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. 2023 Jun 7;13(7):226. doi: 10.1007/s13205-023-03629-5

Transcriptome analysis during ToLCBaV disease development in contrasting tomato genotypes

Bhavya Chidambara 1,2, Gayathri Muthaiah 2, Avverahally T Sadashiva 3, M Krishna Reddy 4, Kundapura V Ravishankar 2,✉
PMCID: PMC10247599  PMID: 37304404

Abstract

Tomato leaf curl Bangalore virus (ToLCBaV) is one of the most important plant viruses. The infection causes substantial yield losses in tomato crop. The current viral disease management is based mainly on introgression of Ty locus into new tomato cultivars. Unfortunately, strains of the leaf curl virus have been evolving and are breaking Ty based tolerance in tomato. In this study, the defence response to ToLCBaV infection has been compared between contrasting tomato genotypes, resistant line (IIHR 2611; without any known Ty markers) and the susceptible line (IIHR 2843). We carried out comparative transcriptome profiling, and gene expression analysis in an effort to identify gene networks that are associated with a novel ToLCBaV resistance. A total of 22,320 genes were examined to identify differentially expressed genes (DEGs). We found that 329 genes of them were expressed significantly and differentially between ToLBaV-infected samples of both IIHR 2611 and IIHR 2843. A good number of DEGs were related to defence response, photosynthesis, response to wounding, toxin catabolic process, glutathione metabolic process, regulation of transcription DNA-template, transcription factor activity, and sequence-specific DNA binding. A few selected genes such as, nudix hydrolase 8, MIK 2-like, RING-H2 finger protein ATL2-like, MAPKKK 18-like, EDR-2, SAG 21 wound-induced basic protein, GRXC6 and P4 were validated using qPCR. The pattern of gene expression was significantly different in resistant and susceptible plants during disease progression. Both positive and negative regulators of virus resistance were found in the present study. These findings will facilitate breeding and genetic engineering efforts to incorporate novel sources of ToLCBaV resistance in tomatoes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03629-5.

Keywords: ToLCBaV, RNA sequencing, Transcriptome, Gene expression, Virus resistance

Introduction

Viral diseases are major limiting factors in crop plant yield. It has been reported that over 136 viral species infect the tomato crop. Among them, the tomato leaf curl virus poses a greater threat to tomato production worldwide (Hanssen et al. 2010). In southern India, the rapid spread of the dominant tomato virus, Tomato leaf curl Bangalore virus (ToLCBaV—a monopartite begomovirus), often causes complete failure of tomato crops (Reddy et al. 2005a, b; Chowda-Reddy et al. 2012). Strategies based on the genetic resistance of the host plant have been most efficient and cost-effective in control of the viral disease spread.

In recent years, studies on resistance to Tomato yellow leaf curl virus (TYLCV) have led to the identification of six different resistant loci. Among them, Ty 1 and Ty 3 are allelic, coding for RNA-dependent RNA polymerases. (Verlaan et al. 2013). Ty 2 encodes an NB-LRR gene (Nucleotide-binding–leucine-rich repeat) (Yang et al. 2014; Yamaguchi et al. 2018). The resistance gene Ty 4 is reported to modulate TYLCV resistance (Ji et al. 2009), while the recessive resistant gene ty 5 is linked to SlNAC1 with the corresponding candidate gene pelota (Wang et al. 2018).

Existing breeding programmes have been focused on introgression of Ty 1/Ty 3, and Ty 2 loci into cultivated tomatoes. Unfortunately, a number of Ty resistance-breaking strains of leaf curl virus have been evolving over the years. Breakdown of Ty 2-mediated resistance has been reported for TYLSCV, a Sardinian strain of TYLCV (Barbieri et al. 2010), and TYLCV-Mld, a mild strain of TYLCV (Ohnishi et al. 2016). Ty 1-based resistance was anticipated to be easily compromised to a significant extent under TYLCD pressure and the association of a DNA betasatellite with the virus (Garcia-Cano et al. 2008; Gelbart et al. 2020). Thus, it is necessary to search for new genetic resources, particularly wild tomato relatives, for a novel source of resistance to address this problem. It has been an ongoing effort to evaluate germplasm for leaf curl virus resistance (Camara et al. 2013; Al-Shihi et al. 2018) and further understand the resistance mechanism using genomic approaches. The introgression of these identified novel sources of resistance into the susceptible tomato cultivars could serve well to counter virus emergence.

Tomato plants infected with TYLCV exhibit yellowing of leaves with stunted plant growth, attributed to the regulation of genes related to photosynthesis (Seo et al. 2018). Plants respond by inducing specific transcripts as a defensive reaction to stop the multiplication and spread of the virus. The resistance response is either through virus-specific resistance genes or general resistance that work against a wide range of viruses infecting (Ronde et al. 2014). In an attempt to unearth the resistance response during ToLCBaV disease development, comparative transcriptome analysis of differentially expressed gene (DEG) profiles in both resistant (IIHR-2611) and susceptible (IIHR-2843) plants was done. IIHR-2611 has not shown any amplification of bands for any of the reported Ty-specific primers/markers and is hence considered a novel source of resistance to begomovirus (Sadashiva et al. 2017). Here RNA seq. analysis from pooled sample captures the overall pattern of disease response in contrasting genotypes, while qPCR validation of a few probable candidate genes reveal the temporal pattern of genes during disease progression.

Materials and methods

Plant materials

Two contrasting tomato genotypes, IIHR 2611 (resistant) and IIHR 2843 (susceptible), for ToLCBaV response were grown in greenhouse conditions. At the seedling stage (10 days old), plants were subjected to whitefly (Bemisia tabaci)-mediated ToLCBaV infection (Singh et al. 2015). Leaf samples were collected at 0, 3, 5, 9, 15 and 21 days following inoculation (DPI).

ToLCBaV DNA isolation and quantification

The viral genome concentration was estimated by following Kaushal et al. (2020). Genomic DNA was isolated from control and infected resistant (R) and susceptible (S) plants using the silicon dioxide matrix method according to Li et al. (2010) from each interval seperatly. The DNA was quantified using Nabi UV/Vis Nano Spectrophotometer (MicroDigitalCo., Ltd. Korea) by measuring absorbance at 260 nm. The DNA of 100 ng was used as a template with 3 pmol/l of each primer (ToLCBaV CP gene), and TB Green Premix Ex Taq II was included in the reaction mixture (Cat No. RR820A, TaKaRa, Japan). For quantitative real-time PCR (qPCR), the Quant StudioTM 7 Flex Real-Time PCR System (Applied Biosystems, USA) was used with the following PCR cycle conditions: incubation at 95 °C for 15 min and 45 cycles of 95 °C for 15 s (denaturation), 55 °C for 30 s (annealing) and 72 °C for 30 s (extension). At the end of PCR amplification a melt curve was generated at 55 °C for 1 min, 95 °C for 1 min, 60 °C for 1 min 30 s and 95 °C for 15 s. Three biological and three technical replicates were run in parallel for each sample. A negative control corresponding to non-inoculated plants was used in each PCR assay and the quantities of viral DNA were expressed in log 10 values.

RNA extraction, RNA-Seq library construction and sequencing

Total RNA was isolated at the time intervals of 0, 3, 5, 9, 15 and 21 DPI for RNA-seq analysis (Fig. 1) with three biological replications of each sample using RNA iso-Plus (TAKARA, BIO INC. Japan). The total RNA isolated from different samples was quantified using NABI UV/Vis Nano Spectrometer. The total RNA of control and inoculated plants from all the intervals at the concentration of 100 ng/μl each were pooled separately into four different samples as resistant control (RC), resistant infected (RI), susceptible control (SC) and susceptible infected (SI). The libraries were prepared from the pooled RNA samples and sequenced on an Illumina Novaseq sequencing platform with 150-bp paired-end reads following the manufacturer’s instructions for RNA-sequencing at M/S Eurofins Genomics facility, Bengaluru. The raw reads were filtered to obtain the clean reads by removing adaptors and uncertain nucleotides N > 10% and also reads with low-quality nucleotides (base quality < 5 and Q score > 50%). The summary of raw sequence data and read alignment statistics are given in supplementary Tables 1 and 2. The RNA sequence data of both control and infected tomato (IIHR 2611 and IIHR 2843) have been submitted to NCBI (SRR 13493714).

Fig. 1.

Fig. 1

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HYPERLINK "sps:id::fig1||locator::gr1||MediaObject::0"Schematic workflow of RNA-Seq of IIHR-2611 (resistant) and IIHR-2843 (susceptible) genotypes contrasting for ToLCBV resistance

DEGs, GO and pathway analysis

The assembled and cured reads were mapped onto indexed Solanum lycopersicum reference genome (SL3.0) using Hisat v2 aligner (Kim et al. 2015). On an average, 98.0% of the reads aligned to the reference genome. Differential expression analysis of genes was carried out using the DESeq2 package (Love et al. 2014). The infected plants were compared to the control samples. Genes with absolute log2 fold change ≥ 2 and p value ≤ 0.05 were considered as significant. The Upset R package software (Lex et al. 2014) was used to generate plots showing overlapping significant genes between treatments. The expression profile of differentially expressed genes (DEGs) across the samples is presented in volcano plots (Supplementary Fig. 1). Significant DEGs were used for Gene Ontology (GO) and pathway enrichment analysis. Enrichment analysis and KEGG pathway were performed using DAVID R package software (Yu et al. 2009). The GO and pathway terms with multiple test adjusted p value ≤ 0.05 are considered significant. To visualize the GO enrichment results, GO plot R package software (Walter et al. 2015) was used.

Quantitative real-time PCR validation

Genes such as nudix hydrolase 8 (LOC101261537), protein SENESCENCE-ASSOCIATED GENE 21 (SAG 21; LOC101259340), MDIS1-interacting receptor like kinase 2-like (MIK 2; LOC109120148), mitogen-activated protein kinase kinase kinase 18-like (MAPKKK 18; LOC101266899), RING-H2 finger protein ATL2-like (LOC101267557), wound-induced basic protein (LOC101251692), protein ENHANCED DISEASE RESISTANCE 2 (EDR 2; LOC101263218), glutaredoxin-C6 (GRXC 6; LOC101251848) and P4 were selected to examine their expression pattern in comparison to reference gene elongation factor 1 α (Lacerda et al. 2015) during the disease development stages. cDNA was synthesized using the Revert Aid First Strand cDNA synthesis kit (Thermo Scientific, #K1621) following the manufacturer's instructions. The resulting cDNA was subjected to qPCR using a Quantstudio 7 Flex thermal cycler (Applied Biosystems) using the intercalation dye TB Green Premix Ex Taq II (TaKaRa; Cat# RR820A) with gene-specific primers (primer sequences are listed in Supplementary Table 3). Three biological replicates and three technical replicates were used per sample and qPCR data were calculated as log2-fold changes (Livak and Schmittgen 2001).

Results

Dynamics of ToLCBaV DNA accumulation during disease development

Contrasting genotypes (IIHR-2611 and IIHR-2843) infected with ToLCBaV were sampled for genomic DNA isolation at different disease development intervals and observed for disease symptoms. Typical disease symptoms, such as slight yellowing, leaf curling and cupping, and stunted seedling growth were observed in the susceptible plants at approximately 21 DPI (Fig. 2a). During the same period, symptoms were non-visible to mild on ToLCBaV-inoculated resistant plants (Fig. 2b). The qPCR analysis confirmed the presence of ToLCBaV in the inoculated leaves as early as 3 DPI in both, resistant (R) and susceptible plants (S) (Fig. 3), indicating virus infection and replication in the inoculated plants. From 5 to 9th DPI, virus concentration continued to increase in the susceptible plants, but ToLCBaV accumulation was decreased in resistant plants (Fig. 3). At later time points, 15 and 21 DPI, a similar trend continued between resistant and susceptible plants with high levels of virus accumulation in susceptible plants, and much lower virus concentrations in resistant plants (Fig. 3).

Fig. 2.

Fig. 2

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ToLCBV infection in IIHR 2611 (R) and IIHR 2843 (S). a IIHR 2611 at 21 DPI; b IIHR 2611 at 21 DPI

Fig. 3.

Fig. 3

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Comparison of ToLCBV DNA accumulation in IIHR 2843 (S) and IIHR 2611 (R) plants at 3, 5, 9, 15, and 21DPI intervals of inoculation

RNA-Seq analysis and differentially expressed genes (DEGs)

To examine the genes/transcripts involved in response to ToLCBaV infection in tomato, RNA-seq analysis was performed in contrasting genotypes IIHR 2611 and IIHR 2843 using the Illumina Novaseq sequencing platform. The RNAseq analysis data detects a total of 30,016 expressed genes, of which a total of 25,615 (85%) are protein coding transcripts. Raw sequence data and number of expressed genes are presented in supplementary Tables 1 and 2. Volcano plots were generated to illustrate distribution patterns of DEGs in both control and infected conditions (Supplementary Fig. 1). In the comparative analysis of gene expression levels, genes with absolute log2 fold change ≥ 2 and p value ≤ 0.05 was considered as statistically significant and differentially expressed genes (DEGs) (Fig. 4a). Among 22,320 tested genes, 329 (1.47%) DEGs were identified between the ToLCBaV-infected resistant line and susceptible lines (Fig. 4a). The SI vs RI comparison shows the maximum number of DEGs with 264 downregulated and 65 upregulated genes (Fig. 4a). One hundred (0.44%) DEGs were identified between RC and RI and 226 DEGs (1.01%) were identified between SC and SI. Comparatively fewer genes were affected in RI than SI. Further comparison of RC with SC revealed that 185 genes (Fig. 4a) were differentially expressed suggesting the possibility of a basal resistant mechanism operating in the resistant plant against the viral infection.

Fig. 4.

Fig. 4

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Differential expression profiles of genes between resistance and susceptible lines. a UpSetR plot representing distribution of up- and downregulated genes. b Bubble plot of the enriched GO terms using significantly expressed genes. The orange line represents the p value threshold (Benjamini–Hochberg p value 0.05). The size of the bubble is proportionate to the number of genes involved in the GO term

Functional characterization of DEGs between R and S plants in response to ToLCBaV infection.

The broad GO categories were used for functional classification of DEGs as the biological process, cellular component category and molecular functions (Supplementary Fig. 2). The enriched GO terms using significantly expressed genes are represented in bubble plot (Fig. 4b). The number of genes significantly expressed were related to transcription factor activity, sequence specific DNA binding, defence response, photosynthesis, chloroplast and chloroplast thylakoid membrane (Fig. 4b).

In host plants, viruses encounter different mechanisms of defence varying from general to specific. General response works against a wide range of viruses as a part of the innate immune system, while specific response is virus specific and involves resistance genes. Major groups of disease responsive differentially expressed genes between R and S plants include: disease resistance genes, heat shock proteins, NBS-LRR genes, protein inhibitors and other disease-responsive genes involved in signalling pathways, glutathione metabolism genes (Supplementary Tables 4, 5 and 6), etc.

RNA sequencing data validation using qPCR

To validate the gene expression data obtained from RNA sequencing, nine DEGs with significant fold change were selected. qPCR analysis was performed and expression levels were calculated with different comparisons (SC vs RC, SI vs RI, SI vs SI and RC vs RI). The results are represented as heatmaps (Fig. 5). The RNA-seq results showed that the genes Nudix hydrolase 8, SAG 21, MIK-2 like, RING-H2 finger protein ATL2-like, GRXC 6 and P4 were upregulated in R plants upon virus infection (Fig. 5b; Supplementary Tables 4 and 6), while the genes EDR2 and MAPKKK18-like were upregulated in S plants in response to ToLCBaV (Supplementary table 5; Fig. 5c). The expression analysis using qPCR also showed that MAPKKK was upregulated in the early stages of infection (5 DPI) in R plants and during later stages of virus infection (15 and 21 DPI) in S plants (Fig. 5b, c).

Fig. 5.

Fig. 5

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Differential expression profiles of selected disease-responsive genes using qPCR. a SC vs RC; b RC vs RI; c SC vs SI; d SI vs RI

A comparison was done between uninoculated R and S lines to understand plant basal resistance. Wound-induced basic protein was shown to be differentially expressed (Fig. 5a; Supplementary Table 4). The EDR2 was significantly downregulated in resistant plants, indicating it to be a negative regulator of disease response, specifically in resistant plant IIHR 2611 (Fig. 5b, d). Unlike all other qPCR validated genes, GRXC6 and P4 were significantly upregulated during most of the disease development stages (upto 15 DPI) (Fig. 5b), indicating their involvement in constant inhibition of the virus spread.

Discussion

Understanding the mechanism of a novel source of genetic resistance offers the potential to mitigate the threat of ever-evolving viral strains. Further, this new source of resistance can be introduced into the cultivated genotypes for the development of elite cultivars. Differential gene expression profiles identified between IIHR 2611 and IIHR 2843 would have most likely resulted from their differential responses to ToLCBaV infection. Differential responses in these contrasting genotypes regulate the accumulation of viral components inside the host plant, thereby altering the disease symptoms. In the current study, qPCR analysis confirmed that both R and S lines accumulated ToLCBaV till 3 DPI. However, from the 5th DPI, viral DNA concentration continued to increase in the S plants, but decreased in the R plants. These results were in accordance with the studies conducted by Wang et al. (2018), Kaushal et al. (2020) and Sade et al. (2020). From the 15th and 21st DPI, the different trends observed in R and S plants with higher levels of virus accumulation in S plants as compared to R plants (Fig. 3). These results indicated that either virus movement or replication or both were restricted and systemic infection was aborted in case of IIHR 2611 plants. On the other hand, the inoculated S plants exhibited severe disease symptoms due to virus particle accumulation in the inoculated plants.

Genes involved in plant signalling in response to ToLCBaV infection

The host plants have a variety of viral-defence systems, categorized as general, that work against a broad range of viruses and the virus-specific ones that involve resistance genes. Lower levels of viral replication could be detected where the expression of genes conferring partial resistance to the virus was observed (Ronde et al. 2014). The highest numbers of DEGs were found in the SI vs RI comparison with 221 genes downregulated and 53 genes upregulated (Fig. 4a). Upon infection, 100 DEGs in R plants and 208 genes in S plants were observed. These results were in accordance with studies by Chen et al. (2013) where they found 209 and 809 DEGs in the R and S tomato line, respectively, in response to infection by tomato yellow leaf curl virus in tomato.

A plethora of information from biochemical and physiological investigations indicate many signalling processes in plant basal defensive responses, including reversible protein phosphorylation catalysed by protein kinases and phosphatases. The wounding in host plants by whitefly phloem feeding, followed by expression of receptor-like kinases activates the defence mechanism. The MIK2 located on the plasma membrane induce the plant defence pathways by acting as PAMP-triggered immunity (PTI) against invading pathogens (Liebrand et al. 2014; Steinbrenner et al. 2020; Coleman et al. 2021). In the present investigation, MIK2-like transcripts were induced significantly in the R line upon ToLCBaV infection (3.33 fold; Fig. 5b). Apparently, this idea of PTI-based innate responses contributing to antiviral plant defence is exclusive and in need of extensive research in a broad spectrum of plant–virus interactions.

Interestingly, the receptor-like protein 33 (LOC101261321) was upregulated (8.82 fold) in S plants (Supplementary table 5) upon virus infection, suggesting that it might be acting as a negative regulator of defence response. Kang and Yeom (2018) studied tomato receptor-like protein (RLP) expression in response to TYLCV infection, wherein 19 RLPs were highly upregulated only in S plants, while only four genes were expressed at higher levels in R plants than in S plants. These dual expression patterns of RLPs suggest their involvement as both resistance and susceptibility factors against pathogens. Higher plants have MAPK cascades, which play a vital role in signal transduction in response to biological signals. RNA-seq analysis showed that MAPKKK18 has significantly upregulated in S (5.32-fold) and downregulated in R (− 1.53-fold) plants (Fig. 5b; c; Supplementary table 5). MAPKKK18 promotes leaf senescence in plants (Matsuoka et al. 2015).

The gene Nudex hydrolase 8 is found to be significantly upregulated in R plants (Fig. 5b). In Arabidopsis, AtNUDX8 was reported to play a positive role in plant immune response upon pathogen attack via SA signalling (Fonseca and Dong 2014). Conversely, the EDR 2 gene acts as a negative regulator of SA-mediated resistance to various pathogens (Vorwerk et al. 2007), while SA is known to enhance the plant resistance to TYLCV infection by modulating the expression of ROS-scavenging genes, and through systemic acquired resistance (Li et al. 2019). Both RNA-seq and qPCR data indicate that the EDR 2 expression is induced significantly in S plants (Supplementary table 4 and Fig. 5c) compared to R plants. These results suggest that EDR2 is a negative regulator of SA-mediated resistance conferring susceptibility.

Regulation of photosynthesis in response to viral resistance

Tomato plants infected with TYLCV exhibited yellowing of leaves, stunted plant growth and regulation of genes related to photosynthesis (Seo et al. 2018). The enriched GO terms using significantly expressed genes as shown in SI vs RI comparison (Fig. 4b) are related to photosynthesis, chloroplast and chloroplast thylakoid membrane along with other defence-related genes like transcription factor activity, sequence-specific DNA binding and defence response genes. These results explain the involvement of photosynthesis-related genes during viral infection. Further, SAG 21 gene transcripts were elevated upon virus infection in R plants (Fig. 5b) mediating oxidative stress tolerance by regulating photosynthesis, minimizing the negative effects of oxidation and premature ageing (senescence) (Mowla et al. 2006; Salleh et al. 2012).

Host plant factors restricting the movement of viral components

RNA-seq results showed a significant upregulation of the GRXC 6 gene (3.17-fold change) in R plants after virus infection (Supplementary table 6). Apparently qPCR analysis also confirmed the significant upregulation (upto 4.23-fold change) of this gene (Fig. 5B). The V2 protein of TYLCV hijacks host proteins and is also involved in the trafficking of viral components—V1 protein and viral genomic DNA. The interaction of host protein SlGRXC6 and viral V2 inhibits the nuclear export of V2, thereby inhibiting the nuclear trafficking of viral components (Zhao et al. 2021). Thus, in R plants, the movement of the virus gets restricted, thereby reducing the viral symptoms.

Individual plants respond differently to a viral infection involving a complex network of receptor proteins, signalling pathway genes, various protein kinase enzymes, gene silencing pathways, transcription factors and specific disease resistance genes. In the present transcriptome study, comparisons were made to capture the genes involved in basal disease resistance (SC vs RC), specific response of individual plants to virus infection (SC vs SI and RC vs RI) and the differential resistance response of resistant plant compared to susceptible plant (SI vs RI). Our RNA-seq and qPCR data reveal the probable candidate resistance genes that are specific to novel sources of resistance against ToLCBaV. Further functional characterization of these candidate genes is required to fully understand their molecular mechanism in the disease resistance network. The characterized genes can be utilized as genomic resources (Fig. 6) in crop protection/improvement either through introgression breeding or genetic engineering approaches.

Fig. 6.

Fig. 6

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Overview of genes responsible for resistance and susceptibility for ToLCBaV and future line of work

Conclusion

Resistant and susceptible genotypes respond differently to pathogen infection, and the development of either resistance or susceptibility involves complex physiological processes involves a large network of genes. Thus, comparative transcriptome profiling of differential gene expression in response to virus infection is crucial to discover the molecular basis of resistance and susceptibility. ToLCBaV infection of resistant (IIHR 2611) and susceptible (IIHR 2843) plants induced a distinct differential transcriptional response. The present study identifies genes involved in basal disease resistance, activation of signalling pathways and specific disease resistance genes in response to ToLCBaV infection. The study also reports the genes acting as positive and negative regulators of defence response based on comparative transcriptome data and their temporal differential expression patterns. The identified candidate genes can be utilized as a potential candidate in understanding the resistance mechanism and also molecular breeding for virus resistance in tomato.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PPTX 1320 KB) (1.3MB, pptx)
Supplementary file2 (PPTX 41 KB) (41.5KB, pptx)
Supplementary file3 (PPTX 69 KB) (68.6KB, pptx)
Supplementary file4 (PPTX 71 KB) (70.6KB, pptx)
Supplementary file5 (XLSX 10 KB) (9.8KB, xlsx)
Supplementary file6 (XLSX 14 KB) (14.2KB, xlsx)
Supplementary file7 (XLSX 12 KB) (11.8KB, xlsx)
Supplementary file8 (XLSX 10 KB) (10KB, xlsx)

Acknowledgements

BC is grateful for the PhD fellowship from the DBT–JRF Programme. KVR, ATS and KRM are thankful for the financial support received from DBT New Delhi, India, through the project titled “Introgression of Bogomovirus resistance genes in Tomato (Solanum lycopersicus L.) using MAS and genomic approach”.

Author contributions

BC: investigation; methodology; data curation; formal analysis; original draft; writing—review and editing. GM: data curation; formal analysis. ATS: conceptualization; funding acquisition; project administration; resources; review and editing. MKR: conceptualization; funding acquisition; project administration. KVR: conceptualization; funding acquisition; project administration; resources; investigation; methodology; validation; visualization; original draft; writing—review and editing; supervision.

Funding

Received financial support from Department of Biotechnology (DBT)-JRF fellowship programme (Award no. DBT/JRF/BET-17/I/2017/AL/297), and DBT-Government of India, New Delhi, India, through the project titled “Introgression of Bogomovirus resistance genes in Tomato (Solanum lycopersicus L.) using MAS and genomic approach”.

Declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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