Approximately 188 F₃ progenies obtained from a self-pollinated F₂ population (derived from crosses between the Pongsu Seribu 2 and Mahsuri) were used for genetic analysis and to evaluate allelic variation. The F₃ plants were cultivated in a greenhouse in the Malaysian Agricultural Research and Development Institute (MARDI), Seberang Perai. The SSR marker panels were tested in parental varieties and entire F₃ families.

Total genomic DNA was extracted from the leaves of selected rice families, according to the methods of Gawel and Jarret [55]. Approximately 2 cm of young leaf tissue was harvested from 4-week-old seedlings. After grinding to a fine powder in liquid nitrogen, the samples were transferred to 1.5 mL centrifuge Eppendorf tubes and mixed with 600 μL of pre-heated extraction buffer [2% CTAB, 1.4 M NaCl, 20 mM EDTA (pH 8.0), 0.1 M Tris–Hcl (pH 8.0), 1% polyvinylpyrrolidone and 0.6 μL 2-merceptoethanol]. The tubes were subsequently incubated at 60 °C in an Eppendorf thermo-mixer comfort machine for 60 min with occasional swirling. The mixture was emulsified with an equal volume of chloroform:isoamyl alcohol 24:1 (v/v) and gently inverted to homogenise the mixture at room temperature for 2 min prior to centrifugation at 12,000 rpm for 5 min. The supernatant was collected into fresh Eppendorf tubes, and the DNA was precipitated with 0.6 volumes of cold (–20 °C) isopropanol. The mixture was gently inverted and incubated on ice for 30 min, and the supernatant was discarded and transferred to a new microcentrifuge tube and centrifuged at 12,000 rpm for 2 min. Subsequently, 50 μL of 70% ethanol was added to the DNA pellet, followed by centrifugation at 12,000 rpm. The supernatant was gently removed, and the dried DNA pellet (30 min) was resuspended in 50–100 μL of 1× TE buffer (10 mM Tris–HCl, pH 8.0 and 1 mM EDTA, pH 8.0) according to the size of the pellet and stored overnight at 4 °C to dissolve the DNA. The DNA was re-precipitated with 1/10 V 3 M sodium acetate (pH 6.8), followed by 2 volumes of absolute ethanol. The mixture was gently inverted and incubated on ice for 30 min, followed by centrifugation at 13,000 rpm for 5 min. Subsequently, the supernatant was discarded, and the pellet was washed with 70% ethanol, air-dried and resuspended in 1× TE buffer. Approximately, 2 μL (10 g/mL) of RNAse was added to the dissolved DNA from each sample and incubated for 30 min at 37 °C. The DNA concentration was spectrophotometrically determined using NanoDrop-ND-1000 Spectrophotometer (NanoDrop-Technologies, USA). The quality of the DNA was determined using 1% agarose gel electrophoresis, followed by staining with 0.1 μg/mL ethidium bromide using 1× TAE buffer at a constant 72 V for 30 min and visualised under UV light. The DNA samples were diluted to 20 ng/μL and stored at –20 °C until further PCR analysis.

Primer sets for 125 microsatellites, related to previously mapped and published blast resistance gene (Pi-Genes) [5,6,9,11], were selected from the Gramene database (www.gramene.org). Parental varieties were used to identify SSR polymorphisms. The genetic polymorphisms were assessed according to the separation of PCR products using 3% agarose gel electrophoresis or the analysis of fluorochrome-labelled PCR products through automated capillary electrophoresis (genetic analyser). Polymorphic markers were used to develop SSR multiplex sets. Thirteen multiplex panels were designed for genotyping and evaluating the F₃ germplasm (Table 1). The forward primers for SSR loci were fluorescently labelled with either 6-carboxyfluorescein (FAM) or hexachloro-6-carboxyfluorescein (HEX) dye from the G5 set (Applied Biosystems) and used for marker amplification in a different panel. Some markers were individually amplified because of the different PCR profiles required by markers in a panel. After amplification, the concentration of the amplicons was determined on 2% agarose gels stained with ethidium bromide.

Length of time and temperature required for primer annealing were optimised using PTC-200 DNA Engine Peltier Thermal Cycler at seven different temperatures (43, 45, 48, 51, 55, 57 and 60 °C). The PCR samples were mixed with bromophenol blue, loaded onto 3% agarose gels (Pharmacia model EPS-200) containing ethidium bromide and run at 5.3 V/cm (Bio-Rad Power Pac 300) for 1 h. The gels were photographed using a gel documentation system (Bio-Rad Molecular Imager Gel Doc XR System).

Factors that alter PCR amplification, such as template DNA, dNTPs, DNA polymerase, Mg²⁺ concentration, etc., were optimised. Two types of PCR assays were performed: uniplex (simplex) and multiplex PCR. For uniplex PCR, the PCR reactions contained 20 ng genomic DNA, 1.5 mM MgCl₂, 0.2 μM of each 3′- and 5′-end primer, 25 mM of dNTPs (0.25 mM each of dATP, dTTP, dGTP and dCTP), 1× PCR reaction buffer and 0.5 units of Taq DNA polymerase in a total volume of 12.5 μL. The uniplex PCR amplification was performed on a thermocycler (PTC-200 Peltier Thermal Cycler DNA Engine) using the following temperature profile: initial denaturation at 94 °C for 5 min, followed by 35 cycles at 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s, with a final extension at 72 °C for 5 min and rapid cooling to 4 °C prior to analysis. For multiplex PCR, the reaction mixture (10 μL) contained 10 ng of template DNA, 0.5 U AmpliTaq Gold DNA Polymerase (Applied Biosystems), 800 μM dNTPs, 2 mM MgCl₂ and 0.1 to 0.3 μM each of forward and reverse primers. The multiplex PCR amplifications were performed in 96-well microtitre plates using a Gene Amp PCR 9700 system (Applied Biosystems). The following PCR profile was used: 94 °C for 5 min, followed by 35 cycles of 94 °C for 30 s, 54 °C, 55 °C or 57 °C (three different annealing temperatures) for 30 s, and 72 °C for 30 s, with a final extension at 72 °C for 5 min. Three different cycling conditions were initially tested, and the most effective condition (programme C) was used for multiplex PCR.

The PCR products were pooled by combining 1.0 μL of each amplified product and adding water, when necessary, to bring the products to a uniform dilution of 1:12. The samples were prepared for gel loading by combining 1 μL of the pooled PCR products with 0.13 μL of LIZ-500 internal size standard and adjusted to a final volume of 10 μL with formamide (98% formamide, 10 mM EDTA, blue dextran). The samples were placed in a 96-well microplate, after denaturing at 95 °C for 5 min, and immediately cooled to 4 °C. Electrophoresis was performed using a capillary electrophoresis instrument (3100 Genetic Analyzer, ABI). The samples were run on a POP4 polymer matrix using the GeneScan 36 POP4 Default Module, with run conditions of 60 °C, 15 kV, and 25 min.

The genotyping assays were performed on a capillary-based ABI PRISM 3100 genetic analyser (Applied Biosystems) according to the manufacturer's instructions. Fluorescent DNA fragments for each individual were scored using Gene Mapper version 4.0, and the allele size and peak-area of the true peaks was determined using Genotyper version 3.7. The software provided an allele size (fragment length) and a chromatograph for each individual. The chromatograph showed the peak height and position of each individual. Individuals with peak heights and positions similar to Pongsu Seribu 2 (male parent) were designated as A, and those similar to Mahsuri (female parent) were designated as B. Individuals with peak heights and positions similar to both parents were designated as AB or H.

The marker data generated for 188 lines using 63 SSR primers were subjected to χ² analysis. The Chi² analysis of the genotypic data was calculated using the formula, χ² = (O – E)²/E, where O is the observed value and E is the expected value. The observed ratios were tested for deviation from the expected values using a Chi² goodness-of-fit test (P < 0.05) for each marker. The expected genotypic ratio (AA:AB:BB) ratio for individuals in each genotypic class was 1:2:1 in the F₃ population. Individuals with a missing genotype at a locus were excluded from the analysis for that locus. In addition, the presence of a segregation distortion region (SDR) was identified when closely linked markers exhibited significant segregation distortion in the F₃ population.

An SSR linkage map for the sixty-three polymorphic loci was constructed using QTL IciMapping [56]. The markers revealed significant segregation distortion in the F₃ population as shown on the map. The most skewed markers in an SDR were considered the most likely location of a distorting factor.

Determining the optimal annealing temperature is a prerequisite for primer pairs of microsatellite loci. Once the annealing conditions have been optimised, it will be easier to study DNA polymorphisms for genome analysis. Thermal cyclers that generate a uniform temperature gradient across the heating block greatly simplify the determination of the optimal annealing temperature. The applicable annealing temperature in PCR is 5 °C below the actual melting temperature [T_m = 4(G + C) + 2(A + T)] of the particular primers. A single-base mismatch lowers the T_m ∼ 5 °C. The temperature and duration of primer annealing rely on the base composition and length of the primers. Although more complex formulas could also be used [57,58], in practice the T_m is variously affected by the individual buffer components and even the primer and template concentrations, therefore any calculated T_m value should be regarded as an approximation. In the present study, 7 different temperatures (43, 45, 48, 51, 55, 57, and 60 °C) were investigated for primer pair annealing using a PTC-200 DNA Engine Peltier Thermal Cycler. Gradient PCR facilitates the empirical determination of an optimal annealing heat range in a minimum number of steps. Using the gradient function of the universal block, a gradient of 43 to 60 °C was set. We also examined a number of possible concentration parameters during the same run. The results revealed that annealing temperatures ranging from 48 to 57 °C typically generate the best outcomes, and at distinct primer concentrations, annealing requires only a few seconds. Fig. 1 shows an agarose gel with the 7 samples loaded across the block. The majority of the microsatellites marker in the designated panels generated single bands at 55 °C and 57 °C (Fig. 2) and were selected as best primers based on clear DNA amplification products. Notably, 10 microsatellites produced double or multiple banding patterns, suggesting that some primers are refractory to optimisation [59]. Increasing the quantity of cycles might result in anaemic PCR reactions, but this specific modification might generate false bands and smears from high molecular weight products containing more single-stranded DNA [60].

In the present study, to optimise the multiplex sets, different concentrations of MgCl₂, Taq DNA polymerase, DNA and PCR conditions were optimised for basic simplex PCR and multiplex SSR–PCR. We observed that the following PCR component concentrations were optimal for most microsatellite analyses: 1× PCR buffer, 25 mM dNTPs, 5 μM of each primer, 5 U/μL Taq polymerase, 2 mM MgCl₂ and ∼ 20 ng template DNA (Table 2). For all the markers examined, the PCR conditions were uniform, except annealing temperature. The results showed that all reagents in the PCR mix influenced the outcome of SSR loci amplification. In this context, the amount and quality of template DNA strongly influenced the PCR results. The template volume cannot be too high; otherwise, non-specific PCR products might be obtained. Previous studies have also shown that, in practice, SSR–PCR fails for various reasons, reflecting many factors that could alter PCR amplification, such as different types/brands of thermocyclers, reaction components (template DNA, dNTPs, DNA polymerase, Mg²⁺ concentration, etc.), or even minor differences in the thickness of the walls of the PCR tubes [61]. The concentrations of template DNA range from 50–100 ng per 25 μL reaction volumes [62]. The MgCl₂ concentration can have an enormous influence on the success of the PCR reaction. Increasing the Mg²⁺ ions enhances Taq activity to an optimum, above which these ions might act as inhibitors of Taq activity [63]. The concentration of MgCl₂ ranges from 1.0–2.5 mM. As substrates of the PCR reaction, dNTP content directly affects the output of PCR amplification. An excess of dNTPs will compete with polymerase binding to Mg²⁺ and thereby inhibit the PCR reaction. The dNTP concentrations range from 0.1 to 0.5 mM [62]. The amount of Taq DNA polymerase affects the amplification efficiency, and when used in excess, this enzyme will generate a high mismatch rate, while, the low amount of Taq will affect the efficiency of enzyme and primer binding [62,64]. The Taq DNA polymerase concentration ranges from 0.5 to 1.0 unit per 25 μL reaction volumes [65]. Although the primer concentration is not as important for the PCR reaction as other parameters, the optimisation of this component is economically important to avoid unnecessary waste. Variable concentrations of forward and reverse primers of different markers have been reported [61,66,67]. In general, the primer concentration ranges from 0.1 to 0.5 μM [65]. Varying the concentration of primers for one locus might affect amplification at the other loci in the multiplex. Differences in the DNA sequences of the loci could also lead to variations in the efficiency of primer binding. Therefore, it is essential to optimise the primer concentrations to obtain not only the best signal intensities, but also balanced peak heights for a multiplex set. Therefore, the results suggest that the concentrations of all PCR components must be optimal for successful amplification.

To amplify the targeted amplicons using multiplex PCR, the extensive optimisation of the cycling conditions is typically required. In the present study, the PCR cycling programme was successfully optimised for the amplification of the selected SSRs (Table 3). The latest programme had a higher extension temperature (72 °C) and three different annealing temperatures with longer extension times. The results suggested that the higher extension temperature decreased amplification. With programmes A and B, some PCR products were missing. Because we anticipated that an entire plate of PCR samples would be amplified for a given marker at one temperature, some samples were not amplified at one latter time with programme C, which should not decrease the overall efficiency of the protocol. However, changes in the annealing temperature increased or decreased the specificity and yield of the PCR products. Fig. 3 shows the results of multiplex PCR reactions using different primers sets from panel 7 with programme C. A thermal cycler with a lower capacity block might be used for fewer samples. Notably, primer integrity is a critical factor for successful SSR–PCR. The problems encountered in SSR–PCR typically reflect the use of incorrect primer concentrations, low-quality primers, or degraded primers (old primer solutions and multiple freeze-thawing cycles). Moreover, the primer extension time is determined based on the length and concentration of the target sequence and temperature applied. In the present study, a two-minute extension time at 72 °C was adequate to yield products of approximately 2 kb in length. These results suggest that, although the cycling conditions might vary depending upon the locus tested and the polymerase used, longer annealing times and higher and therefore more stringent annealing temperatures dramatically improve the efficiency of microsatellite loci amplification. Variations among PCR products might reflect a number of factors, such as well-to-well variation across the thermal cycler, pipetting errors, and inconsistent quality among template DNA samples. These factors might contribute to variations in the efficiency of PCR amplification, exhibited as differences in the peak height among electropherograms.

All SSR loci surveyed on the population were unambiguous and easily scorable. The genotype (sizes of the PCR products) of each sample, based on the pattern of peaks or bands on the electropherogram, was determined for 13 established SSR panels. The genotypic data was obtained from the analysis using GeneMapper version 4.0. The software calls the peaks observed within each sample into bins, consistent with individual previously designated alleles. The software generates an allele size (fragment length) and chromatograph for each microsatellite. The individual microsatellites have a typical fragment pattern with a characteristic number of stutter peaks and an easily distinguished signal peak width, slope and spread. A few stutter peaks on the ABI were observed, and because only the most intense fragments were evaluated for molecular weight, the stuttering did not interfere with allele calling. The individual allele sizes were compared with allele sizes of the parents for a specific marker. Allele binning was performed after rounding off the assigned values to the nearest whole base pair integer to generate a base pair estimate for a given allele. The allele sizes among the F₃ lines showed the allele sizes of parental varieties. The parental varieties in the germplasm are considered as standard genotypes for evaluating allelic diversity and have been previously analysed for all 63 polymorphic microsatellites. Multiple alleles were not frequently observed in the germplasm, and these individuals were genotyped based on DNA samples extracted from single plants. Rice is a self-pollinating diploid crop; thus, microsatellite markers typically reveal single-copy, homozygous loci, and allelic heterogeneity are rare in pure line varieties. This fact simplified the microsatellite work for the analysis of rice varieties. A plant was assigned a null allele for an SSR locus when an amplification product was not generated. For loci with di-nucleotide motifs, the binning process occasionally generated intermediate values for the assigned alleles. A correction was performed to ensure that all values followed the expected sizes for di-nucleotide motif loci, as no previous knowledge concerning microvariants for the selected loci was available. In this case, the most frequent allele was considered as a reference for the expected values. Rice is a naturally inbred crop, therefore multiple alleles in a variety typically indicate mixed pure lines or seed mixtures (heterogeneity), rather than genetic heterozygosity, and this phenomenon is particularly common in landrace varieties [68]. Figs. 4 and 5 show the peak height and the fluorescence intensity of the 500 LIZ size standard (Applied Biosystems) and plant genotyping using the RM104 and RM495 microsatellites from panels 1 and 2, respectively, in the F₃ families. The size standard was effective for estimating the molecular weights of all the PCR products amplified across the multiplex panels, ranging from 73 to 277 bp in length. The peak heights were consistent with those from PCR products with FAM/HEX-labelled primers. The germplasm set examined in the present study was adequate for microsatellite analysis. The results suggested that a useful set of markers should also provide whole genome coverage, with even distribution on each chromosome and high potentiality for multiplexing.

Marker segregation distortion was detected for deviating from the expected Mendelian ratio (1:2:1) of each locus in the F₃ population using the Chi² (χ²) test. In the population studied, among the 41 (65%) markers that deviated from Mendelian segregation (at the 0.05 and 0.01 level of significance), 12 markers (30%) exhibited segregation distortion towards the female parent Mahsuri, whereas 24 markers (58%) deviated towards the male parent, Pongsu Seribu 2. In addition, 5 markers (12%) were distorted towards heterozygote individuals. The marker loci associated with skewed allele frequencies were distributed on all eight chromosomes. These results indicated that genetic factors for segregation distortion present on these chromosomes. A total of 22 (35%) SSR markers fit the expected segregation ratio of 1:2:1 based on a χ² test at 0.05 percent probability. Segregation distortions for 63 polymorphic loci are shown in Table 4.

We surveyed 188 F₃ individuals using primer pairs for 63 polymorphic SSR loci (out of 125), distributed across 10 linkage groups (rice chromosomes). Linkage maps for 63 polymorphic SSR markers were constructed for the F₃ families using the QTL IciMapping programme. The number of polymorphic SSR loci evaluated ranged from 3 (chromosomes 3 and 10) to 10 (chromosome 11). Thus, polymorphic markers were primarily distributed on 11 chromosomes, leading to an expansion of these chromosomes. Ten linkage groups contained an average of seven loci, with a minimum of three (e.g., Ch.3 and Ch.10) and a maximum of ten loci (e.g., Ch.11). All 41 distorted loci (P < 0.05 and P < 0.01) were mapped onto these linkage groups (Fig. 6).

The segregation distortion region (SDR) was declared when three or more closely linked markers presented significant segregation distortion in the F₃ populations (Fig. 6). The map showed that most distorted markers clustered in special regions on chromosomes. Six SDRs were identified on chromosomes 1, 2, 4, 8 and 12. Two SDRs were identified on chromosome 2. The SDRs on chromosome 12 were near centromeric regions. The size of SDR 1 was 26.9 cM, and the sizes of the two SDRs on chromosome 2, SDR 2.1 and 2.2, were 17.10 and 8.20 cM, respectively. The sizes of the SDRs on chromosomes 4, 8 and 12 were 17.70, 24.20 and 16.50 cM, respectively. The SDRs on chromosomes1, 8 and 2 (Fig. 7) were larger than the SDRs on chromosomes 4 and 12.