Detection of single nucleotide polymorphisms in the conserved ESTs regions of Gossypium arboreum Tayyaba Shaheen Yusuf Zafar Mehboob-ur-Rahman* *Corresponding author Financial support: This research was funded by Higher Education Commission (HEC) through a project under the scheme of PYI award (2007-2010) and indigenous PhD scholarship scheme through a PhD student grant. Keywords: conserved regions, Gossypium arboretum, SNPs.
Exploring genetic variation in Gossypium arboreum L. germplasm is useful as it contains many important genes conferring resistance to different stresses. In limited earlier studies, low level of genetic diversity was found by using conventional DNA marker systems which may impede future genome mapping studies. In the present investigation, we explored the extent of Single Nucleotide Polymorphisms (SNP) among 30 conserved regions of Expressed Sequence Tags (EST) of low copy genes between two genotypes of G. arboreum. A total of 27 SNPs including 21 substitutions and 6 Insertions and deletions (Indels) in 7804 bp were found between these genotypes with a frequency of one SNP per 371 bp and one Indel after every 1300 bp. Out of these SNPs, 52% were transitions, whilst 48% SNPs were transversion. In conclusion, SNPs are expedient markers that can explore polymorphism in highly conserved sequences where other markers are not effective.
Single nucleotide polymorphisms (SNPs) are single base change or small insertions and deletion (Indels) in homologous DNA fragments. SNPs are the most abundant source of polymorphisms which have potential to be used in association mapping studies (Ayeh, 2008). For example, human genome contains ~9-10 million SNPs, of which 3.1 million have been identified (The International Hapmap Consortium, 2007), thus are preferred over the other marker assays. SNPs are useful for characterizing allelic variation, quantitative trait locus (QTL) mapping, and implementing marker-assisted selection (MAS) in plant breeding. In multiple investigations, Expressed sequence tags (ESTs) have been used as a source for identifying SNPs in many plant species such as maize (Zea mays L.) (Ching et al. 2002: Barbazuk et al. 2007), rice (Oryza sativa L.) (Nasu et al. 2002) and soybean (Glycine max L. Merr.) (Zhu et al. 2003: Choi et al. 2007). Recently, new re-sequencing approaches (array-based methods) have been developed to identify SNPs. For example, in Arabidopsis more than one million non-redundant SNPs were identified which can be used in disequilibrium mapping studies (Clark et al. 2007). However, reports on identification of SNPs in cotton are meager because of its huge genome size coupled with the polyploidy nature of the cultivated cotton (allotetraploid), which requires the distinction of allelic SNPs, from paralogs (Rahman et al. 2009). Mining SNPs in diploid genomes is more feasible due to low level of complexity in diploid genomes (Wang et al. 2005; Shaheen et al. 2006). G. arboreum is a diploid cultivated cotton species has been present in Pakistan, in a domesticated form, since before 6,000 BC (Moulherat et al. 2002). The species has adaptive features like a deep root system, resistance to insect pests/diseases and indehiscent bolls, which can be utilized in isolation of important genes (Arpat et al. 2004). To the extent of our knowledge, SNPs have not been reported in the nuclear genome of G. arboreum accessions. In the present study, conserved coding regions, least prone to mutations (Koornneef et al. 2004), have been selected to identify SNPs in low copy number genes (preferable single copy) in two G. arboreum genotypes (evolved from two different breeding programs) as the other marker systems can not be effective to explore these regions (Semagn et al. 2006). This preliminary information will set a stage for developing high genetic linkage maps which will be useful for trait mining. Experimental material used in this study was a local cultivar of G. arboreum ‘Ravi’ which was a selection from variety 465-D. Total genomic DNA was isolated by a method used by Iqbal et al. (1997). EST sequences of G. arboreum accession 8401 (Developed in India for long staple length) were obtained from cotton db EST (Udall et al. 2006). Gene specific primers were designed based on conserved regions of ESTs showing homology with low copy genes, preferable one copy gene (Table 1). These ESTs were selected out of 1000 ESTs on basis of their homology with genes of known function and low copy number. Polymerase chain reaction (PCR) was performed in a total volume of 20 µl, using 2.5 µl (15 ng/µl) of cotton DNA, 10 x PCR buffer without MgCl2 (10 mM Tris-HCl, 50 mM KCl, PH 8.3), 3 mM MgCl2, 0.1 mM each of dATP, dGTP, dCTP and dTTP and 0.5 units of Taq DNA polymerase, 0.15 mM of each primer. Taq DNA polymerase together with 10 x PCR buffer, MgCl2 and dNTPs were from MBI Fermentas. Polymerase chain reaction consisted of 35 cycles of 94ºC for 1 min, 94ºC for 30 sec, 50ºC for 30 sec, 72ºC extension for 1 min and final extension at 72ºC for 10 min. PCR products were resolved on 1% agarose to check amplification. Sequencing of PCR products was done on ABI automated DNA sequencer. Sequences were edited manually. To avoid discrepancies in SNP detection, 4 runs of each of the product for sequencing were conducted. Sequences of Arabidopsis thaliana were obtained from GenBank. Thirty gene sequences from two diploid varieties were used for SNP detection (Table 1). Only those SNPs were considered which were detected repeatedly in all sequencing results. Consensus sequence of the 4 runs were used for alignment. DNASTAR (DNASTAR Inc., Madison, WI, USA) and Clustal v were used for sequence alignment (Figure 1). We identified SNPs in the sequenced PCR amplified products of conserved regions of ESTs of G. arboreum. As the primers were based on conserved EST regions and the amplified product size was same as was expected from primers amplification. Hence, it can be concluded that the primers amplified only the exon regions. Development of new SNPs by re-sequencing of PCR amplicons with or without pre-screening has been reported in previous studies (Ayeh, 2008). In most plant species, SNPs have been detected by comparison of two accessions as in maize (Ching et al. 2002) and soybean (Zhu et al. 2003). Similarly, in tetraploid cotton, a PCR based direct DNA sequencing technique was used to identify SNPs in different fiber related genes (Lu et al. 2005). Approximately 7804 bp of G. arboreum DNA was sequenced and a total of 27 polymorphisms were identified (21 SNPs and 6 single base Indels). The calculated SNP frequency was one single nucleotide change every 371 bp, whilst, Indels occurred less frequently, about one every 1300 bp or the rate of variation per nucleotide (0.27%). In previous studies with other molecular markers genetic diversity among G. arboreum varieties has been assessed. Randomly amplified polymorphic DNA (RAPD) estimated 59% to 76% similarity (Kumar et al. 2008) and 47.05% to 98.73 (Rahman et al. 2008), and with SSRs 58% to 87% similarity (Liu et al. 2006), 52% to 98% polymorphism information content (PIC) (Guo et al. 2006) was observed. Commonality among all above studies is the detection of low genetic diversity among G. arboreum accessions. In tetraploid cotton, a total of 94 SNPs including 36 single-base changes (38.3%) and 58 indels (61.7%) were identified in 16 fiber gene fragments with an average frequency of one SNP per 500 bp DNA which was lower than that in coding sequences of many other plant species (Lu et al. 2005). Another SNP study revealed the rate of variation per nucleotide was 0.35% between G. hirsutum and G. barbadense (one SNP every 286 bp) (Rong et al. 2004), which is a higher frequency as compared to frequency observed in this study. In the FIFI gene, regulating the fiber development in G. barbadense, three SNPs were reported while comparing with the corresponding gene in G. arboreum and G. hirsutum with a frequency 1SNP/270 bp interspecifically (Ahmad et al. 2007). In another investigation, one SNP per 77 bases in the six R2R3-MYB genes were reported in different cotton genomes (An et al. 2008). In a total of 21 substitutions, 11 (52%) were transitions and 10 were transversions (Table 2). Such commonalties were also found in rice (61.8%) (Feltus et al. 2004) and citrus (52.7%) (Novelli et al. 2004). Alterations of this type could be attributed to the actions of 5-methylcytosine deamination (Feltus et al. 2004). Out of 21 substitutions 14 were present in ORF region, of which 9 (64%) were synonymous, and 7 were present in non ORF region. These values are comparable with many previous studies conducted in maize (72% synonymous, Ching et al. 2002). Our results explicate a comparable ratio of synonymous to nonsynonymous mutations in cotton (1.8) as compared to (2.6) in soybean (Zhu et al. 2003), and 1.7 in melon (Morales et al. 2004). The synonymous substitutions are frequently found in ORF regions as these are not detrimental to the plant (Morales et al. 2004). In the present study, majority of Indels (67%) were found in non ORF regions because these are not tolerable in ORF regions (Liston and Briedis, 1995) SNPs can prove very effective in MAS if a SNP marker is found associated with target trait. Moreover SNPs are highly stable markers which may contribute directly to phenotype which can further be utilized by plant breeders for MAS to identify individual plants containing a combination of alleles of interest from large segregating populations (Batley and Edwards, 2007). The SNPs identified in this study can further be utilized for traits association and MAS. SNPs identification in polyploids have been simplified with the Illumina BeadArray technology coupled with GoldenGate assay without the need of a prior PCR amplification step e.g., in polyploid wheat pure lines (Akhunov et al. 2009). About 89 and 84% of SNPs in tetraploid and hexaploid wheat, respectively, could be converted into successful genotyping assays. The Illumina BeadArray platform, represents an excellent tool for studying genetic architecture of complex traits, association mapping and, with proper safeguards, evolutionary forces that shape the genetic diversity of polyploids like cotton as well (Akhunov et al. 2009). In conclusion SNPs are an effective tool for whole genome survey and are potent markers to survey conserved regions where other markers may not prove very effective which will pave the way of developing dense genetic maps. Microarray based SNP genotyping can be a very effective tool but it is just in preliminary stages. 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