Association mapping and marker-assisted selection of the lettuce dieback resistance gene Tvr1
© Simko et al; licensee BioMed Central Ltd. 2009
Received: 17 July 2009
Accepted: 23 November 2009
Published: 23 November 2009
Lettuce (Lactuca saliva L.) is susceptible to dieback, a soilborne disease caused by two viruses from the family Tombusviridae. Susceptibility to dieback is widespread in romaine and leaf-type lettuce, while modern iceberg cultivars are resistant to this disease. Resistance in iceberg cultivars is conferred by Tvr1 - a single, dominant gene that provides durable resistance. This study describes fine mapping of the resistance gene, analysis of nucleotide polymorphism and linkage disequilibrium in the Tvr1 region, and development of molecular markers for marker-assisted selection.
A combination of classical linkage mapping and association mapping allowed us to pinpoint the location of the Tvr1 resistance gene on chromosomal linkage group 2. Nine molecular markers, based on expressed sequence tags (EST), were closely linked to Tvr1 in the mapping population, developed from crosses between resistant (Salinas and Salinas 88) and susceptible (Valmaine) cultivars. Sequencing of these markers from a set of 68 cultivars revealed a relatively high level of nucleotide polymorphism (θ = 6.7 × 10-3) and extensive linkage disequilibrium (r2 = 0.124 at 8 cM) in this region. However, the extent of linkage disequilibrium was affected by population structure and the values were substantially larger when the analysis was performed only for romaine (r2 = 0.247) and crisphead (r2 = 0.345) accessions. The association mapping approach revealed that one of the nine markers (Cntg10192) in the Tvr1 region matched exactly with resistant and susceptible phenotypes when tested on a set of 200 L. sativa accessions from all horticultural types of lettuce. The marker-trait association was also confirmed on two accessions of Lactuca serriola - a wild relative of cultivated lettuce. The combination of three single-nucleotide polymorphisms (SNPs) at the Cntg10192 marker identified four haplotypes. Three of the haplotypes were associated with resistance and one of them was always associated with susceptibility to the disease.
We have successfully applied high-resolution DNA melting (HRM) analysis to distinguish all four haplotypes of the Cntg10192 marker in a single analysis. Marker-assisted selection for dieback resistance with HRM is now an integral part of our breeding program that is focused on the development of improved lettuce cultivars.
To pinpoint the location of the Tvr1 gene and develop markers for marker-assisted selection, we employed a combination of classical linkage and association mapping techniques . The association mapping approach is based on the extent of linkage disequilibrium observed in a set of accessions that are not closely related. In contrast to linkage mapping, association mapping is a method that detects relationships between phenotypic variation and genetic polymorphism in existing germplasm, without development of mapping populations. This method incorporates the effects of recombination occurring in many past generations into a single analysis  and is thus complementary to linkage analysis. Association mapping has been successfully applied in mapping resistance genes in several diploid and polyploid plant species (e.g. [10–12]). The main drawback of association mapping is the possibility of false-positive results due to an unrecognized population structure. When the trait of interest is more prevalent in one subpopulation (e.g. dieback resistance in iceberg lettuce) than others, the trait will be associated with any marker allele that is in high frequency in that subpopulation (e.g. ). Our previous analysis of population structure with molecular markers revealed that cultivated lettuce is divided into several well-defined subpopulations that correspond approximately to different horticultural types [14, 15]. Consequently, traits that are strongly correlated with lettuce types display many false-positive results when population structure is ignored. However, these spurious associations disappear when estimates of population structure are included in the statistical model . Therefore, the best approach for avoiding spurious associations in lettuce association studies is to assess relatedness of accessions with molecular markers and to include this information into the statistical model .
In the present study we mapped the Tvr1 gene using a combination of linkage and association mapping. High-resolution DNA melting curve analysis (HRM) was used to assess polymorphism in mapping populations and to detect haplotypes associated with the disease resistance. The potential for marker-assisted selection was then validated in the genetic backgrounds present in most common horticultural types of lettuce. Finally, we used SNP markers to assess intra- and inter-locus linkage disequilibrium in the Tvr1 region.
Linkage mapping population
Recombinant-inbred lines (RILs) were derived from a cross between an F1 of cv. Valmaine (dieback susceptible romaine type) × cv. Salinas 88 and cv. Salinas. Both Salinas and Salinas 88 are iceberg type lettuces resistant to dieback whose appearance and performance is the same, except for reaction to Lettuce mosaic virus (Salinas 88 is resistant). Two hundred and fifty three F8 RILs were screened for resistance to dieback in multiple trials and 192 of these RILs were randomly selected for genotyping with molecular markers.
Association mapping set
List of 200 L. sativa accessions used in the association mapping study.
AvonCrisp, Batavia Beaujolais, Drumhead White Cabbage, Express, Great Lakes 54, Imperial, La Brillante, River Green
Batavia Blonde A Bord Rouge, Batavia Blonde de Paris, Batavia Reine des Glaces, Carnival, Fortessa, Hanson, Holborn's Standard, Iceberg, New York, Progress, Tahoe Red, Webb's Wonderful
Bibb, Cobham Green, Dark Green Boston, Margarita, Tania, Verpia
Ancora, Dandie, Encore, Lednicky, Madrilene, MayKing, Ninja, Saffier, Tinto, Tom Thumb
Astral, Autumn Gold, Ballade, Barcelona, Bix, Black Velvet, Bounty, Bronco, Bullseye, Calmar, Climax, Coyote, Diamond, Duchesse, Eastern Lakes, Empire, Fimba, Formidana, Glacier, Green Lightening, IceCube, Invader, Lighthouse, Mini Green, Misty Day, Monument, Pacific, Primus, Raiders, Red Coach, Salinas, Salinas 88, Sea Green, Sharp Shooter, Sniper, Sureshot, Tiber, Vanguard, Winterhaven, Winterselect, Wolverine
Barnwood Gem, Eruption, Gallega, Little Gem, Pavane, Sucrine
Alpine, Cracoviensis, Grand Rapids, PI177418, Pybas Green, Ruby Ruffles, Salad Bowl, Shining Star, Slobolt, Two Star, Waldmann's Green
Australian, Cavarly, Coastal Star BS, Colorado, Deep red, Deer's Tongue, Flame, Lolla Rossa, Merlot, North Star, Oak Leaf, Prizehead, Red Oak Leaf, Red Salad Bowl, Red Tide, Redina, Royal Red, Ruby, Squadron, Triple Red, Ventana, Vulcan, Xena
01-778M, 01-781M, 01-789M, Athena, Bandit, Blonde Lente a Monter, Defender, PI171666, PI491209, PI491214, PI491224, Skyway, Sturgis, Sx08-003, Sx08-004, Sx08-005, Sx08-006, Sx08-007, Sx08-008, Triple Threat
Annapolis, Apache, Ballon, Bautista, Brave Heart, Caesar, Camino Real, Chicon des Charentes, Clemente, Coastal Star WS, Conquistador, Dark Green Cos, Darkland, Eiffel Tower, Gladiator, Gorilla, Green Forest, Green Towers, Heart's Delight, Infantry, King Henry, Larga Rubia, Lobjoits, Majestic Red, Medallion, Outback, Paris White, Parris Island Cos, PI140395, PI169510, PI177426, PI179297, PI220665, PI268405, PI269503, PI269504, PI289064, PI358027, PI370473, PI420389, Queen of Hearts, Reuben's Red, Romaine Chicon, Rouge d'Hiver, Short Guzmaine, Signal, Tall Guzmaine, Triton, Ultegra, Valcos, Valmaine, Wayahead, White Paris
Balady Bahera, Balady Banha, Balady Barrage, Celtuce, Chima
Balady Aswan, Balady Cairo, PI207490
To validate the marker-trait association detected in the association mapping set, a validation set of 132 accessions was screened for disease resistance and genotyped with the marker, Cntg10192. This set represents the spectrum of phenotypic and genotypic variability observed in cultivated lettuce and includes 12 Batavia types, 11 butterhead types, 36 iceberg types, 1 Latin type, 25 leaf types, 2 oil types, 42 romaine types, and 3 stem types (Table 1).
Assessment of dieback resistance
Dieback resistance data were obtained from field observations as previously described . Susceptibility was evaluated by seeding lettuce directly in the field in Salinas, CA, from which TBSV and LNSV had previously been isolated from plants exhibiting characteristic dieback symptoms . The experiment was comprised of two complete blocks, with ~30 plants per genotype per block. Plants were seeded in two rows on 1 m wide beds and were thinned to obtain spacing of 30 cm between plants. Standard commercial practices were used for irrigation, fertilization, and pest control. Plants were checked weekly for disease symptoms in order to discriminate between plants dying due to dieback and those due to unrelated causes. The percentage of plants that showed typical dieback symptoms (or were dead due to dieback) was recorded at harvest maturity. Accessions with < 5% of symptomatic plants were considered to be resistant. To minimize the possibility of inaccurate scoring, all accessions were tested in at least three independent field trials. If results from all three trials were consistent, the material was not tested further. In the case of inconsistent results, material was retested in another two independent trials, after which all accessions were classified into one of the two groups. The resistance and susceptibility classification was subsequently used in statistical analyses.
Tissue from young leaves of about one-month-old plants was collected and immediately lyophilized. Lyophilized samples were ground to fine powder using a TissueLyser mill (Qiagen, Valencia, CA), before extracting genomic DNA with the NucleoSpin Plant II kit (Macherey-Nagel, Betlehem, PA). The DNA concentration and quality was analyzed with an ND-1000 Spectrometer (NanoDrop Technologies, Wilmington, DE) and gel electrophoresis.
Polymerase chain reaction, allele detection, and product sequencing
Information for nine markers that were sequenced from a set of 68 L. sativa accessions.
EST/Contig in CGPDB
Primers (5' - 3')
F - AGGAGCAAAGGAAAGGCTTC
R - TGCAACTTCTTCAGCCAATG
F - GCATGCCGATTACTCCTTTC
R - TCCCCAATCACCTAAGATGG
F - ATATCCCACCGCCCATAGAT
R - ACGCAACTAACCCGTTTCAT
F - GGGGAGTTCAGACGTTCAGT
R - CGAATTGATACACCGCAAAA
F - CTCGTTTTCAACACCGACAA
R - TTGTCTCCGGCACTGTATCATCG
F - TGCTCAATTACACTCGAACCA
R - CTTCATGGAGAGAAATACAAGGTC
F - TTGTTGAAATTATAAACACGAAGCA
R - CAACAAAGGATGTCTCAAATTCA
F - GCACCTGATGGCTGAATATG
R - CATCCTCAATCGCTTGTGTT
F - GGAGAAATTTTGGAGCTGTAATTAC
R - GGAGGTATGTTGAGGTACATGAC
DNA sequences were analyzed with CodonCode Aligner v. 2.0.6 (CodonCode Corporation, Dedham, MA). We detected three types of polymorphism in our sequences - single feature polymorphism (SFP), insertions and deletions (indels) and variable number tandem repeats (VNTRs). Most of the SFPs that had been detected using the Affymetrix GeneChip  were due to a single nucleotide polymorphism (SNP), but in five cases due to a single base indel. Since Haploview cannot handle missing values, missing bases were substituted prior to data analysis with an appropriate single nucleotide. Because all single-base indels could be tagged with SNPs from the same marker locus (as described below), we use the term SNP throughout the text. Both indels and VNTRs were excluded from data analysis, unless otherwise noted in the text.
High-resolution DNA melting curve (HRM) analysis
Information for six markers that were analyzed in the (Valmaine × Salinas 88) × Salinas mapping population with the HRM approach.
EST/Contig in CGPDB
Primer (5' - 3')
Amplicon size (bp)
F - AGGAGCAAAGGAAAGGCTTC
R - TGCAACTTCTTCAGCCAATG
F - AGAACCAGGTCGAATCATGG
R - TTCTCGCCGTTGAGAAGAAT
Probe - AAGTGGCTATACAGCTTTGATCATAACGA
F - CTCGTTTTCAACACCGACAA
R - TAGGTGGGTCCGACTTTGAG
F - TGCTCAATTACACTCGAACCA
R - CTTCATGGAGAGAAATACAAGGTC
F - GAAGAAACTCATGAATCTGCTCAA
R - TTTGCTCAAGAACTCTTAAACCATT
F - CCAAACCATAGGGACGAAAA
R - GGAGGTATGTTGAGGTACATGAC
One hundred and ninety two RILs derived from a cross between an F1 of cv. Valmaine × cv. Salinas 88 and cv. Salinas were genotyped with EST-derived markers. Selection of markers for this first round of genotyping was based on the molecular linkage map developed from an interspecific cross between L. sativa cv. Salinas and Lactuca serriola accession UC96US23 [17, 18]. Twenty markers were selected to evenly cover linkage group 2 in intervals of approximately 10 to 20 cM. After preliminary mapping of the resistance gene, the region containing Tvr1 was saturated with markers originating from a microarray-based study also carried out on the Salinas × UC96US23 population . Marker polymorphism was tested with HRM analysis, unless the difference between segregating alleles could be visually observed using gel electrophoresis. If polymorphism could not be observed with HRM analysis, PCR products from the two parental genotypes were sequenced and new primers were designed for HRM. Statistical analysis of the linkage between molecular markers and dieback resistance was performed by MapManager QTX software . Dieback resistance for each RIL was considered as a bi-allelic qualitative trait (resistant or susceptible) and used for linkage analysis.
Association mapping and assessment of population structure
Association mapping was performed on a set of 68 accessions from seven horticultural types of lettuce (Table 1). In the first step, markers closely linked to the Tvr1 gene were amplified from each accession and sequenced. In the second step, the sequenced amplicons were analyzed for polymorphism with the CodonCode software and inputted into Haploview v. 4.2 . Intra-locus SNPs were tagged in Haploview with the Tagger function at r2 = 1. Untagged SNPs from all markers and a representative SNP for each tag were then entered into TASSEL v. 2.0.1 . TASSEL was subsequently used to test for association between individual SNPs and resistance to dieback while accounting for the population structure. Both p-values for each SNP and percent of phenotypic variation explained by the model (R2) were calculated with TASSEL after 100,000 permutations.
Prior to association analysis, the population structure in the set of 68 accessions was assessed with thirty EST-SSR markers distributed throughout the genome  using the computer program STRUCTURE 2.2 . Ten runs of STRUCTURE were done by setting the number of populations (K) from 1 to 15. For each run, the number of iterations and burn-in period iterations were both set to 200,000. The ad hoc statistic  was used to estimate the number of subpopulations. The optimum number of subpopulations (K = 5) was subsequently used to calculate the fraction of each individual's genome (q k ) that originates from each of the five subpopulations. The q k values obtained from STRUCTURE were used as covariates in the statistical model given by TASSEL.
Genetic variation and a linkage disequilibrium estimate
The level of genetic variation at the nucleotide level was estimated as nucleotide polymorphism (θ, ) and nucleotide diversity (π, ). To test the neutrality of mutations, we employed Tajima's D test , which is based on differences between π and θ. Analyses of genetic variation and estimates of haplotype diversity (Hd) were carried out using DnaSP v. 5.00.04 software .
Linkage disequilibrium (r2) between pairs of SNP loci in the genome was calculated with Haploview and the values were pooled over the entire data set. Decay of LD with distance was estimated using a logarithmic trend line that was fitted to the data. Distances between markers were calculated from their respective positions on the consensus molecular linkage map. The consensus map was created with JoinMap v. 2.0  from the Salinas × UC96US23 map  and the (Valmaine × Salinas 88) × Salinas map (present work). SNPs with frequency < 5% were excluded from the analysis.
Estimates of nucleotide variation in nine markers linked to the Tvr1 gene.
Polymorphic sites (S)
Haplotype diversity (Hd)
Nucleotide diversity (π× 10-3)
Nucleotide poly-morphism (θ× 10-3)
Association between SNPs and dieback resistance in a set of 68 L. sativa accessions.
235, 236, 251
46, 525, 574, 594
393, 415, 480, 597, 598
480, 486, 489, 490. 492, 493, 499, 544, 577
100, 102, 144, 236, 250, 258, 279, 309, 399, 400, 402, 457, 464, 483
107, 110, 116, 123, 149, 181, 296
525, 534, 559, 583, 590, 748, 798, 799
661, 685, 742, 766, 767
Development of markers for marker-assisted selection
Validation of the haplotype-resistance association detected in the set of 68 L. sativa accessions and two L. serriola genotypes was performed on an additional set consisting of 132 accessions of L. sativa. This set also contained diverse material that represented a broad spectrum of the variability present in cultivated lettuce. We used the HRM approach for marker Cntg10192 and, as before, all genotypes that were susceptible to the disease carried haplotype S1, while resistant material had either the R1 or R2 haplotypes (Figure 5). This association was independent from population structure and was observed across all horticultural types.
Nucleotide polymorphism was observed in all nine markers that were sequenced from the region flanking the Tvr1 gene. The rate of nucleotide substitutions in a set of 68 accessions translates into ~1 SNP per 149 bp (1/θ) between pairs of randomly selected sequences. This SNP frequency was somewhat lower when only coding regions were considered (1 SNP per 187 bp). These values are well within the range observed for other plant species. For example, the average SNP frequency is 60 bp in aspen (Populus tremula L.) , 87 bp in potato (Solanum tuberosum L.) , 104 bp in maize (Zea mays L.) , 130 bp in sugar beet (Beta vulgaris L.) , 232 bp in rice (Oryza sativa L.) , 435 bp in sorghum (Sorghum bicolor L.) , 585 bp in tomato (Solanum lycopersicum L.) , and 1030 bp in soybean (Glycine max L.) . Both nucleotide polymorphism (θ = 6.7 × 10-3, in the coding region 5.4 × 10-3) and nucleotide diversity (π = 9.6 × 10-3, in the coding 8.0 × 10-3) of lettuce are similar to that observed in maize (θ = 9.6 × 10-3, π = 6.3 × 10-3), potato (θ = 11.5 × 10-3, π = 14.6 × 10-3), and sugar beet (π = 7.6 × 10-3), but larger than in tomato (θ = 1.71 × 10-3, π = 1.34 × 10-3), and soybean (θ = 0.97 × 10-3, π = 1.25 × 10-3) [30–32, 35–37]. If results from the analyzed region correspond to those for the whole genome, sequence variation in lettuce is relatively high for a selfing species. It was previously observed that selfing species have generally lower levels of sequence variation than outcrossing species because of smaller effective population sizes . Although polymorphism in lettuce appears to be considerably larger than in selfing soybean and tomato, it is similar to that observed in rice, which is also a self-pollinating species. The ratio of nucleotide diversity in coding (exon) and non-coding (intron) sequences was not analyzed in detail, since data from only four markers (LK1457, Cntg10044, Cntg4252, Cntg11275) are available. However, the ratio (0.32) across these markers appears to be smaller than in Arabidopsis (Arabidopsis thaliana) (0.38 ), soybean (0.45 ), maize (0.65 ), and potato (0.71 ). This difference is likely due to a higher level of functional constraint on the perigenic sequence  of lettuce. Measures of haplotype diversity (Hd) were based on estimated haplotype frequencies , and calculated using the DNAsp software. This measure of diversity is analogous to the heterozygosity at a single locus, and is at its maximum when haplotypes observed in the sample occur at equal frequencies . Diversity based on haplotypes ranged from 0.593 in QGG19E03 to 0.809 in marker Cntg11275, with an average value of 0.732 ± 0.024. These values are higher than in rice (0.507 ± 0.048 ), soybean (0.52 ), and human (0.651 ± 0.016 ). It is possible that the high level of diversity is related to the way that selection of the 68 accessions was performed. We included dieback resistant and susceptible material from all predominant horticultural types, thereby selecting haplotypes at similar frequencies. It would be interesting to observe how haplotype diversity changes in different genomic regions and/or for a different set of accessions.
To test the neutrality of mutations, Tajima's D was calculated for all surveyed markers. The average D (1.48 ± 0.45 for the coding regions and 1.61 ± 0.56 for whole fragments) was larger than in soybean (1.08 ), potato (0.5 ), and sorghum (0.30 ). A positive D value indicates a deficit of low-frequency alleles relative to what is expected. Since large D values can be caused by a population subdivision , it is possible that the presence of subpopulations in the analyzed set of lettuce accessions affects both haplotype diversity and the D values. When neutrality of mutations was tested in individual markers, three markers closely linked to the Tvr1 gene (< 1.5 cM) had Tajima's D values significantly higher (p ≤ 0.01) than expected (Cntg10192 - 2.78, CLSM9959 - 2.72, CLSZ1525 - 3.40). Again, the population structure or selection at the Tvr1 locus or the marker itself could have caused departures from neutrality.
The decay of LD for the Trv1 region was relatively slow when measured both within individual markers and between markers flanking Tvr1. Estimated values of r2 were ~0.322 at 900 bp, and ~0.124 at 8 cM. A fitted logarithmic curve shows that the r2 value of 0.2 (often considered the threshold for estimating the extent of LD) is reached somewhere between 0.5 cM to 1 cM. LD of SNP markers observed in some other selfing species was similar; LD in Arabidopsis was 250 kb or 1 cM ) and in soybean was ~50 kb ). Intra-locus LD decayed very little in tomato, with the log trend showing r2 > 0.6 at 900 bp . However, it is problematic to compare decay of LD across species due to the large variability in LD quantification. LD depends on a combination of many factors, such as the origin of the population, selected set of accessions, analyzed genomic region, molecular marker system, and presence of unidentified subpopulations. Hyten  compared four different soybean populations for levels of LD decline. While in the domesticated Asian G. max population LD did not decline along the 500 kb sequenced region, the wild Glycine soja population had a large LD decline within the LD block size averaging 12 kb. Comparable observations were not only made in the selfing Arabidopsis , but also in the outcrossing maize  and aspen . Our results show a large difference between estimates of LD when analyses were performed across all horticultural types or within each individual type. While the estimate of r2 at a distance of 8 cM was 0.124 for the whole set, it was 0.247 for romaine type and 0.345 for crisphead lettuce. Because only a relatively small part of the genome was analyzed in the present work, it is not possible to calculate LD at distances over 8 cM. However, the trend for the logarithmic curve suggests that LD could reach more than 15 cM in romaine and probably more than 25 cM in crisphead types before declining to the value of r2 < 0.2. When only iceberg types (a subtype of crisphead) were included in the analysis, LD was still at its maximum (r2 = 1) at a distance of 8 cM (data not shown). Although these observations come from a limited number of individuals, they are supported by the fact that the modern iceberg-type lettuce has an extremely limited genetic diversity [14, 15] that is frequently associated with extensive LD.
A previous study on the Salinas × Iceberg mapping population showed that the single, dominant gene (Tvr1) located on linkage group 2 confers resistance to lettuce dieback . We confirmed that the gene is located on linkage group 2 and pinpointed its position with markers Cntg4252 and Cntg10192. Both of these markers co-segregated with the resistance allele in 192 RILs derived from the (Valmane × Salinas 88) × Salinas cross. The molecular linkage map based on the (Valmane × Salinas 88) × Salinas cross showed good colinearity in order of the markers with the map based on the interspecific cross between cv. Salinas and L. serriola accessions UC96US23 . However, the interval from LK1457 to Cntg11275 is more than twice the size when estimated from the interspecific cross (11.0 cM and 4.9 cM, respectively). Similarly, while markers Cntg4252 and Cntg10192 co-segregate in the intraspecific map, they are separated by 1 cM on the interspecific map, despite the latter being based on fewer RILs. These values are within the range of other observations on intra- and interspecific maps of lettuce . Colinearity between the two maps allows for development of a consensus map that places markers Cntg4252 and Cntg10192 0.5 cM apart.
We identified the genomic region carrying resistance against dieback and nine markers closely linked with the Tvr1 gene through linkage analysis. We subsequently used this information to test the linked markers for association with the disease resistance on a set of 68 diverse accessions. Eight of the nine markers showed highly significant association with dieback resistance, consistent with the Tvr1 gene being located in this region. Although the threshold for declaring association significant was set at p < 0.001, most of the associations were significant at p ≤ 0.00001. The only exception was marker Cntg4252, where the most significant association reached only p = 0.0042. The low association between SNPs at this marker and dieback resistance was somewhat unexpected, since Cntg4252 co-segregated with the resistance allele in the (Valmaine × Salinas 88) × Salinas mapping population. While unexpected, it is not uncommon that markers closely linked with a trait in a mapping population do not show association when tested on a set of diverse accessions. This problem is well documented in potato, where markers linked to the Gro1 and H1 resistance genes in the mapping population were tested on 136 unrelated cultivars. The Gro1-specific marker was not correlated with the resistance phenotype, while H1-specific marker was indicative of resistance in only four cultivars . A similar example can be shown for lettuce, where markers most tightly linked to the cor resistance gene were the least useful for diagnostic when tested in a large collection of cultivars . There are several other examples of markers tightly linked to resistance genes, but whose use present problems in material different from the original in which they were identified . Therefore, an important requirement for any molecular marker used in MAS is not just its applicability in a specific cross, but its association in a wide gene pool.
From SNPs that were significantly associated with dieback resistance, the best fit was observed for those located in marker Cntg10192. This is the second of two markers, the other being Cntg4252, that co-segregated with the resistance allele in the mapping population. It is intriguing that one of the two markers co-segregating with the Tvr1 allele in the mapping population showed no significant association in a set of diverse accessions, while the other showed a perfect match. Although these two markers were not separated in the intraspecific population, the linkage map developed from the Salinas × UC96US23 cross indicates that they are 1 cM apart. Therefore it is possible that testing more RILs from the intraspecific population would separate the two markers and Tvr1. Association of SNPs from marker Cntg10192 with the resistance allele was validated in a larger set of 132 diverse accessions from several horticultural types. The marker-trait association was observed not only in L. sativa, but also in two L. serriola accessions included in the study. However, while the susceptible haplotype is identical in both species (S1), the resistant haplotypes are different (R1 & R2 in L. sativa, and R3 in L. serriola). To investigate the relationship between Tvr1 and the resistance observed in L. serriola, we screened 119 F8 RILs from the Salinas × UC96US23 population for resistance to dieback. If Tvr1 and the resistance locus from UC96US23 were distinct and unlinked, approximately 25% susceptible offspring would be observed. However, since all RILs were resistant to the disease (data not shown), we concluded that the resistance locus in UC96US23 is either allelic or linked to Tvr1. The same conclusion was reached for the resistance locus in the primitive romaine-type accession PI491224 . The three resistance loci are associated with three distinct haplotypes; resistance in cv. Salinas with R1, in PI491224 with R2, and in UC96US23 with R3.
Even though all 200 L. sativa accessions from the two testing sets showed the same haplotype-resistance association, it is unlikely that the EST from which this marker was derived is directly involved in dieback resistance. A search for protein similarity in the NCBI database  indicates that Cntg10192 is similar to the copper ion binding protein from castorbean (Ricinus communis L., EEF39175.1, similarity 5e-49) and the plastocyanin-like domain-containing protein from Arabidopsis (NP_563820, similarity 5e-43). The annotated functions of these two proteins do not imply an obvious role in plant-pathogen interactions . Moreover, the two substitutions (at positions 54 and 72) at marker Cntg10192 that are the most significantly associated with dieback resistance are synonymous, coding the same amino acid. Assuming that marker Cntg10192 is not directly involved in the resistance, it is probable that a recombinant genotype will eventually be identified. On the other hand, marker-trait associations can be very strong between some tightly linked alleles. For example, Rick and Forbes  documented linkage between allozyme Aps1 and tomato resistance gene Mi that did not break in as many as 30 backcross generations.
Chromosomal linkage group 2 contains a large cluster of resistance genes that confer resistance to downy mildew (Bremia lactucae) (Dm1, Dm3, Dm6, Dm14, Dm15, Dm16, Dm18) and lettuce root aphid (Ra) [52, 53]. However, the Cntg10192 marker is well separated (> 25 cM) from this cluster on the Salinas × UC96US12 map. Moreover, Tvr1 is one of the few resistance genes that was not at a genetic position coincident with any type of candidate resistance gene so far mapped in lettuce . Thus, it is possible that Tvr1 is different from the common types of pathogen recognition genes.
Using high-resolution DNA melting analysis for marker-assisted selection
We used HRM to directly detect sequence variations in PCR amplicons. High-resolution melting curves were recorded by the slow and steady heating of PCR products in a LightScanner instrument. Changes in the shape of the melting curve were then used to identify mutations and variations. The method worked well for most of the analyzed markers, however, in a few cases, alleles could not be distinguished. When this occurred, we applied two alternative approaches to increase sensitivity through heteroduplex formation. In one approach, the heteroduplex formation was facilitated through mixing of samples prior to PCR. For example, if one sample contained DNA from cv. Salinas only, the other one would contain a mix of DNA (1:1 ratio) from both cv. Salinas and Valmaine. The second alternative used an unlabeled probe 20 bp to 35 bp long that was designed for the region carrying the SNP. The probe was included in the PCR mix prior to cycling but was not consumed during amplification due to 3' block. Genotyping was accomplished by monitoring the melting of probe-target duplexes post-PCR as described in LightScanner manual. Both of the above alternatives improved allele detection; however, the probe-target duplex approach appeared to be more sensitive.
Lettuce dieback is a soil-borne viral disease that is one of the limiting factors for romaine and leaf-type lettuce production in California. Currently, there is no method that effectively reduces, removes, or destroys the virus in infested soil. Thus the best control of lettuce dieback is accomplished by using resistant cultivars. However, development of resistant cultivars up to now has required extensive field-based testing. Our identification of a molecular marker that is tightly linked to the Tvr1 gene conferring durable resistance will reduce the need for field-based screening and accelerate development of resistant cultivars.
A combination of classical linkage mapping and association mapping allowed us to pinpoint the location of the resistance gene on chromosomal linkage group 2. Examination of the Tvr1 region revealed a relatively high level of nucleotide polymorphism (for a selfing species) and extensive linkage disequilibrium. One of the markers (Cntg10192) flanking the Tvr1 gene showed 100% accuracy in detecting resistant and susceptible phenotypes in a set of 200 L. sativa accessions from all horticultural types of lettuce and two accessions from L. serriola. A combination of three SNPs in this EST-based marker identified four haplotypes. Three of the haplotypes are related to dieback resistance, while a single haplotype is always associated with susceptibility to the disease.
Application of high-resolution DNA melting analysis allowed us to distinguish all four haplotypes of the Cntg10192 marker in a single assay. Since heterozygous state is also easily distinguishable by the HRM analysis (data not shown), we can identify and select homozygous individuals whose offspring do not segregate for resistance in the following generation. Screening for dieback resistance with this molecular marker is now part of our breeding program. Marker-assisted selection with Cntg10192 is being used to develop improved romaine and leaf-type cultivars resistant to the disease. In addition, we are employing the molecular markers to prevent inadvertent introgression of the susceptible haplotype into the iceberg lettuce gene pool.
Described sequences have been submitted to GenBank under accession numbers GQ340976 to GQ341571.
List of abbreviations
amplified fragment length polymorphism
Compositae Genome Project Database
- cntg (in marker name):
expressed sequence tag
high-resolution DNA melting curve analysis
insertion or deletion
National Center for Biotechnology Information
polymerase chain reaction
random amplification of polymorphic DNA
variable number tandem repeat.
The authors are grateful to Lisa Lai for the excellent technical assistance and Jeffrey Skinner (Nunhems USA, Inc.) and William Waycott (Seminis Vegetable Seeds, Inc.) for critically reviewing the manuscript. We also thank Gary Higashi for generously providing field space for trials. This project was supported in part by the California Leafy Greens Research Program.
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