- Research article
- Open Access
Patchwork sequencing of tomato San Marzano and Vesuviano varieties highlights genome-wide variations
© Ercolano et al.; licensee BioMed Central Ltd. 2014
- Received: 24 July 2013
- Accepted: 24 January 2014
- Published: 18 February 2014
Investigation of tomato genetic resources is a crucial issue for better straight evolution and genetic studies as well as tomato breeding strategies. Traditional Vesuviano and San Marzano varieties grown in Campania region (Southern Italy) are famous for their remarkable fruit quality. Owing to their economic and social importance is crucial to understand the genetic basis of their unique traits.
Here, we present the draft genome sequences of tomato Vesuviano and San Marzano genome. A 40x genome coverage was obtained from a hybrid Illumina paired-end reads assembling that combines de novo assembly with iterative mapping to the reference S. lycopersicum genome (SL2.40). Insertions, deletions and SNP variants were carefully measured. When assessed on the basis of the reference annotation, 30% of protein-coding genes are predicted to have variants in both varieties. Copy genes number and gene location were assessed by mRNA transcripts mapping, showing a closer relationship of San Marzano with reference genome. Distinctive variations in key genes and transcription/regulation factors related to fruit quality have been revealed for both cultivars.
The effort performed highlighted varieties relationships and important variants in fruit key processes useful to dissect the path from sequence variant to phenotype.
- Combined assembling
- Fruit quality
- NGS sequencing
- Solanum lycopersicum
Tomato (Solanum lycopersicum) is one of the most economically important vegetable crops worldwide. It is a rich source of micronutrients for human diet and a model species for fruit quality. Investigation of tomato genetic resources is a crucial issue for better straight evolution and genetic studies as well as tomato breeding strategies.
Since the late 18th and throughout the 19th and early 20th centuries a huge array of crosses and selection activities has taken place in Europe giving rise to a rich collection of tomato landraces [1, 2]. In particular, an extensive selection work was performed in Italy by “Campania” farmers that developed several varieties adapted to local conditions and with quality requirements well delineated for specific uses. Among them, Vesuviano (RSV) and San Marzano (SM) varieties, grown in rich volcanic soil surrounding Vesuvius, are considered important models for fruit quality parameters. The Vesuviano has been cultivated on the Vesuvio hill, since the end of 19th century. It was selected by the local farmers because of its tolerance to the drought . The origin of the San Marzano variety is very debatable. Some people report that San Marzano was a mutant from the local varieties (Corbarino); other people report that San Marzano was a natural hybridization between the grown varieties in the Agro-Sarnese-Nocerino area. Certainly, the cultivation of the San Marzano ecotype started in the years 1903–1904 in the Agro-Sarnese-Nocerino area becoming immediately a top variety for peeling . Previous studies revealed that presently cultivated Vesuvio and San Marzano genotypes revealed peculiar sensory profiles in perception of sweetness and sourness [5, 6]. San Marzano and Vesuvio fruits can purchased by at a price that is nearly five times higher than that of other varieties .
The advent of genomics era has brought a substantial increase in generation of data, knowledge and tools that can be employed in applied research. Candidate genes for important traits can be identified, and exploring functional nucleotide polymorphisms within genes of interest can facilitate breeders in combining favourable alleles. The decoding of the Heinz 1706 tomato reference genome SL2.40 will allow a better understanding of genetic basis of agronomic traits for developing novel genotypes [8, 9]. Genome sequences and genomic tools offer exciting new perspectives and opportunities to track rates of sequence divergence over time, and provide hints about how genes evolve and generate new products by re-organization and shuffling of genomic sequences. Variant catalogues, however, will remain incomplete if forms of variation are undocumented. Good genome coverage is required to improve variant detection and accuracy and to study the polymorphism distribution across genomes. Genetic diversity studies have been improved by Next Generation Sequencing (NGS) based approaches [10, 11]. However, interpreting the effect of genetic variation has typically relied on a reference genome. Indeed, alignment-consensus methods may have serious limitations in describing polymorphic regions and may also cause biases in interpreting the effect of variation on coding sequences. On the other hand de novo assembly approaches may theoretically overcome such problems, but pose a number of challenges due for example to repetitive sequences, low complexity sequences and closely related paralogs . Alternative hybrid approaches can overcome limitations of alignment-consensus methods [13, 14], allowing to capture a broader spectrum of sequence variation comparing genome with or without reference genome .
Here we describe the generation and analysis of San Marzano and Vesuviano tomato genome sequences. First, we reconstructed the genomes using a combination of iterative mapping and de novo assembly. Then, we annotated genes and documented the variation discovered, describing the typology and the distribution of variants between genotypes at chromosome level. Finally, as proof of concept we assessed the variability in fruit quality related genes, exploring the quantitative and qualitative impact of functional variants. Data produced can be helpful to investigate the genomic origins of phenotypic variation as well as to perform breeding programs.
A total amount of 2.5 μg of genomic DNA was sonicated with Covaris S2 instrument to obtain 400 bp fragments. DNA library preparation of SM and RSV tomato varieties (Additional file 1: Figure S1) was carried out using the TruSeq DNA Sample Prep Kit v2 (Illumina, San Diego, CA) accordingly to manufacturer instructions. RNA library preparation of SM and RSV tomato berry samples was carried out using the TruSeq RNA Sample Prep Kit v2 (Illumina, San Diego, CA) accordingly to manufacturer instructions.
Quality control of libraries was performed using High Sensitivity DNA Kit (Agilent, Wokingham, UK) and an accurate quantification was made using qPCR with KAPA Library Quantification kit (KapaBiosystems, USA). Libraries were then pooled and sequenced using Illumina Hiseq 1000 and applying standard Illumina protocols with TruSeq SBS Kit v3-HS and TruSeq PE Cluster Kit v3-cBot-HS kits (lllumina, USA). Libraries were sequenced with an Illumina Hiseq 1000 sequencer (Illumina Inc., San Diego, CA, USA) and 100-bp paired-end sequences were generated.
Genome assembly and annotation transfer
Genome reconstruction and variants identification were performed with the IMR/DENOM ver. 0.3.3 pipeline  using default parameters and the SL2.40 tomato genome  as reference. Repeats annotation was performed with RepeatMasker (v. open-3.3.0) using a custom redundant database available from SolGenomics website (ftp://ftp.solgenomics.net/tomato_genome/repeats/). ITAG 2.3 gene annotation was translated to the tomato reconstructed genomes by taking into account variants identified by IMR/DENOM pipeline and adjusting the coordinates accordingly using a custom software (http://ddlab.sci.univr.it/downloads/translate_coordinates.exe).
Mapping of transcript sequences
We independently mapped the 34,727 coding sequences (CDSs) [16, 17] defined by the Solanum lycopersicum genome annotation to identify similarities versus RSV and SM tomato genomes using GenomeThreader , CDSs were also re-mapped versus SL2.40 to compare results between the three different genotypes. We filtered out alignments at similarity thresholds lower than 80% coverage and 90% identity. Correspondence among the loci in the three genotypes was defined on the basis of conserved loci position analyses at chromosome level and their distribution is reported using the CIRCOS program .
Variants analysis and validation
Identified variants between SL2.40 genome SM and RSV genotype were analysed using SnpEff version 2.1b (build 2012-04-20)  to predict their the effect on the genes in ITAG2.3 annotation. CDS non-synonymous variants were also submitted to PROVEAN (Protein Variation Effect Analyzer algorithm) analysis, which predicts the functional impact for all classes of protein sequence variations such as single amino acid substitutions but also insertions, deletions, and multiple substitutions . To validate the identified SNPs, paired-end RNA-Seq reads (100 bp) from SM and RSV fruit samples were mapped against the reference genome SL2.40. SNPs were called using SAMtools 0.1.18  with a minimum read depth threshold of 6 and then compared with genomic reads using BEDTools 2.17.0 software .
Our attention was focused on non-synonymous SNPs located in CDS belonging to four gene classes related to fruit quality (ascorbate biosynthesis; MEP/carotenoid pathway; ethylene-related genes; cell wall related genes); transcription factors and transcription regulators potentially involved in fruit ripening process. To evaluate if significant enrichment was present in specific metabolic pathways, an enrichment analysis based on Gene Ontology (GO) terms classification  was performed. We associated a GO term to each gene containing a non-synonymous coding variation running the BLAST2GO platform . The data sets obtained were compared to the entire set of tomato genes with GO annotation (SOL Genomics. http://solgenomics.net/).
We used a hypergeometric test to compare each class to the reference background of genes. Hochberg (FDR) statistical correction was applied and a significance level of 0.05 was set. The minimum number of mapping entries was set as 1 to observe any significant enrichment. Only gene classes with a least 20 protein members (transcription factors, transcription regulators and cell wall) were subject to enrichment analysis.
All next-generation sequencing data are available in the Sequence Reads Archive (SRA) [SRA:SRP027562] Variants data in Snps, Deletions and Insertions (SDI) file format are available on SOL Genomics Network (SGN) website (ftp://ftp.solgenomics.net).
We sequenced Vesuviano (RSV) and San Marzano (SM) tomato varieties using Illumina 100 bp paired-end reads with an insert size of about 250 bp. We obtained 155,751,012 (X2) pareid-end reads for RSV and 177,758,218 (X2) paired-end reads for SM that, considering an expected size of about 900 Mb , correspond to an average expected depth of about 34.6x and 39.5x genome equivalent, respectively (Additional file 2: Table S1). We chose to use a genome reconstruction method based on a combination of iterative read mapping against the tomato reference genome and de novo assembly that is able to describe complex loci on a single pass alignment  (Additional file 3: Figure S2). A similar number of mobile elements (63%) and outstanding proportion of LTR elements (93% of occupied length) with SL2.40 genome was found (Additional file 2: Table S2).
Counts of identified SNPs and of genes affected by them
Length < 6
Length > 100
Length < 6
Length > 100
Transcript sequences mapping
Number of tomato genes mapped versus the reference tomato (SL240), the Vesuviano (RSV) and San Marzano (SM) genomes
Analysis of genetic variants in fruit quality related genes
Number and percentage of polymorphic genes and number of variants identified for each fruit quality-related class of genes in Vesuviano (RSV) and San Marzano (SM) varieties Data are referred to the tomato reference genome (SL240)
Common and specific genes related to fruit quality with variants in Vesuviano (RSV) and San Marzano (SM) varieties
Fruit quality related genes affected by deleterious mutation in SM, RSV or both varieties
B3 domain-containing protein
Auxin response factor 2
NAC domain protein
Zinc finger CCCH domain-containing protein 38
BZIP transcription factor
Chromodomain-helicase-DNA-binding protein 1-like
PHD finger family protein
Glucan synthase like 1
Pollen allergen Phl p 11
Zinc finger-homeodomain protein 2
Heat stress transcription factor A3
Myb-related transcription factor
BZIP transcription factor 3
B3 domain-containing protein
RNA polymerase sigma-70 factor
DNA repair and recombination protein RAD54-like
Mannan endo-1 4-beta-mannosidase
Zinc finger CCCH domain-containing protein 30
WUSCHEL-related homeobox 11
BSD domain containing protein
G-box binding factor 3
Homeodomain-containing transcription factor FWA
Zinc finger family protein
MYB transcription factor
MADS box transcription factor
Transcription factor (Fragment)
MYB transcription factor
Kelch repeat and BTB domain-containing
Cell differentiation protein rcd1
Ripening ethylene related
Fasciclin-like arabinogalactan protein 13
Transmembrane protein 222
Fasciclin-like arabinogalactan protein 7
In this work the tomato RVS and SM genomes have been sequenced and assembled using a strategy based on iterative mapping and de novo assembly . This method showed to be less demanding in terms of sequencing depth and multiple libraries construction compared to a complete de novo assembly. The catalogue of tomato genetic variants produced using this valuable approach allowed enlarging the list available (http://solgenomics.net/search/markers) with a relative low investment. The magnitude of the number of variants found is not comparable with earlier catalogue, based on transcriptome sequencing or oligonucleotide arrays [28–32]. In addition, other types of variations in CDS sequences were evidenced.
The chromosome pseudomolecules obtained allowed studying with high accuracy genome colinearity useful for gene mapping and marker-assisted breeding. At 40x sequence coverage, we estimated that approximately 99% of the tomato reference genome could be genotyped. Our analysis produced approximately 200,000 SNPs and more than 130,000 indels. In accordance with the high level of homozygosis reported for tomato cultivars , a small fraction (approximately 3%) of heterozygous variants or sequence misalignments were identified in either cultivar. Variation in the level of polymorphism among chromosomes was found. Indeed, the chromosome variation could reflect selection history rather than polymorphism discovery . More than 3,000 genes in both varieties showed different similarity values at exon level when compared with reference genome. A slight higher colinearity between SM and the reference genome was found, suggesting a their closer relationship. Genome-wide structural and gene content variations are hypothesized to drive important phenotypic variation within a species . However, in most cases deletions are common to both varieties and their frequency is consistent with previous data on indel errors in the reference genome, and thus we suspect that a percentage of de novo assembled sequences corresponds to sequences missing from the reference genome.
Based on the tomato gene model set, a limited number of altered genes were detected in each variety, while 1,934 RSV and 1,707 SM transferred annotations were affected by mutations potentially causing amino acidic substitutions of unknown effect on the protein function. A subset of these SNPs was restricted to a single variety. The study of distribution of variants across the genomes of the sequenced variety is important. Number, location and predicted effects can gain insights in plant diversification. Indeed, the selective forces acting over time on diverse traits could have driven the fixation of positive mutations in each variety. Whether a polymorphic equilibrium is reached depends on the intensity of selection and the relative distances to the optimum of the homozygosis at each locus .
Analysis of genetic variants for quality related genes showed that genes were differentially affected by genetic variants depending on the functional class they belong to, suggesting different degrees of selection for genetic variants underlying biological processes. We also showed that the position of sequence variants influence the functionality of the encoded protein. Functional variants contributing to deletion in 3′UTR and exon, intron_conserved and exon, intron_conserved region were highlighted; by contrast, a limited number of other intronic/esonic variants were identified. SNPs within the gene classes assessed reflect the fruit quality genetic diversity between RSV and SM varieties. High percent of variation and deleterious substitutions has been found in genes belonging to the transcription factor and transcription regulator classes, such as acetyltrasferase, chromodomain helicase and histone linkers. Interestingly, enrichment for a chromatin remodeler like protein ligase SNF2 in RSV genotypes points out the possibility that the phenotypic differences among these three tomato genotype are mainly due to complex mechanisms of gene regulation and cross-talk. Recently it has been showed that important epigenome modifications are associated with ripening process . The ethylene-related gene class also showed a high number of variants and deleterious substitutions, probably due to the large difference in the ripening process of the two tomato varieties with respect to the reference tomato. In particular, an ACS gene showed a deleterious substitution (T82A) in both varieties and three ACS key genes involved in ethylene biosynthesis varied only in RSV. This is a long-storage tomato variety with extended shelf life. Since ethylene control fruit ripening process , polymorphisms detected in these RSV genes should be further explored to understand their involvement in delaying ripening process. Ethylene production is regulated by combinatorial interplay of the ACS polypeptides. Understand how the “ACS symphony orchestra” is coordinated will be a big challenge for the future . Finally, the result of SEA analyse indicated a significant enrichment of the cell wall genes. GO terms corresponding to hydrolase, galactosidase, beta-glucosidase and beta-galactosidase, involved in chemicals breakdown activity inside the fruits, showed significant differences in both varieties. In particular, RSV-specific non-synonymous variants were enriched in genes involved in xyloglucan biosynthesis and homogalacturonan biosynthesis. Genes related to fruit texture has been frequent targets for genetic engineering, with the goal of extending shelf life . Future investigations on these genes and ethylene related genes should be achieved. The regulation of texture and shelf life is complex and performing a deeper analysis of variants discovered could allow a better understanding of the relationship between changes in the textural and shelf life extension .
The genome sequences reported here and the variants catalogue obtained will be useful to identify the molecular basis of gene complex patterns. Further analysis and functional studies will serve as a basis for understanding trait differences, which will facilitate the identification of markers for genomic marker–assisted breeding. Data produced can be also useful to prioritize mutations to reveal a phenotype. Indeed, large-scale TILLING projects can be used to identify gene of interest saturated with mutations . Collectively, sequence and fine annotation analysis performed can be useful to examine the path from sequence variant to phenotype for improving the utility of the tomato as a model for fruit quality. In addition, the genes we identified that are related to ripening and texture characteristics could be used as target for tomato breeding. The local genomes genotyping is also useful for understanding the genomic features that distinguish modern from traditional varieties. Variants specific for SM and RSV might be explored through a high throughput target re-sequencing approach in other varieties in order to verify that they could represent variants characteristics for these two different tomato typologies.
We sincerely acknowledge Dr. Giuseppe Andolfo for R programming support and Dr. Alberto Ferrarini for his valuable suggestions in improving the manuscript. We wish to dedicate our effort in memory of Dr. Tina Mancuso.
This work was supported by the Ministry of University and Research (GenoPOM-PRO Project), La Semiorto Sementi S.r.l., Sarno, Italy, and Lodato Gennaro & C. S.P.A., Castel San Giorgio Italy.
- Bai Y, Lindhout P: Domestication and breeding of tomatoes: what have we gained and what can we gain in the future?. Ann Bot-London. 2007, 100: 1085-1094. 10.1093/aob/mcm150.View ArticleGoogle Scholar
- Grandillo S, Chetelat R, Knapp SK, Spooner DM, Peralta I, Cammareri M, Perez O, Termolino P, Tripode P, Chiusano ML, Ercolano MR, Fruschiante L, Monte L, Pignone D: Solanum section Lycopersicon. Wild crop relatives: Genomic and breeding resources, Volume 5. Edited by: Kole C. 2011, Berlin, Heidelberg: Springer-Verlag, 129-216.View ArticleGoogle Scholar
- Zago F: Buone varietà di pomodoro. L'Italia Agricola. 1912, 44: 110-456.Google Scholar
- Zago F: Varietà per la preparazione dei pelati. L'Italia Agricola. 1929, 66: 360-362.Google Scholar
- Ercolano MR, Carli P, Soria A, Cascone A, Fogliano V, Frusciante L, Barone A: Biochemical sensorial and genomic profiling of Italian tomato traditional varieties. Euphytica. 2008, 164: 571-582. 10.1007/s10681-008-9768-4.View ArticleGoogle Scholar
- Carli P, Barone A, Fogliano V, Frusciante L, Ercolano MR: Dissection of genetic and environmental factors involved in tomato organoleptic quality. BMC Plant Biol. 2011, 11: 58-10.1186/1471-2229-11-58.PubMed CentralPubMedView ArticleGoogle Scholar
- Garcia-Martinez S, Corrado G, Ruiz-Martinez JJ, Rao R: Diversity and structure of a sample of traditional Italian and Spanish tomato accessions. Genet Resour Crop Evol. 2013, 60: 789-798. 10.1007/s10722-012-9876-9.View ArticleGoogle Scholar
- The Tomato Genome Consortium: The tomato genome sequence provides insights into fleshy fruit evolution. Nature. 2012, 485: 635-641. 10.1038/nature11119.View ArticleGoogle Scholar
- Todd PM, Alba R: The tomato genome fleshed out. Nat Biotechnol. 2012, 30: 765-767. 10.1038/nbt.2319.View ArticleGoogle Scholar
- The 1000 Genomes Project Consortium: An integrated map of genetic variation from 1092 human genomes. Nature. 2012, 491: 56-65. 10.1038/nature11632.PubMed CentralView ArticleGoogle Scholar
- Cao J, Schneeberger K, Ossowski S, Günther T, Bender S, Fitz1 J, Koenig D, Lanz C, Stegle O, Lippert C, Wang X, Ott F, Müller J, Alonso-Blanco C, Borgwardt K, Schmid KJ, Weigel D: Whole-genome sequencing of multiple Arabidopsis thaliana populations. Nat Genet. 2011, 43: 956-963. 10.1038/ng.911.PubMedView ArticleGoogle Scholar
- Treangen TJ, Salzberg SL: Repetitive DNA and next-generation sequencing: computational challenges and solutions. Nat Rev Genet. 2011, 13: 36-46.PubMed CentralPubMedGoogle Scholar
- Schneeberger K, Ossowski S, Ott F, Klein JD, Wang X, Lanz C, Smith LM, Cao J, Fitz J, Warthmann N, Henz SR, Huson DH, Weigel D: Reference-guided assembly of four diverse Arabidopsis thaliana genomes. Proc Natl Acad Sci USA. 2011, 108: 10249-10254. 10.1073/pnas.1107739108.PubMed CentralPubMedView ArticleGoogle Scholar
- Gan X, Stegle O, Behr J, Steffen JG, Drewe P, Hildebrand KL, Lyngsoe R, Schultheiss SJ, Osborne EJ, Sreedharan VT, Kahles A, Bohnert R, Jean G, Derwent P, Kersey P, Belfield EJ, Harberd NP, Kemen E, Toomajian C, Kover PX, Clark RM, Rätsch G, Mott R: Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature. 2011, 477: 419-423. 10.1038/nature10414.PubMedView ArticleGoogle Scholar
- Bevan M: Genomics: endless variation most beautiful. Nature. 2011, 477: 415-416. 10.1038/477415a.PubMedView ArticleGoogle Scholar
- Jiménez-Gómez JM, Maloof JN: Sequence diversity in three tomato species: SNPs, markers, and molecular evolution. BMC Plant Biol. 2009, 9: 85-10.1186/1471-2229-9-85.PubMed CentralPubMedView ArticleGoogle Scholar
- Lunter G, Goodson M: Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res. 2011, 21: 936-939. 10.1101/gr.111120.110.PubMed CentralPubMedView ArticleGoogle Scholar
- Gremme G, Brendel V, Sparks ME, Kurtz S: Engineering a software tool for gene structure prediction in higher organisms. Inf Softw Technol. 2005, 47: 965-978. 10.1016/j.infsof.2005.09.005.View ArticleGoogle Scholar
- Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones S, Marra M: Circos: an information aesthetic for comparative genomics. Genome Res. 2009, 19: 1639-1645. 10.1101/gr.092759.109.PubMed CentralPubMedView ArticleGoogle Scholar
- Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, Land SJ, Lu X, Ruden DM: A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of_Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012, 6: 80-92. 10.4161/fly.19695.PubMed CentralPubMedView ArticleGoogle Scholar
- Choi Y, Sims GE, Murphy S, Miller JR, Chan AP: Predicting the functional effect of amino acid substitutions and indels. PLOSOne. 2012, 7: e46688-10.1371/journal.pone.0046688.View ArticleGoogle Scholar
- Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, and 1000 Genome Project Data Processing Subgroup: The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics. 2009, 25: 2078-2079. 10.1093/bioinformatics/btp352.PubMed CentralPubMedView ArticleGoogle Scholar
- Quinlan AR, Hall IM: BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010, 26 (6): 841-842. 10.1093/bioinformatics/btq033.PubMed CentralPubMedView ArticleGoogle Scholar
- Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology The Gene Ontology Consortium. Nat Genet. 2000, 25: 25-29. 10.1038/75556.PubMed CentralPubMedView ArticleGoogle Scholar
- Conesa A, Götz S, García-Gómez JM, Teroll J, Talónl M, Roblesl M: Blast2GO: a universal tool for annotation visualization and analysis in functional genomics research. Bioinformatics. 2005, 21: 3674-3676. 10.1093/bioinformatics/bti610.PubMedView ArticleGoogle Scholar
- Du Z, Zhou X, Ling Y, Zhang Z, Su Z: agriGO: a GO analysis toolkit for the agricultural community. Nucl Acids Res. 2012, 38: W64-W70.View ArticleGoogle Scholar
- Tipney H, Hunter L: An introduction to effective use of enrichment analysis software. Hum Genomics. 2010, 4: 202-206. 10.1186/1479-7364-4-3-202.PubMed CentralPubMedView ArticleGoogle Scholar
- Hamilton JP, Sim SC, Stoffel K: Single nucleotide polymorphism discovery in cultivated tomato via sequencing by synthesis. The Plant Genome. 2012, 5: 17-29. 10.3835/plantgenome2011.12.0033.View ArticleGoogle Scholar
- Sim SC, Robbins MD, Van Deynze A, Michel AP, Francis DM: Population structure and genetic differentiation associated with breeding history and selection in tomato (Solanum lycopersicum L). Heredity. 2011, 106: 927-935. 10.1038/hdy.2010.139.PubMed CentralPubMedView ArticleGoogle Scholar
- Sim SC, Van Deynze A, Stoffel K, Douches DS, Zarka D, Ganal MW, Chetelat RT, Hutton SF, Scott JW, Gardner RG, Panthee DR, Mutschler M, Myers JR, Francis DM: High-density SNP genotyping of tomato (Solanum lycopersicum L) reveals patterns of genetic variation due to breeding. PLOSOne. 2012, 7: e45520-10.1371/journal.pone.0045520.View ArticleGoogle Scholar
- Blanca J, Cañizares J, Cordero L, Pascual L, Diez MJ, Nuez F: Variation revealed by SNP genotyping and morphology provides insight into the origin of the tomato. PLOSOne. 2012, 7: e48198-10.1371/journal.pone.0048198.View ArticleGoogle Scholar
- Hirakawa H, Shirasawa K, Ohyama A, Fukuoka H, Aoki K, Rothan C, Sato S, Isobe S, Tabata S: Genome-wide SNP genotyping to infer the effects on Gene functions in tomato. DNA Res. 2013, 20 (3): 221-233. 10.1093/dnares/dst005. doi:10.1093/dnares/dst005PubMed CentralPubMedView ArticleGoogle Scholar
- McHale LK, Haun WJ, Xu WW, Bhaskar PB, Anderson JE, Hyten DL, Gerhardt DJ, Jeddeloh JA, Stupar RM: Structural variants in the soybean genome localize to clusters of biotic stress-response genes. Plant Physiol. 2012, 159: 1295-1308. 10.1104/pp.112.194605.PubMed CentralPubMedView ArticleGoogle Scholar
- Pavlidis P, Metzler D, Stephan W: Selective sweeps in multilocus models of quantitative traits. Genetics. 2012, 192: 225-239. 10.1534/genetics.112.142547.PubMed CentralPubMedView ArticleGoogle Scholar
- Zhong S, Fei Z, Chen YR, Zheng Y, Huang M, Vrebalov J, McQuinn R, Gapper N, Liu B, Xiang J, Shao Y, Giovannoni JJ: Single-base resolution methylomes of tomato fruit development reveal epigenome modifications associated with ripening. Nat Biotechnol. 2013, 31: 154-159. 10.1038/nbt.2462.PubMedView ArticleGoogle Scholar
- Klee HJ, Giovannoni JJ: Genetics and control of tomato fruit ripening and quality attributes. Annu Rev Genet. 2011, 45: 41-59. 10.1146/annurev-genet-110410-132507.PubMedView ArticleGoogle Scholar
- Tsuchisaka A, Yu G, Jin H, Alonso JM, Ecker JR, Zhang X, Gao S, Theologis A: A combinatorial interplay among the 1-aminocyclopropane-1-carboxylate isoforms regulates ethylene biosynthesis in Arabidopsis thaliana. Genetics. 2009, 183: 979-1003. 10.1534/genetics.109.107102.PubMed CentralPubMedView ArticleGoogle Scholar
- Matas A, Gapper N, Chung M, Giovannoni J, Rose JKC: Biology and genetic engineering of fruit maturation for enhanced quality and shelf-life. Curr Opin Biotech. 2009, 20: 197-203. 10.1016/j.copbio.2009.02.015.PubMedView ArticleGoogle Scholar
- Ng PC, Henikoff S: Predicting the effects of amino acid substitutions on protein function. Annu Rev Genomics Hum Genet. 2006, 7: 61-80. 10.1146/annurev.genom.7.080505.115630.PubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.