Identification of a novel candidate gene for rolled leaf in rice

Lee, Yoon Kyung; Woo, Mi-Ok; Lee, Dongryung; Lee, Gileung; Kim, Backki; Koh, Hee‐Jong

doi:10.1007/s13258-016-0451-1

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…Finally, we included only 42 RL genes in our analysis for which locus IDs were available. As a result, we confined all of our analyses with only those 42 RL genes: OsACL1 (Li et al ., 2010), OsADL1 (Hibara et al ., 2009), OsAGO1a (Li et al ., 2013a), OsAGO7 (Shi et al ., 2007), OsARF18 (Huang et al ., 2016), OsARVL4 (Wang et al ., 2016), OsAS2 (Ma et al ., 2009), OsCFL1 (Wu et al ., 2011), OsDCL1 (Liu et al ., 2005), OsHB4 (Zhang et al ., 2018), OsI_14279 (Wang et al ., 2017), OsLBD3-7 (Li et al ., 2016), OsLC2 (Zhao et al ., 2010), OsLRRK1 (Zhou et al ., 2018), OsMYB103L (Yang et al ., 2014), OsNAL1 (Qi et al ., 2008), OsNAL11 (Wu et al ., 2016; Zhao et al ., 2017), OsNAL2 (Cho et al ., 2013), OsNAL3 (Cho et al ., 2013), OsNAL7 (Fujino et al ., 2008), OsNAL9 (Li et al ., 2013b), OsNRL1 (Hu et al ., 2010; Wu et al ., 2010), OsNRL4 (Liang et al ., 2016), OsREL1 (Chen et al ., 2015), OsREL2 (Yang et al ., 2016), OsRFS (Cho et al ., 2018; Yoshimura et al ., 1997), OsRL14 (Fang et al ., 2012), OsRL15 (Lee et al ., 2016), OsRL16 (Liu et al ., 2015), OsRL9 (Yan et al ., 2008), OsRRK1 (Ma et al ., 2017), OsRoc5 (Zou et al ., 2011), OsSCL1 (Shen, 2011), OsSFL1 (Alamin et al ., 2017), OsSLL2 (Zhang et al ., 2015), OsSND2 (Ye et al ., 2018), OsSRL1 (Xiang et al ., 2012), OsSRL2 (Liu et al ., 2016), OsSRS5 (Segami et al ., 2012), OsYABBY1 (Dai et al ., 2007), OsYABBY6 (Xia et al ., 2017) and OsZHD1 (Xu et al ., 2014). Then we downloaded the genomic sequence, coding sequence (CDS) and protein sequence from the Rice Genome Annotation Project database () for each of the 42 RL genes included in our study.…”

Section: Methodsmentioning

confidence: 99%

“…Finally, we included only 42 RL genes in our analysis for which locus IDs were available. As a result, we confined all of our analyses with only those 42 RL genes: OsACL1 (Li et al, 2010), OsADL1 (Hibara et al, 2009), OsAGO1a (Li et al, 2013a), OsAGO7 (Shi et al, 2007), OsARF18 (Huang et al, 2016), OsARVL4 (Wang et al, 2016), OsAS2 (Ma et al, 2009), OsCFL1 (Wu et al, 2011), OsDCL1 (Liu et al, 2005) (Chen et al, 2015), OsREL2 (Yang et al, 2016), OsRFS (Cho et al, 2018;Yoshimura et al, 1997), OsRL14 (Fang et al, 2012), OsRL15 (Lee et al, 2016), OsRL16 (Liu et al, 2015), OsRL9 (Yan et al, 2008), OsRRK1 (Ma et al, 2017), OsRoc5 (Zou et al, 2011), OsSCL1 (Shen, 2011), OsSFL1 (Alamin et al, 2017), OsSLL2 (Zhang et al, 2015), OsSND2 (Ye et al, 2018), OsSRL1 (Xiang et al, 2012), OsSRL2 (Liu et al, 2016), OsSRS5 (Segami et al, 2012), OsYABBY1 (Dai et al, 2007), OsYABBY6 (Xia et al, 2017) and OsZHD1 (Xu et al, 2014). Then we downloaded the genomic sequence, coding sequence (CDS) and protein sequence from the Rice Genome Annotation Project database (http://rice.…”

Section: Data Collection Procedures For Rl Related Genesmentioning

confidence: 99%

See 1 more Smart Citation

Bioinformatics studies on structures, functions and diversifications of rolling leaf related genes in rice (Oryza sativaL.)

Alam

Al-Amin

Sultana

et al. 2020

Plant Genet. Resour.

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Leaf morphology of crop plants has significant value in agronomy. Leaf rolling in rice plays a vital role to increase grain yield. However, collective information on the rolling leaf (RL) genes reported to date and different comparative bioinformatics studies of their sequences are still incomplete. This bioinformatics study was designed to investigate structures, functions and diversifications of the RL related genes reported till now through several studies. We performed different comparative and functional analyses of the selected 42 RL genes among 103 RL genes using different bioinformatics techniques including gene structure, conserved domain, phylogenetic, gene ontology (GO), transcription factor (TF), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein–protein network. Exon-intron organization and conserved domain analysis showed diversity in structures and conserved domains of RL genes. Phylogenetic analysis classified the proteins into five major groups. GO and TF analyses revealed that regulation-related genes were remarkably enriched in biological process and 10 different TF families were involved in rice leaf rolling. KEGG analysis demonstrated that 14 RL genes were involved in the KEGG pathways, among which 50% were involved in the metabolism pathways. Of the selected RL proteins, 55% proteins were non-interacting with other RL proteins and OsRL9 was the most interacting RL protein. These results provide important information regarding structures, conserved domains, phylogenetic revolution, protein–protein interactions and other genetic bases of RL genes which might be helpful to the researchers for functional analysis of new candidate RL genes to explore their characteristics and molecular mechanisms for high yield rice breeding.

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Section: Methodsmentioning

confidence: 99%

Section: Data Collection Procedures For Rl Related Genesmentioning

confidence: 99%

Bioinformatics studies on structures, functions and diversifications of rolling leaf related genes in rice (Oryza sativaL.)

Alam

Al-Amin

Sultana

et al. 2020

Plant Genet. Resour.

View full text Add to dashboard Cite

show abstract

“…Numerous studies confirmed that mutants change the number, size, and pattern of small veins, bulliform cells, parenchyma cells, and mesophyll cells, as well as vascular bundles, which leads to leaf rolling. Further, these mutations subsequently alter the leaf angle at later stages, such that a lower level of leaf area/unit land degrades the high photosynthesis rate [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Non-Invasive Morphological Characterization of Rice Leaf Bulliform and Aerenchyma Cellular Regions Using Low Coherence Interferometry

Kim

et al. 2019

Applied Sciences

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Non-invasive investigation of rice leaf specimens to characterize the morphological formation and particular structural information that is beneficial for agricultural perspective was demonstrated using a low coherence interferometric method called swept source optical coherence tomography (SS-OCT). The acquired results non-invasively revealed morphological properties of rice leaf, such as bulliform cells; aerenchyma, parenchyma, and collenchyma layer; and vascular bundle. Beside aforementioned morphologic characteristics, several leaf characteristics associated with cytological mechanisms of leaf rolling (leaf inclination) were examined for the pre-identification of inevitable necrosis and atrophy of leaf tissues by evaluating acute angle information, such as angular characteristics of the external bi-directional angles between the lower epidermis layer and lower mid-vein, and internal angle of lower mid-vein. To further assist the pre-identification, acquired cross-sections were employed to enumerate the small veins of each leaf specimen. Since mutants enlarge leaf angles due to increased cell division in the adaxial epidermis, healthy and abnormal leaf specimens were morphologically and quantitatively compared. Therefore, the results of the method can be used in agriculture, and SS-OCT shows potential as a rigorous investigation method for selecting mutant infected rice leaf specimens rapidly and non-destructively compared to destructive and time consuming gold-standard methods with a lack of precision.

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Morphological, physiological and genetic analyses of an upward-curling leaf mutant in Brassica napus L.

Faisal

Guo

et al. 2020

Acta Physiol Plant

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Identification of a novel candidate gene for rolled leaf in rice

Cited by 3 publications

References 25 publications

Bioinformatics studies on structures, functions and diversifications of rolling leaf related genes in rice (Oryza sativaL.)

Bioinformatics studies on structures, functions and diversifications of rolling leaf related genes in rice (Oryza sativaL.)

Non-Invasive Morphological Characterization of Rice Leaf Bulliform and Aerenchyma Cellular Regions Using Low Coherence Interferometry

Morphological, physiological and genetic analyses of an upward-curling leaf mutant in Brassica napus L.

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