Genetic variability and genome‐wide marker association studies for starch traits contributing to low glycaemic index in pearl millet

Pearl millet [Pennisetum glaucum (L.) R Br.] is an important staple food crop in the semi-arid tropics of Asia and Africa. It is a cereal grain that has the prospect to be used as a substitute for wheat flour for celiac patients. It is an important antioxidant food resource present with a wide range of phenolic compounds that are good sources of natural antioxidants. The present study aimed to identify the total antioxidant content of pearl millet flour and apply it to evaluate the antioxidant activity of its 222 genotypes drawn randomly from the pearl millet inbred germplasm association panel (PMiGAP), a world diversity panel of this crop. The total phenolic content (TPC) significantly correlated with DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity (% inhibition), which ranged from 2.32 to 112.45% and ferric-reducing antioxidant power (FRAP) activity ranging from 21.68 to 179.66 (mg ascorbic acid eq./100 g). Genome-wide association studies (GWAS) were conducted using 222 diverse accessions and 67 K SNPs distributed across all the seven pearl millet chromosomes. Approximately, 218 SNPs were found to be strongly associated with DPPH and FRAP activity at high confidence [–log (p) > 3.0–7.4]. Furthermore, flanking regions of significantly associated SNPs were explored for candidate gene harvesting. This identified 18 candidate genes related to antioxidant pathway genes (flavanone 7-O-beta-glycosyltransferase, GDSL esterase/lipase, glutathione S-transferase) residing within or near the association signal that can be selected for further functional characterization. Patterns of genetic variability and the associated genes reported in this study are useful findings, which would need further validation before their utilization in molecular breeding for high antioxidant-containing pearl millet cultivars.

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Genome-Wide Association Studies and Genomic Selection in Pearl Millet: Advances and Prospects

Frontiers in Genetics ◽

10.3389/fgene.2019.01389 ◽

2020 ◽

Vol 10 ◽

Cited By ~ 5

Author(s):

Rakesh K. Srivastava ◽

Ram B. Singh ◽

Vijaya Lakshmi Pujarula ◽

Srikanth Bollam ◽

Madhu Pusuluri ◽

...

Keyword(s):

Genomic Selection ◽

Pearl Millet ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Genetic variability and association studies in pearl millet for green fodder yield and quality traits

Electronic Journal of Plant Breeding ◽

10.5958/0975-928x.2018.00158.8 ◽

2018 ◽

Vol 9 (3) ◽

pp. 1263

Author(s):

Anusha Mariam Thomas ◽

C. Babu ◽

K. Iyanar

Keyword(s):

Genetic Variability ◽

Pearl Millet ◽

Association Studies ◽

Quality Traits ◽

Yield And Quality ◽

Green Fodder ◽

Fodder Yield

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Metabolite Diversity and Metabolic Genome-Wide Marker Association Studies (Mgwas) for Health Benefiting Nutritional Traits in Pearl Millet Grains

Cells ◽

10.3390/cells10113076 ◽

2021 ◽

Vol 10 (11) ◽

pp. 3076

Author(s):

Chandra Bhan Yadav ◽

Rakesh K. Srivastava ◽

Prakash I. Gangashetty ◽

Rama Yadav ◽

Luis A. J. Mur ◽

...

Keyword(s):

Lipid Metabolism ◽

Pearl Millet ◽

High Resolution Mass Spectrometry ◽

Association Studies ◽

Inbred Lines ◽

Ascorbate Oxidase ◽

Log P ◽

P Value ◽

Phenotypic Traits ◽

Genome Wide

As efforts are made to increase food security, millets are gaining increasing importance due to their excellent nutritional credentials. Among the millets, pearl millet is the predominant species possessing several health benefiting nutritional traits in its grain that are helpful in mitigating chronic illnesses such as type−2 diabetes and obesity. In this paper, we conducted metabolomic fingerprinting of 197 pearl millet inbred lines drawn randomly from within the world collection of pearl millet germplasm and report the extent of genetic variation for health benefitting metabolites in these genotypes. Metabolites were extracted from seeds and assessed using flow infusion high-resolution mass spectrometry (FIE-HRMS). Metabolite features (m/z), whose levels significantly differed among the germplasm inbred lines, were identified by ANOVA corrected for FDR and subjected to functional pathway analysis. A number of health-benefiting metabolites linked to dietary starch, antioxidants, vitamins, and lipid metabolism-related compounds were identified. Metabolic genome-wide association analysis (mGWAS) performed using the 396 m/z as phenotypic traits and the 76 K SNP as genotypic variants identified a total of 897 SNPs associated with health benefiting nutritional metabolite at the -log p-value ≤ 4.0. From these associations, 738 probable candidate genes were predicted to have an important role in starch, antioxidants, vitamins, and lipid metabolism. The mGWAS analysis focused on genes involved in starch branching (α-amylase, β-amylase), vitamin-K reductase, UDP-glucuronosyl, and UDP-glucosyl transferase (UGTs), L-ascorbate oxidase, and isoflavone 2′-monooxygenase genes, which are known to be linked to increases in human health benefiting metabolites. We demonstrate how metabolomic, genomic, and statistical approaches can be utilized to pinpoint genetic variations and their functions linked to key nutritional properties in pearl millet, which in turn can be bred into millets and other cereals crops using plant breeding methods.

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Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk

Brain Communications ◽

10.1093/braincomms/fcz022 ◽

2019 ◽

Vol 1 (1) ◽

Cited By ~ 12

Author(s):

Dervis A Salih ◽

Sevinc Bayram ◽

Sebastian Guelfi ◽

Regina H Reynolds ◽

Maryam Shoai ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Genetic Variability ◽

Disease Risk ◽

Association Studies ◽

Amyloid Deposition ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Risk Genes ◽

Genome Wide

Abstract Genome-wide association studies of late-onset Alzheimer’s disease risk have previously identified genes primarily expressed in microglia that form a transcriptional network. Using transgenic mouse models of amyloid deposition, we previously showed that many of the mouse orthologues of these risk genes are co-expressed and associated with amyloid pathology. In this new study, we generate an improved RNA-seq-derived network that is expressed in amyloid-responsive mouse microglia and we statistically compare this with gene-level variation in previous human Alzheimer’s disease genome-wide association studies to predict at least four new risk genes for the disease (OAS1, LAPTM5, ITGAM/CD11b and LILRB4). Of the mouse orthologues of these genes Oas1a is likely to respond directly to amyloid at the transcriptional level, similarly to established risk gene Trem2, because the increase in Oas1a and Trem2 transcripts in response to amyloid deposition in transgenic mice is significantly higher than both the increase of the average microglial transcript and the increase in microglial number. In contrast, the mouse orthologues of LAPTM5, ITGAM/CD11b and LILRB4 (Laptm5, Itgam/CD11b and Lilra5) show increased transcripts in the presence of amyloid plaques similar in magnitude to the increase of the average microglial transcript and the increase in microglia number, except that Laptm5 and Lilra5 transcripts increase significantly quicker than the average microglial transcript as the plaque load becomes dense. This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimer’s disease risk, and identification of these genes may help to predict the risk of developing Alzheimer’s disease. These findings also provide further insights into the mechanisms underlying Alzheimer’s disease for potential drug discovery.

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