More markers are required to cover through the genome of S

pimpinellifolium

The observed and expected heterozygosity of this population were 0.0761 and 0.2786, respectively, slightly higher than those in previous researches (Blanca et al., 2012; Blanca et al., 2015). Since S. pimpinellifolium was detected with up to a 40%

outcrossing rate (Rick et al., 1977) and demonstrated high genetic variation, it is expected to cause rapid LD decay. In this study, LD decay was within 18 Kb throughout the genome, which was much shorter than cultivated tomatoes (Bauchet et al., 2017;

Sim et al., 2012). However, to put at least one SNP marker within each of 18 Kb intervals in this genome, the 900-Mb tomato genome would require at least 50,000 markers to fulfill QTL detection in GWAS. Therefore, acquiring many SNPs using different methods is essential to conduct a GWAS in the S. pimpinellifolium population.

Here, we proposed three possible approaches to increase markers. One is to increase the sample size evenly for each subpopulation (Brachi, Morris, & Borevitz, 2011). Since approximately 64% of alleles were rare in this population, the augmentation of the subpopulation size may adjust rare alleles to common alleles, potentially increasing the SNPs without extending coverage. One is to construct DNA libraries with a frequently cutting restriction enzyme. This approach can be simulated and optimized in silico to

balance sequencing resource between sample sizes and sequencing coverage (Shirasawa et al., 2016). Another is exome sequencing, a selective genome sequencing technology that selects desired sequencing regions by the hybridization of designed probes (Kaur &

Gaikwad, 2017). Based on tomato genome sequence information, such as the gene model or EST database, one could design different sets of probes to limit sequencing regions (Ruggieri et al., 2017). Given the approximately 110 Mb total gene length in the ITAG2.4 gene model, the potential coverage could reach 12% and all target the gene region. This exome sequencing strategy may be able to increase SNPs without increasing population size.

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