Genome-wide association study (GWAS) is a strategy for genetic dissection of quantitative traits with high mapping resolution. Haplotypes based on multiple SNPs provide an effective alternative for exploring loci associated with complex quantitative traits. In this study, haplotype-based GWAS (Hap-GWAS) was conducted for seven fruit-related traits in the 287 tomato accessions, consisting of 237 S. lycopersicum, 30 S. lycopersicum var. cerasiforme, and 20 S. pimpinellifolium. Phenotypic variations of the fruit-related traits (weight, shape, locule number, pericarp thickness, number of flowers, number of fruits, and Brix) were assessed in three-years of field trials. Over 28.7 million SNPs were identified from whole genome-resequencing and a core set of 137,706 SNPs was used to construct 3,884 haplotype blocks across 12 chromosomes. The 11,970 haplotypes in these blocks found high levels of genetic diversity and differentiation with and between species in the GWAS panel. A total of 32 haplotypes, corresponding to 30 QTL, showed significant associations with fruit-related traits at a false discovery rate (FDR) adjusted P < 0.05 in at least two of the four phenotypic datasets (each of three years and combined), explaining up to 51.67

BACKGROUND:The Citrus species are major fruit crops cultivated in the world and have complex genetic relationships due to sexual comparability between Citrus and related genera. Of these, satsuma mandarin (C. unshiu (Mak.) Marc.) and sweet orange (C. sinensis (L.) Osb.) are widely grown diploid species. In this study, genotyping by sequencing (GBS) was conducted to identify single nucleotide polymorphisms (SNPs) for investigating genetic variation in a citrus collection. RESULTS:A total of 26,903 high-quality SNPs were detected across nine chromosomes in the 144 citrus varieties, consisting of 70 C. unshiu, 40 C. sinensis, 22 interspecific hybrids, and 12 others. Of these, a core set of 481 SNPs was filtered based on polymorphism information content and genome distribution. Both principal component analysis (PCA) and model-based clustering showed genetic differentiation between C. unshiu and C. sinensis. For interspecific hybrids, these were separated from two species in PCA, but were mixed with each species in model-based clustering. Significant genetic differentiations between three populations were also found using the pairwise Fst. In addition, interspecific hybrids showed higher level of genetic diversity relative to the C. unshiu and C. sinensis populations. With the 481 SNPs, four subsets (192, 96, 48, and 24 SNPs) were generated to evaluate their performance for variety identification. Both 192 and 96 SNP sets distinguished all 144 varieties, while the 48 and 24 SNP sets separated 134 (93.1%) and 110 (76.4%), respectively. CONCLUSIONS:The GBS-based SNP discovery led to robust and cost-effective molecular marker sets to assess genetic variation in the cultivated citrus species with narrow genetic bases. The resulting SNP sets are a resource to enhance the phenotype-based DUS testing by developing a DNA barcode system and thus facilitate new variety breeding and protection in citrus.

Background Genomic selection (GS) is an efficient breeding strategy to improve quantitative traits. It is necessary to calculate genomic estimated breeding values (GEBVs) for GS. This study investigated the prediction accuracy of GEBVs for five fruit traits including fruit weight, fruit width, fruit height, pericarp thickness, and Brix. Two tomato germplasm collections (TGC1 and TGC2) were used as training populations, consisting of 162 and 191 accessions, respectively. Results Large phenotypic variations for the fruit traits were found in these collections and the 51K Axiom ™ SNP array generated confident 31,142 SNPs. Prediction accuracy was evaluated using different cross-validation methods, GS models, and marker sets in three training populations (TGC1, TGC2, and combined). For cross-validation, LOOCV was effective as k -fold across traits and training populations. The parametric (RR-BLUP, Bayes A, and Bayesian LASSO) and non-parametric (RKHS, SVM, and random forest) models showed different prediction accuracies (0.594–0.870) between traits and training populations. Of these, random forest was the best model for fruit weight (0.780–0.835), fruit width (0.791–0.865), and pericarp thickness (0.643–0.866). The effect of marker density was trait-dependent and reached a plateau for each trait with 768−12,288 SNPs. Two additional sets of 192 and 96 SNPs from GWAS revealed higher prediction accuracies for the fruit traits compared to the 31,142 SNPs and eight subsets. Conclusion Our study explored several factors to increase the prediction accuracy of GEBVs for fruit traits in tomato. The results can facilitate development of advanced GS strategies with cost-effective marker sets for improving fruit traits as well as other traits. Consequently, GS will be successfully applied to accelerate the tomato breeding process for developing elite cultivars.

Bacterial wilt (BW) is a soil-borne disease that leads to severe damage in tomato. Host resistance against BW is considered polygenic and effective in controlling this destructive disease. In this study, genomic selection (GS), which is a promising breeding strategy to improve quantitative traits, was investigated for BW resistance. Two tomato collections, TGC1 (n = 162) and TGC2 (n = 191), were used as training populations. Disease severity was assessed using three seedling assays in each population, and the best linear unbiased prediction (BLUP) values were obtained. The 31,142 SNP data were generated using the 51K Axiom array™ in the training populations. With these data, six GS models were trained to predict genomic estimated breeding values (GEBVs) in three populations (TGC1, TGC2, and combined). The parametric models Bayesian LASSO and RR-BLUP resulted in higher levels of prediction accuracy compared with all the non-parametric models (RKHS, SVM, and random forest) in two training populations. To identify low-density markers, two subsets of 1,557 SNPs were filtered based on marker effects (Bayesian LASSO) and variable importance values (random forest) in the combined population. An additional subset was generated using 1,357 SNPs from a genome-wide association study. These subsets showed prediction accuracies of 0.699 to 0.756 in Bayesian LASSO and 0.670 to 0.682 in random forest, which were higher relative to the 31,142 SNPs (0.625 and 0.614). Moreover, high prediction accuracies (0.743 and 0.702) were found with a common set of 135 SNPs derived from the three subsets. The resulting low-density SNPs will be useful to develop a cost-effective GS strategy for BW resistance in tomato breeding programs.

Pear (Pyrus spp.) is a major fruit crop in the Rosaceae family, and extensive efforts have been undertaken to develop elite varieties. With advances in genome sequencing technologies, single-nucleotide polymorphisms (SNPs) are commonly used as DNA markers in crop species. In this study, a large-scale discovery of SNPs was conducted using genotyping by sequencing in a collection of 48 cultivated pear accessions. A total of 256,538 confident SNPs were found on 17 chromosomes, and 288 SNPs were filtered based on polymorphic information content, heterozygosity rate, and genome distribution. This subset of SNPs was used to genotype an additional 144 accessions, consisting of P. pyrifolia (53), P. ussuriensis (27), P. bretschneideri (19), P. communis (26), interspecific hybrids (14), and others (5). The 232 SNPs with reliable polymorphisms revealed genetic variations between and within species in the 192 pear accessions. The Asian species (P. pyrifolia, P. ussuriensis, and P. bretschneideri) and interspecific hybrids were genetically differentiated from the European species (P. communis). Furthermore, the P. pyrifolia population showed higher genetic diversity relative to the other populations. The 232 SNPs and four subsets (192, 96, 48, and 24 SNPs) were assessed for variety identification. The 192 SNP subset identified 173 (90.1%) of 192 accessions, which was comparable to 175 (91.1%) from the 232 SNPs. The other three subsets showed 81.8% (24 SNPs) to 87.5% (96 SNPs) identification rates. The resulting SNPs will be a useful resource to investigate genetic variations and develop an efficient DNA barcoding system for variety identification in cultivated pears.

Early blight (EB), caused by Alternaria linariae (Neerg.) (syn. A. tomatophila) Simmons, is a disease that affects tomatoes (Solanum lycopersicum L.) throughout the world, with tremendous economic implications. The objective of the present study was to map the quantitative trait loci (QTL) associated with EB resistance in tomatoes. The F2 and F2:3 mapping populations consisting of 174 lines derived from NC 1CELBR (resistant) × Fla. 7775 (susceptible) were evaluated under natural conditions in the field in 2011 and in the greenhouse in 2015 by artificial inoculation. In all, 375 Kompetitive Allele Specific PCR (KASP) assays were used for genotyping parents and the F2 population. The broad-sense heritability estimate for phenotypic data was 28.3%, and 25.3% for 2011, and 2015 disease evaluations, respectively. QTL analysis revealed six QTLs associated with EB resistance on chromosomes 2, 8, and 11 (LOD 4.0 to 9.1), explaining phenotypic variation ranging from 3.8 to 21.0%. These results demonstrate that genetic control of EB resistance in NC 1CELBR is polygenic. This study may facilitate further fine mapping of the EB-resistant QTL and marker-assisted selection (MAS) to transfer EB resistance genes into elite tomato varieties, including broadening the genetic diversity of EB resistance in tomatoes.

Lettuce is one of the economically important leaf vegetables and is cultivated mainly in temperate climate areas. Cultivar identification based on the distinctness, uniformity, and stability (DUS) test is a prerequisite for new cultivar registration. However, DUS testing based on morphological features is time-consuming, labor-intensive, and costly, and can also be influenced by environmental factors. Thus, molecular markers have also been used for the identification of genetic diversity as an effective, accurate, and stable method. Currently, genome-wide single nucleotide polymorphisms (SNPs) using next-generation sequencing technology are commonly applied in genetic research on diverse plant species. This study aimed to establish an effective and high-throughput cultivar identification system for lettuce using core sets of SNP markers developed by genotyping by sequencing (GBS). GBS identified 17 877 high-quality SNPs for 90 commercial lettuce cultivars. Genetic differentiation analyses based on the selected SNPs classified the lettuce cultivars into three main groups. Core sets of 192, 96, 48, and 24 markers were further selected and validated using the Fluidigm platform. Phylogenetic analyses based on all core sets of SNPs successfully discriminated individual cultivars that have been currently recognized. These core sets of SNP markers will support the construction of a DNA database of lettuce that can be useful for cultivar identification and purity testing, as well as DUS testing in the plant variety protection system. Additionally, this work will facilitate genetic research to improve breeding in lettuce.

Bacterial wilt (Ralstonia solanacearum) is a devastating disease of cultivated tomato resulting in severe yield loss. Since chemicals are often ineffective in controlling this soil-borne pathogen, quantitative trait loci (QTL) conferring host resistance have been extensively explored. In this study, we investigated effects of ambient temperature and major QTL on bacterial wilt resistance in a collection of 50 tomato varieties. The five-week-old seedlings were inoculated using the race 1 (biovar 4 and phylotype I) strain of R. solanacearum and placed at growth chambers with three different temperatures (24 °C, 28 °C, and 36 °C). Disease severity was evaluated for seven days after inoculation using the 1–5 rating scales. Consistent bacterial wilt resistance was observed in 25 tomato varieties (R group) with the means of 1.16–1.44 for disease severity at all three temperatures. Similarly, 10 susceptible varieties with the means of 4.37–4.73 (S group) were temperature-independent. However, the other 15 varieties (R/S group) showed moderate levels of resistance at both 24 °C (1.84) and 28 °C (2.16), while they were highly susceptible with a mean of 4.20 at 36 °C. The temperature-dependent responses in the R/S group were supported by pairwise estimates of the Pearson correlation coefficients. Genotyping for three major QTL (Bwr-4, Bwr-6 and Bwr-12) found that 92% of varieties in the R group had ≥ two QTL and 40% of varieties in the R/S group had one or two QTL. This suggests that these QTL are important for stability of resistance against bacterial wilt at high ambient temperature. The resulting 25 varieties with temperature-independent resistance will be a useful resource to develop elite cultivars in tomato breeding programs.

Plant variety protection is essential for breeders' rights granted by the International Union for the Protection of New Varieties of Plants. Distinctness, uniformity, and stability (DUS) are necessary for new variety registration; to this end, currently, morphological traits are examined, which is time-consuming and laborious. Molecular markers are more effective, accurate, and stable descriptors of DUS. Advancements in next-generation sequencing technology have facilitated genome-wide identification of single nucleotide polymorphisms. Here, we developed a core set of single nucleotide polymorphism markers to identify cabbage varieties and traits of test guidance through clustering using the Fluidigm assay, a high-throughput genotyping system. Core sets of 87, 24, and 10 markers are selected based on a genome-wide association-based approach. All core markers could identify 94 cabbage varieties and determine 17 DUS traits. A genotypes database was validated using the Fluidigm platform for variety identification, population structure analysis, cabbage breeding, and DUS testing for plant cultivar protection.

Soil salinity is one of the major environmental stresses that restrict the growth and development of tomato (Solanum lycopersicum L.) worldwide. In Arabidopsis, the calcium signaling pathway mediated by calcineurin B-like protein 4 (CBL4) and CBL-interacting protein kinase 24 (CIPK24) plays a critical role in salt stress response. In this study, we identified and isolated two tomato genes similar to the Arabidopsis genes, designated as SlCBL4 and SlCIPK24, respectively. Bimolecular fluorescence complementation (BiFC) and pull-down assays indicated that SlCBL4 can physically interact with SlCIPK24 at the plasma membrane of plant cells in a Ca2+-dependent manner. Overexpression of SlCBL4 or superactive SlCIPK24 mutant (SlCIPK24M) conferred salt tolerance to transgenic tomato (cv. Moneymaker) plants. In particular, the SlCIPK24M-overexpression lines displayed dramatically enhanced tolerance to high salinity. It is notable that the transgenic plants retained higher contents of Na+ and K+ in the roots compared to the wild-type tomato under salt stress. Taken together, our findings clearly suggest that SlCBL4 and SlCIPK24 are functional orthologs of the Arabidopsis counterpart genes, which can be used or engineered to produce salt-tolerant tomato plants.

Bacterial wilt (BW), caused by the soil-borne Ralstonia solanacearum, is a major disease in cultivated tomato (Solanum lycopersicum L.). Host resistance provides an environment-friendly and cost-effective strategy to control this disease. To investigate quantitative trait loci (QTL) for BW resistance, we conducted a genome-wide association study (GWAS) in a core collection of 191 tomato varieties. The 51 K Axiom (R) tomato array was used for genotyping and 38,541 confident SNPs were filtered for GWAS. We evaluated disease severity of the core collection in two independent seedling assays following inoculation with race 1 of R. solanacearum. A total of eight marker-trait associations (MTAs) for BW resistance was detected at P < 0.0005 using the compressed mixed linear model. Of these, the MTAs on chromosomes 4 and 12 were consistently found in both disease assays and their corresponding QTL (Bwr-4 and Bwr-12) explained 8.36-18.28% of total phenotypic variations. We also detected Bwr-6 on chromosome 6 at P < 0.0005 (the 1st assay) and P < 0.01 (the 2nd assay). Further analysis with 37 commercial F-1 cultivars demonstrated that the resulting SNP markers for these major QTL were effective in identifying resistant tomatoes. The cultivars with two of three major QTL showed higher levels of resistance relative to those with a single QTL. In addition, four MTAs on chromosomes 1 and 8-10 were found from only one of two assays, suggesting the presence of environment-specific QTL. These results facilitate genetic dissection of BW resistance and marker-assisted selection for developing elite cultivars in tomato breeding programs.

Plant variety identification is essential for the official registration of new cultivars and for variety protection. It is therefore imperative to have rapid and highly reliable methods for plant variety identification. In this study, a core 96-SNP set optimized for use with Fluidigm EP1TM assay was developed to facilitate cultivar identification in cucumber. Genotyping-by-sequencing (GBS) of 88 F1 hybrids comprising nine cultivar groups (Korean Gasi, Korean Nakhap, Korean Baekdadagi, Japanese Gasi, Chinese Gasi, Chinese Baekdadagi, Southeast Asian slice, European slice, and pickle groups) was carried out, and a total of 10,996 high-quality SNPs were generated. Population structure, principle component analysis, and hierarchical clustering indicated that the nine cultivar groups were clearly divided into four subpopulations (subpopulation G for Gasi type, B for Baekdadagi type, N for Nakhap type, and E for slice and pickle types). Population differentiation measures based on pairwise FST values indicated that the closest relationship (0.124) was between subpopulations B and N and subpopulations E (0.140) and G, while subpopulations B and E were the most clearly distinct from each other (0.208). The metrics of genetic differentiation measured by AMOVA also indicated that significant genetic division exists among the subpopulations, while variation among cultivars within each subpopulation is extremely low, indicating high genetic exchange within the subpopulations. By applying filtering criteria to the SNPs, including FST and linkage disequilibrium decay values, 240 SNPs were filtered from the original 10,996 for use with a Fluidigm assay, from which a core 96-SNP set was obtained. This set demonstrated high reproducibility and discrimination power. Hierarchical clustering confirmed that the core 96-SNP set could distinguish all 88 cultivars and delineate them clearly according to their population structures. A Mantel test based on 10,996 SNPs and 37 traits revealed a high level of correlation (r = 0.57) between molecular and morphological distance. Our core 96-SNP set is not only suitable for generating signature profiles of released cucumber cultivars, but also represents a promising supplement to morphological trait-based distinctness, uniformity, and stability testing for cultivar identification.

Genetic diversity analysis and cultivar identification were performed using a core set of single nucleotide polymorphisms (SNPs) in cucumber (Cucumis sativus L.). For the genetic diversity study, 280 cucumber accessions collected from four continents (Asia, Europe, America, and Africa) by the National Agrobiodiversity Center of the Rural Development Administration in South Korea and 20 Korean commercial F1 hybrids were genotyped using 151 Fluidigm SNP assay sets. The heterozygosity of the SNP loci per accession ranged from 4.76 to 82.76%, with an average of 32.1%. Population genetics analysis was performed using population structure analysis and hierarchical clustering (HC), which indicated that these accessions were classified mainly into four subpopulations or clusters according to their geographical origins. The subpopulations for Asian and European accessions were clearly distinguished from each other (FST value = 0.47), while the subpopulations for Korean F1 hybrids and Asian accessions were closely related (FST = 0.34). The highest differentiation was observed between American and European accessions (FST = 0.41). Nei’s genetic distance among the 280 accessions was 0.414 on average. In addition, 95 commercial F1 hybrids of three cultivar groups (Baekdadagi-, Gasi-, and Nakhap-types) were genotyped using 82 Fluidigm SNP assay sets for cultivar identification. These 82 SNPs differentiated all cultivars, except seven. The heterozygosity of the SNP loci per cultivar ranged from 12.20 to 69.14%, with an average of 34.2%. Principal component analysis and HC demonstrated that most cultivars were clustered based on their cultivar groups. The Baekdadagi- and Gasi-types were clearly distinguished, while the Nakhap-type was closely related to the Baekdadagi-type. Our results obtained using core Fluidigm SNP assay sets provide useful information for germplasm assessment and cultivar identification, which are essential for breeding and intellectual right protection in cucumber.

Genome-wide association study (GWAS) is effective in identifying favorable alleles for traits of interest with high mapping resolution in crop species. In this study, we conducted GWAS to explore quantitative trait loci (QTL) for eight fruit traits using 162 tomato accessions with diverse genetic backgrounds. The eight traits included fruit weight, fruit width, fruit height, fruit shape index, pericarp thickness, locule number, fruit firmness, and brix. Phenotypic variations of these traits in the tomato collection were evaluated with three replicates in field trials over three years. We filtered 34,550 confident SNPs from the 51 K Axiom ® tomato array based on < 10% of missing data and > 5% of minor allele frequency for association analysis. The 162 tomato accessions were divided into seven clusters and their membership coefficients were used to account for population structure along with a kinship matrix. To identify marker-trait associations (MTAs), four phenotypic data sets representing each of three years and combined were independently analyzed in the multilocus mixed model (MLMM). A total of 30 significant MTAs was detected over data sets for eight fruit traits at P < 0.0005. The number of MTA per trait ranged from one (brix) to seven (fruit weight and fruit width). Two SNP markers on chromosomes 1 and 2 were significantly associated with multiple traits, suggesting pleiotropic effects of QTL. Furthermore, 16 of 30 MTAs suggest potential novel QTL for eight fruit traits. These results facilitate genetic dissection of tomato fruit traits and provide a useful resource to develop molecular tools for improving fruit traits via marker-assisted selection and genomic selection in tomato breeding programs.

Single nucleotide polymorphisms (SNPs) have been widely used as a molecular marker in crop species with advances in next-generation sequencing technology. The use of SNP markers for variety identification is a cost-effective strategy to protect breeder’s intellectual property rights. This study was conducted to identify genome-wide SNPs and develop core marker sets for assessing genetic variations in commercial tomato cultivars. A total of 10,615 confident SNPs was generated from genotyping by sequencing for 48 F1 cultivars representing four market classes (large-fruited fresh market, cherry, grape, and rootstock). Of these, 288 SNPs across 12 chromosomes were selected to genotype additional 94 F1 cultivars using the Fluidigm assay and 224 SNPs showed reliable polymorphisms in 91 F1 cultivars. Both model-based and hierarchical clustering analyses with these markers found that the large-fruited fresh market cultivars were significantly distinct from the cherry and grape cultivars. In addition, the cherry and grape cultivars showed higher levels of genetic diversity relative to the large-fruited fresh market cultivars. The 224 SNP markers were also effective in differentiating all 139 F1 cultivars and Heinz 1706 (an inbred for the tomato reference genome). Of the five subsets, the 192 and 96 markers identified all of these tomato cultivars, respectively. Furthermore, the other three subsets of 48, 24, and 12 markers showed 80.0–93.6 % of identification rates. These results demonstrate that all five subsets of SNP markers will be useful in developing a high-throughput DNA barcoding system for variety identification in commercial tomato cultivars.

The Oriental melon is an important delicious fruit crop across East Asia. Single-nucleotide polymorphisms (SNPs) are considered to be a useful genotyping tool both to detect genetic diversity and to protect breeder rights. This study used genotyping-by-sequencing (GBS) to detect genome-wide SNPs by analyzing 48 commercial Oriental melon varieties to generate 5640 filtered SNPs. Based on the high polymorphism information content (PIC), genetic and physical distances, a subset of 192 SNPs was selected as putative SNPs for validation via the Fluidigm JunoTM system. Of these, 164 SNPs were successfully validated in 87 Oriental melon varieties with a validation ratio of 85.41 %. Furthermore, these 87 Oriental melon varieties were classified into ten distinct groups, based on 164 SNP markers. Therefore, these large set of SNP markers detected here has several application, such as genetic diversity studies, varietal identification and marker-assisted selection (MAS) in the Oriental melon. Genome-wide associations (GWAS) analyses detected significant 18 SNPs associated with various morphological traits, including two novel SNPs for sex expression on chromosomes 1 and 8 that were not colocalized with previous studies. The four potential candidate genes such as MELO3C015898, MELO3C015904, MELO3C024563, and MELO3C024565 were predicted within the GWAS-SNPs regions for sex expression in the Oriental melon. Hence, identification of these candidate genes has provided the foundation to study the molecular genetic mechanism of sex expression trait in the Oriental melon.

Three pumpkin species Cucurbita maxima, C. moschata, and C. pepo are commonly cultivated worldwide. To identify genome-wide SNPs in these cultivated pumpkin species, we collected 48 F1 cultivars consisting of 40 intraspecific hybrids (15 C. maxima, 18 C. moschata, and 7 C. pepo) and 8 interspecific hybrids (C. maxima x C. moschata). Genotyping by sequencing identified a total of 37,869 confident SNPs in this collection. These SNPs were filtered to generate a subset of 400 SNPs based on polymorphism and genome distribution. Of the 400 SNPs, 288 were used to genotype an additional 188 accessions (94 F1 cultivars, 50 breeding lines, and 44 landraces) with a SNP array-based platform. Reliable polymorphisms were observed in 224 SNPs (78.0%) and were used to assess genetic variations between and within the four predefined populations in 223 cultivated pumpkin accessions. Both principal component analysis and UPGMA clustering found four major clusters representing three pumpkin species and interspecific hybrids. This genetic differentiation was supported by pairwise Fst and Nei's genetic distance. The interspecific hybrids showed a higher level of genetic diversity relative to the other three populations. Of the 224 SNPs, five subsets of 192, 96, 48, 24, and 12 markers were evaluated for variety identification. The 192, 96, and 48 marker sets identified 204 (91.5%), 190 (85.2%), and 141 (63.2%) of the 223 accessions, respectively, while other subsets showed <25% of variety identification rates. These SNP markers provide a molecular tool with many applications for genetics and breeding in cultivated pumpkin.

Tomato yellow leaf curl virus (TYLCV) is a disease causing serious yield reduction of tomato in the world. An effective control strategy for this virus is required for stable tomato production. Six resistant genes, Ty-1 to Ty-6 were previously identified in several wild species. In this study, we investigated novel sequence variations associated with Ty-2 and Ty-3 resistance to develop gene-based or functional markers suitable for improving TYLCV resistance in tomato breeding programs. Two resistant and susceptible inbred varieties were used for sequence analysis of each gene. For a Ty-2 candidate gene, we found a total of 39 single nucleotide polymorphisms (SNPs) and seven insertion/deletions (InDels). Of these, three SNPs were derived from coding sequences but were synonymous mutations. The SNPs and InDels from intron sequences were not responsible for alternative splicing in this gene. In addition, three large InDels of 50 bp, 42 bp, and 15 bp were found in upstream sequences, which are located at 688 bp, 611 bp, and 499 bp from 5' UTR. Using the 50 bp and 42 bp InDels, a molecular marker was developed for Ty-2 selection. Nine non-synonymous SNPs and a 12 bp InDel were detected on coding sequences of the Ty-3 gene. Three of these (two SNPs and an InDel) were used to develop cleaved amplified polymorphic sequence (CAPS) markers. The resulting markers for Ty-2 and Ty-3 selection were validated using 18 commercial F1 cultivars, nine inbred lines, and three wild species with known phenotypes against TYLCV. Furthermore, these markers were used for genetic analysis of Ty-2 and Ty-3 resistance in a collection of 171 germplasm. The InDel and CAPS markers will be a useful resource to facilitate marker-assisted selection for pyramiding Ty-2 and Ty-3 in elite tomato varieties.

The reporting of effect sizes in social-scientific articles is becoming increasingly widespread and encouraged, particularly when research and experimental designs are involved. Two widely used experimental designs where the uniqueness of estimation can be guaranteed, the cell means and treatment effect models, are first introduced. Then, under those two experimental designs, it is proposed to explore the distributions of the effect sizes such as eta-squared ($$\eta ^2$$), omega-squared ($$\omega ^2$$) and Cohen’s $$f^2$$. For each effect size in every experimental design, it is found that the distribution or transformation of distribution belongs to the non-central Beta family. Confidence intervals for effect size in the corresponding hypothesis are obtained by applying the results from the distributions combined with the probability limits. Based on the first two moments of distributions, which lead to the mean and standard deviation, a simulation study is given to help better understand the behaviour of $$\eta ^2$$ at different sample sizes and group numbers. This provides a reference for choosing sample and group sizes in experimental design. An application is reported for a psychological data set in order to illustrate how effect sizes perform in practice.