Loci and Natural Alleles for Low-Nitrogen-Induced Growth Response Revealed by the Genome-Wide Association Study Analysis in Rice (Oryza sativa L.)

Lv, Yang; Ma, Jie; Wang, Yueying; Wang, Quan; Lu, Xueli; Hu, Haitao; Qian, Qian; Guo, Longbiao; Shang, Lei

doi:10.3389/fpls.2021.770736

Cited by 6 publications

(9 citation statements)

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“…Seedlings of barren-tolerant wild soybean are more adaptive to phosphorus stress than common wild soybean, which absorb more phosphorus by increasing root length, and MYB61 is a key transcription factor for resistance to low phosphorus stress in barren-tolerant wild soybean [36]. Rice MYB61 may regulate the efficiency of crop nitrogen usage, which in turn affects rice growth and yield [37]. TCP (teosinte branched1/ccincinnata/proliferating cell factor) is a set of specific transcription factors plays an important role in plant growth and development, and PCF3 is a TCP family transcription factor [38].…”

Section: Discussionmentioning

confidence: 99%

WGCNA Identifies a Comprehensive Gene Co-Expression Network Associated with Development in autotetraploid potato tissues

Li¹,

Wang²,

Wang³

2023

Preprint

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The formation and development of potato tissues and organs is a complex process regulated by a variety of genes and environmental factors. However, the regulatory mechanisms underlying the growth and development are still unclear. In this study, we used autotetraploid potato JC14 as experimental subject to analyze the transcriptome of root, stem and leaf at seedling, tuber formation and tuber expansion stages to explore the spatio-temporal expression pattern of genes and genetic development characteristics. The results identified thousands of differentially expressed genes and KEGG pathway enrichment analysis showed that these genes were mainly involved in defense response and carbohydrate metabolism pathways. A total of 12 co-expressed Gene modules were identified by Weighted Gene Co-expression Network Analysis (WGCNA), and 4 modules were screened out with the highest correlation with potato stem developmental traits. Core genes in the network were further investigated and functionally annotated by computing the connectivity of genes within the module. The results unveiled number of hub genes in stems at different developmental stages, including carbohydrate metabolism related genes, the defense response related genes, and transcription factors. These findings provide important leads for further understanding of the molecular regulation and genetic mechanisms of potato tissue development.

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Section: Discussionmentioning

confidence: 99%

WGCNA Identifies a Comprehensive Gene Co-Expression Network Associated with Development in autotetraploid potato tissues

Li¹,

Wang²,

Wang³

2023

Preprint

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“…Unraveling the genetic factors for salt tolerance in plants is a challenging endeavor. Association mapping emerged as a useful tool to identify alleles and QTLs associated with agronomically important traits (Thomson et al, 2010;Lv et al, 2021;Wei et al, 2021b). The collection of a wide range of germplasm resources with different genetic backgrounds is an essential step in association analysis.…”

Section: Discussionmentioning

confidence: 99%

“…The significance threshold was calculated using the formula "−log10 (1/the effective number of independent SNPs)." The threshold was set at −log P = 5 to identify significant association signals (Gao et al, 2020;Lv et al, 2021), and the candidate genes were detected as those within 200 kb of the significant association signals (Yu et al, 2017) using a mixed linear model (MLM) model (Kang et al, 2010). Plots that represented the GWAS results (Manhattan and Quantile-Quantile plots) were generated using the package qqman in R 3.4.2 (Turner, 2014).…”

Section: Genome-wide Association Studymentioning

confidence: 99%

“…Additionally, rice domestication could provide a reliable basis to identify favorable variants for modern breeding (Meyer et al, 2016). In our previous studies, we analyzed the phenotype of 225 rice variety population under normal and low nitrogen conditions and conducted GWAS analysis to obtain four candidate genes (Lv et al, 2021). In this study, we analyzed the salt resistance of 191 rice varieties, performed a GWAS analysis, and combined this information with evaluation scoring results for salt tolerance, genetic differentiation and transcriptomic analysis to identify the genetic underlying basis for salt resistance in rice.…”

Section: Introductionmentioning

confidence: 99%

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Combining GWAS, Genome-Wide Domestication and a Transcriptomic Analysis Reveals the Loci and Natural Alleles of Salt Tolerance in Rice (Oryza sativa L.)

Hua

et al. 2022

Front. Plant Sci.

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Soil salinity poses a serious threat to the sustainable production of rice (Oryza sativa L.) throughout the world. Thus, the detection of loci and alleles responsible for salt tolerance is fundamental to accelerating the improvement of rice and producing the resilient varieties that will ensure future harvests. In this study, we collected a set of 191 mini-core rice populations from around the world, evaluated their salt tolerance based on plant growth and development phenotypes at the seedling stage, and divided a standard evaluation score (SES) of visual salt injury into five different grades. We used ∼3.82 million single nucleotide polymorphisms (SNPs) to identify 155 significant SNPs and 275 genes associated with salt sensitivity based on a genome-wide association study (GWAS) of SES. In particular, two candidate genes, ZFP179 and OsDSR2, were associated with salt tolerance, and OsHKT1;1 was co-detected in the entire GWAS of all the panels and indica. Additionally, we investigated the transcriptional changes in cultivars 93-11 and PA64s under normal and salinity stress conditions and found 517 co-upregulated and 223 co-downregulated genes. These differentially expressed genes (DEGs) were highly enriched in “response to chemical” and “stress” based on the gene ontology enrichment analysis. Notably, 30 candidate genes that were associated with the salt tolerance analysis were obtained by integrating GWAS and transcriptomic DEG analyses, including 13 cloned genes that had no reports of tolerance to salt and 17 candidate genes whose functions were unknown. To further explore these genes and their alleles, we performed haplotype analysis, genome-wide domestication detection, and transcriptome analysis to breed improved varieties. This data and the genetic resources provided will be valuable for the development of salt tolerant rice varieties.

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“…Differences in NUE (and N levels) impact various morpho-agronomic and physiological traits, including tiller number (TN), effective panicle number (EPN), spikelet number, 1,000-grain weight (TGW), plant height (PH), grain yield per plant (GYPP), leaf color, and dry weight of the shoots and roots (Ali et al, 2018;Sandhu et al, 2021). Analyses of quantitative trait loci (QTLs) controlling NUE in rice have been performed using various traits or characteristics as indicators based on different biparental populations as well as natural populations (Tong et al, 2006;Cho et al, 2007;Senthilvel et al, 2008;Wang et al, 2009;Wei et al, 2012;Yue et al, 2015;Nguyen et al, 2016;Zhou et al, 2017;Bai et al, 2021;Lv et al, 2021;Rakotoson et al, 2021;Shen et al, 2021;Xin et al, 2021;Li et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive QTL analyses of nitrogen use efficiency in indica rice

et al. 2022

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Nitrogen-use efficiency (NUE) in rice is a complex quantitative trait involved in multiple biological processes and agronomic traits; however, the genetic basis and regulatory network of NUE remain largely unknown. We constructed a high-resolution microarray-based genetic map for 261 recombinant inbred lines derived from two indica parents. Using 2,345 bin markers, comprehensive analyses of quantitative trait loci (QTLs) of seven key agronomic traits under two different N levels were performed. A total of 11 non-redundant QTLs for effective panicle number (EPN), 7 for grain number per panicle, 13 for thousand-grain weight, 2 for seed-setting percentage, 15 for plant height, 12 for panicle length, and 6 for grain yield per plant were identified. The QTL regions were as small as 512 kb on average, and more than half spanned an interval smaller than 100 kb. Using this advantage, we identified possible candidate genes of two major EPN-related QTLs. One QTL detected under both N levels possibly encodes a DELLA protein SLR1, which is known to regulate NUE, although the natural variations of this protein have not been reported. The other QTL detected only under a high N level could encode the transcription factor OsbZIP59. We also predicted the possible candidate genes for another three of the NUE-related QTLs. Our results provide a reference for improving NUE-related QTL cloning and promote our understanding of NUE regulation in indica rice.

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Loci and Natural Alleles for Low-Nitrogen-Induced Growth Response Revealed by the Genome-Wide Association Study Analysis in Rice (Oryza sativa L.)

Cited by 6 publications

References 46 publications

WGCNA Identifies a Comprehensive Gene Co-Expression Network Associated with Development in autotetraploid potato tissues

WGCNA Identifies a Comprehensive Gene Co-Expression Network Associated with Development in autotetraploid potato tissues

Combining GWAS, Genome-Wide Domestication and a Transcriptomic Analysis Reveals the Loci and Natural Alleles of Salt Tolerance in Rice (Oryza sativa L.)

Comprehensive QTL analyses of nitrogen use efficiency in indica rice

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