- Research article
- Open Access
Identification, characterization and utilization of unigene derived microsatellite markers in tea (Camellia sinensis L.)
BMC Plant Biology volume 9, Article number: 53 (2009)
Despite great advances in genomic technology observed in several crop species, the availability of molecular tools such as microsatellite markers has been limited in tea (Camellia sinensis L.). The development of microsatellite markers will have a major impact on genetic analysis, gene mapping and marker assisted breeding. Unigene derived microsatellite (UGMS) markers identified from publicly available sequence database have the advantage of assaying variation in the expressed component of the genome with unique identity and position. Therefore, they can serve as efficient and cost effective alternative markers in such species.
Considering the multiple advantages of UGMS markers, 1,223 unigenes were predicted from 2,181 expressed sequence tags (ESTs) of tea (Camellia sinensis L.). A total of 109 (8.9%) unigenes containing 120 SSRs were identified. SSR abundance was one in every 3.55 kb of EST sequences. The microsatellites mainly comprised of di (50.8%), tri (30.8%), tetra (6.6%), penta (7.5%) and few hexa (4.1%) nucleotide repeats. Among the dinucleotide repeats, (GA)n.(TC)n were most abundant (83.6%). Ninety six primer pairs could be designed form 83.5% of SSR containing unigenes. Of these, 61 (63.5%) primer pairs were experimentally validated and used to investigate the genetic diversity among the 34 accessions of different Camellia spp. Fifty one primer pairs (83.6%) were successfully cross transferred to the related species at various levels. Functional annotation of the unigenes containing SSRs was done through gene ontology (GO) characterization. Thirty six (60%) of them revealed significant sequence similarity with the known/putative proteins of Arabidopsis thaliana. Polymorphism information content (PIC) ranged from 0.018 to 0.972 with a mean value of 0.497. The average heterozygosity expected (H E ) and observed (H o ) obtained was 0.654 and 0.413 respectively, thereby suggesting highly heterogeneous nature of tea. Further, test for IAM and SMM models for the UGMS loci showed excess heterozygosity and did not show any bottleneck operating in the tea population.
UGMS markers identified and characterized in this study provided insight about the abundance and distribution of SSR in the expressed genome of C. sinensis. The identification and validation of 61 new UGMS markers will not only help in intra and inter specific genetic diversity assessment but also be enriching limited microsatellite markers resource in tea. Further, the use of these markers would reduce the cost and facilitate the gene mapping and marker-aided selection in tea. Since, 36 of these UGMS markers correspond to the Arabidopsis protein sequence data with known functions will offer the opportunity to investigate the consequences of SSR polymorphism on gene functions.
The ubiquity of microsatellite or simple sequence repeats (SSRs) in eukaryotic genomes and their usefulness as genetic markers has been well established over the last decade. Microsatellites are mainly characterized by high frequency, co-dominance, multi-allelic nature, reproducibility, extensive genome coverage and ease of detection by polymerase chain reaction with unique primer pairs that flank the repeat motif . As a result of these characteristics, microsatellites have become the most favoured genetic markers for plant breeding and genetics applications such as, assessment of genetic diversity, constructing framework genetic maps, mapping of useful genes, marker aided selection and comparative mapping studies [2, 3].
In general, SSRs are identified from either genomic DNA or cDNA sequences. The standard method for development of SSR markers involves the creation of small insert genomic DNA libraries, followed by a subsequent DNA hybridization selection by probing them either with radioactively labeled probes or trapping them with biotinylated SSR motifs, and clone sequencing [4, 5]. These processes are time consuming, and labour intensive. Furthermore, SSRs acquired by these methods are limited with probed SSR motifs (most common are di or tri types), and hence the advantages are partially offset. Availability and continuous enrichment of expressed sequence tags (ESTs) database http://www.ncbi.nlm.nih.gov in most of the crop species can serve as an alternative strategy for identification and development of microsatellite markers. SSRs can be directly sourced from such databases, thereby reducing time and cost for microsatellite development. However, non-availability of sufficient sequence information (as generation of EST-SSR markers is primarily limited to those species and their close relatives for which large number of ESTs are available) and redundancy that yield multiple set of markers at the same locus are among the major drawbacks of EST derived microsatellite markers. More recently unique gene sequences (unigenes) have been developed via clustering of overlapping EST sequences, which overcomes the problem of redundancy in EST database and detect variation in the functional genome with unique identity and position . Parida et al.  identified and characterized microsatellite motifs in the unigenes available in five cereal crops (rice, wheat, maize, sorghum, barley) and Arabidopsis. These unigene derived microsatellite (UGMS) markers are expected to possess high inter specific transferability as they belong to relatively conserved regions of the genome.
Tea is the oldest, widely consumed and least expensive natural beverage grown mostly in the tropical countries of Asia (India, Sri Lanka, China, Indonesia), Africa (Kenya, Uganda, Malawi) and to some extent Latin America (Argentina). Three Camellia species namely C. sinensis L. (small leaves), C. assamica (Masters; big leaf) and C. assamica ssp. lasiocalyx (Planchon ex Watt; intermediate leaf), traditionally referred as China, Assam and Cambod varieties, respectively are the important source of foreign exchange for almost all the tea producing countries in the world, including India. The complex life cycle and out breeding nature of tea poses several limitations for its genetic improvement through conventional breeding. The discrimination between true archetypal China, Assam and Cambod varieties is difficult due to heterogeneous nature of tea . Furthermore, morphological characteristics are unable to reflect the inherent genetic variation within the crop, which actually shows high plasticity with respect to biochemical and physiochemical descriptors [9–12]. Therefore, identification of highly reliable molecular tools such as microsatellite or SSR markers is extremely important to reveal the unexplored genetic variation in tea. Despite the obvious advantages of microsatellite markers in terms of inferring allelic variation, estimating gene flow and development of genetic linkage maps , only a few microsatellite makers have been reported in tea [13–15]. Over the past few years, various EST projects and studies [16–18] have generated publicly available EST sequence data in tea. These ESTs were mostly derived from different organs/tissues such as, young & mature leaves and tender shoots under natural environmental conditions. Considering the multiple applications of such data in gene discovery and comparative genomics, publicly available EST sequence data (as on May 21, 2006) in C. sinensis was mined in the present study for SSR identification via clustering random ESTs into unigenes/contigs. These unigenes were also searched for abundance, repeat motif types and pattern of distribution of SSRs in the non-redundant (NR) expressed genome of tea. Functional analysis of unigenes containing SSRs was done through gene ontology (GO) annotations with the Arabidopsis information resource http://www.arabidopsis.org.
We report the development of UGMS primer pairs flanking these microsatellite motifs additional to those reported by Zhao et al. . The UGMS markers developed were also tested for cross species transferability to different Camellia species. Locus orthology was monitored by analyzing the amplification patterns and by sequencing selected amplicons. Polymorphisms detected within the accessions of one species and between a set of Camellia species was also analyzed to assess as to whether these markers could be useful for diversity studies and also for distinguishing the Camellia species.
ESTs/Unigenes data set
A total 1,223 (893 singletons and 330 contigs) unigenes were predicted from 2,181 publicly available EST database in C. sinensis by clustering of 2 – 34 random EST sequences. Non-redundant (NR) sequence data set represented ~425.67 kb expressed genome of tea (C. sinensis).
Abundance and distribution of SSRs
All 1,223 potential unigenes were searched for the presence of microsatellites. A total of 109 (8.9%) unigenes containing 120 SSRs with motif length ranging from 2 to 6 bp were identified (Additional file 1). One sequence contained three SSRs and three sequences contained two SSRs each. Six SSRs were of compound types (SSR containing stretches of two or more different repeats). Of these, four compound SSRs were uninterrupted, while remaining two were interrupted by the presence of ≤ 8 arbitrary nucleotides. One SSR was detected for every 3.55 kb of the EST sequences. Further analysis of SSR containing unigene sequence data revealed that majority of them (94.1%) were perfect repeat and/or class I (≥20 nucleotides; nts length). However, remaining 5.8% (comprising of 2.5% di repeats and 0.83% each of tri repeats, tetra and penta repeats) were found to be of class II types (≥12 nts and <20 nts length).
Data analysis of SSR motifs in unigenes revealed 61 di repeats (50.8%), 37 tri repeats (30.8%), 8 tetra repeats (6.67%), 9 penta repeats (7.5%) and 5 hexa repeats (4.16%) (Table 1). Among the di-nucleotide repeats the (TC)n.(GA)n motifs were most abundant (83.6%) followed by (CA)n.(TG)n and (TA)n. Among the mirosatellites containing tri-repeats, (CAT)n.(ATG)n and (TTC)n.(GAA)n were the maximum (18.9%), which was followed by (TGG)n.(CCA)n and (CTG)n.(CAG)n. Abundance of other tri repeat containing SSRs were more or less in the similar range. Frequency of tetra, penta and hexa repeat containing SSRs was the least.
UGMS primer designation
Of the 109 NR unigenes containing one or more SSRs, 91 (83.5%) were amenable to design flanking oligonucleotide primer pairs. Ninety six UGMS primer pairs (55 from singletons and 41 from clusters) flanking to different repeat motifs could be designed. Primer pairs flanking di repeats (54.2%) were the most abundant followed by tri (30%), penta (8.3%), tetra (5.2%) and hexa (2.1%) repeats containing microsatellites. Primers could not be designed for the rest eighteen (16.5%) SSR containing unigenes because of either insufficient flanking sequence (occurrence of SSR near or/at either end of the unigene) or inability to fulfill the criteria for primer design. Five (4.6%) of the 109 unigenes were used to design more than one primer pairs targeting NR SSR loci. Thus, a non-redundant set of UGMS primers could be designed for 7.4% of the total unigene sequences in our study.
Annotations and functional classification
Of the 60 unigenes that had successful primer pairs developed and validated, 36 (60%) matched to Arabidopsis genes with high expectation value (Table 2). To get a better view of the annotated unigenes, we downloaded Gene Ontology (GO) annotations  from the TAIR website  to classify SSRs containing unigenes into functional categories. Relative frequencies of GO hits for C. sinensis unigenes were assigned to the functional categories. Biological process, cellular components and molecular function as defined for Arabidopsis proteome are presented in Figure 1. In case of biological processes, the C. sinensis unigenes were assigned to thirteen categories. Majority were assigned to the two categories namely "other metabolic processes" (22.98%) and "other cellular processes" (21.84%). However, other important categories were "protein metabolism" (10.35%), "response to stress" (6.9%), "cell organization and biogenesis" (5.74%), etc. For the cellular components, the unigenes were assigned in thirteen categories with majority of them representing genes participating in "other intracellular components" (18.23%), "other cytoplasmic components" (14.84%) and "other membranes components" (13.8%). The remaining were assigned to important cellular components of "chloroplast" (12.16%), "ribosomes" (4.97%), "mitochondria" (3.88%), etc. When grouped according to likely molecular functions, the unigenes were assigned to fourteen categories and covered "protein binding" (10.23%), "other binding domains" (14.77%), "structural molecular activity" (10.23%), "various catalytic protein groups" (hydrolase, 6.8%; kinase, 1.14%) etc. There was considerable representation of unknown processes or fractions irrespective of the GO categories such as "unknown molecular functions" (26.14%), "unknown biological processes" (9.77%) and "unknown cellular components" (8.29%).
In general, the SSRs containing unigene sequences detected in tea were homologous to proteins having distinct molecular functions such as, binding, catalytic, transport, enzyme regulators, and structural activities in different biological processes, and cellular and sub-cellular organization.
Marker evaluation and polymorphism detection
Ninety six primer pairs designed in this study were used to amplify DNA from a panel of 34 accessions of cultivated tea and related species. Of these, 61 (63.5%) primer pairs produced repeatable and reliable amplifications in at least four accessions of tea, while 35 (36.5%) primer pairs either completely failed or led to weak amplifications and thus were excluded from further analysis. Marker evaluation details are given in Table 3. PCR products of the expected size were obtained in all the cases except in one UGMS primer (TUGMS83) that had amplified larger size additional amplicons in some cases. Multi-locus amplifications were recorded in case of TUGMS27 and TUGMS46. Over all, amplification success rate was the maximum in case of TUGMS primer pairs containing tri repeats (72%), followed by di-repeat (61.5%). The PCR success rate of UGMS classes having tetra, penta and hexa repeats were ranged from 50% to 60%. Seven polymorphic primer pairs namely TUGMS3, TUGMS7, TUGMS33, TUGMS46, TUGMS52, TUGMS75, TUGMS85 gave amplification in all the tested genotypes irrespective of species (Table 3) and hence can be utilized as universal markers for molecular analysis in tea. However, these markers need to be validated in a larger panel of Camellia species.
Sixty one primer pairs amplified 324 alleles of which 321 (99%) were found to be polymorphic. All the UGMS markers identified in the present study remained highly polymorphic (Figure 2). The number of alleles detected in the present case ranged from 2 to 16 with an average of 5.3. The UGMS markers namely TUGMS52 and TUGMS15 recorded a maximum of 16 and 15 alleles, respectively. Total number of alleles detected among the accessions belonging to three varietal types i.e. Assam, Cambod and China were 213, 214 & 278, respectively. A high level of polymorphism has been observed at the species level. No significant difference was detected in percentage polymorphism of China and Assam (~94% in each case), however, due to hybrid nature of C. assamica ssp. lasiocalyx, a slightly higher level of polymorphism (98.4%) was recorded in Cambod. The H E and H o ranged from 0.140 to 0.909 (with an average of 0.654) and 0.029 to 0.853 (with an average of 0.413), respectively (Table 3). All the UGMS markers showed a significant departure from Hardy-Weinberg equilibrium (HWE) at P < 0.001 level. The polymorphism information content (PIC) ranged from 0.018 to 0.972 with an average of 0.497. There was significant difference in the average PIC values was recorded in UGMS locus harboring different repeat types. Average PIC values ranged from 0.183 (penta repeats) to 0.725 (tetra repeats). However, an average of 0.578 and 0.390 PIC values were recorded in TUGMS primers with di and tri repeats, respectively (Table 3). Of the 34 UGMS primer pairs with PIC values ≥ 0.50, 5 (13.8%) namely TUGMS3, TUGMS52, TUGMS73, TUGMS74, TUGMS78 recorded amplification in ≥30 accessions were identified as informative and thus would be useful in future marker assisted studies in tea. Further, at least 14 primer pairs with PIC values ≥ 0.70 were identified, which may also be categorized as informative primers after their validation in a larger panel of tea accessions.
In mutation drift equilibrium, heterozygosity excess/deficiency under different mutation models (IAM & SMM) generated by BOTTLENECK showed significant excess of heterozygosity in both the models. All the tested loci showed excess heterozygosity in sign test and found to be significant in both standardized and Wilcoxen test (Table 4).
To assess the conservation of C. sinensis UGMS loci across the Camellia species, we tested the cross amplification of 61 primer pairs on five species representing ten accessions each of C. assamica and C. assamica ssp. lasiocalyx (cultivated tea) and one accession each representing C. lutescens, C. irrawadiensis, C. japonica white flower and C. japonica red flower (wild and/or ornamental species). Except for the annealing temperature (Ta), identical PCR conditions were used to assess the extent of transferability to related species. All the 61 primers recorded transferability in C. assamica and C. assamica ssp. lasiocalyx showing high degree of locus conservation in the cultivated species. However, 51 UGMS primers gave reproducible amplification at least in a single related species (C. lutescens; 63.4%, C. irrawadiensis; 34.4%, C. japonica; red; 59% and white flower; 57.4%) and recorded an overall 83.6% cross transferability rate. Marker wise amplification pattern of successful UGMS primers is presented in Table 5. Furthermore, transferability rate was significantly higher in TUGMS primers containing tri or hexa repeats (≥ 95%) followed by the primers with di and penta repeats (75% in each case). Least transferability was recorded in primers with tetra repeats. As a whole, 15 (~25%) UGMS primers recorded cross-transferability in all the tested species.
Sequence comparison of SSR locus
To validate the conservation of SSRs across the varieties and species, at least one amplicon from different genotypes/species and multiple amplicons from the same genotypes were sequenced. Multiple amplicons from single genotype were selected to determine the orthology and paralogy of the sequence. When a locus wise DNA sequences data in each case was compared, it showed electromorphic size variation solely attributed either due to expansion/contraction of the SSRs, or due to interruptions in the SSR regions. This was most notable among different alleles where the size differences resulted from either simple or complex variation in SSR motifs. Even at the multiple amplicons from the diploid genotypes similar situation was noticed. As illustrated in Figure 3, the size of the multiple amplicons having (GA)n motif and consumed primer sites were 95, 89, 82 bp longer in case of genotype UPASI-10 for marker TUGMS27. Similarly, for the Kangra Jat genotype amplicon size 124, 138 and 151 bp were obtained for TUGMS46 that amplified TC repeats. Similar situation was observed with identical amplicon size, and repeat motifs for allelic amplicons from different genotypes as in case of TUGMS3 and TUGMS53, respectively. Further, in order to confirm DNA polymorphism and cross-transferability at the sequence level, selected amplicons from C. lutescens, C. irrawadiensis and C. japonica (RF: red flower & WF; white flower) were sequenced for three UGMS primers namely TUGMS3, TUGMS-34 and 73. The presence of the target microsatellites were observed in all the cases (Figure 4).
Inter and intra specific genetic variations among the tea accessions
In the present study, correlations observed between the genetic similarity (GS) matrixes based on Jaccard's and Nei and Li's coefficients methods was 0.991. The average GS among the 34 accessions of Camellia species was 22%. Within C. sinensis, GS ranged from 26% between Kangra Jat and Sikkim-1 to 59% between Teesta Valley-1 and Sikkim-1. Within C. assamica GS was ranging from 15% to 71%, where as GS ranged from 26% to 46% in C. assamica ssp. lasiocalyx. The average GS remained almost similar in case of C. assamica (Assam; 28.6%) and C. assamica ssp. lasiocalyx (Cambod; 28%), while slightly less among the accessions of C. sinensis (China; 27%). We recorded 37% GS between the two accessions of ornamental types C. japonica with red and white flowers.
The phenetic analysis of the UGMS data by two methods showed distinct groups and subgroups (Figure 5a &5b). The cluster analysis with Jaccard's similarity matrix corresponded well with the Nei and Li's matrix. Though minor changes were evident within the subclusters of the major varietal types, the relative position of the major clusters remained preserved. The neighbour joining (NJ) tree was more precise in differentiating the closely related accessions with high bootstrap values (Figure 5b). Clustering of thirty four accessions of genus Camellia into three major groups was strongly supported by high bootstrap values (≥ 90%). However, accession of C. lutescens remained isolated as a single solitary genotype with 100% bootstrap value and defined as outgroup. All the China accessions were clustered together in group I. However, two accessions namely UPASI 6 (Assam) and C-6017 (Cambod) were also clustered in this group. Majority of Assam and Cambod tea accession clustered together in group II with bootstrap values of 65%. All but one (TV-19), TV series accessions representing either Assam or Cambod also clustered together in group II. Interestingly, two accessions namely UPASI 13 and UPASI 9 known for excellent spread and are the source of good quality tea, remained together as intermediates between groups I and II. Accession 124/48/8, an extreme Cambod type with broad-elliptic leaves without distinct marginal veins with pink pigmentation at the petiole base, along with TV-19 (Cambod) clustered as an intermediate group between ornamentals and cultivated tea accessions. As expected, all the three species (C. irrawadiensis, C. lutescens, C. japonica with white and red flower) clustered separately in the present case.
Abundance and distribution of SSRs and UGMS primer development
The present study was designed to utilize the publicly available tea ESTs for development of reliable UGMS markers. We assembled ESTs into unigenes, consisting of consensus sequences of contigs and the singleton sequences for SSR analysis. The assembly generates longer sequences, which gives a better chance of association of sequences with the proteins. Generation of longer sequences can be useful for SSR studies since it can give longer SSR surrounding sequences for primer designing. In addition, the use of NR sequences can give a better estimation of the sequence features in the genome.
In case of tea, we found that 8.9% unigenes contained NR SSRs. This EST-SSR frequency was in the 2.65 – 10.62% range obtained for 49 dicot species . However, it was higher than the 1.5 – 4.7% range reported for monocots . Frequency of EST-SSRs in various plant genomes is significantly influenced by the repeat length and the criteria used to search the SSRs in database mining . If the repeat length is 20 bp, in general 5% of ESTs have recorded the presence of microsatellites . The present study recorded a relatively higher abundance of SSRs as compared to earlier reports in tea  and also in other plant species such as grapes , sugarcane , cereals [7, 22, 26] and coffee ESTs [23, 27]. Cardle et al.  in a comprehensive computational and experimental characterization of publicly available EST sequence database of different plant genomes recorded a significant difference in the type and abundance of SSRs. The average distribution of SSRs estimated to be ranging from 3.4 kb in rice to 7.4 kb in soybean, 8.1 kb in maize, 11.1 kb in tomato, 13.8 in Arabidopsis, 14.0 kb in popular and 20 kb in cotton. Furthermore, occurrence of high frequency of Class I (94.1%) and or perfect repeats in the present case is possibly due to the criteria that had been implemented for mining of SSRs. Experimental data originally reported for human  and then confirmed in many other organisms including rice [30, 31] had suggested that longer perfect repeats are more polymorphic. The rate of strand slippage has been shown to increase with increasing length of blocks of repeats. Therefore, longer perfect repeats are highly variable. However, the lower rate of polymorphism of repeat sequences containing interruptions may be due to the fact that strand slippage of these sequences produces structures with non-complementary bases.
The frequency analysis of various nucleotide repeats in C. sinensis ESTs revealed that di nucleotide SSRs were the most abundant SSRs followed by tri-, tetra-, penta- and hexa repeats. This is in agreement with the frequency trend has been earlier reported in tea . In general, microsatellites containing tri-repeats remained most common among the monocots and dicots . However, Kumpata and Mukhopadhyay  recorded the abundance of di-repeats in most of the dicots species investigated. High frequency of di-nucleotide repeat has also been reported in case of eucalyptus  and citrus  ESTs. High frequency of dinucleotide repeats as observed in the present case could be because ~70% of the overall sequences included in analysis correspond to 5' end of the transcript , which included 5' UTRs. Hence, representation of di nucleotide repeats in this region would not affect the reading frame and thus tolerated more as compared to amino acid coding regions. However, certain frequency of di nucleotide could be abundant in the coding regions such (TC)n.(GA)n in the present case, which might represent GAG, AGA, UCU and CUC codon in a mRNA population and translate into the amino acids Arg, Glu, Ala and Leu, respectively. Ala and Leu are present in proteins at high frequencies of 8% and 10%, respectively . (TC)n.(GA)n motifs were also the most frequently observed SSRs in different plant species including coffee, cereals and forage crops [23, 26, 31, 34] and also in other perennial crops, such as eucalyptus , apple , strawberry  and citrus [37, 38].
The most abundant tri nucleotide repeats observed in present study were (CAT)n.(ATG)n and (TTC)n.(GAA)n making up 18.9% each of total tri-repeats mined, which is the second most abundant motif in Arabidopsis . Further, (CCG)n.(CGG)n repeats, which accounted for half of the tri repeats in rice, were rare in dicots (Arabidopsis and soybean) and moderately abundant in monocots other than rice , were found to be ~8% of mined tri-nucleotide repeats in present case. Parida et al , while analyzing the unigenes sequence data of five cereals and Arabidopsis observed that monocot and dicots possess common tri repeats. AGC/AGT/TCA/TCC/TCG/TCT (16.6%) coding for serine was the most abundant motifs in Arabidopsis, followed by glutamic acid (GAA/GAG, 12.3%) and leucine (CTA/CTC/CTG/CTT/CTC/TTA/TTG, 10.9%). Abundance of small/hydrophilic amino acid repeat motifs like that of alanine and serine in the unigenes of cereals and Arabidopsis was perhaps because these are tolerated in many proteins, while strong selection pressure possibly eliminates codon repeats encoding hydrophobic/other amino acids . This observation suggested that considerable sequence divergence, since their early separation about 200 million year ago, between monocot and dicot has led to differential amino acid repeat motifs in the proteins, and that the selection has played a significant role in greater retention of those which are tolerated more.
The overall frequency of NR UGMS primer designation was 7.4% of the unigene sequence data. This figure is significantly higher than that found in the case of grapes and sugarcane [24, 25], where the frequency of non-redundant SSRs in the total population of the clones in the cDNA library was 2.5% and 2.88%, respectively.
We characterized a set of unigenes containing successful UGMS markers by function. Since, the ESTs utilized here were obtained mostly from leaf and tender shoot tissues under natural environmental conditions hence, functional classification in relation to the organ or physiological conditions is not possible with the available data. However, a considerable frequency (60%) of unigenes containing UGMS markers was identified that correspond to the Arabidopsis gene sequence data base. These markers were present either in 5' UTR (52.8%) or in the ORFs (47.2%). As observed in earlier studies, majority of the transcripts detected through GO annotations represent enzymes of general metabolism [32, 35, 36]. However, transcripts related to biological process such as response to abiotic and biotic stresses can be readily mapped using the existing populations. This might reveal functional identity of particular marker locus. Since, these markers have recorded allelic variation across selected tea accessions, thereby working with these UGMS markers may arguably provide a shortcut to candidate genes and gene based functional markers. One of the approaches for their functional validation could be the establishment of association between trait phenotypes and UGMS markers based on these unigenes. In this context, UGMS primer pairs designed in tea would be very important assets for understanding functional diversity and also in marker-assisted breeding in this important commercial crop.
Marker evaluation and polymorphism detection
Only 63.5% of the designed UGMS primer pairs proved to be functional. Similar findings were made for sugarcane , where 40% of all primer pairs failed to amplify the products. Possible explanation for this could be that primers extend across a splice site, the presence of large intron in the genomic sequence, or primers that were derived from chimeric cDNA clones. In general, because of conserved nature, limited polymorphism has been detected for EST-SSRs than the SSRs derived from genomic libraries [30, 41, 42]. Contrarily, a high level of polymorphism was detected in present case irrespective of the Camellia species. This is in agreement with some earlier studies that reported high [43, 44] to even higher level of polymorphism with EST-SSR markers than genomic SSRs markers [6, 45]. Furthermore, the ability to detect per primer a higher number of alleles than Zhao et al.  might be due to high abundance of di-repeats containing UGMS primer pairs (62%). However, the average number of alleles observed in this study remained comparatively lower than that for genomic microstellites (8.3 alleles and 7.8 alleles per primer, respectively) reported by Freeman et al.  and Hung et al. . Detection of larger amplicons than the expected in few cases was probably due to the presence of introns which were excluded during processing of hnRNA into mRNA. Alternatively, multi-locus amplification detected with limited cases, were probably due to duplication and heterozygosity in tea, as was previously reported in tall fescue  and wheat . The mean PIC estimated for genomic SSRs in tea , is higher than the estimated mean PIC for UGMS markers in the present study. The mean heterozygosities expected (H E ; 0.654) and observed (H o ; 0.413) estimates were also slightly less in the present study . Further, test for IAM (Infinite allele model) and SMM models (Stepwise mutation model) for the UGMS loci showed excess heterozygosity in sign test and found to be significant in standardized and Wilcoxon test suggested that the studied marker loci did not show any bottleneck operating in the tea population and remain highly out breeding.
Cross species amplification and sequence comparison of UGMS markers
UGMS markers identified in present study are highly transferable with in species and, frequently among species as reported in barley . For instance, all the 61 UGMS markers developed for C. sinensis are fully transferable to C. assamica &C. assamica ssp. lasiocalyx, and at the various levels to C. lutescens; C. irrawadiensis, C. japonica white flower and C. japonica red flower. Similar pattern of cross transferability has been recorded in case of genomic SSRs in earlier studies in tea [13, 14]. Interestingly, there were 15 (~25%) of the UGMS primer pairs which recorded cross-transferability in all the tested species. This suggested possible representation of highly conserved genes with some important biological/cellular/molecular functions. Further, conservation of repeat motif sequences at the species level and even at the multiple amplicons from the diploid genotypes suggests the wider utility of UGMS markers. Conservation of multiple repeats in diploid genotypes suggests presence of paralogs due to duplication of a particular locus within the genome.
UGMS markers for evaluation of inter and intra specific genetic variations
The results obtained with 34 accessions tested from six tea species indicate that UGMS markers could be utilized for evaluation of genetic relationships within and at the species level. The genetic similarity matrix obtained from the two methods (Jaccard's and Nei & Li's) was significantly correlated confirm the utility of UGMS markers in tea. The genetic relationship among the cultivated C. sinensis, C. assamica and C. assamica ssp lasicalayx accessions reported in this study (GS; 28%) is comparable with RAPD based genetic relationship in 34 Keneyan accessions by Wachira et al. . However, overall an extensive genetic variation was obtained at the intra and inter species level among the 34 accessions [48–52]. The difference in GS might be due to the use of different markers which most likely assay variation in the different genomic regions. However, SSR variation within the genic regions should be very critical for gene activity. Few of the UGMS markers that have shown significant hits in the Arabidopsis proteome can occupy certain positions in coding regions. Expansion and contraction of SSR repeats with known function in these regions might help to establish the association with phenotypic variation as reported earlier in the case of rice  and should detect "true genetic diversity" in crop species [26, 54, 55].
Cluster analysis of 34 tea accessions representing C. sinensis and related species revealed genetic affinities (Figure 5a &5b), which were broadly in agreement with known taxonomic classification of tea . Traditionally, Cambod is considered a sub group of Assam type or sometimes referred to as a subspecies of Assamica known as lasiocalyx , therefore, majority of C. assamica (Assam) and C. assamica ssp. lasiocalyx (Cambod) tea accessions were clustered together in group II with high bootstrap values. Betjan 3/1, a fast growing, high quality tea accession, being an extreme Assam type was also clustered in this group . Tea accessions namely TV-15 and TV-16 are moderately tolerant to tolerant to drought and hence clustered as a distinct subgroup under the major group II. Possible explanation of clustering TV-19 (Cambod; drought tolerant high yielder) and 124/53/8 (an extreme Cambod type) as an intermediate group between ornamental and cultivated accessions is due to their development from progenies of open pollinated seeds. TV-19 developed, introduced by T.C. Tunstall in the year 1918 was selected from progenies 124/53/25 and 124/41/42 of St.124 developed through open pollinated seeds collected from plants of 19/22 . Further, C. irrawadiensis clustered along with two accessions of C. japonica, with red and white flowers in group III suggesting a possibility of introgressive hybridization between these two species. In general, limited introgressive hybridization had occurred in wild/ornamental species because of small populations and narrow geographical distributions. This might also be the reason for clustering of C. lutescens as a single solitary out-group in the present study. Conversely, self incompatibility and long term allogamy make the cultivated tea accessions highly heterogeneous and consequently with broad genetic variations .
Our study revealed the insight of abundance and distribution of microsatellite in the expressed component of the tea genome. Sixty one UGMS markers developed and experimentally validated for genetic diversity analysis in different Camellia spp. will be enriching the limited existing microsatellite markers resource in tea. Most of the UGMS primers were highly polymorphic and were able to unambiguously differentiate the tea germplasm at the inter and intra specific levels. The use of these markers would reduce the cost and facilitate genetic diversity assessment, gene mapping and marker-aided selection in tea. Functional categorization of these UGMS markers corresponded to many genes with biological, cellular and molecular functions, and hence offer an opportunity to investigate the consequences of SSR polymorphism on gene functions.
Screening of newly identified UGMS markers was performed on a test array of 34 accessions of Camellia species (Table 6). This included 30 accessions of the main class of cultivated tea belonging to three major traditional varietal types namely C. sinensis (China type), C. assamica (Assam type) and C. assamica ssp.lasiocalyx (Cambod or Indian type). Three Camellia species comprising of C. lutescens, C. irrawadiensis, C. japonica (red flower), C. japonica (white flower), significantly exploited either in tea improvement programme as wilds and/or as ornamentals used for the examination of cross-species amplification of newly identified UGMS markers. The genomic DNA from the individual tea bush in each case was isolated from young leaves using CTAB method as described by Doyle and Doyle  with minor modifications.
EST data mining, unigenes prediction and SSR detection
A total of 2,181 FASTA formatted EST sequences in Camellia sinensis were retrieved on May 21, 2006 from the National Center for Biotechnology Information (NCBI; http://0-www.ncbi.nlm.nih.gov.brum.beds.ac.uk/entrez) for subsequent data mining. This dataset was scanned and assembled using SeqMan DNA Star lasergene version 7.1 (DNASTAR Inc, Madison, WI) and predicted potential unigenes that contained contigs and singletons from all the EST sequences with parameters (match size: 5, minimum match percentage: 80, match spacing: 150, gap penalty: 0.00, gap length penalty: 0.70, maximum mismatch bases: 15). Further, gaps in the aligned sequences due to limited dataset were removed on the basis of probability function of nucleotide occurring at the particular position using Gene Runner version 3.05 nucleotide windows and stored as the relational database. All the unigenes were subsequently searched individually for the presence of SSRs with help of Repeat masker http://www.repeatmasker.org/cgi-bin/WEBRepeatMasker and SSRs with a minimum length of ≥ 18 bp (di & tri) and ≥ 15 bp (tetra, penta & hexa) were masked. These parameters were chosen to identify SSRs with high polymorphic rate. Uninterrupted type of microsatellites in the present case are continuous, however interrupted one's are defined as presence of ≤8 arbitrary nucleotides in between ≥2 SSR motifs.
Initially an annotation of the SSR containing unigenes was done using BLAST in the complete GenBank NR database, and the complete coding sequences from Arabidopsis . Further classification of these unigenes was done using Gene Ontology (GO) system . All the Arabidopsis hits with an high expectation values (Table 2) were submitted to the GO annotation search tool at TAIR website [20, 61], and relative gene counts assigned to the different GO functional classes were displayed as pie chart using Microsoft Excel.
Primer pairs from the SSR containing unigenes were designed with Gene Runner 3.05 software with the following criteria; i) nucleotide length of 18 – 22 base pairs, ii) a Tm value of 50°C to 60°C, iii) the 3' end base with a G or C, preferably and iv) an amplified fragment size of 100 – 350 bp. The formation of secondary structure and primer dimmers were critically monitored to get success of the primers. The names of the primers were prefixed as TUGMS (Tea unigene derived microsatellite) markers as the source is from Camellia sinensis unigene database (Additional file 1).
PCR amplification of all the primers were performed in 10 μl reaction volume consisting 1× PCR buffer (10 mM Tris- pH 9.0, 50 mM KCl, 0.01% Geletin, 1.5 mM MgCl2), 200 μM of each dNTPs, 15 ng each of forward and reverse primers, 0.2 U Taq DNA polymerase (Bangalore Genei) and 20 ng of template DNA. Forward primer was labeled with γ33P ATP (phosphorylation by T4 polynucleotide kinase). The PCR protocol was consisted of one denaturation cycle at 94°C for 4 min, followed by 35 cycles of 94°C for 1 min, annealing at optimum temperature (T a ) (Table 3) for 1 min, and extension at 72°C for 2 min. The final extension cycle was carried out at 72°C for 7 min. All the PCR reactions were carried in I-Cycler (Bio-Rad).
PCR fragments were separated on denaturing polyacrylamide gels consisting of 7% polyacrylamide (AA: BIS = 19:1) and 7 M urea in 1× TBE buffer. The PCR reactions were mixed with equal volume of loading buffer (98% formamide containing 0.8 mM EDTA and 0.025% of each bromophenol blue and xylene cyanol), denatured at 94°C for 5 min and snap cooled on ice. Samples were loaded in preheated Sequi-Gen GT sequencing cells (Bio Rad, Australia), which run at 60 W for 1.5 up to 2.0 hrs depending upon the fragment sizes to be separated. After run, the gel was blotted on the chromatographic paper CP3M (PALL Life Sciences) and vacuum dried for two hrs before subjecting it to autoradiography for 2–3 days at -70°C depending on the signal intensity. The size of the fragments was estimated using 20 bp DNA size standard (Cambrex Bioproduct, USA).
Sequencing of PCR product
PCR products were separated on polyacralamide gel. Selected fragments were excised and dipped in 10 μl nuclease free water for 30 min. Another round of PCR was made following the same protocol with extracted DNA as template. The PCR products were separated on 2% Seakem LE agarose (Cambrex bioproduct, USA) gel and extracted using kit (Montage Millipore Corp, USA). DNA concentration in each case was measured using NanoDrop 1000 (NanoDrop spectrophotometer, USA). The PCR products were ligated to pGEM-T easy vector (Promega, USA). Sequencing was performed using ABI 3730 xl DNA Analyzer in 20 μl of sequencing reactions consisted of 250 ng of template DNA, 4.0 pmol universal sequencing primer, 8 μl of ready reaction mix BigDye terminator (Applied Biosystem Version 3.1). The base calling and post processing of the sequence data were done using sequence analysis software (Applied Biosystem Version 5.2). The nucleotide sequences were aligned using DNASTAR software (MegAlign DNA Star lasergene version 7.1) using Clustal W algorithm method.
The fragment size is reported for the most intensely amplified band for each UGMS locus or average stutter if the intensity was same using 20 bp DNA size standard. Null alleles were assigned to genotypes with confirmed no amplification products under the standard conditions. The polymorphism determined according to the presence (1) or absence (0) and data was entered in a binary data matrix as discrete variables. Jaccard's coefficient was calculated to develop a phylogenetic tree on the unweighted pair group method with arithmetic mean (UPGMA). The computer package NTSYS-pc Ver. 2.02e, Rohlf,  was used for cluster analysis and matrix correlation. Genetic similarities (GS) based on Jaccards's coefficient were again checked by Nei and Li's formula  as GSxy = 2Nxy (Nx + Ny), where Nxy is number of bands shared in accessions X and Y, Nx is the number of bands shared in accession X, Ny is the number of fragments shared in accessions Y, were calculated using TREECON software package . The robustness of neighbour joining tree was evaluated by bootstrapping (1000 bootstrap replicate) using TREECON. Popgene software package by Yeh et al.  was used to calculate heterozygosity (observed & expected). The polymorphism information content (PIC) of each marker was calculated according to Anderson et al. :
Where Pij is the frequency of the jth pattern for marker i and summation extends over n patterns.
The fit of each locus distribution to expected distribution under two different mutation models, the IAM (infinite allele model) and SMM (step mutation model) was tested using the program BOTTLENECK . Considering the locus limitations in data analysis using BOTTLENECK, particularly 40 UGMS loci having detected PIC ≥ 3.0 were selected. Observed allele frequency and sample sizes were input parameters. These analyses provide a test statistic, the Wilcoxon sign-rank test, for the probability that an observed allele distribution with a given heterozygosity (gene diversity) was generated under each of the two mutation models.
Gupta PK, Varshney RK: The development and use of microsatellite markers for genetic analysis and plant breeding with emphasis on bread wheat. Euphytica. 2000, 113: 163-185. 10.1023/A:1003910819967.
Wu K, Tanksley SD: Abundance, polymorphism and genetic mapping of microsatellites in rice. Mol Gen Genet. 1993, 241: 225-235. 10.1007/BF00280220.
Gonzalo MJ, Oliver M, Garcia MJ, Monfort A, Dolcet SR, Katzir N, Arus PM: A Simple-sequence repeat markers used in merging linkage maps of melon (Cucumis melo L.). Theor Appl Genet. 2005, 110: 802-811. 10.1007/s00122-004-1814-6.
Paniego N, Echaide M, Munž M, Fernàde ZL, Torales S, Faccio P, Fuxan I, Carrera M, Zandomeni R, Suàez EY, Hopp HE: Microsatellite isolation and characterization in sunflower (Helianthus annuus L.). Genome. 2002, 45: 34-43. 10.1139/g01-120.
Lowe AJ, Moule C, Trick M, Edwards KJ: Efficient large scale development of SSRs for marker and mapping applications in Brassica crop species. Theor Appl Genet. 2004, 108: 1103-1112. 10.1007/s00122-003-1522-7.
Varshney RK, Garner A, Sorells ME: Genic microsatellite markers in plants: features and applications. Trends Biotechnol. 2005, 23: 48-55. 10.1016/j.tibtech.2004.11.005.
Parida SK, RajKumar A, Dalal V, Singh NK, Mohapatra T: Unigene derived microsatellite markers for cereal genomes. Theor Appl Genet. 2006, 112: 808-817. 10.1007/s00122-005-0182-1.
Visser T: Tea, Camellia sinensis (L.) O. Kuntze. Outline of Perennial Crop Breeding in the Tropics. Edited by: Ferwarda FP, Wit F, Veenman H, Zonen NV. Wageningen, The Netherlands; 1969:459-493.
Purseglove JW: Tropical Crops: Dicotyledons1. John Wiley and Sons, New York; 1968:332
Wickremasinghe RL: Tea. Advances in food research. Edited by: Mark EM, Steward GF. Acad press, New York. 1979, 24: 229-286.
Wickremaratne MR: Variation in some leaf characteristics in tea (C. sinenesis L.) and their use in identification of clones. Tea Q. 1981, 50: 183-189.
Banerjee B: Dry matter production and partitioning by tea varieties under differential pruning. Appl Agric Res. 1988, 3: 326-328.
Freeman S, West J, James C, Lea V, Mayes S: Isolation and characterization of highly polymorphic microsatellites in tea (Camellia sinensis). Mol Ecol Notes. 2004, 4: 324-326. 10.1111/j.1471-8286.2004.00682.x.
Hung CY, Wang KH, Huang CC, Gong X, Ge XJ, Chiang TY: Isolation and characterization of 11 microsatellite loci from Camellia sinensis in Taiwan using PCR-based isolation of microsatellite arrays (PIMA). Conserv Genet. 2007.
Zhao LP, Liu Z, Chen EL, Yao EMZ, Wang EXC: Generation and characterization of 24 novel EST derived microsatellites from tea plant (Camellia sinensis) and cross-species amplification in its closely related species and varieties. Conserv Genet. 2007.
Park JS, Kim JB, Haha BS, Kim KH, Ha SH, Kim JB, Kim YH: EST analysis of genes involved in secondary metabolism in Camellia sinensis (tea), using suppression subtractive hybridization. Plant Sci. 2004, 166: 953-961. 10.1016/j.plantsci.2003.12.010.
Chen L, Zhao LP, Gao QK: Generation and analysis of expressed sequence tags from the tender shoots cDNA library of tea plant (Camellia sinensis). Plant Sci. 2005, 168: 359-363. 10.1016/j.plantsci.2004.08.009.
Sharma P, Kumar S: Differentail display-mediated identification of three drought-responsive expressed sequence tags in tea [Camellia sinensis (L) O. Kuntze]. J Biosci. 2005, 30: 231-235. 10.1007/BF02703703.
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genetics. 2000, 25: 25-29. 10.1038/75556.
Berardini TZ, Mundodi S, Reiser R, Huala E, Garcia-Hernandez M, Zhang P, Mueller LM, Yoon J, Doyle A, Lander G, Moseyko N, Yoo D, Xu I, Zoeckler B, Montoya M, Miller N, Weems D, Rhee SY: Functional annotation of the Arabidopsis genome using controlled vocabularies. Plant Physiology. 2004, 135: 1-11. 10.1104/pp.104.040071.
Kumpatla SP, Mukhopadhyay S: Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species. Genome. 2005, 48: 985-998. 10.1139/g05-060.
Kantety RV, La Rota M, Matthews DE, Sorrells ME: Data mining for simple sequence repeats in expressed sequence tags from barley, maize, rice, sorghum and wheat. Plant Mol Biol. 2002, 48: 501-510. 10.1023/A:1014875206165.
Poncet V, Rondeau M, Tranchant C, Cayrel A, Hamon S, Kochko A, Hamon P: SSR mining in coffee tree EST databases: potential use of EST-SSRs as markers for the Coffea genus. Mol Genet Genomics. 2006, 276: 436-449. 10.1007/s00438-006-0153-5.
Scott KD, Eggler P, Seaton G, Rossetto M, Ablett EM, Lee LS, Henry RJ: Analysis of SSRs derived from grape ESTs. Theor Appl Genet. 2000, 100: 723-726. 10.1007/s001220051344.
Cordeiro GM, Casu R, Mclntyre CL, Manners JM, Henry RJ: Microsatellite markers from sugarcane (Saccharum spp.) ESTs cross transferable to erianthus and sorghum. Plant Sci. 2001, 160: 1115-1123. 10.1016/S0168-9452(01)00365-X.
Thiel T, Michalek W, Varshney RK, Graner A: Exploiting EST databases for the development of cDNA derived microsatellite markers in barley (Hordeum vulgare L.). Theor Appl Genet. 2003, 106: 411-422.
Aggarwal RK, Prasad SH, Varshney RK, Prasanna R, Bhat KV, Singh L: Identification, characterization and utilization of EST-derived genic microsatellite markers for genome analyses of coffee and related species. Theor Appl Genet. 2007, 114: 359-372. 10.1007/s00122-006-0440-x.
Cardle L, Ramsay L, Milbourne D, Macaulay M, Marshall D, Waugh R: Computational and experimental characterization of physically clustered simple sequence repeats in plants. Genetics. 2000, 156 (2): 847-854.
Weber JL: Informativeness of human (dC-dA)n.(dG-dT)n polymorphism. Genomics. 1990, 7: 524-530. 10.1016/0888-7543(90)90195-Z.
Cho YG, Ishii T, Temnykh S, Chen X, Lipovich L, Park WD, Ayres N, Cartinhour S, McCouch SR: Diversity of microsatellites derived from genomic libraries and GenBank sequences in rice (Oryza sativa L.). Theor Appl Genet. 2000, 100: 713-722. 10.1007/s001220051343.
Temnykh S, Park WD, Ayers N, Cartinhour S, Hauck N, Lipovich L, Cho YG, Ishii T, McCouch SR: Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.). Theor Appl Genet. 2000, 100: 697-712. 10.1007/s001220051342.
Ceresini PC, Petrarolha Silva CLS, Missio RF, Souza EC, Fischer CN, Guillherme IR, Gregorio I, da Silva EHT, Cicarelli RMB, da Silva MTA: Satellyptus: Analysis and database of microsatellites from ESTs of Eucalyptus. Genet Mol Biol. 2005, 28: 589-600. 10.1590/S1415-47572005000400014.
Palmieri DA, Novelli VM, Bastianel M, Cristofani-Yaly M, Astúa-Monge G, Carlos EF, Carlos de Oliveira A, Machado MA: Frequency and distribution of microsatellites from ESTs of citrus. Genet Mol Biol. 2007, 30 (3 suppl): 1009-1018.
Gao LF, Tang JF, Li HW, Jia JZ: Analysis of microsatellites in major crops assessed by computational and experimental approaches. Mol Breed. 2003, 12: 245-261. 10.1023/A:1026346121217.
Newcomb RD, Crowhurst RN, Gleave AP, Rikkerink EHA, Allan AC, Beuning LL, Bowen JH, Gera E, Jamieson KR, Janssen BJ: Analyses of expressed sequence tags from apple. Plant Physiol. 2006, 141: 147-166. 10.1104/pp.105.076208.
Folta KM, Staton M, Stewart PJ, Jung S, Bies DH, Jesdurai C, Main D: Expressed sequence tags (ESTs) and simple sequence repeat (SSR) markers from octoploid strawberry (Fragaria × ananassa). BMC Plant Biol. 2005, 5: 12-10.1186/1471-2229-5-12.
Chen C, Zhou P, Choi YA, Huang S, Gmitter FG: Mining and characterizing from citrus ESTs. Theor Appl Genet. 2006, 112: 1248-1257. 10.1007/s00122-006-0226-1.
Dong J, Guang-Yan Z, Qi-Bing H: Analysis of microsatellites in citrus unigenes. Acta Genet Sinica. 2006, 33: 345-353. 10.1016/S0379-4172(06)60060-7.
Morgante M, Hanafey M, Powell W: Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nature Genet. 2002, 30: 194-200. 10.1038/ng822.
Katti MV, Ranjekar PK, Gupta VS: Differential distribution of simple sequence repeats in eukaryotic genome sequences. Mol Biol Evol. 2001, 18 (7): 1161-1167.
Eujayl I, Sorrells M, Baum M, Wolters P, Powell W: Assessment of genotypic variation among cultivated durum wheat based on EST-SSRs and genomic SSRs. Euphytica. 2001, 119: 39-43. 10.1023/A:1017537720475.
Gupta PK, Rustagi S, Sharma S, Singh R, Kumar N, Balyan HS: Transferable EST-SSR markers for the study of polymorphism and genetic diversity in bread wheat. Mol Genet Genomics. 2003, 270: 315-323. 10.1007/s00438-003-0921-4.
Eujayl I, Sledge MK, Wang L, May GD, Chekhovskiy K, Zwonitzer JC, Mian MA: Medicago truncatula EST-SSRs reveal cross-species genetic markers for Medicago spp. Theor Appl Genet. 2004, 108: 414-422. 10.1007/s00122-003-1450-6.
Saha MC, Mian MA, Eujayl I, Zwonitzer JC, Wang L, May GD: Tall fescue EST-SSR markers with transferability across several grass species. Theor Appl Genet. 2004, 109: 783-791. 10.1007/s00122-004-1681-1.
Liewlaksaneeyanawin C, Ritland CE, El-Kassaby YA, Ritland K: Single-copy, species-transferable microsatellite markers developed from loblolly pine ESTs. Theor Appl Genet. 2004, 109: 361-369. 10.1007/s00122-004-1635-7.
Yu JK, Dake TM, Singh S, Benscher D, Li W, Gill B, Sorrells ME: Development and mapping of EST-Derived simple sequence repeat (SSR) markers for hexaploid wheat. Genome. 2004, 47: 805-818. 10.1139/g04-057.
Wachira FN, Waugh R, Hackett CA, Powell W: Detection of genetic diversity in tea (Camellia sinensis) using RAPD markers. Genome. 1995, 38: 201-210. 10.1139/g95-025.
Paul S, Wachira FN, Powell W, Waugh R: Diversity and genetic differentiation among populations of Indian and Kenyan tea (Camellia sinensis (L.) Kuntze, O) revealed by AFLP markers. Theor Appl Genet. 1997, 94: 255-263. 10.1007/s001220050408.
Mondal TK: Assessment of genetic diversity of tea (Camellia sinensis (L.) O. Kuntze) by inter-simple sequence repeat polymerase chain reaction. Euphytica. 2002, 128: 307-315. 10.1023/A:1021212419811.
Balasaravanan T, Pius PK, RajKumar R, Muraleedharan N, Shasany AK: Genetic diversity among south Indian tea germplasm (Camellia sinensis, C. assamica and C. assamica spp. lasiocalyx) using AFLP markers. Plant Sci. 2003, 165: 365-372. 10.1016/S0168-9452(03)00196-1.
Chen L, Gao QK, Chen DM, Xu CJ: The use of RAPD markers for detecting genetic diversity, relationship and molecular identification of Chinese elite tea genetic resources (Camellia sinensis (L.) O. Kuntze) preserved in tea germplasm repository. Biodiversity Conserv. 2005, 14: 1433-1444. 10.1007/s10531-004-9787-y.
Chen L, Yamaguchi S: RAPD markers for discriminating tea germplasms at the inter-specific level in China. Plant Breed. 2005, 124: 404-409. 10.1111/j.1439-0523.2005.01100.x.
Ayres NM, McClung AM, Larkin PD, Bligh HFJ, Jones CA, Park WD: Microsatellites and a single nucleotide polymorphism differentiate apparent amylose classes in an extended pedigree of US rice germplasm. Theor Appl Genet. 1997, 94: 773-781. 10.1007/s001220050477.
Eujayl I, Sorrells ME, Baum M, Wolters P, Powell W: Isolation of EST-derived microsatellite markers for genotyping the A and B genomes of wheat. Theor Appl Genet. 2002, 104: 339-407. 10.1007/s001220100738.
Maestri E, Malcevschi A, Massari A, Marmiroli N: Genome analysis of cultivated barley (Hordeum vulgare) using sequencetagged molecular markers. Estimates based on divergence based on RFLP and PCR markers derived from stress-responsive genes, and simple sequence repeats (SSRs). Mol Genet Genomics. 2002, 267: 186-201. 10.1007/s00438-002-0650-0.
Wight W: Tea classification revised. Curr Sci. 1962, 31: 298-299.
Bezbaruah HP, Dutta AC: Tea germplasm collection of Tocklai Experimental Station. Two & Bud. 1977, 24: 22-30.
Singh ID: Indian tea germplasm and its contribution to the World's tea Industry. Two & Bud. 1979, 26: 23-26.
Doyle JJ, Doyle JE: Isolation of plant DNA from fresh tissue. Focus. 1990, 12: 13-15.
TIGR: The TIGR Eukaryotic Projects Databases. [http://www.tigr.org/tdb/euk/].
TAIR: The Arabidopsis Information Resource. [http://www.arabidopsis.org/].
Rohlf FJ: NTSYS-pc 2.0e. Exeter Software, Setauket, New York, USA; 1998.
Nei M, Li WH: Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc Nat Acad Sci, USA. 1979, 76: 5269-5273. 10.1073/pnas.76.10.5269.
Peer Van de Y, De Wachter R: TREECON for Windows: a software package for the construction and drawing of evolutionary trees for the Microsoft Windows environment. Comput Appl Biosci. 1994, 10: 569-570.
Yeh FC, Yang RC, Boyle T: POPGENE, Version 1.3.1. A Microsoft Windows-Based Freeware for Population Genetic Analysis. University of Alberta and the Centre for International Forestry Research, Edmonton, Canada; 1999. [http://www.ualberta.ca/~fyeh/].
Anderson JA, Churchill GA, Autrique JE, Tanksley SD, Sorrells ME: Optimizing parental selection for genetic linkage maps. Genome. 1993, 36: 181-186. 10.1139/g93-024.
Cornuet JM, Luikart G: Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics. 1996, 144: 2001-2014.
The research work presented in the manuscript was funded by Department of Biotechnology (DBT) and Council of Scientific and Industrial Research (CSIR), Government of India. We thank Dr S. Rajkumar for providing help in statistical analysis. This is IHBT communication No. 0674.
RKS conceived the study, participated in designing, coordination, data analysis, interpretation, checked the data, drafted, reviewed and improved the manuscript. PB carried out mining of EST data, unigenes prediction, GO study, analysis of repeat type and frequency of microsatellites, genotyping, and sequencing and helped in drafting the manuscript. RN carried out the microsatellite analysis for genotyping. TM helped in interpretations and improved the manuscript. PSA helped in overall coordination. All authors have read and approved the final manuscript.
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Sharma, R.K., Bhardwaj, P., Negi, R. et al. Identification, characterization and utilization of unigene derived microsatellite markers in tea (Camellia sinensis L.). BMC Plant Biol 9, 53 (2009). https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2229-9-53
- Gene Ontology
- Polymorphism Information Content
- White Flower
- Camellia Sinensis
- Average Polymorphism Information Content