The heterozygous BC4 line 04GH0030 from Goodstal et al. containing a single copy of the S. habrochaites allele for fine-mapped QTL stm9 was used to generate a BC5 segregating for only the chromosome 9 region of interest from S. habrochaites. The BC5S1 generation was marker genotyped to identify recombinant individuals within the fine-mapped stm9 region flanked by markers T1670 and T0532 . Self-pollinated seed was collected from individuals chosen for their chromosome 9 introgressions, and these BC5S1 individuals were marker screened for further recombination events within the chromosome interval containing stm9. Self-seed from two heterozygous BC5S1 individuals and two heterozygous BC5S2 individuals were screened for recombinants via marker-assisted selection . Individuals that contained recombination events within the chromosome 9 fine-mapped stm9 region were selected, grown to maturity, and allowed to self-pollinate to produce seed of fully homozygous individual sub-NILs in the BC5S2 or BC5S3 generation . Recombinant homozygous individual sub-NILs were allowed to self-pollinate to generate ample seeds for replicated experiments. Phenotyping experiments were performed with one representative line from each recombinant class. All plant materials were grown in greenhouses at UC Davis. Seeds were planted in 73-cell flats containing soil media. Flats were watered daily, and plants were fertilized with a 10:30:20 NPK solution once a week. Greenhouses containing plants in flats, pots, and hydroponic tanks were maintained at ambient conditions of 25–37 °C with 55–80 % relative humidity during the day, and 18–25 °C with 20–55 % relative humidity at night. Plants from which seed was to be collected were transferred at the 4th to 5th true leaf stage to individual 8-L pots filled with soil media, and grown to maturity to obtain seed.After 2 weeks of growth in flats containing soil media ,procona London container the roots of two seedlings of each sub-NIL or control were carefully washed free of soil media in deionized water and transferred to a hydroponic growth tank set at 20 °C containing a modified Hoagland solution at 20 % of full strength .
Efforts were made to use vigorous seedlings of similar size. Plants were grown in the hydroponic tank for 1 week under ambient illumination in the greenhouse, with constant aeration and circulation of the nutrient solution. Subsequently, the plants were randomized and transferred to a separate refrigerated hydroponic tank containing fresh modified Hoagland solution at 20 % strength. Plants were acclimated overnight at a solution temperature of 20 °C. The following morning supplementary lighting was provided by one 1000 W metal halide lamp starting at 7:00 am and used throughout the experiment to maintain a light level above 1000 µmol m−2 s −2 PAR. The tank solution was maintained at 20 °C for 1 h after the supplementary lighting was turned on, and then the tank temperature was decreased to 6 °C. The tank was held at 6 °C for 2 h prior to phenotyping. Each experiment was conducted as a Randomized Complete Block Design and repeated in two seasons , with days as blocks and two replicate plants of each genotype per block. In addition to the two individual plants per recombinant sub-NIL, each replication of the experiment included controls: four plants of chilling-sensitive S. lycopersicum cv. T5, and two plants of a chilling-tolerant NIL, 03GH1322 that was also used as a tolerant control by Goodstal et al. . Six repetitions of the experiment that were conducted from May 9th to June 13th comprise the Spring data set, and four repetitions of the experiment that were carried out from October 7th to October 20th comprise the Fall data set. Plants were individually phenotyped for shoot turgor maintenance under root chilling according to the rating scale described in Goodstal et al. . Briefly, shoot turgor was scored for each plant on a scale of 0–3, with a stmscore of 0 denoting maintenance of shoot turgor, and a stmscore of 3 denoting severe loss of shoot turgor .The chromosomal location of stm9 in our study agrees with Goodstal et al. who fine-mapped stm9 to marker interval T1670–T1673 . We refined the location of stm9 to marker interval H358–T1673, a genetic distance of 0.32 cM. Our data suggests that the gene or polymorphisms controlling the tolerance phenotype are located close to marker H348 and within the marker interval H358–T1673. The chromosomal location of QTL stm9 detected in both data sets was coincident despite the significant Genotype × Season interaction in the ANOVA.
To examine the cause of the significant Genotype × Season interaction in more detail, we plotted recombinant sub-NIL stmscore means across the two seasons to create interaction plots . Inspection of the plots suggests that the changes in sub-NIL mean values across seasons primarily derived from greater chilling susceptibility of susceptible sub-NILs in the Spring than in the Fall . Magnitude differences would cause the size of the LOD peaks to differ among seasons, but not change the peak location, which is in agreement with our results . In addition to the increase in the magnitude of means for stmscore of the susceptible sub-NILs, two sub-NILs were classified as tolerant in the Spring dataset but as susceptible in the Fall dataset . Sub-NIL C4 had a mean of slightly over 1.0 in the Spring data set, and clearly grouped as susceptible in the Fall dataset . None of these lines contain the S. habrochaites introgression for high-resolution mapped stm9, but the introgressions do all flank stm9. These results suggest the possibility that there are environmentally sensitive genetic modifiers of the stmscore phenotype in this region of chromosome 9, and that the interaction of these modifiers with the environment could be causing the significant Genotype × Season interaction. Phenotypic plasticity in the presence of abiotic stress has been noted and reviewed previously . The rank changes seen within the tolerant group may be due to differences in the genomic content of S. habrochaites sequence in the flanking regions of QTL stm9, and not a direct effect of the environment on the gene or polymorphisms controlling the tolerant stm9 phenotype. Previous work in tomato has shown that the stomatal response of a plant when subjected to root chilling conditions differs between susceptible and tolerant phenotypes . Stomatal control is regulated by multiple environmental factors including light, temperature, day length, humidity, and CO2 levels . The Spring experiments were conducted under longer day lengths, higher air temperatures, and lower humidity than the Fall experiments . These seasonal differences affect the conditions in the greenhouse and may have contributed to the significant Genotype × Season interaction, as well as differences in relative response among the sub-NILs in the Spring versus Fall data sets. In the context of phenotypic plasticity, seasonal effects on sub-NIL performance would account for the more gradual separation of means in the Spring dataset compared to the Fall .Low marker density and small population sizes in initial genome-wide QTL mapping studies may bias upwards the estimation of QTL effects due to the inability to resolve closely linked, smaller effect QTL . Consequently,cut flower transport bucket single large effect QTL may resolve or fractionate into multiple, smaller effect QTL after fine- and high-resolution mapping . The original interspecific BC1 population used by Truco et al. to map QTL for shoot turgor maintenance under root chilling consisted of 196 individuals genotyped with 112 markers. Truco et al. mapped a major effect QTL to a 28-cM region on the short arm of chromosome 9 which accounted for 33 % of the phenotypic variation for shoot turgor maintenance under root chilling .
Despite the large initial genetic size of the QTL stm9 region detected by Truco et al. , subsequent fine-mapping by Goodstal et al. and high-resolution mapping in our present study do not provide any evidence of multiple QTL or QTL fractionation. The relatively small genetic size of high resolution mapped stm9 and the lack of QTL fractionation indicates that this level of resolution is suitable for the identification of candidate genes for stm9. There are numerous examples in the literature of environmentally stable, high resolution mapped QTL that have led to candidate gene identification and in some cases subsequent causal gene/ polymorphism determination.These QTL include qCTS12 , qCtss11 , and qCTB7 . Tomato-specific QTL examples include fw2.2, a fruit weight QTL, and se2.1, a stigma exsertion QTL, both identified in progeny derived from S. pennellii, another wild tomato relative . The causal gene underlying QTL fw2.2 was identified by Frary et al. , who proposed that changes in the regulation of ORFX , not changes in the sequence or structure of the expressed protein, are responsible for changes in fruit size. Chen and Tanksley determined the casual mutation underlying se2.1 is a mutation in the Style2.1 promoter that results in a down-regulation of Style2.1 expression during flower development. Collectively, the results from these studies suggest that candidate gene identification and functional testing for QTL stm9 should focus on mutations in regulatory and promoter regions of candidate genes in addition to mutations that may affect the sequence or structure of expressed proteins.Many genes have been identified as being involved directly or indirectly in plant tolerance or resistance to abiotic stresses , including chilling/cold tolerance . Plant responses to abiotic stresses can include multiple pathways that involve a variety of gene products such as receptors, signaling molecules, transporters, transcription regulators, and transcription factors . Many of the identified stress response pathways have been associated with tolerance to a range of abiotic stresses . The plant’s response to abiotic stress may result in both reversible and irreversible activation of stress response pathways . Because of the complex nature of the pathways involved, the specific genotype of the plant also has a large influence on abiotic stress response . Plant responses to abiotic stressors are dependent on the interplay of abiotic stress, environment, and genotype . Therefore, a particular abiotic stress applied in different environmental contexts may result in overlapping, but distinct responses from a single genotype . We analyzed the physical region in the cultivated tomato reference genome that is syntenic to the S. habrochaites QTL stm9 region because an assembled S. habrochaites whole genome sequence is not available. All of the protein products of the S. lycopersicum annotated genes located within 30 kb of the QTL stm9 peak marker have features that are shared with genes involved in responses to water stress and other abiotic stresses. In addition, the majority of the S. lycopersicum genes located within the syntenic high-resolution mapped stm9 region have been implicated in abiotic stress response pathways . It is possible that plant responses to root chilling stress may induce a more complex transcriptional response than other types of water stress such as those caused by salt or polyethylene-glycol , although overlap has been seen in the response to all three stresses . For example, in grape, under root chilling stress only transcripts for protein synthesis and the cell cycle were up-regulated to a lesser extent than under salt or PEG stress. The regulation of plant metabolism, protein metabolism, signal transduction, calcium signaling, stress hormone pathways, and transcription factors were all increased to a greater extent under root chilling in grape . These categories of genes account for the majority of genes located within the syntenic S. lycopersicum QTL stm9 region. While the total number of annotated genes within the S. lycopersicum reference genome region containing QTL stm9 is relatively small, there are no estimates available for S. habrochaites due to the unavailability of assembled whole genome sequence for this wild species. A comparison of the genetic and S. lycopersicum physical maps of the chromosome 9 region containing stm9 shows a variable rate of recombination across this region . The average kbp/cM for marker interval T1670–T1673 is 952 kbp/ cM, whereas for marker interval T1673–T0532, it is 385 kbp/cM. Recombination occurs more frequently in generich euchromatic regions, but can be suppressed due to lack of homology, heterochromatic regions, and/or the presence of repetitive elements . It is possible that this variable rate of recombination is due to the presence of repetitive elements or other local structural polymorphisms affecting the synteny and colinearity of the S. lycopersicum and S. habrochaites genome sequences in this region. In addition, our flow cytometry results indicated that the genome size of S. habrochaites is 1.5 × that of S. lycopersicum .