ABSTRACT
Crop genetics helps to identify valuable genes for crop improvement. One significant usage of crop genomics is identifying genomic variation associated with traits. Various studies have discussed using multiple high-throughput sequencing technologies for allele mining. Advancements in sequencing technology have led to the identification of single nucleotide polymorphism (SNP); single sequence repeat (SSR) within multiple plant species. In this chapter, we overview the critical high-throughput techniques and various computational methods used to identify alleles related to tomato’s fundamental traits and functional genes. Some examples indicate the use of machine learning and multi-omics profiles for predicting stable yields in tomato species are summarized. A detailed description of alleles associated with plant growth, fruit quality, and fruit ripening in tomatoes is also discussed.
