Abstract
Recent next generation sequencing-driven mass production of genomic data and multi-omics-integrated approaches have significantly contributed to broadening and deepening our knowledge on the molecular system of living organisms. Accordingly, translational genomics (TG) approach can play a pivotal role in creating an informational bridge between model systems and relatively less studied plants. This review focuses mainly on addressing recent advancement in omics-related technologies, a diverse array of bioinformatic resources and potential applications of TG for the crop breeding. To accomplish above objectives, information on omics data production, various DBs and high throughput technologies was collected, integrated, and used to analyze current status and future perspectives towards omics-assisted crop breeding. Various omics data and resources have been organized and integrated into the databases and/or bioinformatic infrastructures, and thereby serve as the ome’s information center for cross-genome translation of biological data. Although the size of accumulated omics data and availability of reference genomes are different among plant families, translational approaches have been actively progressing to access particular biological characteristics. When multi-layered omics data are integrated in a synthetic manner, it will allow providing a stereoscopic view of dynamic molecular behavior and interacting networks of genes occurring in plants. Consequently, TG approach will lead us to broader and deeper insights into target traits for the plant breeding. Furthermore, such systems approach will renovate conventional breeding programs and accelerate precision crop breeding in the future.
Highlights
What is ‘translational genomics (TG)’? And how can genetic and/or genomic information be translated across diverse species? TG is possible on the basis of two assumptions
This review mainly focuses on translational genomics and other omics-derived approaches in plants and crops, including current status of recently advanced technologies for massive production of omics data, representative public resources of databases, and strategy and perspectives of TG applications for the crop breeding in the future
Out of 140 genome accessions, rice (Oryza sativa) genome accounts for the highest (14 accessions), followed by corn (Zea mays, 7 accessions). These reference or draft genome data have played a central role in producing and enriching other types of omics information; direct whole genome resequencing (WGR) for main purposes of discovering nucleotide variations followed by genome-wide association study (GWAS) and fabrication of SNP arrays, RNA sequencing for transcriptome analysis, genotyping by sequencing (GBS), methylome profiling for epigenomic analyses, small/ long non-coding RNA profiling and Chip-seq analysis for DNA–protein interactions (Mochida and Shinozaki 2011)
Summary
What is ‘translational genomics (TG)’? And how can genetic and/or genomic information be translated across diverse species? TG is possible on the basis of two assumptions. Out of 140 genome accessions, rice (Oryza sativa) genome accounts for the highest (14 accessions), followed by corn (Zea mays, 7 accessions) These reference or draft genome data have played a central role in producing and enriching other types of omics information; direct whole genome resequencing (WGR) for main purposes of discovering nucleotide variations followed by genome-wide association study (GWAS) and fabrication of SNP arrays, RNA sequencing for transcriptome analysis, genotyping by sequencing (GBS), methylome profiling for epigenomic analyses, small/ long non-coding RNA profiling and Chip-seq analysis for DNA–protein interactions (Mochida and Shinozaki 2011). Once sufficient amount data for the nucleotide variation are obtained, millions of SNPs and InDels can be fabricated into DNA chips, for representative examples Illumina Infinium HD (https://sapac.illumina.com/science/technology/) and Affymetrix Axiom (http://www.affymetrix.com/support/technical/) These array-based analytical platforms can be applied to the genome-wide analyses, such as GWAS, genotyping-by-sequencing (GBS) and QTL mapping. Number of accessions Sequencing depth Nucleotide variations Related traits and discovered loci
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