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Development of Genetic Markers in Eucalyptus Species by Target Enrichment and Exome Sequencing

  • Modhumita Ghosh Dasgupta ,

    Affiliation Division of Plant Biotechnology, Institute of Forest Genetics and Tree Breeding, P.B. No. 1061, R.S. Puram, Coimbatore–641002, India

  • Veeramuthu Dharanishanthi,

    Affiliation Division of Plant Biotechnology, Institute of Forest Genetics and Tree Breeding, P.B. No. 1061, R.S. Puram, Coimbatore–641002, India

  • Ishangi Agarwal,

    Affiliation Genotypic Technology Private Limited, #2/13, Balaji Complex, Poojari Layout, 80, Feet Road, R. M. V. 2nd Stage, Bangalore-560094, India

  • Konstantin V. Krutovsky

    Affiliations Department of Forest Genetics and Forest Tree Breeding, Büsgen Institute, Georg August University of Göttingen, Büsgenweg 2, D-37077 Göttingen, Germany, Department of Ecosystem Science and Management, Texas A&M University, 2138 TAMU, College Station, TX 77843-2138, United States of America, N.I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Genome Research and Education Center, Siberian Federal University, 50a/2 Akademgorodok, Krasnoyarsk 660036, Russia


The advent of next-generation sequencing has facilitated large-scale discovery, validation and assessment of genetic markers for high density genotyping. The present study was undertaken to identify markers in genes supposedly related to wood property traits in three Eucalyptus species. Ninety four genes involved in xylogenesis were selected for hybridization probe based nuclear genomic DNA target enrichment and exome sequencing. Genomic DNA was isolated from the leaf tissues and used for on-array probe hybridization followed by Illumina sequencing. The raw sequence reads were trimmed and high-quality reads were mapped to the E. grandis reference sequence and the presence of single nucleotide variants (SNVs) and insertions/ deletions (InDels) were identified across the three species. The average read coverage was 216X and a total of 2294 SNVs and 479 InDels were discovered in E. camaldulensis, 2383 SNVs and 518 InDels in E. tereticornis, and 1228 SNVs and 409 InDels in E. grandis. Additionally, SNV calling and InDel detection were conducted in pair-wise comparisons of E. tereticornis vs. E. grandis, E. camaldulensis vs. E. tereticornis and E. camaldulensis vs. E. grandis. This study presents an efficient and high throughput method on development of genetic markers for family– based QTL and association analysis in Eucalyptus.


The genus Eucalyptus belongs to family Myrtaceae and consists of over 700 species [1] that occupy a broad range of environmental conditions. Most of the species are native to Australia and have been introduced to India, France, Chile, Brazil, South Africa and Portugal in the first quarter of 1800s [2]. It is one of the most widely planted hardwood crop in the world because of its superior growth, adaptability and wood properties and occupies 20.07 M hectares globally. India ranks second in area under Eucalyptus plantation (3.943 M ha) after Brazil (4.259 M ha) [3]. In tropical and subtropical regions, E. grandis, E. urophylla and their hybrids are highly preferred for pulp production and solid wood, while E. globulus is favored in the temperate regions [4]. Six species including E. camaldulensis, E. grandis, E. globulus, E. pellita, E. tereticornis and E. urophylla are reported to be suitable for Indian agro-climatic conditions and widely planted in the subcontinent [56].

Eucalyptus is a potential out-crosser and due to unlimited free natural hybridizations, the populations are highly heterozygous. Hence, extensive studies were conducted to determine genetic diversity at species and population levels using different marker systems [716].

Linkage maps in different species of Eucalypts have been widely reported [1721]. QTL mapping in this genus has been conducted tagging important traits like wood properties, vegetative propagation, response to biotic and abiotic stress, juvenile traits, stem growth, water stress tolerance and frost tolerance [2227]. QTL studies in Eucalyptus species was recently reviewed in detail by Grattapaglia et al. [28]. Population based association studies were reported for E. nitens and E. globulus targeting wood property traits [2931]. Recently, the first experimental study of Genomic Selection was reported by Resende and co workers [32] in two Eucalyptus populations for growth and wood property traits.

The genomic data in Eucalyptus species are well-documented and available in public databases, private collections and consortia as EST resources [3334] and transcriptome resources [16, 3542]. Several dedicated databases are available for Eucalyptus genome research, such as EUCANEXT, EucalyptusDB, Eucspresso [38], EUCATOUL, EUCAWOOD [33], EucaCold [34], EucGenIE [43] and Phytozome10.

Subsequently, the Eucalyptus genome sequencing project was initiated independently for E. grandis at the US Department of Energy Joint Genome Institute, USA and E. camaldulensis at Kazusa DNA Research Institute in Japan. Recently, the complete genome sequence of E. grandis (‘BRASUZ1’) was published [44] and the assembled non-redundant chromosome-scale reference (v1.0) was released with 640 Mb (94%) genome coverage organized into 11 pseudomolecules. It was also reported that 34% of the protein-coding genes occur as tandem duplication and 84% share similarity to rosid lineages.

The draft genome sequence of E. camaldulensis sequenced in Japan had a total length of 655,922,307 bp of non-redundant genomic sequences consisting of 81,246 scaffolds and 121,194 singlets. These sequences accounted for approximately 92% of the gene-containing regions. A total of 77,121 complete and partial structures of protein-encoding genes were annotated [45]. The database containing the draft sequence can be accessed at

In the last decades several generic DNA markers have been employed for molecular breeding. These markers are usually effective but their development is labor-intensive and time consuming. However, with the advent of ‘next generation’ sequencing technologies, a paradigm shift has occurred in DNA sequencing approach, resulting in high throughput and cost effective sequencing methods [4647]. Nevertheless, sequencing of large number of genomes is still not feasible due to the substantial cost, time, management and storage of the enormous informatics data. Hence, considerable effort has been directed towards sequencing of genome sub-regions by ‘target enrichment’ methods. Re-sequencing of these enriched genomic regions is time and cost effective and the data analysis is less complex [48].

In the present study, we conducted target enrichment of exomes for 94 genes involved in xylogenesis and re-sequenced them in three Eucalyptus species, which were used in developing mapping pedigrees. Presence of SNVs and InDels across different species in pair-wise comparisons and in comparison to the E. grandis reference genome was documented. This study presents an efficient and high throughput method on development of genetic markers for family – based QTL and Association analysis in Eucalyptus.

Materials and Methods

Plant Material and DNA Isolation

Three genotypes from Eucalyptus camaldulensis, E. tereticornis and E. grandis were selected for target enrichment. E. camaldulensis (Ec111) belonging to Kennedy River Provenance from Queensland, Australia is a selection from the Provenance Resource Stand, Pudukkotai, Tamil Nadu, India while E. tereticornis (Et86) is a selection from Seed Production Area, Pudukkotai, Tamil Nadu, India. E. grandis (Eg9) is a selection from the Lorne provenance trial at Hossammund, Ootacamund, Tamil Nadu, India. These genotypes were used as parents for development of mapping populations targeting wood property traits.

The leaf tissues from the three genotypes were harvested and immediately frozen at −80°C. Genomic DNA was isolated from the leaf tissues using the GenElute Plant Genomic DNA isolation kit (Sigma Aldrich, USA) and quantified using NanoDrop ND1000 spectrophotometer (Thermo Scientific, USA).

Selection of Genes and Probe Design for Sequence Capture Array

Genes involved in different steps of secondary xylem formation including cell division, cell expansion, cell wall thickening, cell wall proteins, lignin biosynthesis and programmed cell death in Arabidopsis, Populus, Zinnia and Eucalyptus spp. were short-listed from literature and 94 genes were selected for target enrichment and re-sequencing. Their respective gene orthologs were downloaded from E. grandis genome database hosted by Phytozome portal ( The sequences were functionally annotated and their position in chromosome, protein domains, biological pathways and gene ontology were defined based on the recent assembly of E. grandis using Phytozome v10 [44].

Hundred and twenty bp long hybridization probes (“baits”) were designed with 1bp tilling using SureSelect eArray software (Agilent Technologies, Santa Clara, California, USA) targeting exons and UTRs in 94 genes. A total of 169,700 baits were designed to capture the exons and UTRs in the three species. Using this design, a customized array was synthesized at Agilent Technologies.

Library Preparation, Target Enrichment and Validation

Ten micrograms of DNA from each sample in 100 μl of nuclease free water were sonicated to fragment DNA to size range of 100 to 500 bp. The size distribution was checked on the Agilent 2100 Bioanalyzer, and the DNA was cleaned using the Agencourt AMPure XP SPRI beads (Beckman Coulter, Australia). The libraries for each sample were prepared using the Illumina TruSeq DNA Sample Preparation Kit (Illumina Inc., San Diego, CA, USA). The sheared DNA was subjected to a series of enzymatic reactions that repair frayed ends, phosphorylated the fragments, added a single nucleotide overhang to code the libraries and ligated adaptors using manufacturer’s protocol for the Illumina TruSeq DNA sample preparation kit. Subsequently, PCR enrichment (10 cycles) was performed to amplify the library. The three barcoded libraries were pooled in equimolar amounts and approximately 20mg of DNA was hybridized on the Agilent 244Kmicroarray (AMADID: EA560-037734) following manufacturers’ protocol. The hybridization was carried out at 65°C for 65 hrs as described by Hodges et al. [49]. After standard washing procedures, DNA was eluted in nuclease free water by incubating the array at 95°C for 10 min. The captured library was PCR amplified for 18 cycles and purified using the Agencourt AMPure XP SPRI beads (Beckman Coulter, Australia).

The enriched library was quantified using a NanoDrop Spectrophotometer and the quality was checked on the Agilent High Sensitivity Bioanalyzer Chip. RT-qPCR was conducted on pre- and post-captured library using primer pairs designed for the target (EtCesA1, EtCesA2 and EtCesA5) and non-target (EteIF4 and EtH2B) genes (S1 Table) to confirm enrichment of the targeted regions. The qRT-PCR data was analyzed using the ΔΔCT method described by Livak and Schmittgen [50].

Sequencing and Analysis

The three pooled barcoded libraries were subjected to cluster generation and 2 × 100bp paired end sequencing was conducted using the Illumina GAII Analyzer. High Quality (HQ) reads were filtered from raw data using SeqQC_V2.2 (a proprietary QC tool of Genotypic Technologies Ltd., Bangalore, India) with cutoff Phred quality scores (Q) of 20 (the probability of 1 in 100 bases sequenced may be due to an error). Further, the quality passed sequencing reads were trimmed for Adapter, B Block and low quality end sequences with 50bp cut off using Raw Data Processing Script. The trimmed reads were aligned (gapped alignment) to the E. grandis reference sequence using bowtie 2-2.0.0-beta5 [51] with affine read gap penalty and affine reference gap penalty of 5 for gap open and 3 for gap extension. The un-gapped alignment was done using bowtie version 0.12.7 [52]. The variations across the aligned sequences were taken into account from both gapped and un-gapped alignments to overcome the possibilities of false variations induced by allowing gaps. Variations reported in both alignments are expected to be of higher confidence. SNV calling and InDel detection was done using SAMtools version 0.1.7a ( with default parameters [53]. The cut off thresholds of 3 and 10 were set for the minimum number of reads showing variation and for the minimum RMS mapping quality for SNVs, respectively. The same tool was used to generate the consensus sequence of the aligned reads, while multiple alignments were done using ClustalW version 2.0.12. Pair wise comparison of the sequence data for the three species was conducted to identify SNVs and InDels based on their positions using R Bioconductor code. The ambiguous SNVs generated due to genetic divergence of the three species were not considered for analysis.

Results and Discussion

Selection of Candidate Genes

Ninety four xylogenesis-related genes involved in different stages of wood formation including biosynthesis of lignin, cellulose, pectin, monoterpene, xyloglucan, cell wall related genes, genes involved in carbohydrate metabolism, programmed cell death, phyto-hormone signaling, transcription factors and regulatory proteins were selected for the present study (Table 1). The position of the genes in chromosomes and their biological functions in respect to the E. grandis reference genome are presented in S2 Table. As many as 14 genes were localized on chromosome 7, while only 4 genes localized on chromosome 8. Two genes, monoterpene glucosyl transferase and IAA binding domain were not assigned to any chromosome.

The formation of the secondary cell wall is driven by the coordinated expression of numerous genes involved in the biosynthesis of cellulose and hemicellulose, lignin, pectin, cell wall proteins and minor soluble and insoluble compounds [5459], [33, 3839]. Expressed wood-formation genes show high functional conservation across plant genera and up to 90% of genes expressed in loblolly pine have homologs in Arabidopsis [60]. Similarly, a high proportion of poplar ESTs appear to have homologs in the Arabidopsis genome [6162].

The role of transcription factors as master switches in vascular and xylem development has been investigated in detail in poplar, eucalypts, pine and Arabidopsis. Highly expressed transcription factors like MYB and NAC families are implicated as critical regulators of vascular differentiation, phenylpropanoid metabolism, xylem differentiation and secondary wall formation. The other important regulators include the homeodomain superfamily of transcription factors (HD-Zip, WOX, KNOX, and ZF-HD), ethylene responsive elements (AP2/ERF domain), bZIP, WRKY and LIM [6370].

Hormonal regulation of wood formation is well documented and major phyto-hormones playing pivotal role in cambial activity and wood formation include auxin, cytokinin, gibberellic acid, brassinosteroids and ethylene. The receptors of hormone responsive genes and transcription factors are reported to be expressed during cambial development and wood formation [7174].

The selection of genes in the present study was based on the literature survey as described above and major functional and regulatory genes presumably involved in cambial development and wood formation were selected.

Validation of Target Enrichment

The array based hybridization enrichment was conducted to capture the 94 xylogenesis-related genes in three species of Eucalyptus. The enrichment of the targeted regions after hybridization was validated using the RT-qPCR on pre- and post-capture libraries for target genes EtCesA1, EtCesA2 and EtCesA5 and non target genes EteIF4 and EtH2B. The comparison of pre and post hybridization data demonstrated 64 fold, 165 fold and 59 fold enrichments of the target genes, EtCesA1, EtCesA2 and EtCesA5 respectively, while no enrichment was observed for the non target genes, EteIF4 and EtH2B.

Read and Alignment Statistics

The 2 × 100 bp paired end raw reads were subjected to quality checking using SeqQC_V2.2. In E. camaldulensis (Ec111), a total of 15.75 million reads were generated and the total number of HQ reads were 13.86 million (88.02%), while in E. tereticornis (Et 86), the total number of reads were 17.07 million and the number of HQ reads were 15.14 million (88.69%). In E. grandis (Eg9), the total number of reads was 11.41 million with 10.22 million HQ reads (89.59%).

The HQ reads from all the three species were aligned with the E. grandis reference sequence using both gapped and un-gapped alignment tools. In E. camaldulensis, 170866bp (98.43% read coverage) were aligned with the reference sequence, which had a total sequence length of 173593bp, while in E. tereticornis, 170825bp sequence length was aligned with reference with 98.41% coverage. Similarly, in E. grandis, 170671bp was aligned with the reference sequence with coverage of 98.32%. The total percent of reference covered with at least 5X depth was 97.71%, 97.86% and 97.12% in E. camaldulensis, E. tereticornis and E. grandis, respectively, while reference covered with at least 10X read depth was 96.99%, 97.36% and 95.67%, respectively. Similarly, the alignment statistics for reference covered with 20X depth was 95.9%, 96.34% and 93.53% in E. camaldulensis, E. tereticornis and E. grandis, respectively. The optimized average read depth in E. camaldulensis was ∼223X, while in E. tereticornis it was calculated as ∼227X. The optimized average read depth in E. grandis was ∼199X. The aligned sequence data was deposited in NCBI Short Read Archive with the accession number SRP045253 for E. tereticornis (SRX747331), E. camaldulensis (SRX669390) and E. grandis (SRX747330).

Next generation sequencing platforms produce robust sequence output making high throughput DNA marker discovery feasible and cost effective [7576]. It was reported that considering all available NGS platforms, Illumina was preferred for de novo sequencing, re-sequencing and high-throughput SNP discovery, due to generation of high read depth leading to reference based contig assembly with high confidence [7577]. The efficiency of this platform in SNP discovery has been well documented in E. camaldulensis [78]; Arabidopsis [79]; wheat [8082]; olive [83]; Solanum spp. [84]; Douglas—fir [85]; soybean [8687]; apple [88] and pine [89].

Another important consideration while conducting target enrichment and re-sequencing is the read depth to reliably detect SNPs. It was reported that a minimum of 8X coverage [90] and up to 200X [91] was optimal for SNP calling. In the present study, the read depth was significantly high at ∼223X in E. camaldulensis, ∼227X in E. tereticornis and ∼199X in E. grandis. Similar studies in Fragaria vesca documented the average depth as 120X [92], while in E. camaldulensis, the average read depth for all the bases was 6124X [78].

Specificity (the number of reads that map to the targeted sequence) is an important aspect of target enrichment experiments. The present study documented high read coverage with E. camaldulensis showing 98.43% coverage, E. tereticornis with 98.41% coverage and E. grandis with coverage of 98.32% with reference sequence, suggesting high specificity of the hybridized probes to the target sequences. Similarly, in an earlier study in E. camaldulensis, 94.2% coverage was reported with reference genome of E. grandis [78]. In the wheat, NimbleGen array with genomic DNA derived from eight wheat varieties was used for target enrichment and exome sequencing and an average of 38.1% (22%–44.5%) was aligned to the reference sequence [80], while Saintenac and co workers [82] reported an increase in specificity of reads on target to 60% and the number of covered target bases reported was 92%. In Populus trichocarpa, an average of 86.8% of base pairs in the bait regions was mapped on the reference sequence [93]. Hence, the high read depth and coverage achieved in the present investigation can be considered optimal for identification of variation with high confidence.

Identification of Variants (Snvs And Indels) in Three Eucalyptus Species across E. Grandis Reference Genome

The SNVs and InDels present in the sequences aligned with the reference were individually determined for each species. A total of 5905 SNVs were discovered in all three species, which included 2294 SNVs in E. camaldulensis (604 and 299 SNVs from gapped and un-gapped alignments, respectively and 1391 SNVs common for both gapped and un-gapped alignments), 2383 SNVs in E. tereticornis (636 and 303 SNVs from gapped and un-gapped alignments, respectively and 1444 SNVs common for both alignments), and 1228 SNVs in E. grandis (460 and 122 SNVs from gapped and un-gapped alignments, respectively and 646 SNVs common for both alignments) (Table 2).

Table 2. SNVs and InDels across 94 genes in three Eucalyptus species.

The presence of SNVs in UTRs and exons were also identified and maximum number of SNVs was recorded in the exon region (4187), while 1226 SNVs were documented in the 3’UTR. A total number of 492 SNVs were identified in the 5’UTR across all the three species (Table 3, 4 & 5). In E. tereticornis, the maximum number of SNVs was recorded in SuSy1 (85), while only one SNV was observed in PTM5 (S3a Table). In E. camaldulensis, a similar trend was observed with maximum of 72 SNVs identified in SuSy1 and only one SNV recorded in PTM5 (S4a Table). However, when the E. grandis sequences were compared with the reference genome, a maximum of 60 SNVs was observed in C3H while a single SNV was documented in several genes, including AP2L, ARF, ARF2, EXPA, GATA1, LAC2, PTM5, VND6. No SNVs were detected in CCAAT, FLA1, and LBD (S5a Table).

Table 3. SNV frequency in three Eucalyptus species in 5′UTR region.

Table 4. SNV frequency in three Eucalyptus species in Exon region.

Table 5. SNV frequency in three Eucalyptus species in 3′ UTR region.

The SNV frequency was calculated for exon and the UTR regions individually in each species. The SNV frequency in 5′UTR of E. tereticornis, E. camaldulensis and E. grandis was 1/78.49bp, 1/101.11bp and 1/170.42 respectively, while SNV frequency in the exon region was 1/126.78, 1/125.61 and 1/306.72 for E. tereticornis, E. camaldulensis and E. grandis respectively. In 3′UTR, the SNV frequency was 1/86.61, 1/100.23 and 1/176.08 for E. tereticornis, E. camaldulensis and E. grandis respectively (Table 3, 4 & 5).

Further, the presence of SNVs in pair-wise combination between the three Eucalyptus species was also conducted. The gene-wise presence of ambiguous nucleotides was not considered and SNV with no ambiguity was mapped on the candidate genes (S6 Table). When E. camaldulensis and E. tereticornis were compared, a total of 317 SNVs were documented with a minimum of one SNV in 4CL, bZIP, CCoAOMT1, CesA3, EXPA, GRAS1, NAM1, PIP1, PTM5, SBP1, SND1, STM, SuSy1, TUA1, VND7 and a maximum of 25 SNVs in LAC. Larger number of SNVs were recorded when E. grandis was compared with E. tereticornis and E. camaldulensis with 875 and 1014 SNVs respectively. In both pair-wise combinations, the maximum number of SNVs was observed in LAC with 53 SNVs when compared across E. camaldulensis and 46 SNVs when compared across E. tereticornis.

The presence of InDels were also detected when the sequences of 94 genes were compared individually across the reference and a total of 1406 InDels were discovered with the size range of 1–24 nucleotides (Table 2). The position of InDels in exons and UTRs was also determined and the total number documented was 843, 309 and 254 in exons, 3’UTR and 5’UTR, respectively (Table 6). In E. tereticornis, a total of 518 InDels were detected and a maximum of 20 InDels was recorded in the transcription factor HB1 Class III, while a single InDel was documented in several genes including CCAAT, DUF1,ERF, MUR3,MYB2,PL, PTM5,UXS1 and WUS1. No InDels were recorded in ASP, CAld5H, DOF1, F5H, DIR1, and FLA1 (S3b Table). In E. camaldulensis, a total of 479 InDels were recorded and the maximum number of InDels was discovered in HB1ClassIII (18), while only a single InDel was identified in DIR1, DUF1, ERF, GRAS1, GT, IAA, MUR3, PAAPA, PTM5, UGT and WUS1. InDels were not detected in ASP, CAld5H, DOF1, F5H, FLA1, GATA1, PL and UXS1 (S4b Table). In E. grandis, a total of 409 InDels were discovered and a maximum of 17 InDels was documented in HB1ClassIII, while only a single InDel was identified in FLA1, DUF1, IAA, MUR3, PTM5, CCAAT, LBD, DHN, MYB2, C4H and HCT. InDels were not found in ASP, CAld5H, DOF1, F5H, GATA1, PL, UXS1, DIR1 and WUS1 (S5b Table). The InDel frequency was calculated for each species (Table 6). The InDel frequency (bp/InDel) was the highest in the exon region for all the three species with 411.14, 446.38 and 482.58 in E. tereticornis, E. camaldulensis and E. grandis, respectively. The total InDel frequency was 332.05, 359.08 and 420.54 bp per InDel in E. tereticornis, E. camaldulensis and E. grandis respectively, across the all the genes selected (Table 6).

Similarly, the presence of InDels was also documented in pair-wise combination and a total of 731 and 699 InDels were detected across E. grandis & E. tereticornis and E. grandis & E. camaldulensis, respectively. A total of 702 InDels were detected between E. camaldulensis and E. tereticornis. Maximum number of InDels across all combinations was observed in HB1 Class III transcription factor with 26 InDels when compared between E. grandis and E. tereticornis, 27 InDels between E. grandis and E. camaldulensis and 27 InDels between E. camaldulensis and E. tereticornis. A minimum of one InDel was documented across several genes like FLA1; DIR1, EXPB, FLA1, WUS1 and DIR1, DUF1, PL, UXS1 in E. grandis & E. tereticornis; E. grandis & E. camaldulensis and E. camaldulensis & E. tereticornis respectively (S7a,b,c Table).

The abundance of SNPs / SNVs in plant genome and the availability of cost effective technologies for genotyping has made high-throughput SNP genotyping pivotal for genetic mapping, gene discovery, germplasm characterization and population genomics [94]. NGS based SNP discovery is reported in several crop like wheat [80], [81], [82]; Eucalyptus [95]; rice [96]; barley [97]; cotton [98]; soybean [86]; potato [99]; Arabidopsis [100]; maize [101] and several other species. Use of SNP marker panels for genetic analysis has been widely explored in less domesticated crop [102] and trees [103105]. SNP genotyping in Eucalypts species is reported from E. grandis [35], E. globulus, E. nitens, E. camaldulensis and E. loxophleba [16], inter-specific hybrids of Eucalyptus [106], E. pilularis [107], E. globulus [108] and E. camaldulensis [41,78].

The SNP frequency in Eucalyptus species is considered to be one of the highest in woody species due to its recent domestication, large population size and outbred mating system [94]. Kulheim and coworkers [16] reported that the SNP density in E. nitens was 1/33bp, 1/31 bp in E. globulus, while in E. camaldulensis and E. loxophleba it was significantly high at 1/16bp and 1/17bp respectively. However, a later study showed that the SNP frequency was 1/83.9bp in E. camaldulensis [78]. In the present study, the SNV frequency ranged from 1/78.49bp to 1/306.72bp across different genic regions of E. camaldulensis, E. tereticornis and E. grandis. Recently, the SNP frequency in inter-specific hybrids of Eucalypts was documented as 1/133bp [109], suggesting that the SNP frequency was depended on the target region. In heterozygous species, the SNP frequency is generally high as documented in pine with 1/102.6bp [110], grapevine with 1/64bp [111], maize with 1/60bp [112] and rye which registered a SNP frequency of 1 SNP at 52bp interval [113].

Insertion and deletion polymorphisms (InDels) are an important source of genomic variation in plant and animal genomes. Mechanisms such as insertion and excision of transposable elements, slippage in simple sequence replication, errors in DNA synthesis and repair, recombination and unequal crossover can result in the formation of InDels [114115]. However, accurate genotyping from low-coverage sequence data can be challenging [116]. Further, polymorphism in short InDels is increasingly being used as an important marker in humans [117], Drosophila melanogaster [118] and G. gallus [119]. Report on InDel genotyping in plants are limited to rice [120], Arabidopsis thaliana [121], Citrus clementina [122] and Phaseolus vulgaris [123]. In tree species, InDel discovery is reported from Salix spp. [124] and Populus spp. [125126]. InDel markers for species discrimination have been reported in E. grandis and E. gunnii [39] and Populus spp. [125,127].

In the present study, high number InDels in the size range of 1–24 nucleotides were documented in the three Eucalypts species at a frequency of 332.05, 359.08 and 420.54 bp per InDel in E. tereticornis, E. camaldulensis and E. grandis, respectively. This is higher than the earlier reported InDel frequency of 1.5 InDel/1000 bp [115] in Eucalyptus genome and 1/2756bp in inter-specific hybrid population [109]. Similarly, in Pinus taeda, Kong et al. [128] reported that InDels were infrequent with only 0.67% frequency in targeted regions. The probable reason for this variance in the present investigation could be due to the highly divergent genotypes selected in the present study, indicating that InDels could be a useful marker for genetic analysis in Eucalyptus species.


The NGS platforms have brought in paradigm shift in understanding the different aspects of plant biology especially in model species and plants with small genome. Its downstream usefulness in linkage map construction, genetic diversity analyses, association mapping, and marker—assisted selection has been demonstrated in several plants [129]. However, sequencing of complete genomes cannot be regularly employed due to high cost and computational limitations in handling robust informatics data. With availability of complexity reduction strategies, sequencing of sub-genomic regions by on-array/in-solution target enrichment technology has provided an efficient alternate strategy to amplicon re-sequencing for SNP/ SNV discovery [130]. In the present study, this strategy was implemented in re-sequencing ninety four genes across three Eucalypts species. This study has also revealed that target enrichment strategy can be successfully used for identification of markers (SNVs and InDels) for future use in QTL and association mapping studies in Eucalyptus species.

Supporting Information

S1 Table. Primer pairs used for RT-qPCR to confirm enrichment of targeted genes.


S2 Table. Functional Annotation of selected genes across E. grandis genome sequence using Phytozome v10.


S3 Table. A, Details of SNVs documented in E. tereticornis across reference sequence.

B, Details of InDels documented in E. tereticornis across reference sequence.


S4 Table. A, Details of SNVs documented in E. camaldulensis across reference sequence.

B, Details of InDels documented in E. camaldulensis across reference sequence.


S5 Table. A, Details of SNVs documented in E. grandis across reference sequence.

B, Details of InDels documented in E. grandis across reference sequence.


S6 Table. Presence of SNVs in Pair-wise comparison across three Eucalyptus species.


S7 Table. A, Presence of InDels in Pair-wise comparison across E. grandis and E. tereticornis.

B, Presence of InDels in Pair-wise comparison across E. grandis and E. camaldulensis. C, Presence of InDels in Pair-wise comparison across E. camaldulensis and E. tereticornis.



The authors acknowledge Dr. V. Sivakumar and Shri D.R.S. Sekar, Scientists, Institute of Forest Genetics and Tree Breeding, Coimbatore, India for providing the plant material for the study. The authors are grateful to Genotypic Technologies Private Limited, Bangalore, India for array design, library construction and analysis of the data. MGD acknowledges the funding support by Department of Biotechnology, Government of India under the DBT-CREST Awardship. VD acknowledges the Department of Biotechnology, Government of India for research fellowship.

Author Contributions

Conceived and designed the experiments: MGD KVK. Performed the experiments: MGD VD. Analyzed the data: MGD VD IA. Contributed reagents/materials/analysis tools: MGD IA KVK. Wrote the paper: MGD KVK.


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