Computational protocol: Development of genomic SSR markers for fingerprinting lettuce (Lactuca sativa L.) cultivars and mapping genes

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[…] Genomic SSR markers were developed from L. sativa cv. Salinas according to the protocols of Glenn and Schable [] and Farias et al. [], with some modifications. The procedure consists of DNA extraction, DNA digestion with a restriction enzyme, ligation of linkers to DNA fragments, PCR-enrichment for microsatellite-containing fragments, hybridization to microsatellite-specific probes, recovery of microsatellite-containing fragments, and cloning and sequencing of products.Approximately 100 mg of tissue from young leaves of a month-old, greenhouse-grown plant was collected and immediately lyophilized. The sample was ground to fine powder using a TissueLyser mill before extracting DNA with DNeasy Plant Mini Kit (both from Qiagen, Valencia, CA). The DNA concentration and quality was analyzed with an ND-1000 Spectrometer (NanoDrop Technologies, Wilmington, DE). Three μg of genomic DNA was digested with BfuCI, an isoschizomer of Sau3AI (New England Biolabs Ipswich, MA) according to the manufacturer’s instructions. The enzyme was deactivated at 80°C for 20 min and a 5 μl aliquot was run on a 0.8% agarose gel to verify the digestion. The linkers were created by hybridizing two oligonucleotides: Er1BhGATCSticky 5′-GAT CGG CAG GAT CCA CTG AAT TCG C-3′ and Er1Bh1Blunt 5′-GCG AAT TCA GTG GAT CCT GCC-3′. These linkers were then ligated to the fractioned DNA using T4 DNA ligase (New England Biolabs, Ipswich, MA) following the manufacturer’s instructions.A PCR was set up to increase quantity of the fragments that are containing SSRs. PCR-enrichment was performed using the product of the ligation as a template and Er1Bh1Blunt as a primer. The reaction was set up as follows: 1 × PCR ready mix (Promega, Fitchburg, WI), 0.25 mM Er1BhBlunt primer, 1 μl template and bidistilled water to 25 μl final volume (Table ). Unincorporated nucleotides and primers were cleaned up with Exonuclease I and Antarctic phosphatase (New England Biolabs, Ipswich, MA). The oligonucleotide probes were biotinylated using terminal transferase (New England Biolabs, Ipswich, MA) following the manufacturer’s instructions. In order to produce 1–3 biotins per oligonucleotide, a proportion of 1 pmol of 3′ ends to 0.01 mmol of biotin-14-dATP (Invitrogen, Grand Island, NY) was used. The oligonucleotides were mixed as suggested by Glenn and Schable []: mix 2 ((AG)12, (TG)12, (AAC)6, (AAG)8, (AAT)12, (ACT)12, (ATC)8); mix 3 ((AAAC)6, (AAAG)6, (AATC)6, (AATG)6, (ACAG)6, (ACCT)6, (ACTC)6, (ACTG)6); and mix 4 ((AAAT)8, (AACT)8, (AAGT)8, (ACAT)8, (AGAT)8). The mixes were biotinylated independently at 37°C for 30 min and the enzyme was deactivated by heating to 70°C for 10 min. The excess biotin was removed using precipitation with 3 M sodium acetate and absolute ethanol, and resuspending the probes in 100 μl of bidistilled water. To isolate SSR-containing fragments, the probes were attached to Streptavidin magnetic beads (New England Biolabs, Ipswitch, MA) according to the manufacturer’s instructions. The product of the enrichment-PCR was denatured at 95°C for 5 min and quickly chilled on ice. This product was then hybridized to the probes in an oven at 55°C for 3 hours and washed with 2 × SSC buffer and 0.1% SDS buffer twice, and then with 1 × TE buffer-50 mM NaCl and resuspended in 200 μl of 1 × TE buffer. To recover SSR-containing fragments, the probe-SSR complex was denatured at 95°C for 5 min and the beads were quickly removed with a magnet. A PCR was set up to test recovery of fragments using the Er1Bh1Blunt oligonucleotide as a primer and the product of the hybridization as a template (Table ). The PCR products were then run on a 1.2% agarose gel.Once the fragment recovery was verified, a second PCR-enrichment was set up to prepare sequences for cloning. Four reactions were set up with 0.8 mM dNTPs, 1× PCR buffer, 0.4 μM Er1Bh1Blunt primer, 2.5 U Taq Polymerase and 1 μl of the hybridization product (Table ). The PCR products were pooled, cleaned with QiaQuick columns (Qiagen, Valencia, CA), and cloned using Topo TA cloning kit for sequencing and E. coli Mach1-T1R cells (Invitrogen, Grand Island, NY), according to the manufacturer’s instructions. Transformed cells were passed to 96 well plates with lysogeny broth (LB) containing 50 mg/ml ampicillin, and grown for at least 4 hours at 37°C. A confirmation PCR was carried out using standard M13 forward and reverse primers and 2–3 μl of the LB medium with bacterial growth as a template. Bovine serum albumin in the concentration of 25 μg/ml was added to the PCR; all other reagents were used in concentrations described above. E. coli colonies that contained products of expected size were transferred to Wu Broth supplemented with ampicillin and submitted for sequencing to the USDA-ARS Genomics and Bioinformatics Research Unit in Stoneville, MS. Sequencing data were cleaned up from vector contamination and assembled in contigs using CLC DNA workbench 5.0 (CLCBio Aarhus, Denmark). The SSRs with the minimal length of 14 bp were identified using WebSat []. Primers for SSR amplification were designed by Primer3 software [] integrated into WebSat. Primer quality analysis was performed with OligoAnalizer 3.1 (Integrated DNA Technologies Inc, Coralville, IA). When sequences contained multiple SSRs, different primer-pairs were designed for each SSR. If amplification with the Primer 3-designed primers did not yield expected products, a second pair of primers was designed using CLC DNA workbench. Sequences of SSR-containing fragments were compared in January 2012 to the GenBank database ( using CLC DNA workbench 5.0. The ‘blastn’ option of the BLAST algorithm [] was applied to search the nucleotide collection (nr) of the viridiplantae database using low complexity filter to avoid spurious hits based on microsatellite sequence only. The threshold of significance to report similarity was set at 1e-4. [...] A set of 36 accessions was used to test polymorphism of newly developed SSR markers. This set comprised 33 L. sativa cultivars plus a single accession from each of the three wild species sexually compatible with cultivated lettuce; prickly lettuce (L. serriola L.), willowleaf lettuce (L. saligna L.), and bitter lettuce (L. virosa L.). Genotyped cultivars belonged to seven horticultural types: crisphead, leaf, romaine, butterhead, stem, Latin, and oil lettuce (Table ).Genotyping with SSR markers: The PCR conditions for SSR amplification were optimized for each primer pair. The optimal PCR conditions are described in Additional file . In general, the reactions were set up using 0.2 μM of each primer, 5 ng of DNA template, and 1× of Taq PCR master mix (New England Biolabs, Ipswich, MA) in a final volume of 10 μl (Table ). The PCR products were separated using eGene HDA-GT12 DNA analyzer (currently known as QIAxcel System, from Qiagen, Valencia, CA) and scored by Biocalculator software (eGene, Irvine, CA).Analysis of genetic heterozygosity: The statistical analyses of SSR data were performed with GenAlEx 6.1 [] for codominant markers and GenoDive v.2.0b20 []. Missing data and null alleles were excluded from the analysis. The unbiased estimate of genetic heterozygosity UHe[] and observed number of different alleles Na were used to measure marker informative value (GenAlEx 6.1). Genetic distances (Fst) [] between all pairs of horticultural types with at least two accessions, analysis of molecular variance (AMOVA) [], and principal components analysis (PCA) were calculated using GenoDive v.2.0b20. The significance of the differences between the EST-based [] and genomic SSRs were tested with Student’s t-test.Consistency of molecular marker datasets: Data resolution (DR) statistics were used to evaluate the internal consistency of the SSRs dataset with the program written by van Hintum []. DR values can be in the range from 0 to 1; where higher values indicate higher internal consistency of the data. The number of replications was set to 10,000.Identification of genotypes: The software MultiLocus ver. 1.3b [] was used to estimate the number of different genotypes that can be identified in a set of 36 accessions with a gradually increasing number of markers. This analysis shows whether scoring more markers leads to increasing number of identified genotypes. One thousand samplings of markers were performed at random from 1 to m-1, where m is the total number of markers. The relative number of identified genotypes was calculated by dividing the number of identified genotypes by the total number of accessions. […]

Pipeline specifications

Software tools CLC Assembly Cell, WebSat, Primer3, BLASTN, GenAlEx, Genodive
Applications Population genetic analysis, qPCR
Organisms Lactuca sativa