Publications by authors named "Siddhant Kalra"

Gene expression variation results from numerous sources including genetic, environmental, life stage, and even the environment experienced by previous generations. While the importance of each has been demonstrated in diverse organisms, their relative contributions remain understudied because few investigations have simultaneously determined each within a single experiment. Here we quantified genome-wide gene expression traits in Drosophila, quantified the contribution of multiple different sources of trait variation and determined the molecular mechanisms underlying observed variation.

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Upregulation of RNA polymerase I (Pol I) transcription and the overexpression of Pol I transcriptional machinery are crucial molecular alterations favoring malignant transformation. However, the causal molecular mechanism(s) of this aberration remain largely unknown. Here, we found that Pol I transcription and its core machinery are upregulated in lung adenocarcinoma (LUAD).

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Dramatic genomic alterations, either inducible or in a pathological state, dismantle the core regulatory networks, leading to the activation of normally silent genes. Despite possessing immense therapeutic potential, accurate detection of these transcripts is an ever-challenging task, as it requires prior knowledge of the physiological gene expression levels. Here, we introduce EcTracker, an R-/Shiny-based single-cell data analysis web server that bestows a plethora of functionalities that collectively enable the quantitative and qualitative assessments of bona fide cell types or tissue-specific transcripts and, conversely, the ectopically expressed genes in the single-cell ribonucleic acid sequencing datasets.

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Article Synopsis
  • Machine Learning is being used to quickly find important molecules in big databases like a detective looking for clues.
  • A new program called Machine-OlF-Action (MOA) makes it easier for anyone to use this technology by letting them input chemical information without needing advanced computer skills.
  • MOA can find new chemical "helpers" for certain smell receptors in humans and mice, and it's available for download on different computer systems along with a user guide.
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Article Synopsis
  • Olfactory receptors help us smell and are usually found in the nose, but new technologies show they are also in other body parts where we don't expect them.
  • The new methods, like single-cell RNA sequencing, help scientists understand which specific cells these receptors come from, which is really important for studying how they work.
  • The article discusses the challenges in studying these unusual olfactory receptors and suggests ways to use new technologies to learn more about how they function in unexpected places.
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Ectopically expressed olfactory receptors (ORs) have been linked with multiple clinically-relevant physiological processes. Previously used tissue-level expression estimation largely shadowed the potential role of ORs due to their overall low expression levels. Even after the introduction of the single-cell transcriptomics, a comprehensive delineation of expression dynamics of ORs in tumors remained unexplored.

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A prominent clinical symptom of 2019-novel coronavirus (nCoV) infection is hyposmia/anosmia (decrease or loss of sense of smell), along with general symptoms such as fatigue, shortness of breath, fever and cough. The identity of the cell lineages that underpin the infection-associated loss of olfaction could be critical for the clinical management of 2019-nCoV-infected individuals. Recent research has confirmed the role of angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) as key host-specific cellular moieties responsible for the cellular entry of the virus.

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