Abstract
The early-matured japonica (Geng) rice variety, Suijing18 (SJ18), carries multiple elite traits including durable blast resistance, good grain quality, and high yield. Using PacBio SMRT technology, we produced over 25 Gb of long-read sequencing raw data from SJ18 with a coverage of 62×. Using Illumina paired-end whole-genome shotgun sequencing technology, we generated 59 Gb of short-read sequencing data from SJ18 (23.6 Gb from a 200 bp library with a coverage of 59× and 35.4 Gb from an 800 bp library with a coverage of 88×). With these data, we assembled a single SJ18 genome and then generated a set of annotation data. These data sets can be used to test new programs for variation deep mining, and will provide new insights into the genome structure, function, and evolution of SJ18, and will provide essential support for biological research in general.
Highlights
Background & SummaryAs the leading staple food resource for humans, rice has been adopted as an important model organism for biological research, especially for monocots
It has become clear that one single genome is not enough to represent the huge amount of variation in rice genomes
In addition to the previously published de novo assemblies, including 93–11, PA64S, IR64, DJ1232, HR-123, and Swarna[4], three new sets of indica/Xian genomes have been released with the aid of third-generation sequencing technology for variation deep mining, including MH63RS1, ZS97RS15, and R4986
Summary
As the leading staple food resource for humans, rice has been adopted as an important model organism for biological research, especially for monocots. In addition to the previously published de novo assemblies, including 93–11 (indica/Xian, two-line hybrid restorer), PA64S (admixture type with roughly 55% indica/Xian, 25% japonica/Geng, and 20% javanica, a two-line hybrid sterile line), IR64 (indica/Xian), DJ123 (aus type indica/Xian)[2], HR-12 (indica/Xian)[3], and Swarna (indica/Xian)[4], three new sets of indica/Xian genomes have been released with the aid of third-generation sequencing technology for variation deep mining, including MH63RS1 (indica/Xian, three-line hybrid restorer), ZS97RS1 (indica/Xian, three-line hybrid maintainer)[5], and R498 (indica/Xian, three-line hybrid restorer)[6] These data sets have enriched our knowledge of the genomic variations of indica/Xian rice. With the resources and data generated in this study, were we able assemble de novo a good quality genome sequence for early-matured japonica/Geng, and were able to provide the scientific community with data to advance biological research at the genomic level, especially for the deep mining of genetic variations, and provided more information for genome-based molecular breeding of crops
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