Abstract
Seedling growth is an important factor for direct seeding of rice. However, the genetic and transcriptomic factors involved in this process are largely unknown. In this study, transcripts affecting shoot weight were identified in rice (Oryza sativa L.) using RNA sequencing (RNA-Seq) data from 20 backcrossed inbred lines (BILs) and their parental cultivars. The selection frequency of the genes for the regression model was determined using repeated analysis of random subsets of the transcriptome. The qLTG3-1gene, controlling low-temperature germinability, and short grain 1 gene (SG1), known to decrease organ elongation, showed high frequency. The quantitative trait loci (QTLs) analysis performed for BILs revealed that qLTG3-1 was included in the QTLs for shoot weight but SG1 was not. No nucleotide polymorphisms were found in the coding region of SG1 in either of the parental cultivars. Quantitative real-time PCR showed that SG1 expression was negatively correlated with shoot weight for all 104 BILs analyzed in this study. Expression QTL (eQTLs) analysis showed an eQTL for SG1 expression located in the same region as the QTL for shoot weight. However, no eQTLs were detected on the same chromosome as SG1, suggesting that nucleotide polymorphisms around the gene do not affect its expression in analyzed growth stage. Overall, these results indicate that RNA-Seq is a useful tool for identifying transcripts that can be related to seedling growth rate.
Highlights
Direct seeding of rice (Oryza sativa L.) is less laborious and costly than transplanting but has some limitations
To identify the transcripts associated with the initial growth rate, the parental cultivars and 20 backcrossed inbred lines (BILs) with varying shoot weights were analyzed by RNA sequencing (RNA-Seq) (Figure 1C)
It has been shown that short grain 1 gene (SG1) upregulation decreases organ elongation (Nakagawa et al, 2012), it was not clear if SG1 expression differed among natural rice lines
Summary
Direct seeding of rice (Oryza sativa L.) is less laborious and costly than transplanting but has some limitations. Seedling growth rate and other agronomical traits have. Selection of Transcripts Using RNA-Seq been suggested to be regulated by complex genetic and environment interactions, it is important to elucidate the genetic factors involved in enhancing these traits, as this will allow selecting preferable traits during rice breeding to improve the efficacy of direct seeding. One tool used to identify genetic factors affecting agronomical traits is quantitative trait loci (QTLs) analysis, which was previously performed to evaluate traits affecting seedling vigor (Iwata et al, 2010; Abe et al, 2012; Yano et al, 2012; Fukuda et al, 2014). QTLs analysis is laborious, time consuming, and only reveals genomic mutations; in some cases, it involves significant genetic bias
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