Saurabh Gupta

Dr. Saurabh Gupta

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Journal Article
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FRFiaz Rasul
Fiaz Rasul
SGSaurabh Gupta
Saurabh Gupta
JOJustyna Olas
Justyna Olas
TGTsanko Gechev
Tsanko Gechev
NSNeerakkal Sujeeth
Neerakkal Sujeeth
BMBernd Mueller-Roeber
Bernd Mueller-Roeber
Drought represents a major threat to plants in natural ecosystems and agricultural settings. The biostimulant Super Fifty (SF), produced from the brown alga Ascophyllum nodosum, enables ecologically friendly stress mitigation. We investigated the physiological and whole-genome transcriptome responses of Arabidopsis thaliana to drought stress after a treatment with SF. SF strongly decreased drought-induced damage. Accumulation of reactive oxygen species (ROS), which typically stifle plant growth during drought, was reduced in SF-primed plants. Relative water content remained high in SF-treated plants, whilst ion leakage, a measure of cell damage, was reduced compared to controls. Plant growth requires a functional shoot apical meristem (SAM). Expression of a stress-responsive negative growth regulator, RESPONSIVE TO DESICCATION 26 (RD26), was repressed by SF treatment at the SAM, consistent with the model that SF priming maintains the function of the SAM during drought stress. Accordingly, expression of the cell cycle marker gene HISTONE H4 (HIS4) was maintained at the SAMs of SF-primed plants, revealing active cell cycle progression after SF priming during drought. In accordance with this, CYCP2;1, which promotes meristem cell division, was repressed by drought but enhanced by SF. SF also positively affected stomatal behavior to support the tolerance to drought stress. Collectively, our data show that SF priming mitigates multiple cellular processes that otherwise impair plant growth under drought stress, thereby providing a knowledge basis for future research on crops.

5 April 2017 in European Journal of Human Genetics
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Journal Article
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JEJamie Ellingford
Jamie Ellingford
CCChristopher Campbell
Christopher Campbell
SBStephanie Barton
Stephanie Barton
SBSanjeev Bhaskar
Sanjeev Bhaskar
SGSaurabh Gupta
Saurabh Gupta
GBGraeme Black
Graeme Black
Although a common cause of disease, copy number variants (CNVs) have not routinely been identified from next-generation sequencing (NGS) data in a clinical context. This study aimed to examine the sensitivity and specificity of a widely used software package, ExomeDepth, to identify CNVs from targeted NGS data sets. We benchmarked the accuracy of CNV detection using ExomeDepth v1.1.6 applied to targeted NGS data sets by comparison to CNV events detected through whole-genome sequencing for 25 individuals and determined the sensitivity and specificity of ExomeDepth applied to these targeted NGS data sets to be 100% and 99.8%, respectively. To define quality assurance metrics for CNV surveillance through ExomeDepth, we undertook simulation of single-exon (n=1000) and multiple-exon heterozygous deletion events (n=1749), determining a sensitivity of 97% (n=2749). We identified that the extent of sequencing coverage, the inter- and intra-sample variability in the depth of sequencing coverage and the composition of analysis regions are all important determinants of successful CNV surveillance through ExomeDepth. We then applied these quality assurance metrics during CNV surveillance for 140 individuals across 12 distinct clinical areas, encompassing over 500 potential rare disease diagnoses. All 140 individuals lacked molecular diagnoses after routine clinical NGS testing, and by application of ExomeDepth, we identified 17 CNVs contributing to the cause of a Mendelian disorder. Our findings support the integration of CNV detection using ExomeDepth v1.1.6 with routine targeted NGS diagnostic services for Mendelian disorders. Implementation of this strategy increases diagnostic yields and enhances clinical care.

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MOM. Amin Omidbakhsh-Fard
M. Amin Omidbakhsh-Fard
NSNeerakkal Sujeeth
Neerakkal Sujeeth
SGSaurabh Gupta
Saurabh Gupta
NONooshin Omranian
Nooshin Omranian
KGKieran J Guinan
Kieran J Guinan
TGTsanko Gechev
Tsanko Gechev
Abiotic stresses cause oxidative damage in plants. Here, we demonstrate that foliar application of an extract from the seaweed Ascophyllum nodosum, SuperFifty (SF), largely prevents paraquat (PQ)-induced oxidative stress in Arabidopsis thaliana. While PQ-stressed plants develop necrotic lesions, plants pre-treated with SF (i.e., primed plants) were unaffected by PQ. Transcriptome analysis revealed induction of reactive oxygen species (ROS) marker genes, genes involved in ROS-induced programmed cell death, and autophagy-related genes after PQ treatment. These changes did not occur in PQ-stressed plants primed with SF. In contrast, upregulation of several carbohydrate metabolism genes, growth, and hormone signaling as well as antioxidant-related genes were specific to SF-primed plants. Metabolomic analyses revealed accumulation of the stress-protective metabolite maltose and the tricarboxylic acid cycle intermediates fumarate and malate in SF-primed plants. Lipidome analysis indicated that those lipids associated with oxidative stress-induced cell death and chloroplast degradation, such as triacylglycerols (TAGs), declined upon SF priming. Our study demonstrated that SF confers tolerance to PQ-induced oxidative stress in A. thaliana, an effect achieved by modulating a range of processes at the transcriptomic, metabolic, and lipid levels.

5 February 2014 in BMC Bioinformatics
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SPSwetansu Pattnaik
Swetansu Pattnaik
SGSaurabh Gupta
Saurabh Gupta
ARArjun A Rao
Arjun A Rao
BPBinay Panda
Binay Panda
Background: The rapid advancements in the field of genome sequencing are aiding our understanding on many biological systems. In the last five years, computational biologists and bioinformatics specialists have come up with newer, better and more efficient tools towards the discovery, analysis and interpretation of different genomic variants from high-throughput sequencing data. Availability of reliable simulated dataset is essential and is the first step towards testing any newly developed analytical tools for variant discovery. Although there are tools currently available that can simulate variants, none present the possibility of simulating all the three major types of variations (Single Nucleotide Polymorphisms, Insertions and Deletions and Copy Number Variations) and can generate reads taking a realistic error-model into consideration. Therefore, an efficient simulator and read generator is needed that can simulate variants taking the error rates of true biological samples into consideration. Results: We report SInC (Snp, Indel and Cnv) an open-source variant simulator and read generator capable of simulating all the three common types of biological variants taking into account a distribution of base quality score from a most commonly used next-generation sequencing instrument from Illumina. SInC is capable of generating single- and paired-end reads with user-defined insert size and with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes. Conclusions: We have come up with a user-friendly multi-variant simulator and read-generator tools called SInC. SInC can be downloaded from http://sourceforge.net/projects/sincsimulator.

23 May 2024 in Nature Genetics
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AKAamir W. Khan
Aamir W. Khan
VGVanika Garg
Vanika Garg
SSShuai Sun
Shuai Sun
SGSaurabh Gupta
Saurabh Gupta
ODOlga Dudchenko
Olga Dudchenko
Rajeev VarshneyRajeev Varshney
Rajeev Varshney

28 July 2014 in DNA Research
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MSMeeta Sunil
Meeta Sunil
AHArun K. Hariharan
Arun K. Hariharan
SNSoumya Nayak
Soumya Nayak
SGSaurabh Gupta
Saurabh Gupta
SNSuran R. Nambisan
Suran R. Nambisan
SSSubhashini Srinivasan
Subhashini Srinivasan
Grain amaranths, edible C4 dicots, produce pseudo-cereals high in lysine. Lysine being one of the most limiting essential amino acids in cereals and C4 photosynthesis being one of the most sought-after phenotypes in protein-rich legume crops, the genome of one of the grain amaranths is likely to play a critical role in crop research. We have sequenced the genome and transcriptome of Amaranthus hypochondriacus, a diploid (2n = 32) belonging to the order Caryophyllales with an estimated genome size of 466 Mb. Of the 411 linkage single-nucleotide polymorphisms (SNPs) reported for grain amaranths, 355 SNPs (86%) are represented in the scaffolds and 74% of the 8.6 billion bases of the sequenced transcriptome map to the genomic scaffolds. The genome of A. hypochondriacus, codes for at least 24,829 proteins, shares the paleohexaploidy event with species under the superorders Rosids and Asterids, harbours 1 SNP in 1,000 bases, and contains 13.76% of repeat elements. Annotation of all the genes in the lysine biosynthetic pathway using comparative genomics and expression analysis offers insights into the high-lysine phenotype. As the first grain species under Caryophyllales and the first C4 dicot genome reported, the work presented here will be beneficial in improving crops and in expanding our understanding of angiosperm evolution.