Genome wide association analysis for grain micronutrients and anti-nutritional traits in mungbean [Vigna radiata (L.) R. Wilczek] using SNP markers Article Swipe
Mayank Kumar Sinha
,
Muraleedhar S. Aski
,
Gyan P. Mishra
,
Monu Kumar
,
Prachi Yadav
,
Jayanti Tokas
,
Sanjeev Gupta
,
Aditya Pratap
,
Shiv Kumar
,
Ramakrishnan M. Nair
,
Roland Schafleitner
,
Harsh Kumar Dikshit
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fnut.2023.1099004
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3389/fnut.2023.1099004
Mungbean is an important food grain legume for human nutrition and nutritional food due to its nutrient-dense seed, liked palatability, and high digestibility. However, anti-nutritional factors pose a significant risk to improving nutritional quality for bio-fortification. In the present study, genetic architecture of grain micronutrients (grain iron and zinc concentration) and anti-nutritional factors (grain phytic acid and tannin content) in association mapping panel of 145 diverse mungbean were evaluated. Based on all four parameters genotypes PUSA 1333 and IPM 02-19 were observed as desired genotypes as they had high grain iron and zinc concentration but low grain phytic acid and tannin content. The next generation sequencing (NGS)-based genotyping by sequencing (GBS) identified 14,447 genome-wide SNPs in a diverse selected panel of 127 mungbean genotypes. Population admixture analysis revealed the presence of four different ancestries among the genotypes and LD decay of ∼57.6 kb kb physical distance was noted in mungbean chromosomes. Association mapping analysis revealed that a total of 20 significant SNPs were shared by both GLM and Blink models associated with grain micronutrient and anti-nutritional factor traits, with Blink model identifying 35 putative SNPs. Further, this study identified the 185 putative candidate genes. Including potential candidate genes Vradi07g30190 , Vradi01g09630 , and Vradi09g05450 were found to be associated with grain iron concentration, Vradi10g04830 with grain zinc concentration, Vradi08g09870 and Vradi01g11110 with grain phytic acid content and Vradi04g11580 and Vradi06g15090 with grain tannin content. Moreover, two genes Vradi07g15310 and Vradi09g05480 showed significant variation in protein structure between native and mutated versions. The identified SNPs and candidate genes are potential powerful tools to provide the essential information for genetic studies and marker-assisted breeding program for nutritional improvement in mungbean.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fnut.2023.1099004
- OA Status
- gold
- Cited By
- 17
- References
- 111
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4319438891
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4319438891Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fnut.2023.1099004Digital Object Identifier
- Title
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Genome wide association analysis for grain micronutrients and anti-nutritional traits in mungbean [Vigna radiata (L.) R. Wilczek] using SNP markersWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-02-07Full publication date if available
- Authors
-
Mayank Kumar Sinha, Muraleedhar S. Aski, Gyan P. Mishra, Monu Kumar, Prachi Yadav, Jayanti Tokas, Sanjeev Gupta, Aditya Pratap, Shiv Kumar, Ramakrishnan M. Nair, Roland Schafleitner, Harsh Kumar DikshitList of authors in order
- Landing page
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https://doi.org/10.3389/fnut.2023.1099004Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3389/fnut.2023.1099004Direct OA link when available
- Concepts
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Vigna, Radiata, Biology, SNP, Micronutrient, Genome-wide association study, Genetic association, Single-nucleotide polymorphism, Biotechnology, Botany, Agronomy, Genetics, Genotype, Gene, Medicine, PathologyTop concepts (fields/topics) attached by OpenAlex
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17Total citation count in OpenAlex
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2025: 10, 2024: 3, 2023: 4Per-year citation counts (last 5 years)
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111Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(GBS) | 110 |
| abstract_inverted_index.02-19 | 79 |
| abstract_inverted_index.Based | 69 |
| abstract_inverted_index.Blink | 168, 179 |
| abstract_inverted_index.SNPs. | 184 |
| abstract_inverted_index.among | 134 |
| abstract_inverted_index.decay | 139 |
| abstract_inverted_index.found | 205 |
| abstract_inverted_index.genes | 197, 236, 256 |
| abstract_inverted_index.grain | 5, 43, 89, 96, 172, 210, 215, 222, 231 |
| abstract_inverted_index.human | 8 |
| abstract_inverted_index.liked | 18 |
| abstract_inverted_index.model | 180 |
| abstract_inverted_index.noted | 147 |
| abstract_inverted_index.panel | 62, 119 |
| abstract_inverted_index.seed, | 17 |
| abstract_inverted_index.study | 187 |
| abstract_inverted_index.tools | 260 |
| abstract_inverted_index.total | 157 |
| abstract_inverted_index.(grain | 45, 53 |
| abstract_inverted_index.14,447 | 112 |
| abstract_inverted_index.factor | 176 |
| abstract_inverted_index.genes. | 193 |
| abstract_inverted_index.legume | 6 |
| abstract_inverted_index.models | 169 |
| abstract_inverted_index.native | 247 |
| abstract_inverted_index.phytic | 54, 97, 223 |
| abstract_inverted_index.shared | 163 |
| abstract_inverted_index.showed | 240 |
| abstract_inverted_index.study, | 39 |
| abstract_inverted_index.tannin | 57, 100, 232 |
| abstract_inverted_index.between | 246 |
| abstract_inverted_index.content | 225 |
| abstract_inverted_index.desired | 83 |
| abstract_inverted_index.diverse | 65, 117 |
| abstract_inverted_index.factors | 25, 52 |
| abstract_inverted_index.genetic | 40, 267 |
| abstract_inverted_index.mapping | 61, 152 |
| abstract_inverted_index.mutated | 249 |
| abstract_inverted_index.present | 38 |
| abstract_inverted_index.program | 272 |
| abstract_inverted_index.protein | 244 |
| abstract_inverted_index.provide | 262 |
| abstract_inverted_index.quality | 33 |
| abstract_inverted_index.studies | 268 |
| abstract_inverted_index.traits, | 177 |
| abstract_inverted_index.∼57.6 | 141 |
| abstract_inverted_index.Further, | 185 |
| abstract_inverted_index.However, | 23 |
| abstract_inverted_index.Mungbean | 0 |
| abstract_inverted_index.analysis | 126, 153 |
| abstract_inverted_index.breeding | 271 |
| abstract_inverted_index.content) | 58 |
| abstract_inverted_index.content. | 101, 233 |
| abstract_inverted_index.distance | 145 |
| abstract_inverted_index.mungbean | 66, 122, 149 |
| abstract_inverted_index.observed | 81 |
| abstract_inverted_index.physical | 144 |
| abstract_inverted_index.powerful | 259 |
| abstract_inverted_index.presence | 129 |
| abstract_inverted_index.putative | 183, 191 |
| abstract_inverted_index.revealed | 127, 154 |
| abstract_inverted_index.selected | 118 |
| abstract_inverted_index.Including | 194 |
| abstract_inverted_index.Moreover, | 234 |
| abstract_inverted_index.admixture | 125 |
| abstract_inverted_index.candidate | 192, 196, 255 |
| abstract_inverted_index.different | 132 |
| abstract_inverted_index.essential | 264 |
| abstract_inverted_index.genotypes | 74, 84, 136 |
| abstract_inverted_index.important | 3 |
| abstract_inverted_index.improving | 31 |
| abstract_inverted_index.mungbean. | 277 |
| abstract_inverted_index.nutrition | 9 |
| abstract_inverted_index.potential | 195, 258 |
| abstract_inverted_index.structure | 245 |
| abstract_inverted_index.variation | 242 |
| abstract_inverted_index.versions. | 250 |
| abstract_inverted_index.Population | 124 |
| abstract_inverted_index.ancestries | 133 |
| abstract_inverted_index.associated | 170, 208 |
| abstract_inverted_index.evaluated. | 68 |
| abstract_inverted_index.generation | 104 |
| abstract_inverted_index.genotypes. | 123 |
| abstract_inverted_index.genotyping | 107 |
| abstract_inverted_index.identified | 111, 188, 252 |
| abstract_inverted_index.parameters | 73 |
| abstract_inverted_index.sequencing | 105, 109 |
| abstract_inverted_index.(NGS)-based | 106 |
| abstract_inverted_index.Association | 151 |
| abstract_inverted_index.association | 60 |
| abstract_inverted_index.genome-wide | 113 |
| abstract_inverted_index.identifying | 181 |
| abstract_inverted_index.improvement | 275 |
| abstract_inverted_index.information | 265 |
| abstract_inverted_index.nutritional | 11, 32, 274 |
| abstract_inverted_index.significant | 28, 160, 241 |
| abstract_inverted_index.architecture | 41 |
| abstract_inverted_index.chromosomes. | 150 |
| abstract_inverted_index.Vradi01g09630 | 200 |
| abstract_inverted_index.Vradi01g11110 | 220 |
| abstract_inverted_index.Vradi04g11580 | 227 |
| abstract_inverted_index.Vradi06g15090 | 229 |
| abstract_inverted_index.Vradi07g15310 | 237 |
| abstract_inverted_index.Vradi07g30190 | 198 |
| abstract_inverted_index.Vradi08g09870 | 218 |
| abstract_inverted_index.Vradi09g05450 | 203 |
| abstract_inverted_index.Vradi09g05480 | 239 |
| abstract_inverted_index.Vradi10g04830 | 213 |
| abstract_inverted_index.concentration | 93 |
| abstract_inverted_index.micronutrient | 173 |
| abstract_inverted_index.palatability, | 19 |
| abstract_inverted_index.concentration) | 49 |
| abstract_inverted_index.concentration, | 212, 217 |
| abstract_inverted_index.digestibility. | 22 |
| abstract_inverted_index.micronutrients | 44 |
| abstract_inverted_index.nutrient-dense | 16 |
| abstract_inverted_index.marker-assisted | 270 |
| abstract_inverted_index.anti-nutritional | 24, 51, 175 |
| abstract_inverted_index.bio-fortification. | 35 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5047921896, https://openalex.org/A5073998797, https://openalex.org/A5042866242 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 12 |
| corresponding_institution_ids | https://openalex.org/I179420787, https://openalex.org/I45509622 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.7799999713897705 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.96840064 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |