Science CamasWA) and fresh weight was determined Samples were flash-frozen in liquid nitrogen and stored atminus80∘C Frozen sampleswere weighed to determine frozen weight (for approximatingdry weight) A subsample (sim100mg) of the frozen leaf tissuewas placed in an oven to dry at 100∘C over night and sentto the Cornell University Stable Isotope Laboratory (IthacaNY) for elemental analysis of N by combustion method Allsampling data were then statistically analyzed by ANOVA(120572 = 005) and Tukeyrsquos HSD test was then used to determinesignificance

22 RNA Isolation and Strand-Specific RNA-seq Library Con-struction and Sequencing Three biological replicates of eachtreatment of each leaf (L1 and L2) at each time point (T1and T2) were selected for RNA-seq analysis a total of 24samples (two treatments two time points two leaves andthree biological replicates) Total RNA was isolated fromsim5 g of ground leaf tissue using the Spectrum Plant TotalRNA Kit (Sigma Aldrich St Louis MO) following themanufacturerrsquos protocol The isolated RNA quantity andquality were evaluated by electrophoresis (2 agarose gel)followed by ethidium bromide staining and quantification byNanodrop 1000 (Thermo Scientific Waltham MA)

A 5 120583g subsample of the isolated total RNA from eachsample was treated with 1 120583L DNase I (Invitrogen CarlsbadCA) incubated at RT for 15 minutes followed by 70∘C for 10minutes The DNase treated total RNA samples were used to

The Scientific World Journal 3

isolate mRNA in order to construct strand-specific RNA-seqlibrary using NEBNext Poly(A) mRNA Magnetic IsolationModule and NEBNext Ultra Directional RNA Library PrepKit for Illumina (NewEngland Biolabs IpswichMA) Brieflythe mRNA was isolated with 14 120583L of NEBNext MagneticOligo d(T)

25and eluted with 16 120583L of Elution Buffer Five-

microliter of the isolatedmRNAwas fragmented inNEBNextFirst Strand Synthesis Buffer by heating at 94∘C for 15minutesand then used for the first-stranded cDNA synthesis byreverse transcription using random primersThe synthesizedfirst strand cDNA was then used as a template to synthesizedouble stranded cDNAThe resulting double stranded cDNAwas end-repaired dA-tailed and then ligated with NEBNextadaptor Small size (approximately 300 bp) fragments wereselected using Agencourt AMPure XP beads (BechmanCoulter Pasadena CA) in 06 volumes of ligation reactionAnother round of size selection was performed with 025volumes of the cDNA library solution and then digestedwith 1 120583L of NEBNext USER enzyme at 37∘C for 15 minutesThe cDNA library was enriched by PCR with NEBNextindex primers following conditions 98∘C for 30 seconds15 cycles of 98∘C for 10 seconds 65∘C for 30 seconds and72∘C for 30 seconds 72∘C for 5 minutes and then held at4∘C The PCR-enriched cDNA libraries were purified by 14volumes of Agencourt AMPure XP beads and eluted in 22120583LElution BufferThe purified cDNA library was analyzed alongwith Quick-Load 1 kb Extended DNA Ladder (New EnglandBiolabs Ipswich MA) by electrophoresis (2 agarose gel)followed by ethidium bromide staining to visualize theoptimal size range of the cDNA library (250 bpndash400 bp) ThecDNA library of optimal sizes was quantified by Qubit 20Fluorometer using the dsDNA HS Assay Kit (InvitrogenCarlsbad CA) Three sets of 8 multiplexed libraries (30 ngper library) were configured and sent to Cornell UniversityBiotechnology Resource Center (Ithaca NY) for single-endsequencing of 101 bases using three lanes (one lane per set ofthe multiplexed libraries) on Illumina HiSeq 2000 (IlluminaSan Diego CA)

23 Reads Processing and Data Analysis The Illuminasequencing generated a total of 3775 million raw readspassing the Illumina pipeline in software CASAVA v18 inSanger FASTQ format for the 24 samples On average therewere 157 plusmn 67 million raw reads per library (Table 1) TheRNA-seq data was analyzed with CLC Genomics Work-bench (CLC) version 65 (CLCBio Cambridge MA) Thecucumber reference genome (Chinese long version 20) [27]and annotation file were downloaded from the InternationalCucurbit Genomic Database (httpwwwicugiorg) Map-Man gene ontology of the reference transcriptome of 23248genes was obtained via the web-based search tool Mer-cator (httpmapmangabipdorg) which searched severaldatabases including Arabidopsis TAIR 10 (The ArabidopsisInformation Resources) SwissProtUniref 90 (UniProt Ref-erence Clusters) CDD (ConservedDomanDatabase NCBI)KOG (Eukaryotic Orthologous Groups of proteins NCBI)InterPro (EMBL-EBI) and others

Reads mapping against the reference genome (Chi-nese long version 20) was conducted using the following

parameters The limit for read unspecific match to the refer-ence genome was set to 10 minimum length fraction was 09and minimum similarity fraction was 098 Normalized readcounts RPKM (reads per kilobase exon model per millionmapped reads) for each gene was calculated and genes withRPKM lower than 10 were considered not expressed andexcluded from analysis In order to identify differentiallyexpressed genes (DEGs) pairwise comparisons of RPKMswere performed between control and treated plants in eachleaf tissue at each time point (control T1-L1 versus treated T1-L1 control T1-L2 versus treated T1-L2 control T2-L1 versustreated T2-L1 and control T2-L2 versus treated T2-L2) Theresults were weighted by the 119905-type test statistics (119901 value)and FDR (false discovery rate) corrected 119901 values usingBaggerleyrsquos test [28] The cutoff for defining a DEG is 119875FDR lt005

24 Gene Network Construction and Visualization The coex-pression gene networks were constructed using weightedgene coexpression network analysis (WGCNA) (v141) pack-age in R [29] using square root normalized RPKM data fromthe 24 samples A total of 620 differentially expressed genes(DEGs) were used The adjacency matrix was created bycalculating Pearsonrsquos correlation between all genes and raisedto a default power of 6 The Topological Overlap Measure(TOM) which is a measure of overlap in shared neighborswas calculated using the adjacency matrix The dissimilarityTOM was used as input for the dendrogram and moduleswere detected using the DynamicTreeCut algorithm Mod-ules are defined as clusters of highly interconnected genesand genes within the same cluster have high correlationcoefficients among one another [29 30] All modules wereassigned a unique color (blue yellow brown turquoiseand gray) The module eigengenes were used to representeach module which were calculated by the first principalcomponent capturing the maximal amount of variation ofthe module The eigengenes were then used to estimate thecorrelations between module eigengenes and the traits ofinterest total leaf area (TLA) fresh weight (FW) frozenweight (DW) and total nitrogen percent (PercentN) Thegene network of the blue module was visualized usingCytoscape (v300) the most relevant module in explainingthe trait variations such as the effect of the treatments

25 Expression Analysis Using qRT-PCR Expression pro-file of 5 genes (Csa1G066570 Csa1G590300 Csa5G589260Csa5G140480 and Csa5G319910) was confirmed in the 12samples taken at time point 2 using qRT-PCR A house-keeping gene (Csa6M484600) encoding ACTIN was usedas reference Primers were designed using BatchPrimer3v10 software [31] (Table 2) Genes were selected from the620 DEGs identified from pairwise comparisons of RPKMsbetween control and treated plants at each leaf tissue in eachtime point The RPKM and qRT-PCR expression values weresquare root transformed

The mRNA was purified from 5 120583g of total RNA foreach of the 12 samples and reverse transcribed in a finalvolume of 20 120583L using the High Capacity cDNA ReverseTranscription Kit (Applied Biosystems Foster City CA)


Table 1 Overview of mapping of RNA-seq reads against the reference genome

Sample Treatment Time pointleaf Rep Number ofTotal reads

Uniquelymappedreads

Percent readuniquelymapped to

reference ()

Percent readuniquelymapped toexons ()

Percent readuniquelymapped tointrons ()

1 Control T1-L1 1 12019363 9350227 7779 9871 1292 Control T1-L1 2 8624277 6592181 7644 9861 1393 Control T1-L1 3 14970567 10499989 7014 9936 0644 Control T1-L2 1 10128190 7724322 7703 9873 1275 Control T1-L2 2 9216330 6472955 7023 9833 1676 Control T1-L2 3 14144786 9498041 6715 9886 1147 Treated T1-L1 1 17361035 13764974 7929 9910 0908 Treated T1-L1 2 8794498 4518865 5138 9899 1019 Treated T1-L1 3 16744466 12843001 7670 9917 08310 Treated T1-L2 1 21897381 16628402 7594 9864 13611 Treated T1-L2 2 8393223 5533323 6593 9858 14212 Treated T1-L2 3 16743616 12757850 7620 9809 19113 Control T2-L1 1 13141492 10676776 8124 9862 13814 Control T2-L1 2 13736384 10695841 7787 9861 13915 Control T2-L1 3 23334193 17068298 7315 9898 10216 Control T2-L2 1 12638497 10042325 7946 9919 08117 Control T2-L2 2 16590125 2877719 1735 9906 09418 Control T2-L2 3 32818854 23045970 7022 9917 08319 Treated T2-L1 1 8454166 5946132 7033 9850 15020 Treated T2-L1 2 14493239 11039888 7617 9861 13921 Treated T2-L1 3 25311395 19265850 7612 9853 14722 Treated T2-L2 1 8279148 6515229 7869 9911 08923 Treated T2-L2 2 25182470 4169826 1656 9899 10124 Treated T2-L2 3 24438920 17400788 7120 9800 200Total 377456615 254928772Mean 15727359 10622032 6886 9877 123SD 6671306 5195189 1715 035 035

Table 2 qRT-PCR primer sequence (forward and reverse) by gene (feature ID)

Feature ID Forward (51015840-31015840) Reverse (51015840-31015840)ACT CCGTTCTGTCCCTCTACGCTAGTG GGAACTGCTCTTTGCAGTCTCGAGCsa1G066570 TGAGCAATGCCCTGTCCAAC ATCACCTTCCTGGCCCACAACsa1G590300 ATTGCTGGCGTTGTCACTGG TCCCAAGCATGGCTTCACAACsa5G140480 CTGCATTTCCCCGGATTCTG GCGGGGTCGAACTTGTCATCCsa5G319910 AGCCCATGTGCCTTCGTTGT GATCGCCTGTTCCCCGATTTCsa5G589260 GGTGTTGGCCGGTTTTTGAA CTTTCAGTGCGGCAGCTCCT

according to the manufacturerrsquos protocol The qRT-PCR wasperformed using 50 ng of cDNA in a final volume of 20120583Lcontaining 10 120583L of LightCycler 480 SYBR Green MasterMix(Roche Applied Science Germany) and 2 120583L of 10mmol ofspecific primers (Table 2) Triplicates of each sample were runin the LightCycler 480 instrument (Roche Applied ScienceGermany)The total amount of cDNAwas normalized by thecoamplification of the ACTIN gene and by calibrating therelative expression using the relative quantification methoddescribed by Pfaffl [32 33]

3 Results

31 Evaluation of Growth and Nitrogen Content The growthmeasurements of the plants treated with gelatin capsules weregenerally greater than the control in both time points (T1and T2) (Figures 1(a) 1(b) 1(c) and 1(d)) One week afteremergence (T1) there were significant differences betweenthe first leaf (L1) of control and that of plants treated by gelatincapsules with a 36 increase in total leaf area (119901 = 00314)(Figure 1(a))Therewere no significant differences in leaf area


B

A

A

A

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45

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(a)

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Control2 capsules

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a (cm

2)

(c)

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mg)

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(d)

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3

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Time 1

Control2 capsules

Time 2

Fres

h w

eigh

t (g)

(e)

Figure 1 Evaluation of the effect of cucumber (ldquoVlaspikrdquo) seed gelatin treatment on plant growth and nitrogen content Data were analyzedby ANOVA (120572 = 005) and Tukeyrsquos HSD test was then used to compare mean separation Letters not associated with the same letter weresignificantly different Bars represent standard deviation Legend shows control and gelatin capsule treatment (2 capsules) (a) Total leaf areasat one week after emergence (T1) between control and gelatin capsule treatment (2 capsules) First leaf (leaf 1) and second leaf (leaf 2) wereharvested separately (b) Total leaf areas at two weeks after emergence (T2) between control and gelatin capsule treatment (2 capsules) (c)Fresh weight at one week after emergence (time 1) and two weeks after emergence (time 2) (d) Frozen weight at one week after emergence(time 1) and two weeks after emergence (time 2) (e) Nitrogen contents at one week after emergence (time 1) and two weeks after emergence(time 2)


between the control and the treated plants on the second leaf(L2) (Figure 1(a)) Two weeks after emergence (T2) both L1and L2 were significantly different between the control andtreated plants (119901 = 00230 and 119901 = 00292) respectively(Figure 1(b)) There was a 28 and a 40 increase in leafarea from the control compared to the treated for L1 and L2respectively (Figure 1(b))

There were no significant differences in fresh weight oneweek after emergence (T1) between the control and treatedplants However a significant difference (119901 = 00076) wasmeasured on the second week after emergence (T2) with a52 increase in the treated plant compared to the control(Figure 1(c))

Frozen weight also increased with the gelatin capsuletreatments with a 16 increase one week after emergenceand a 28 increase twoweeks after emergenceThere were nosignificant differences in frozen weight between control andtreated plants at T1 but significant differences weremeasuredat T2 (119901 lt 00076) (Figure 1(d))

The nitrogen content increase was less significant withonly a 4 increase in nitrogen in the treated plants comparedto the control one week after emergence and a 12 increasetwo weeks after emergence However there was not a signif-icant increase at T1 but a significant difference in nitrogencontent was measured at T2 (119901 lt 00076) (Figure 1(e))

32 Transcriptome Analysis RNA sequencing of the 24 sam-ples (two treatments two time points two leaf types andthree biological replicates) yielded a total of 3775 millionreads translating to a mean of 157 plusmn 67 million readsper sample Mapping of the 3775 million reads against thereference genome (Chinese long version 20) indicated that69 (2601 million) were mapped of which 988 (2570million) were mapped to exons and 12 (31 million) tointrons In this study 980 (2550 million) of the 2601millionmapped reads weremapped uniquely to the referencegenome (Table 1) The first leaf of the control plants (L1)at T1 had a total of 14864 expressed genes (RPKM gt 10)whereas L1 of the treated plants at T1 had the fewest numberof expressed genes in the whole group with only 13885expressed genes The samples from L2 in T1 had the highestnumber of expressed genes with 15764 expressed genes inthe control and 15874 expressed genes in the treated plantsThe control L1 from T2 had 14713 expressed genes and thetreated had 14843 expressed genes The control L2 fromT2 had 14756 expressed genes and the treated had 15287expressed genes

33 Differentially Expressed Genes in Plant Tissue One Weekafter Emergence (T1) In this study a cutoff of 119901FDR lt 005 inBaggerleyrsquos test was used to judge the significant differencesin gene expression A total of 22 genes (Supplementary Table1) were differentially expressed between the treated and thecontrol in the first leaf (L1) one week after emergence (T1)Out of 22 differentially expressed genes (DEG) nine genes(Csa4G622870 Csa2G258100 Csa1G049960 Csa5G623650Csa4G124910 Csa7G398090 Csa5G171700 Csa3G872080and Csa5G207960) were downregulated in treated samples(lower expression in the treated compared to the control)

and 13 genes (Csa6G109650 Csa2G079660 Csa6G425840Csa3G120410 Csa7G039260 Csa2G247040 Csa7G447100Csa7G047970 Csa6G118330 Csa2G355030 Csa6G194150Csa4G000030 and Csa3G822300) were upregulated (higherexpression in the treated compared to the control) TheDEGs were involved in development (Csa7G398090 andCsa4G124910) photosynthesis (Csa2G079660) hormonemetabolism (Csa2G258100) cell wall degradation(Csa1G049960) signaling (Csa6G194150) and bioticstress (Csa6G425840) (Supplementary Table 1) The secondleaf (L2) had 13 DEGs (Supplementary Table 1) two of whichwere downregulated (Csa5G161900 and Csa3G027190) andten genes (Csa1G569290 Csa1G569270 Csa6G150530CsaUNG029290 Csa7G009730 Csa3G047780Csa2G024440 Csa3G128920 Csa1G172630 Csa1G540870and Csa5G576740) were upregulated (SupplementaryTable 1) in the treated plants as compared with controlsThe MapMan bin classification revealed that these DEGsbelonged to protein synthesis (Csa1G540870) cell wall relatedfunctions (Csa7G009730 Csa6G150530) abiotic stress(Csa1G569270 Csa1G569290) hormone metabolism(Csa2G024440) and photosynthesis (Csa5G576740) (Sup-plementary Table 1)

34 Differentially Expressed Genes Two Weeks after Emer-gence (T2) Samples from second leaf (L2) at T2 had 588DEGs between treatment and controls of which 146 weredownregulated in the treated and 442 were upregulated(Supplementary Table 1) despite the fact that the first leaf(L1) revealed no DEG at the set threshold value The Map-Man bin classification revealed that the largest functioncategories were protein synthesis transcription factor trans-port hormone and secondary metabolism as well as lipidmetabolism The list of DEGs at T2 (588 genes) was muchmore extensive compared to that of T1 (22 genes) Despitethe limited number of DEGs at T1 there were six overlappingDEGs between T1 (L1) and T2 (L2) including Csa2G247040Csa2G355030 Csa4G000030 Csa6G109650 Csa6G425840and Csa7G398090 (Supplementary Table 1)

35 Identification of Coexpression Gene Modules and Net-work Hub Genes Highly Associated with Enhanced Growthby Gelatin Seed Treatment Weighted gene coexpressionnetwork analysis (WGCNA) of the 24 RNA-seq samplesusing the 620 DEGs (Supplementary Table 1) showed fourclusters along the lines between two time points and two leafpositions that is T1-L1 T1-L2 T2-L1 and T2-L2 (Figure 2)There was no subclustering by the treatment for T1-L1 T1-L2and T2-L1 However for T2-L2 the subclustering is clearlyseparated according to the treatment and all control samplesare clustered under one branch which are separated fromthe treated samples reflecting the fact that 588 of the 620genes were DEGs between the control and the treated in T2-L2 (Figure 2)

The WGCNA analyses further identified that the 620DEGs were clustered into five modules which are labeled bycolors blue yellow brown turquoise and gray (Figure 3)There were 208 genes in the blue module 90 genes in thebrown module 249 genes in the turquoise module 66 genes


TrT1

L2_1

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9CK

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1CK

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_7CK

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_18

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_17

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L2_2

4Tr

T2L2

_22

TrT2

L2_2

3

0

50

150

250

Hei

ght

Figure 2 Cluster dendrogram illustrating the relationships amongthe leaf tissues harvested at different time points (T1T2) leafposition (L1L2) of control plants (CK) and plants treated withgelatin capsule (Tr) which were calculated based on the expressiondata of the 620 DEGs

02

04

06

08

Hei

ght

Module colors

Figure 3 Hierarchical cluster tress showing coexpression modulesidentified by WGCNA The major branches constitute 5 moduleslabeled by different colors (grey module is for genes unassigned)Each branch in the dendrogram constitutes a module and each leafin the branch represents one gene

in the yellow module and 4 genes in the grey module (forunassigned genes) (Supplementary Table 1)

Themodule-trait (TLA FWDW and PercentN) relation-ship (Figure 4) revealed that the blue module had a strongpositive correlation with the leaf area (TLA 119877 = 086 119901 lt1 times 10

minus7) and nitrogen percent (PercentN 119877 = 085 119901 lt2times10minus7) and amoderate positive correlationwith freshweight

(FW 119877 = 064 119901 lt 7 times 10minus4) and frozen weight (DW1198772= 064 119901 lt 7 times 10minus4) The yellow module had a moderate

positive correlation with all the traits The turquoise moduleon the other hand had a strong negative correlation with TLA(119877 = minus083 119901 lt 6 times 10minus7) and PercentN (119877 = minus077119901 lt 1 times 10

minus5) and the brown module showed a moderatenegative correlation with FW (119877 = minus061 119901 lt 0002) andDW (119877 = minus061 119901 lt 0002) (Figure 4)

To study the relationships among modules and howthe modules were related to the four growth traits an

minus1

minus05

0

TLA FW DW PecentN

05

1MEblue

MEyellow

MEbrown

MEturquoise

MEgrey

086 064 064 085

067 059(0002)

059(0002)

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minus011(06)

minus061(0002)

minus061(0002)

minus018(04)

minus083 minus011(06)

minus011(06)

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minus024(03)

minus013(05)

minus013(05)

minus017(04)

(1e minus 07) (7e minus 04) (7e minus 04) (2e minus 07)

(3e minus 04) (3e minus 04)


Figure 4 Module-trait association Each row corresponds to amodule and each column corresponds to a specific trait total leafarea (TLA) fresh weight (FW) frozen weight (DW) and percentnitrogen (PercentN) The color of the cell indicates the correlationcoefficient between the module and trait dark red color indicateshigh degree of positive correlation and dark green indicates highdegree of negative correlation between each module and trait Thenumbers in the cell indicate the module-trait correlation value (top)and 119901 value (below)

FW DW

MEy

ello

w

MEb

lue

TLA

Perc

entN

MEb

row

MEt

urqu

oise

00

10

0

02

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1FWDW

FW DW

TLAPercentN

TLA

Perc

entN

Figure 5 Module eigengene network and its relationship withgrowth traitsThe dendrogram on the top illustrates the relationshipamong the module eigengenes and traits total leaf area (TLA) freshweight (FW) frozenweight (DW) and percent nitrogen (PercentN)Each row and column on the heat map correspond to a moduleor a trait The color of the cell indicates the adjacencies amongthe module eigengenes and traits dark red color indicates closeardencies and dark blue no or little adjacencies

eigengene network was inferred by calculating their adjacen-cies (Figure 5) The network indicated that there were twomajor branches one comprising the blue and yellow moduleeigengenes and the other comprising the brown and turquoisemodule eigengenes The four growth traits were collectivelydetermined to be closer to the blue and yellow module


Gen

e sig

nific

ance

for T

LA

09

08

07

06

05

04

03

09

08

07

06

05

04

07

05

03

01

Module membership in blue module05 06 07 08 09 10



Gen

e sig

nific

ance

for P

erce

ntN

Gen

e sig

nific

ance

for F

W

Module membership versus gene significance Module membership versus gene significance

Module membership versus gene significance

cor = 079 p = 12e minus 45 cor = 085 p = 3e minus 59

cor = 053 p = 18e minus 16

Figure 6 Intramodular analysis of gene significance (GS) andmodule membership (MM) of the genes in the blue module Data for trait DWwas not included which is nearly identical to that of FW

eigengenes than to those of the brown and turquoisemoduleseigengenes The FW and DW were extremely close to eachother and were nearly equally related to the eigengenes ofblue module and those of yellow module However the TLAand PercentN were highly related to each other and weremarkedly close to the blue module eigengenes These resultsstrongly suggest that the blue module eigengenes were mostclosely related to the four growth traits therefore the bluemodule was determined to be of the greatest importance andwas investigated in more detail (Figure 5)

The intramodular analysis of gene significance (GS) theabsolute value of the correlation between the gene and thetrait and module membership (MM) and the correlationof the module eigengene and the gene expression profileof the 208 genes in the blue module identified a numberof genes of high significance for the growth traits as wellas high module membership in the module (Figure 6) Thedata suggested that GS and MM were highly correlated

with all four growth traits especially for PercentN and TLA(Figure 5)

For better visualization of the intramodular connectivity(network degree) the gene network in the blue modulewas exported into Cytoscape 31 (Figure 7) Network analysisusing Network Analyzer [34] a Cytoscape plugin identi-fied 16 network hub genes of the highest network degree(60ndash92) in the blue module Csa2G357860 Csa5G615830Csa2G358860 Csa4G618490 Csa6G538630 Csa1G212830Csa2G351820 Csa5G011650 Csa2G163170 Csa7G395800Csa2G345990 Csa6G127320 Csa1G007850 Csa2G359890Csa3G848170 and Csa4G056640 (Figure 7 Table 3) Ofthese network hub genes five are of particular interestincluding Csa6G127320 encoding aNAC transcription factorCsa1G007850 a MYB transcription factor Csa5G615830 anamino acid transporter Csa2G163170 a plasma membranelocalized ammonium transporter and Csa7G395800 a xeno-biotic detoxifier-glutathione S-transferase (Figure 7 Table 3)


Table 3 List of 16 network hub genes identified in the blue module Degree represents the number of edges between genes which representcoexpression correlations

Gene MapMan gene ontology Annotation DegreeCsa7G395800 Miscellaneous Glutathione S-transferase PARB 92Csa2G345990 Not assigned Unknown protein 90Csa6G127320 Development NAC domain containing protein 36 (NAC036) 89Csa1G007850 Transcription factor Myb-like DNA binding domain 87Csa2G359890 Not assigned Unknown protein 86Csa4G056640 Hormone metabolism Nine-cis-epoxycarotenoid dioxygenase 4 (NCED4) 85Csa3G848170 Protein degradation Aminopeptidase M1 (APM1) 85Csa2G357860 Not assigned Unknown protein 81Csa5G615830 Transport Transmembrane amino acid transporter family protein 81Csa2G358860 Not assigned Unknown protein 77Csa4G618490 Transport Zinc transporter 5 precursor (ZIP5) 75Csa6G538630 Cofactor and vitamin metabolism Molybdenum cofactor sulfurase family protein 74Csa2G351820 Protein targeting Vacuolar-processing enzyme precursor 68Csa1G212830 Secondary metabolism 2-oxoglutarate (2OG) and Fe(II)-dependent oxygenase superfamily protein 68Csa5G011650 Miscellaneous NAD(P)-binding Rossmann-fold superfamily protein 66Csa2G163170 Transport Ammonium transporter 11 (AMT11) 60

92

1

(deg

)

Figure 7 Visualization of a coexpression network of 150 of 208genes in the blue module The network TOM similarity wascalculated with a power of 30 and edges are of weight higher than025 The 16 hub genes of the highest network degree (60ndash92) areshown on the left panel of the figure

36 Expression Analysis Using qRT-PCR Five genes(Csa1G066570 Csa1G590300 Csa5G589260 Csa5G140480and Csa5G319910) were selected from the 620 DEGs forthe qRT-PCR validation of their expression levels measuredby RNA-seq (RPKM) Correlation analysis between theqRT-PCR relative expression value and the RPKM ofRNA-seq indicated that they were significantly correlated(1198772 = 048ndash079 119901 = 00121ndash00001) validating the expres-sion levels measured by RNA-seq (Figures 8(a)ndash8(e))

4 Discussion

41 Amino Acid and Nitrogen Transport The increasedexpression of nitrogen source transporters in plants treatedwith gelatin capsules provided an insight into the mechanismof amino acid transport from the gelatin capsule to theplant as well as the nitrogen translocation within the plant

These transport proteins include amino acid transporter(Csa5G615830 Table 3) amino acid permease 3 (AAP3Csa6G381850 Supplementary Table 1) amino acid permease6 (AAP6 Csa3G894480 Supplementary Table 1) ammo-nium transporter 11 (AMT11 Csa2G163170 Table 3) andammonium transporter 2 (AMT2 Csa3G730930 Supple-mentary Table 1)

Gelatin capsules are composed of hydrolyzed collagena polypeptide found primarily in the flesh and connectivetissues of animals [35 36] Collagen can be broken downthrough hydrolysis to form hydrolyzed collagen and furtherhydrolysis will break down the peptide to single amino acids[35 37] Plants are capable of acquiring nitrogen as nitrate(NO3

minus) and ammonium (NH4

+) but also as organic formssuch as amino acids and proteins from the soil [38] Assim-ilation pathways of amino acids have been demonstratedwith 15N-labelled amino acids [39 40] as well as throughmetabolic profile analysis using GC-MS [41 42] Transportstudies with plant tissues have demonstrated the presenceof multiple transport systems for amino acids in plants [43ndash46] The amino acids enter the xylem in roots [47] and areexported from the xylem to the surrounding tissue [48] Theamino acids are then transported from xylem to the phloemleading to cycling within the plant [48]

One of the amino acid transporters upregulated with thegelatin capsule treatment AAP3 is preferentially expressedin the phloem and has been associated with long distancetransport of basic amino acids such as arginine histidineand lysine [49ndash51] The long distance transport by AAP3has been attributed to amino acid loading from the apoplastinto the phloem [46 48 49] AAP6 on the other hand isexpressed mainly in xylem parenchyma cells in sink tissuessuch as sink leaf cauline leaf and roots [52] Unlike AAP3which is responsible for high affinity transport of basic aminoacids AAP6 is a high affinity transporter of acidic and neutralamino acids such as aspartic acid proline alanine and valine


0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

qRT-PCR relative expressionRNA-seq (RPKM)

(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)

Figure 8 Comparison of gene expression betweenRNA-seq and qRT-PCRThedatawere transformedby square root Bars represent standarddeviation (a) Csa1G066570 (1198772 = 0597 119901 = 00032) (b) Csa1G590300 (1198772 = 0519 119901 = 00082) (c) Csa5G589260 (1198772 = 0483 119901 = 00121)(d) Csa5H140480 (1198772 = 0798 119901 = 00001) and (e) Csa5G319910 (1198772 = 0591 119901 = 00035)

[48 51 52] The relatively low concentration of amino acidsin the xylem compared to that in the phloem sap means thata high affinity transporter would be necessary in the xylemparenchyma cells to mediate the amino acid transfer fromthe xylem to the phloem [48] The high affinity nature ofAAP6 as well as its expression in the xylem parenchymacells suggests that AAP6 plays a role in the xylem to phloemtransfer of amino acids Hunt et al [53] demonstrated thatAAP6 mutant (aap6) had a reduced amino acid content inthe sieve element sap

The increased expression of amino acid transportersAAP3 (Csa6G381850) and AAP6 (Csa3G894480) in theplants treated with gelatin capsules suggests that aminoacid transport in the plants was positively affected by thetreatment possibly by the amino acids from the treatmentbeing taken up by the plants Wang et al [42] demonstratedthat in pak choi (Brassica rapa var chinensis) amino acidsupply was considered an N-limiting condition compared to

N source from NO3

minus which further enforces the effect ofavailability of amino acids in plant growth promotion

AAPs are selectively expressed in areas where expressionof H+ATPases is localized as AAPs are driven by a protongradient and require a high proton concentration to fuelthe active transport involved in uptake of amino acids fromthe apoplast into the phloem [48 54 55] Expression ofboth AAP3 and AAP6 is localized in the plasma membrane[48] which is where the expression of H+ATPase 4 (AHA4Csa1G008520 Supplementary Table 1) another gene highlyexpressed in plants treated with gelatin capsules is foundto be localized [55] Expression of AAP1 AAP2 and AAP8correlates with the expression pattern of two H+ATPasegenes AHA10 and AHA3 [56 57] This suggests couplingof H+ATPases with AAPs which have been characterizedas proton symporters energized by H+ATPase [58 59] It ispossible that AAP3 and AAP6 transport activity is coupledwith AHA4 generating protonmotive force required for high


affinity transport of the amino acids between xylem andphloem however further examination is necessary to linkthese genes together in a concrete manner

AMT2 (Csa3G730930 Supplementary Table 1) andAMT11 (Csa2G163170 Table 3) were another two genesinvolved in nitrogenmetabolism that showed high expressionin plants treated with gelatin capsule and were also shown tobe in the same module (blue) in WGCNA analysis Ammo-nium is an important intermediate in nitrogen metaboliteand the transport of and distribution of NH

4

+ across cellularmembranes depend on ammonium transporters (AMT) Inplants AMT-mediated ammonium transport is critical forproviding sufficient nitrogen for optimal growth [60 61] GFPstudies with AMT2 demonstrated its expression in the vascu-lar tissue in roots pith of stem petiole and leaf hydathodesand it mediated electroneutral ammonium transport in theformofNH

3[61]This is especially advantageous for the plant

as there is no need to actively export cotransported protonsby energy consumingH+ pumps allowing AMT2 to functionas a high affinity NH

4

+ transporter in the plasma membrane[61ndash63] Root AMT2 expression has been reported to beregulated by N-supply by Sohlenkamp et al [62] in whichthe AMT2 transcript increased in roots after N-deprivationhowever transcript level in shoots remained unchanged Theincrease in AMT2 transcript in plants treated with gelatincapsules suggests an increase inN-transport exportingNH

4

+

from the vascular tissue and importing NH3into the cyto-

plasmThe increase in total N observed in plants treated withgelatin capsules is hypothesized to be due to the increase inN-assimilation However none of the genes associated withN-assimilation (GSGOGAT)were differentially expressed inthe plants treated with gelatin capsules As the GSGOGATsystem is dependent upon the N-concentration in the tissueit may be that the concentration of NH

3in the tissue was not

high enough to upregulate gene involved in N-assimilation

42 NAC Transcription Factors NAC (NAM ATAF12 andCUC2) proteins are one of the largest families of plant-specific transcription factors and the family is present in awide range of plants with more than 100 predicted membersin Arabidopsis thaliana [64 65] Due to such large num-ber only a small portion of the NAC proteins has beencharacterized and yet the family has been implicated invarious plant processes including developmental programsdefense and abiotic responses [65] NAC proteins commonlyhave highly conserved sequences named NAC domains intheir N-terminal regions [66] NAC domains consist offive subdomains (AndashE) [67] and subdomains D and E arerequired for DNA-binding while the C-terminal regions canfunction as a transcriptional activation domain [64 68] NACproteins have been classified into 18 subgroups by similarityin the amino acid sequence in the NAC domains [69] TheNAC036 gene (Csa6G127320 Table 3) is one of the networkhub genes identified in theWGCNAanalysis and is amemberof theONAC022 subgroup RNAgel blot analysis has revealedthat NAC036 gene is strongly expressed in leaves and plantsoverexpressing NAC036 gene have a semidwarf phenotype[64] Kato et al [64] through microscopic observation deter-mined that dwarfing in these plants was due to reduction in

cell size however the mechanism by which overexpressionof NAC036 gene causes reduction of cell size is unclearMicroarray data has confirmed that expression of NAC036gene was induced by abiotic stress such as osmotic stressand salt stress which lead the authors to speculate that theoverexpression ofNAC036 leads to excessive stress responseswhich subsequently compromises cell growth In this studyNAC036 expression was downregulated in the treated plantsin T2-L2 which agrees with the leaf area data in which therewas an increase in leaf area in the treated plants in T2-L2 It ispossible that the NAC036 genes are involved in other abioticstress response pathways such as ABA SA and JA howeverthis relationship is unclear without further investigation

43 Detoxifying Proteins Plants are continually exposed topotentially toxic chemicals (xenobiotic) These chemicalscannot be used for nutrition or source of energy and thusplants have found a way to remove such compounds fromtheir system by either storing in a secure place (ie vacuole)or destroying them by biodegradation [70] The process ofchemical modification of xenobiotic compounds in plants isclassified by three phases phase I (activation reaction whichinvolves hydrolysis or oxidation) phase II (conjugation reac-tion) and phase III (compartmentalization and processing)In phase I the hydrolysis reactions are catalyzed by esterasesbut most of the reactions are oxidation which are catalyzedby cytochrome P450 system [70] In phase II the phase Iactivated metabolites are deactivated by covalent linkage toan endogenousmolecule such as glutathione to form awater-soluble conjugate [71] Glutathione S-transferase (GST) forinstance is a soluble enzyme that is often thought of asdetoxification enzyme with the ability to metabolize a widevariety xenobiotics via GHS conjugation [71ndash73] GSTs aregrouped into four classes phi zeta tau and theta Zeta andtheta GST are found in both animals and plants but tau andphi classes are only found in plants [73] Phi and tau GSTs areinduced after exposure to biotic and abiotic stressesTheGSTphi 8 (GSTF8 Csa7G395800 Table 3) was found to be highlyassociated with plant treated with gelatin capsules which wasupregulated in the second leaf of the treated plants during thesecond week after emergence (T2-L2)The hub gene GSTF8is used as a marker for early stress and defense responsesGSTF8 expression can be induced by a range of biotic andabiotic stresses including SA auxin herbicides andmicrobialinfections [74] The endogenous function of GSTF8 is stillpoorly understood It is cytosolic and highly expressed inroots where it may act to detoxify products of oxidative stressresulting from pathogen attach or foreign chemicals in thesoil [74]

The inactive water-soluble conjugates formed in phaseII are then exported from the cytosol by membrane-locatedtransport proteins such as plasma membrane intrinsic pro-tein 1C (PIP1C Csa5G53020 Supplementary Table 1) whichinitiate phase III the compartmentalization andprocessing ofthe detoxification system [70] The transport of glutathioneconjugates from the cytosol to the vacuole requires passingthrough the tonoplast The tonoplast intrinsic proteins andABC transporters are thought to be involved in this processThere were numerous genes associated with detoxifying


function in the list of genes that are highly associated withgelatin capsule treatments (Supplementary Table 1) suchas ABC protein 9 (NAP9 Csa1G181360) tonoplast intrinsicprotein 23 (TIP23 Csa7G447100) and tonoplast intrinsicprotein 2 (TIP2 Csa6G486670) The NAP9 and TIP2 geneswere upregulated in the second leaf of the treated plantduring the second week after emergence (T2-L2) whereasTIP23 was upregulated in the first leaf during the firstweek after emergence in the treated plants ABC transportersuperfamily mediates excretion of potentially toxic com-pounds conferring heavy-metal tolerance [75] The UDP-glycotransferase (UGT Csa4G618520 Supplementary Table1) a gene involved in biodegradation of xenobiotics is oneof the genes highly associated with gelatin capsule treatmentwhich further supports the hypothesis that gelatin capsuletreatment increases the expression of genes associated withdetoxification which allows for increased plant growth andaccumulation of biomass The UGT gene was upregulated inthe second leaf during the second week after emergence inthe treated plants It is possible that GSTF8 and other GSTsthat are upregulated in plants treated with gelatin capsuletreatments are involved in detoxifying products of oxidativestress in the root which allows for efficient uptake of aminoacids and nitrogen from the soil

5 Conclusions

In this study we confirmed that gelatin treatment of seedsenhanced the growth of cucumber seedlings although theenhancement effect was more significant in two-week-old plants than in one-week-old ones Based on com-parative RNA-seq data analyses the beneficial effect ofseed gelatin treatment could be defined by the differ-ential expression of the 620 DEGs between the treatedand nontreated control Further analysis of the 620 DEGsusing WGCNA suggested that the blue coexpression genenetwork module of 208 of 620 DEGs is the most rele-vant for the gelatin growth enhancement which is fea-tured with 16 most interconnected hub genes Membersof the 16 hub genes include a NAC transcription factor(Csa6G127320) a MYB transcription factor (Csa1G007850)an amino acid transporter (Csa5G615830) an ammo-nium transporter (Csa2G163170) a xenobiotic detoxifier-glutathione S-transferase (Csa7G395800) and others Theseresults suggested that the increased expression of amino acidand nitrogen transporter genes and the xenobiotic detoxifica-tion system involved genes and their possible transcriptionalregulation through the two transcription factors might be animportant mechanism explaining the enhanced growth andincreased abiotic stress tolerance of gelatin seed treatment

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This project was partially supported by a grant from AllianceSeedCapsules a joint venture of SeedCoating Inc and Sakata

Seed Sudamerica Ltda and the United States Multi-StateProject W-2168

References

[1] K L Takahashi and J Trias ldquoPromotion of plant growth usingcollagen-based gelatinrdquoWO2012109522A1 PCTUS2012024172012

[2] E Kunicki A Grabowska A Sekara and R WojciechowskaldquoThe effect of cultivar type time of cultivation and biostimulanttreatment on the yield of spinach (Spinacia oleracea L)rdquo FoliaHorticulturae vol 22 no 2 2010

[3] R Bulgari G Cocetta A Trivellini P Vernieri and A FerranteldquoBiostimulants and crop responses a reviewrdquoBiological Agricul-ture and Horticulture vol 31 no 1 pp 1ndash17 2015

[4] V Ziosi R Zandoli A Di Nardo S Biondi F Antognoniand F Calandriello ldquoBiological activity of different botanicalextracts as evaluated bymeans of an array of in vitro and in vivobioassaysrdquo Acta Horticulturae vol 1009 pp 61ndash66 2012

[5] P du Jardim ldquoThe science of plant biostimulantsmdasha biblio-graphic analysis Contract 30-CE045551500-96 ad hoc studyon bio-stimulants productsrdquo 2012

[6] European Biostimulants Industry Council 2014 httpwwwbiostimulantseu

[7] J Parrado J Bautista E J Romero A M Garcıa-Martınez VFriaza andMTejada ldquoProduction of a carob enzymatic extractpotential use as a biofertilizerrdquo Bioresource Technology vol 99no 7 pp 2312ndash2318 2008

[8] A Koukounaras P Tsouvaltzis and A S Siomos ldquoEffect of rootand foliar application of amino acids on the growth and yieldof greenhouse tomato in different fertilization levelsrdquo Journal ofFood Agriculture and Environment vol 11 no 2 pp 644ndash6482013

[9] J P Morales-Payan and W M Stall ldquoPapaya (Carica papaya)response to foliar treatments with organic complexes of pep-tides and amino acidsrdquo Proceedings of the Florida State Horti-cultural Society vol 116 pp 30ndash31 2003

[10] A Ertani M Schiavon A Muscolo and S Nardi ldquoAlfalfaplant-derived biostimulant stimulate short-term growth of saltstressed Zea mays L plantsrdquo Plant and Soil vol 364 no 1-2 pp145ndash158 2013

[11] A Ertani D Pizzeghello A Altissimo and S Nardi ldquoUseof meat hydrolyzate derived from tanning residues as plantbiostimulant for hydroponically grown maizerdquo Journal of PlantNutrition and Soil Science vol 176 no 2 pp 287ndash295 2013

[12] A Grabowska E Kunicki A Sękara A Kalisz and R Woj-ciechowska ldquoThe effect of cultivar and biostimulant treatmenton the carrot yield and its qualityrdquo Vegetable Crops ResearchBulletin vol 77 no 1 pp 37ndash48 2012

[13] G Colla E Svecova Y Rouphael et al ldquoEffectiveness of a plant-derived protein Hydrolysate to improve crop performancesunder different growing conditionsrdquo Acta Horticulturae vol1009 pp 175ndash180 2012

[14] L Lucini Y Rouphael M Cardarelli R Canaguier P Kumarand G Colla ldquoThe effect of a plant-derived biostimulant onmetabolic profiling and crop performance of lettuce grownunder saline conditionsrdquo Scientia Horticulturae vol 182 pp124ndash133 2015

[15] M Boehme Y Schevschenko and I Pinker ldquoUse of biostim-ulators to reduce abiotics stress in cucumber plants (Cucumissativus L)rdquo Acta Horticulturae vol 774 pp 339ndash344 2008


[16] M Boehme J Schevtschenko and I Pinker ldquoPlant nutritionmdasheffect of biostimulators on growth of vegetables in hydroponicalsystemsrdquo Acta Horticulturae vol 697 pp 337ndash344 2005

[17] A Przybysz H Gawronska and J Gajc-Wolska ldquoBiologicalmode of action of a nitrophenolates-based biostimulant casestudyrdquo Frontiers in Plant Science vol 5 article 713 2014

[18] N Parađikovic T Vinkovic I Vinkovic Vrcek I Zuntar MBojic and M Medic-Saric ldquoEffect of natural biostimulants onyield and nutritional quality an example of sweet yellow pepper(CapsicumannuumL) plantsrdquo Journal of the Science of Food andAgriculture vol 91 no 12 pp 2146ndash2152 2011

[19] A Petrozza A Santaniello S Summerer et al ldquoPhysiologi-cal responses to Megafol treatments in tomato plants underdrought stress a phenomic and molecular approachrdquo ScientiaHorticulturae vol 174 no 1 pp 185ndash192 2014

[20] G L Kauffman III D P Kneivel and T L Watschke ldquoEffectsof a biostimulant on the heat tolerance associated with photo-synthetic capacity membrane thermostability and polyphenolproduction of perennial ryegrassrdquo Crop Science vol 47 no 1pp 261ndash267 2007

[21] K C Jisha and J T Puthur ldquoSeed priming with BABA (120573-aminobutyric acid) a cost-effective method of abiotic stress tolerancein Vigna radiata (L) Wilczekrdquo Protoplasma 2015

[22] M Schiavon A Ertani and S Nardi ldquoEffects of an alfalfaprotein hydrolysate on the gene expression and activity ofenzymes of the tricarboxylic acid (TCA) cycle and nitrogenmetabolism in Zea mays Lrdquo Journal of Agricultural and FoodChemistry vol 56 no 24 pp 11800ndash11808 2008

[23] A Ertani L Cavani D Pizzeghello et al ldquoBiostimulant activ-ity of two protein hydrolyzates in the growth and nitrogenmetabolism of maize seedlingsrdquo Journal of Plant Nutrition andSoil Science vol 172 no 2 pp 237ndash244 2009

[24] P Maini ldquoThe experience of the first biostimulant based onamino acids and peptides a short retrospective review on thelaboratory researches and practival resultsrdquo Fertilitas Agrorumvol 1 pp 29ndash43 2006

[25] P Calvo L Nelson and J W Kloepper ldquoAgricultural uses ofplant biostimulantsrdquo Plant and Soil vol 383 pp 3ndash41 2014

[26] S Vaccaro A Ertani A Nebbioso et al ldquoHumic substancesstimulate maize nitrogen assimilation and amino acid me-tabolism at physiological and molecular levelrdquo Chemical andBiological Technologies in Agriculture vol 2 no 1 pp 1ndash12 2015

[27] Z Li Z Zhang P Yan S Huang Z Fei and K Lin ldquoRNA-Seqimproves annotation of protein-coding genes in the cucumbergenomerdquo BMC Genomics vol 12 article 540 2011

[28] K A Baggerly L Deng J SMorris andCM Aldaz ldquoDifferen-tial expression in SAGE accounting for normal between-libraryvariationrdquo Bioinformatics vol 19 no 12 pp 1477ndash1483 2003

[29] P Langfelder and S Horvath ldquoWGCNA an R package forweighted correlation network analysisrdquo BMC Bioinformaticsvol 9 article 559 2008

[30] C A Hollender C Kang O Darwish et al ldquoFloral transcrip-tomes in woodland strawberry uncover developing receptacleand anther gene networksrdquo Plant Physiology vol 165 no 3 pp1062ndash1075 2014

[31] F M You N Huo Y Q Gu et al ldquoBatchPrimer3 a highthroughput web application for PCR and sequencing primerdesignrdquo BMC Bioinformatics vol 9 article 253 2008

[32] D Fraga T Meulia and S Fenster ldquoReal-time PCRrdquo CurrentProtocolsmdashEssential Laboratory Techniques vol 10 pp 1031ndash10333 2008

[33] M W Pfaffl ldquoA new mathematical model for relative quantifi-cation in real-time RT-PCRrdquoNucleic Acids Research vol 29 no9 article e45 2001

[34] Y Assenov F Ramırez S E Schelhorn T Lengauer andM Albrecht ldquoComputing topological parameters of biologicalnetworksrdquo Bioinformatics vol 24 no 2 pp 282ndash284 2008

[35] G Balian and J H Bowes ldquoThe structure and properties ofcollagenrdquo inThe Science and Technology of Gelatin A G Wardand A Courts Eds pp 1ndash27 Academic Press London UK1977

[36] R Schrieber and H Gareis Gelatin Handbook Theory andIndustrial Practice Wiley 2007

[37] J M Regenstein and G Boran ldquoFish gelatinrdquo Advances in Foodand Nutrition Research vol 60 pp 119ndash143 2010

[38] T Nasholm K Kielland and U Ganeteg ldquoUptake of organicnitrogen by plantsrdquo New Phytologist vol 182 no 1 pp 31ndash482009

[39] S Schmidt and G R Stewart ldquoGlycine metabolism by plantroots and its occurrence in Australian plant communitiesrdquoAustralian Journal of Plant Physiology vol 26 no 3 pp 253ndash264 1999

[40] B Thornton S M Osborne E Paterson and P Cash ldquoAproteomic and targeted metabolomic approach to investigatechange in Lolium perenne roots when challenged with glycinerdquoJournal of Experimental Botany vol 58 no 7 pp 1581ndash15902007

[41] H-J Wang L-H Wu M-Y Wang Y-H Zhu Q-N Tao andF-S Zhang ldquoEffects of amino acids replacing nitrate on growthnitrate accumulation and macroelement concentrations inPak-choi (Brassica chinensis L)rdquo Pedosphere vol 17 no 5 pp595ndash600 2007

[42] X-L Wang W-J Yu Q Zhou R-F Han and D-F HuangldquoMetabolic response of Pakchoi leaves to amino acid nitrogenrdquoJournal of Integrative Agriculture vol 13 no 4 pp 778ndash7882014

[43] A Ortiz-Lopez H-C Chang and D R Bush ldquoAmino acidtransporters in plantsrdquo Biochimica et Biophysica Acta vol 1465no 1-2 pp 275ndash280 2000

[44] X Liu and D R Bush ldquoExpression and transcriptional regula-tion of amino acid transporters in plantsrdquo Amino Acids vol 30no 2 pp 113ndash120 2006

[45] M G GuoMolecular and Genomic Analysis of Nitrogen Regula-tion of Amino Acid Permease I (AAP1) in Arabidopsis Universityof Illinois at Urbana-Champaign 2004

[46] WN Fischer B Andre D Rentsch et al ldquoAmino acid transportin plantsrdquoTrends in Plant Science vol 3 no 5 pp 188ndash195 1998

[47] C SchobertW Kockenberger and E Komor ldquoUptake of aminoacids by plants from the soil a comparative study with castorbean seedlings grown under natural and axenic soil conditionsrdquoPlant and Soil vol 109 no 2 pp 181ndash188 1988

[48] S Okumoto R Schmidt M Tegeder et al ldquoHigh affinity aminoacid transporters specifically expressed in xylem parenchymaand developing seeds of Arabidopsisrdquo The Journal of BiologicalChemistry vol 277 no 47 pp 45338ndash45346 2002

[49] S Okumoto W Koch M Tegeder et al ldquoRoot phloem-specificexpression of the plasma membrane amino acid proton co-transporter AAP3rdquo Journal of Experimental Botany vol 55 no406 pp 2155ndash2168 2004

[50] H H Marella E Nielsen D P Schachtman and C G TaylorldquoThe amino acid permeases AAP3 and AAP6 are involvedin root-knot nematode parasitism of Arabidopsisrdquo MolecularPlant-Microbe Interactions vol 26 no 1 pp 44ndash54 2013


[51] W-N FischerDD F LooWKoch et al ldquoLow andhigh affinityamino acidH+-cotransporters for cellular import of neutral andcharged amino acidsrdquo Plant Journal vol 29 no 6 pp 717ndash7312002

[52] D Rentsch B Hirner E Schmelzer and W B Frommer ldquoSaltstress-induced proline transporters and salt stress-repressedbroad specificity amino acid permeases identified by suppres-sion of a yeast amino acid permease-targeting mutantrdquo PlantCell vol 8 no 8 pp 1437ndash1446 1996

[53] E Hunt S Gattolin H J Newbury et al ldquoA mutation inamino acid permease AAP6 reduces the amino acid contentof the Arabidopsis sieve elements but leaves aphid herbivoresunaffectedrdquo Journal of Experimental Botany vol 61 no 1 pp55ndash64 2010

[54] T Niittyla A T Fuglsang M G PalmgrenW B Frommer andW X Schulze ldquoTemporal analysis of sucrose-induced phospho-rylation changes in plasma membrane proteins of ArabidopsisrdquoMolecular amp Cellular Proteomics vol 6 no 10 pp 1711ndash17262007

[55] V Vitart I Baxter P Doerner and J F Harper ldquoEvidence fora role in growth and salt resistance of a plasma membrane H+-ATPase in the root endodermisrdquo Plant Journal vol 27 no 3 pp191ndash201 2001

[56] N D Dewitt B Hong M R Sussman and J F HarperldquoTargeting of two Arabidopsis H+-ATPase isoforms to theplasma membranerdquo Plant Physiology vol 112 no 2 pp 833ndash844 1996

[57] J F Harper L Manney and M R Sussman ldquoThe plasmamembrane H+-ATPase gene family in Arabidopsis genomicsequence of AHA10 which is expressed primarily in developingseedsrdquo Molecular amp General Genetics vol 244 no 6 pp 572ndash587 1994

[58] K J Boorer W B Frommer D R Bush M Kreman D D FLoo and E M Wright ldquoKinetics and specificity of a H+aminoacid transporter from Arabidopsis thalianardquo The Journal ofBiological Chemistry vol 271 no 4 pp 2213ndash2220 1996

[59] K J Boorer andW N Fischer ldquoSpecificity and stoichiometry ofthe Arabidopsis H+amino acid transporter AAP5rdquoThe Journalof Biological Chemistry vol 272 no 20 pp 13040ndash13046 1997

[60] D Loque andN vonWiren ldquoRegulatory levels for the transportof ammonium in plant rootsrdquo Journal of Experimental Botanyvol 55 no 401 pp 1293ndash1305 2004

[61] B Neuhauser M Dynowski and U Ludewig ldquoChannel-likeNH3 flux by ammonium transporter AtAMT2rdquo FEBS Lettersvol 583 no 17 pp 2833ndash2838 2009

[62] C Sohlenkamp C C Wood G W Roeb and M K UdvardildquoCharacterization of Arabidopsis AtAMT2 a high-affinityammonium transporter of the plasma membranerdquo Plant Physi-ology vol 130 no 4 pp 1788ndash1796 2002

[63] S Khademi J I OrsquoConnell J Remis Y Robles-ColmenaresL J W Miercke and R M Stroud ldquoMechanism of ammoniatransport by AmtMEPRh structure of AmtB at 135 ArdquoScience vol 305 no 5690 pp 1587ndash1594 2004

[64] H Kato T Motomura Y Komeda T Saito and A KatoldquoOverexpression of the NAC transcription factor family geneANAC036 results in a dwarf phenotype inArabidopsis thalianardquoJournal of Plant Physiology vol 167 no 7 pp 571ndash577 2010

[65] A N Olsen H A Ernst L L Leggio and K Skriver ldquoNACtranscription factors structurally distinct functionally diverserdquoTrends in Plant Science vol 10 no 2 pp 79ndash87 2005

[66] M Aida T Ishida H Fukaki H Fujisawa and M TasakaldquoGenes involved in organ separation in Arabidopsis an analysis

of the cup-shaped cotyledon mutantrdquo Plant Cell vol 9 no 6pp 841ndash857 1997

[67] K Kikuchi M Ueguchi-Tanaka K T Yoshida Y Nagato MMatsusoka and H-Y Hirano ldquoMolecular analysis of the NACgene family in ricerdquo Molecular and General Genetics vol 262no 6 pp 1047ndash1051 2000

[68] M Duval T-F Hsieh S Y Kim and T L Thomas ldquoMolecularcharacterization of AtNAM a member of the Arabidopsis NACdomain superfamilyrdquo Plant Molecular Biology vol 50 no 2 pp237ndash248 2002

[69] H Ooka K Satoh K Doi et al ldquoComprehensive analysis ofNAC family genes in Oryza sativa and Arabidopsis thalianardquoDNA Research vol 10 no 6 pp 239ndash247 2003

[70] J O D Coleman M M A Blake-Kalff and T G E DaviesldquoDetoxification of xenobiotics by plants chemical modificationand vacuolar compartmentationrdquo Trends in Plant Science vol2 no 4 pp 144ndash151 1997

[71] M C J Wilce and M W Parker ldquoStructure and functionof glutathione S-transferasesrdquo Biochimica et Biophysica ActamdashProtein Structure andMolecular Enzymology vol 1205 no 1 pp1ndash18 1994

[72] D P Dixon and R Edwards ldquoGlutathione transferasesrdquo TheArabidopsis Book vol 8 no 8 Article ID e0131 2010

[73] D P Dixon A Lapthorn and R Edwards ldquoPlant glutathionetransferasesrdquo Genome Biology vol 3 2002

[74] L FThatcher C Carrie C R Andersson K SivasithamparamJ Whelan and K B Singh ldquoDifferential gene expression andsubcellular targeting of Arabidopsis glutathione S-transferaseF8 is achieved through alternative transcription start sitesrdquoJournal of Biological Chemistry vol 282 no 39 pp 28915ndash28928 2007

[75] E Martinoia M Klein M Geisler et al ldquoMultifunctionalityof plant ABC transportersmdashmore than just detoxifiersrdquo Plantavol 214 no 3 pp 345ndash355 2002

Submit your manuscripts athttpwwwhindawicom

Nutrition and Metabolism

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Food ScienceInternational Journal of

Agronomy


International Journal of



Microbiology

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

AgricultureAdvances in


PsycheHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

BiodiversityInternational Journal of


ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

GenomicsInternational Journal of


Plant GenomicsInternational Journal of


Biotechnology Research International


Forestry ResearchInternational Journal of


Journal of BotanyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

EcologyInternational Journal of


Veterinary Medicine International


Cell BiologyInternational Journal of


Evolutionary BiologyInternational Journal of



mass [15 16] Atonik a synthetic biostimulant composed ofnitrophenolates have been shown to increase leaf area androot system development Plants treatedwith nitrophenolateshave been characterized as having greater inhibition of IAAoxidase which ensures a higher activity of naturally synthe-sized auxins [17] MEGAFOL a biostimulant composed ofa complex of vitamins amino acids proteins and betainespositively increased crop yield in sweet yellow pepper [18]The biostimulant also provided drought stress resistance intomato and MEGAFOL treated plants were able to recovermore quickly from drought stress Analyzing the expres-sion levels of drought-stress marker genes in tomato plantstreated with MEGAFOL demonstrated a lower expression ofdrought-related genes [19] An alfalfa plant-derived biostim-ulant increased maize plant biomass under salinity conditionand enhanced Na+ accumulation and reduced K+ accumu-lation in roots and leaves [10] Perennial ryegrass treatedwith an animal membrane hydrolysate Macro-Sorb Foliar(FOLIAR) when subjected to high air temperature stressexhibited increased photochemical efficiency and membranethermostability compared to plants without the treatment[20] Seed priming with BABA (120573-amino butyric acid) anonprotein amino acid reduced the abiotic stress in Vignaradiate by enhancing photosynthesis and proline accumula-tion and antioxidant enzyme activities in seedlings subjectedto NaClPEG [21]

Protein hydrolysate was shown to stimulate carbon andnitrogen metabolism and increase nitrogen assimilation inplants [22 23] A biostimulant containing amino acid Ami-noplant enhanced the nitrate reductase activity in spinach[2] NAD-dependent glutamate dehydrogenase nitrate re-ductase and malate dehydrogenase in maize had higheractivities following application of animal epithelial hydrol-ysate [24] Alfalfa protein hydrolysate applied to hydro-ponically grown maize increased the activity of malatedehydrogenase isocitrate dehydrogenase and citrate syn-thase which are enzymes found in the TCA cycle as wellas nitrogen metabolism enzymes nitrate reductase nitritereductase glutamine glutamine synthetase (GS) glutaminesynthase and aspartate aminotransferase [22] Ertani et al[23] reported that both alfalfa protein hydrolysate and animalconnective tissue hydrolysate stimulated plant growth andalso increased nitrate conversion into organic nitrogen byinducing nitrate reductase and GS activities The treatmentsespecially enhanced theGS2 isoform which is responsible forassimilation of ammonia produced by nitrate reduction thusconfirming that protein hydrolysate enhances plant growthby upregulating nitrate assimilation [23 25] Similarly Vac-caro et al [26] demonstrated that low concentration of humicacid positively influenced nitrate metabolism by increasingthe content of soluble protein and amino acid synthesiswhich was stimulated by significant increase in activity andtranscription of enzymes functioning in N assimilation andKrebs cycle

Seed encapsulation using gelatin capsules is a novelapproach as a seed treatment to enhance plant growth [1]The effect of gelatin applied at time of sowing on cucumberplant increased leaf surface area and fresh and dry weightas compared to the nontreated control and increased salinity

tolerance in plants treated with gelatin capsules (Wilson andTaylor unpublished) However the underlying molecularmechanisms of the plant growth promotion by proteinhydrolysate are unknown The objective of this study wasto characterize the effect of gelatin capsules on cucumbergrowth and development at the transcriptome level usingmRNA sequencing (RNA-seq) based genome-wide geneexpression profiling approach

2 Materials and Methods

21 Plant Materials and Evaluation of Growth and NitrogenContent Cucumber seeds ldquoVlaspikrdquo (Seminis Oxnard CA)were planted in a controlled greenhouse maintained at24∘C21∘C temperature with 1410-hour photoperiod at NewYork State Agricultural Experiment Station in Geneva NewYork in the winter of 2013 Two size 3 gelatin capsules(Capsule Line Pompano Beach FL) were placed adjacentto each seed in a 4-inch pot (Supplementary Figure 1A)these are referred to as treated plants Capsules were placedadjacent to the seeds to prevent decrease in germinationrate and for controlling the amount of gelatin used in thetreatment Total weight of two gelatin capsules was 937mgwith a nitrogen content of 142mg and protein contentof 800mg The nontreated control plants did not receivegelatin capsule treatment Thirty-two plants (16 control and16 treated plants) were placed in the greenhouse followinga completely randomized design First (L1) and second (L2)true leaves from 8 plants in each treatment group weresampled at each of two different time points one (T1) andtwo (T2) weeks after emergence Total leaf area wasmeasuredusing a CI-202 Leaf Area Meter (CID Bio-Science CamasWA) and fresh weight was determined Samples were flash-frozen in liquid nitrogen and stored atminus80∘C Frozen sampleswere weighed to determine frozen weight (for approximatingdry weight) A subsample (sim100mg) of the frozen leaf tissuewas placed in an oven to dry at 100∘C over night and sentto the Cornell University Stable Isotope Laboratory (IthacaNY) for elemental analysis of N by combustion method Allsampling data were then statistically analyzed by ANOVA(120572 = 005) and Tukeyrsquos HSD test was then used to determinesignificance

22 RNA Isolation and Strand-Specific RNA-seq Library Con-struction and Sequencing Three biological replicates of eachtreatment of each leaf (L1 and L2) at each time point (T1and T2) were selected for RNA-seq analysis a total of 24samples (two treatments two time points two leaves andthree biological replicates) Total RNA was isolated fromsim5 g of ground leaf tissue using the Spectrum Plant TotalRNA Kit (Sigma Aldrich St Louis MO) following themanufacturerrsquos protocol The isolated RNA quantity andquality were evaluated by electrophoresis (2 agarose gel)followed by ethidium bromide staining and quantification byNanodrop 1000 (Thermo Scientific Waltham MA)

A 5 120583g subsample of the isolated total RNA from eachsample was treated with 1 120583L DNase I (Invitrogen CarlsbadCA) incubated at RT for 15 minutes followed by 70∘C for 10minutes The DNase treated total RNA samples were used to














Uniquelymappedreads


reference ()







3 Results



B

A

A

A

0

5

10

15

20

25

30

35

40

45

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(a)

A

B

A

A

0

01

02

03

04

05

06

07

08

Time 1 Time 2

Froz

en w

eigh

t (g)

Control2 capsules

(b)

B B

AA

0

20

40

60

80

100

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(c)

A

B

A

A

0

2

4

6

8

10

12

Time 1 Time 2

Nitr

ogen

cont

ent (

mg)

Control2 capsules

(d)

A

B

A

A

0

05

1

15

2

25

3

35

4

45

5

Time 1

Control2 capsules

Time 2

Fres

h w

eigh

t (g)

(e)














TrT1

L2_1

2CK

T1L2

_4CK

T1L2

_5Tr

T1L2

_11

CKT1

L2_6

TrT1

L2_1

0CK

T2L1

_13

CKT2

L1_1

5Tr

T2L1

_20

TrT2

L1_1

9CK

T2L1

_14

TrT2

L1_2

1CK

T1L1

_1CK

T1L1

_2Tr

T1L1

_7CK

T1L1

_3Tr

T1L1

_8Tr

T1L1

_9CK

T2L2

_18

CKT2

L2_1

6CK

T2L2

_17

TrT2

L2_2

4Tr

T2L2

_22

TrT2

L2_2

3

0

50

150

250

Hei

ght


02

04

06

08

Hei

ght

Module colors









minus1

minus05

0

TLA FW DW PecentN

05

1MEblue

MEyellow

MEbrown

MEturquoise

MEgrey

086 064 064 085

067 059(0002)

059(0002)

068

minus011(06)

minus061(0002)

minus061(0002)

minus018(04)


minus011(06)

minus077

minus024(03)

minus013(05)

minus013(05)

minus017(04)





FW DW

MEy

ello

w

MEb

lue

TLA

Perc

entN

MEb

row

MEt

urqu

oise

00

10

0

02

04

06

08

1FWDW

FW DW

TLAPercentN

TLA

Perc

entN




Gen

e sig

nific

ance

for T

LA

09

08

07

06

05

04

03

09

08

07

06

05

04

07

05

03

01




Gen

e sig

nific

ance

for P

erce

ntN

Gen

e sig

nific

ance

for F

W




cor = 053 p = 18e minus 16









92

1

(deg

)



4 Discussion








0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014





































Uniquelymappedreads


reference ()







3 Results



B

A

A

A

0

5

10

15

20

25

30

35

40

45

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(a)

A

B

A

A

0

01

02

03

04

05

06

07

08

Time 1 Time 2

Froz

en w

eigh

t (g)

Control2 capsules

(b)

B B

AA

0

20

40

60

80

100

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(c)

A

B

A

A

0

2

4

6

8

10

12

Time 1 Time 2

Nitr

ogen

cont

ent (

mg)

Control2 capsules

(d)

A

B

A

A

0

05

1

15

2

25

3

35

4

45

5

Time 1

Control2 capsules

Time 2

Fres

h w

eigh

t (g)

(e)














TrT1

L2_1

2CK

T1L2

_4CK

T1L2

_5Tr

T1L2

_11

CKT1

L2_6

TrT1

L2_1

0CK

T2L1

_13

CKT2

L1_1

5Tr

T2L1

_20

TrT2

L1_1

9CK

T2L1

_14

TrT2

L1_2

1CK

T1L1

_1CK

T1L1

_2Tr

T1L1

_7CK

T1L1

_3Tr

T1L1

_8Tr

T1L1

_9CK

T2L2

_18

CKT2

L2_1

6CK

T2L2

_17

TrT2

L2_2

4Tr

T2L2

_22

TrT2

L2_2

3

0

50

150

250

Hei

ght


02

04

06

08

Hei

ght

Module colors









minus1

minus05

0

TLA FW DW PecentN

05

1MEblue

MEyellow

MEbrown

MEturquoise

MEgrey

086 064 064 085

067 059(0002)

059(0002)

068

minus011(06)

minus061(0002)

minus061(0002)

minus018(04)


minus011(06)

minus077

minus024(03)

minus013(05)

minus013(05)

minus017(04)





FW DW

MEy

ello

w

MEb

lue

TLA

Perc

entN

MEb

row

MEt

urqu

oise

00

10

0

02

04

06

08

1FWDW

FW DW

TLAPercentN

TLA

Perc

entN




Gen

e sig

nific

ance

for T

LA

09

08

07

06

05

04

03

09

08

07

06

05

04

07

05

03

01




Gen

e sig

nific

ance

for P

erce

ntN

Gen

e sig

nific

ance

for F

W




cor = 053 p = 18e minus 16









92

1

(deg

)



4 Discussion








0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014

























B

A

A

A

0

5

10

15

20

25

30

35

40

45

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(a)

A

B

A

A

0

01

02

03

04

05

06

07

08

Time 1 Time 2

Froz

en w

eigh

t (g)

Control2 capsules

(b)

B B

AA

0

20

40

60

80

100

Leaf 1 Leaf 2

Control2 capsules

Tota

l lea

f are

a (cm

2)

(c)

A

B

A

A

0

2

4

6

8

10

12

Time 1 Time 2

Nitr

ogen

cont

ent (

mg)

Control2 capsules

(d)

A

B

A

A

0

05

1

15

2

25

3

35

4

45

5

Time 1

Control2 capsules

Time 2

Fres

h w

eigh

t (g)

(e)














TrT1

L2_1

2CK

T1L2

_4CK

T1L2

_5Tr

T1L2

_11

CKT1

L2_6

TrT1

L2_1

0CK

T2L1

_13

CKT2

L1_1

5Tr

T2L1

_20

TrT2

L1_1

9CK

T2L1

_14

TrT2

L1_2

1CK

T1L1

_1CK

T1L1

_2Tr

T1L1

_7CK

T1L1

_3Tr

T1L1

_8Tr

T1L1

_9CK

T2L2

_18

CKT2

L2_1

6CK

T2L2

_17

TrT2

L2_2

4Tr

T2L2

_22

TrT2

L2_2

3

0

50

150

250

Hei

ght


02

04

06

08

Hei

ght

Module colors









minus1

minus05

0

TLA FW DW PecentN

05

1MEblue

MEyellow

MEbrown

MEturquoise

MEgrey

086 064 064 085

067 059(0002)

059(0002)

068

minus011(06)

minus061(0002)

minus061(0002)

minus018(04)


minus011(06)

minus077

minus024(03)

minus013(05)

minus013(05)

minus017(04)





FW DW

MEy

ello

w

MEb

lue

TLA

Perc

entN

MEb

row

MEt

urqu

oise

00

10

0

02

04

06

08

1FWDW

FW DW

TLAPercentN

TLA

Perc

entN




Gen

e sig

nific

ance

for T

LA

09

08

07

06

05

04

03

09

08

07

06

05

04

07

05

03

01




Gen

e sig

nific

ance

for P

erce

ntN

Gen

e sig

nific

ance

for F

W




cor = 053 p = 18e minus 16









92

1

(deg

)



4 Discussion








0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014




































TrT1

L2_1

2CK

T1L2

_4CK

T1L2

_5Tr

T1L2

_11

CKT1

L2_6

TrT1

L2_1

0CK

T2L1

_13

CKT2

L1_1

5Tr

T2L1

_20

TrT2

L1_1

9CK

T2L1

_14

TrT2

L1_2

1CK

T1L1

_1CK

T1L1

_2Tr

T1L1

_7CK

T1L1

_3Tr

T1L1

_8Tr

T1L1

_9CK

T2L2

_18

CKT2

L2_1

6CK

T2L2

_17

TrT2

L2_2

4Tr

T2L2

_22

TrT2

L2_2

3

0

50

150

250

Hei

ght


02

04

06

08

Hei

ght

Module colors









minus1

minus05

0

TLA FW DW PecentN

05

1MEblue

MEyellow

MEbrown

MEturquoise

MEgrey

086 064 064 085

067 059(0002)

059(0002)

068

minus011(06)

minus061(0002)

minus061(0002)

minus018(04)


minus011(06)

minus077

minus024(03)

minus013(05)

minus013(05)

minus017(04)





FW DW

MEy

ello

w

MEb

lue

TLA

Perc

entN

MEb

row

MEt

urqu

oise

00

10

0

02

04

06

08

1FWDW

FW DW

TLAPercentN

TLA

Perc

entN




Gen

e sig

nific

ance

for T

LA

09

08

07

06

05

04

03

09

08

07

06

05

04

07

05

03

01




Gen

e sig

nific

ance

for P

erce

ntN

Gen

e sig

nific

ance

for F

W




cor = 053 p = 18e minus 16









92

1

(deg

)



4 Discussion








0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014

























Gen

e sig

nific

ance

for T

LA

09

08

07

06

05

04

03

09

08

07

06

05

04

07

05

03

01




Gen

e sig

nific

ance

for P

erce

ntN

Gen

e sig

nific

ance

for F

W




cor = 053 p = 18e minus 16









92

1

(deg

)



4 Discussion








0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014



























92

1

(deg

)



4 Discussion








0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014

























0123456

0

005

01

015

RNA-

seq

(RPK

M)

qRT-

PCR

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(a)

RNA-

seq

(RPK

M)

qRT-

PCR

01020304050

005

115

225

3

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(b)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

002040608

1

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(c)

RNA-

seq

(RPK

M)

qRT-

PCR

0

2

4

6

8

0

005

01

015

02

CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2


(d)

RNA-

seq

(RPK

M)

qRT-

PCR

024681012

001020304050607


CK-L1

CK-L1

CK-L1

Tr-L1

Tr-L1

Tr-L1

CK-L2

CK-L2

CK-L2

Tr-L2

Tr-L2

Tr-L2

(e)




N source from NO3






4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014



























4




4


4

+











5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014


























5 Conclusions




Acknowledgments



References

















































































Journal of




Agronomy





Microbiology




Volume 2014

























































































Journal of




Agronomy





Microbiology




Volume 2014
























research article transcriptome analysis of gelatin seed...

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