Applications and challenges for efficient exploration of omics interventions for the enhancement of nutritional quality in rice (<i>Oryza sativa</i>L.)

Rana, Nitika; Rahim, Mohammed Saba; Kaur, Guneet; Bansal, Ruchi; Kumawat, Surbhi; Roy, Joy; Deshmukh, Rupesh; Sonah, Humira; Sharma, Tilak Raj

doi:10.1080/10408398.2019.1685454

Cited by 34 publications

(7 citation statements)

References 156 publications

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“…Rice RNA-seq and microarray data are deposited in specific databases, such as NCBI SRA ( ), RiceXPro ( ), BAR ( ), or GEO ( ). Whereas the majority of transcriptome profiling has been conducted for stress response, fewer efforts have been dedicated to rice nutritional quality [ 50 ]. For instance, in relation to mineral nutrient homeostasis, a study investigating the role of alternative splicing was conducted through whole-transcriptome RNA sequencing on rice roots grown in the presence/absence of different nutrients, indicating that alternative splicing is highly nutrient-specific [ 51 ].…”

Section: Transcriptomics Blueprint Of Biofortified Ricementioning

confidence: 99%

Transcriptomics View over the Germination Landscape in Biofortified Rice

Dueñas

Slamet‐Loedin

Macovei

2021

Genes

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Hidden hunger, or micronutrient deficiency, is a worldwide problem. Several approaches are employed to alleviate its effects (e.g., promoting diet diversity, use of dietary supplements, chemical fortification of processed food), and among these, biofortification is considered as one of the most cost-effective and highly sustainable. Rice is one of the best targets for biofortification since it is a staple food for almost half of the world’s population as a high-energy source but with low nutritional value. Multiple biofortified rice lines have been produced during the past decades, while few studies also reported modifications in germination behavior (in terms of enhanced or decreased germination percentage or speed). It is important to underline that rapid, uniform germination, and seedling establishment are essential prerequisites for crop productivity. Combining the two traits, biofortified, highly-nutritious seeds with improved germination behavior can be envisaged as a highly-desired target for rice breeding. To this purpose, information gathered from transcriptomics studies can reveal useful insights to unveil the molecular players governing both traits. The present review aims to provide an overview of transcriptomics studies applied at the crossroad between biofortification and seed germination, pointing out potential candidates for trait pyramiding.

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Section: Transcriptomics Blueprint Of Biofortified Ricementioning

confidence: 99%

Transcriptomics View over the Germination Landscape in Biofortified Rice

Dueñas

Slamet‐Loedin

Macovei

2021

Genes

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“…Rice, a staple food in many countries, contributes around 21% to the total per capita calorie intake across the globe [ 1 , 2 ]. Rice is consumed in several forms such as processed and fermented products.…”

Section: Introductionmentioning

confidence: 99%

Deciphering Haplotypic Variation and Gene Expression Dynamics Associated with Nutritional and Cooking Quality in Rice

Rana

Kumawat

Kumar

et al. 2022

Cells

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Nutritional quality improvement of rice is the key to ensure global food security. Consequently, enormous efforts have been made to develop genomics and transcriptomics resources for rice. The available omics resources along with the molecular understanding of trait development can be utilized for efficient exploration of genetic resources for breeding programs. In the present study, 80 genes known to regulate the nutritional and cooking quality of rice were extensively studied to understand the haplotypic variability and gene expression dynamics. The haplotypic variability of selected genes were defined using whole-genome re-sequencing data of ~4700 diverse genotypes. The analytical workflow identified 133 deleterious single-nucleotide polymorphisms, which are predicted to affect the gene function. Furthermore, 788 haplotype groups were defined for 80 genes, and the distribution and evolution of these haplotype groups in rice were described. The nucleotide diversity for the selected genes was significantly reduced in cultivated rice as compared with that in wild rice. The utility of the approach was successfully demonstrated by revealing the haplotypic association of chalk5 gene with the varying degree of grain chalkiness. The gene expression atlas was developed for these genes by analyzing RNA-Seq transcriptome profiling data from 102 independent sequence libraries. Subsequently, weighted gene co-expression meta-analyses of 11,726 publicly available RNAseq libraries identified 19 genes as the hub of interactions. The comprehensive analyses of genetic polymorphisms, allelic distribution, and gene expression profiling of key quality traits will help in exploring the most desired haplotype for grain quality improvement. Similarly, the information provided here will be helpful to understand the molecular mechanism involved in the development of nutritional and cooking quality traits in rice.

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“…The unpolished brown rice with bran layer is higher in nutrient content than its counterpart white milled rice grains. Rice bran is also rich in dietary fiber content and is an important part of the functional foods spectrum of rice eating countries (Rana et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Identification of genomic loci governing pericarp colour through GWAS in rice (Oryza sativa L.)

Rana¹,

Kumawat²,

Singh³

et al. 2022

IJGPB

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Rice pericarp colour is one of the nutritional traits that is now gaining attention worldwide. In the present investigation, genome-wide association GWAS) was performed to identify loci governing pericarp colour in rice. A set of 1,349,269 SNPs and precise phenotyping across 325 diverse accessions of rice were used for the GWAS. The accessions belong to five rice isozyme classification groups viz., indica, japonica, aromatic, aus, and admix. The GWAS identified two significant loci gPC5-1and gPC7-1 on chromosomes, 5 and 7, respectively, associated with the pericarp colour in rice. The SNPs on chromosome 7 co-localized with the functionally characterized Os07g0211500 (Rc gene) known to control pericarp colour and Os07g0214900 which is similar to the Chalcone synthase 2(OsCHS2) gene involved in flavonoid synthesis pathway. Linkage disequilibrium analysis across 0.25 Mbp upstream and downstream of these markers suggested three strong linkage blocks on chromosome 7. More interestingly, the novel locus identified on chromosome 5 gPC5-1 does not harbor any homolog of previously reported genes. Therefore, the locus can serve as a basis for identifying a new gene for rice pericarp colour. The results presented here will be helpful to understand the genetic regulation of pericarp colour and for genomic-assisted breeding in rice.

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Applications and challenges for efficient exploration of omics interventions for the enhancement of nutritional quality in rice (Oryza sativaL.)

Cited by 34 publications

References 156 publications

Transcriptomics View over the Germination Landscape in Biofortified Rice

Transcriptomics View over the Germination Landscape in Biofortified Rice

Deciphering Haplotypic Variation and Gene Expression Dynamics Associated with Nutritional and Cooking Quality in Rice

Identification of genomic loci governing pericarp colour through GWAS in rice (Oryza sativa L.)

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