Validation of Genes Affecting Rice Grain Zinc Content Through Candidate Gene-Based Association Analysis

Liu, Jindong; Zhan, Jiasui; Chen, Jingguang G.; Lü, Xiang; Zhi, Shuai; Ye, Guoyou

doi:10.3389/fgene.2021.701658

Cited by 4 publications

(6 citation statements)

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“…The essential component includes identification of the target population and staple food (crop) consumption, establishing a breeding baseline and nutrient target levels, and screening and characterizing germplasm for target nutrients. The outcomes of the discovery phase will guide the Dwivedi et al 10.3389/fpls.2023.1119148 Frontiers in Plant Science frontiersin.org Rice qGZn9a linked with high-grain Zn levels in O. meridionalis W1627 but with reduced fertility levels; a partial defect in anther dehiscence correlates with increased grain Zn; eight candidate genes in the qGZn9a region, with one specifically expressed in the developing anther and possibly regulates anther dehiscence; thereby, a balancing selection is needed to effect simultaneous improvement Ogasawara et al, 2021 Two QTL qZPR.1.1 and QTL qZPR.11.1 on chromosome 1 and a common QTL on chromosome 2 for grain Zn in polished rice; two candidate genes related to transporters Suman et al, 2021 Haplotype-based association mapping involving 65 genes related to Zn responses on three diverse panels revealed five (OsNRAMP6, OsYSL15, OsIRT1, OsIDEF1, and OsZIFL7; PVE 7.70%-15.39%), three (OsFRDL1, OsIRT1, and OsZIP7, 11.87%-17.99%), and two (OsYSL7 and OsZIP7, 9.85%-10.57%) genes, respectively, associated with grain Zn in diversity panels from Southeast Asia (SEA) and South China (SC), and MAGIC population; haplotype analysis revealed that Hap1-OsNRAMP5, Hap5-OsZIP4, Hap1-OsIRT1, Hap3-OsNRAMP6, Hap6-OsMTP1, and Hap6-OsYSL15 had the largest effects for Zn in SEA and Hap3-OsOPT7, Hap4-OsIRT2, Hap4-OsZIP7, Hap5-OsIRT1, and Hap5-OsSAMS1 had the most significant effects in the SC panels Liu et al, 2021a Zn in polished grains associated with SNPs located in three putative candidate genes on chromosomes 3 and 7; chromosome 7 genomic region colocalized with previously identified genomic regions (rMQTL 7 . 1 ) and OsNAS3 candidate gene Babu et al, 2020 Six, 7, 11, and…”

Section: Cross Breeding and Genomic-assisted Breedingmentioning

confidence: 99%

“…qGZn9a linked to high-grain Zn in Oryza meridionalis also adversely affects fertility levels. One of the eight candidate genes in qGZn9a specifically expressed in the developing anther and possibly regulated anther dehiscence, which suggests that a balancing selection is needed to ensure simultaneous improvement in rice ( Ogasawara et al., 2021 ), while haplotype-based association mapping involving 65 genes related to Zn responses on diverse germplasm panels and MAGIC populations revealed diversity panel- or population- specific candidate genes associated with high seed Zn content ( Liu et al., 2021a ). Many of the candidate genes associated with Fe and Zn uptake, transport, storage, and regulation in wheat were orthologs of known Arabidopsis and rice genes related to Fe and Zn homeostasis ( Tong et al., 2022 ), while SNPs mapped on chromosome 1A and 2A in wheat genome significantly associated with seed Fe and Zn content had no adverse effects on seed weight ( Liu et al., 2021b ).…”

Section: Spatial and Temporal Distribution And Accumulation Of Fe And Znmentioning

confidence: 99%

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Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Dwivedi¹,

Garcia‐Oliveira

Govindaraj

et al. 2023

Front. Plant Sci.

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Malnutrition results in enormous socio-economic costs to the individual, their community, and the nation’s economy. The evidence suggests an overall negative impact of climate change on the agricultural productivity and nutritional quality of food crops. Producing more food with better nutritional quality, which is feasible, should be prioritized in crop improvement programs. Biofortification refers to developing micronutrient -dense cultivars through crossbreeding or genetic engineering. This review provides updates on nutrient acquisition, transport, and storage in plant organs; the cross-talk between macro- and micronutrients transport and signaling; nutrient profiling and spatial and temporal distribution; the putative and functionally characterized genes/single-nucleotide polymorphisms associated with Fe, Zn, and β-carotene; and global efforts to breed nutrient-dense crops and map adoption of such crops globally. This article also includes an overview on the bioavailability, bioaccessibility, and bioactivity of nutrients as well as the molecular basis of nutrient transport and absorption in human. Over 400 minerals (Fe, Zn) and provitamin A-rich cultivars have been released in the Global South. Approximately 4.6 million households currently cultivate Zn-rich rice and wheat, while ~3 million households in sub-Saharan Africa and Latin America benefit from Fe-rich beans, and 2.6 million people in sub-Saharan Africa and Brazil eat provitamin A-rich cassava. Furthermore, nutrient profiles can be improved through genetic engineering in an agronomically acceptable genetic background. The development of “Golden Rice” and provitamin A-rich dessert bananas and subsequent transfer of this trait into locally adapted cultivars are evident, with no significant change in nutritional profile, except for the trait incorporated. A greater understanding of nutrient transport and absorption may lead to the development of diet therapy for the betterment of human health.

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Section: Cross Breeding and Genomic-assisted Breedingmentioning

confidence: 99%

Section: Spatial and Temporal Distribution And Accumulation Of Fe And Znmentioning

confidence: 99%

Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Dwivedi¹,

Garcia‐Oliveira

Govindaraj

et al. 2023

Front. Plant Sci.

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“…Identifying minor genes of complex traits by CAS were conducted in Arabidopsis , rice, maize and common wheat ( Zhao et al., 2015 ). Haplotype is the combination of alleles at different position on the same genomic regions for common inheritance ( Liu et al., 2021 ), effective than SNP (Single nucleotide polymorphism) and InDel (Insertion-deletion) in crop marker-assisted selection (MAS) breeding ( Li et al., 2017 ; Resende et al., 2017 ; Prodhomme et al., 2020 ). Superior haplotype identification has been proven to be an effective way to identify genes associated with complex traits and availability for crop breeding ( Bevan et al., 2017 ; Abbai et al., 2019 ; Sinha et al., 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes

Wang¹,

Liu²,

Meng³

et al. 2023

Front. Plant Sci.

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Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.

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“…Based on genome-wide association studies, 11 genes were selected for haplo-pheno analysis to identify the superior haplotypes for resistant starch, the glycemic index and grain and cooking quality in rice [21]. Liu et al [22] evaluated the effects of 65 genes related to rice zinc responses on grain zinc content using two panels of breeding lines, and superior haplotypes were identified. Abbai et al [23] conducted a candidate gene-based association study for 120 genes and identified 21 strongly associated genes governing 10-grain yield and quality traits and identified superior haplotypes for the associated genes upon phenotyping the subset of the 3k rice genome panel.…”

Section: Introductionmentioning

confidence: 99%

Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice (Oryza sativa L.)

Liu,

Qiu,

et al. 2023

Genes

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The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length–width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.

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Validation of Genes Affecting Rice Grain Zinc Content Through Candidate Gene-Based Association Analysis

Cited by 4 publications

References 52 publications

Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes

Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice (Oryza sativa L.)

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