Pedigree genome data of an early-matured Geng/japonica glutinous rice mega variety Longgeng 57.

By using PacBio HiFi technology, we produced over 700 Gb of long-read sequencing (LRS) raw data; and by using Illumina paired-end whole-genome shotgun (WGS) sequencing technology, we generated more than 70 Gb of short-read sequencing (SRS) data. With LRS data, we assembled one genome and then generate a set of annotation data for an early-matured Geng/japonica glutinous rice mega variety genome, Longgeng 57 (LG57), which carries multiple elite traits including good grain quality and wide adaptability. Together with the SRS data from three parents of LG57, pedigree genome variations were called for three representative types of genes. These data sets can be used for deep variation mining, aid in the discovery of new insights into genome structure, function, and evolution, and help to provide essential support to biological research in general.

Identification of reliable QTLs and designed QTL breeding for grain shape and milling quality in the reciprocal introgression lines in rice.

Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers' final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.

Comparison between Acid Digestion (ICP-OES) and X-ray Fluorescence (XRF) Spectrometry for Zinc Concentration Determination in Rice (Oryza sativa L.).

The determination of mineral concentrations in rice grain samples is crucial for analyzing their nutritional content. Most mineral content analysis techniques depend on inductively coupled plasma (ICP) spectrometry and are often complicated, expensive, time-consuming, and laborious. Recently, the handheld X-ray fluorescence (XRF) spectrometer has been randomly used in earth sciences; however, it is hardly practiced in quantifying mineral content in rice samples. In this research, the reliability of XRF results was compared with that of the ICP-OES to determine zinc (Zn) concentration in rice (Oryza sativa L.). Approximately 200 dehusked rice samples and four known high-Zn samples were analyzed using both XRF and ICP-OES techniques. The concentrations of Zn were recorded using the XRF technique and then correlated with the ICP-OES results. The results indicated a high positive relationship between two methods, with R2 = 0.83, p = 0.000, and the Pearson correlation value of 0.91 at the level of 0.05. This work demonstrates the potential of XRF as a reliable and low-cost as well as an alternative technique to ICP-OES methods for determining Zn content in rice as it allows the analysis of a greater number of samples in a short period at a considerably low price.