Essential genes from genome-wide screenings as a resource for neuropsychiatric disorders gene discovery

Zhang, Wei; Quevedo, Joao L De; Fries, Gabriel R.

doi:10.1038/s41398-021-01447-y

Cited by 6 publications

(4 citation statements)

References 46 publications

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“…We identified an increase in the number of publications, antibody counts, and monoclonal antibody counts for essential genes compared with non-essential genes, suggesting a focus on essential genes in research [65][66][67][68][69][70] . However, we also found that Tdark proteins had the least amount of associated data, indicating a knowledge deficit 27,29,30,36 .…”

Section: Discussionmentioning

confidence: 88%

Shedding Light on the Dark Genome: Insights into the Genetic, CRISPR-based, and Pharmacological Dependencies of Human Cancers and Disease Aggressiveness

Kafita,

Nkhoma,

Dzobo

et al. 2023

Preprint

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Investigating the human genome is vital for identifying risk factors and devising effective therapies to combat genetic disorders and cancer. Despite the extensive knowledge of the "light genome", the poorly understood "dark genome" remains understudied. In this study, we integrated data from 20,412 protein-coding genes in Pharos and 8,395 patient-derived tumours from The Cancer Genome Atlas (TCGA) to examine the genetic and pharmacological dependencies in human cancers and their treatment implications. We discovered that dark genes exhibited high mutation rates in certain cancers, similar to light genes. By combining the drug response profiles of cancer cells with cell fitness post-CRISPR-mediated gene knockout, we identified the crucial vulnerabilities associated with both dark and light genes. Our analysis also revealed that tumours harbouring dark gene mutations displayed worse overall and disease-free survival rates than those without such mutations. Furthermore, dark gene expression levels significantly influenced patient survival outcomes. Our findings demonstrated a similar distribution of genetic and pharmacological dependencies across the light and dark genomes, suggesting that targeting the dark genome holds promise for cancer treatment. This study underscores the need for ongoing research on the dark genome to better comprehend the underlying mechanisms of cancer and develop more effective therapies.

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Section: Discussionmentioning

confidence: 88%

Shedding Light on the Dark Genome: Insights into the Genetic, CRISPR-based, and Pharmacological Dependencies of Human Cancers and Disease Aggressiveness

Kafita,

Nkhoma,

Dzobo

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…We identified an increase in the number of publications, antibody counts, and monoclonal antibody counts for essential genes compared with non-essential genes, suggesting a focus on essential genes in research [ 67 – 72 ]. However, we also found that Tdark proteins had the least amount of associated data, indicating a knowledge deficit [ 28 , 30 , 31 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

Shedding light on the dark genome: Insights into the genetic, CRISPR-based, and pharmacological dependencies of human cancers and disease aggressiveness

Kafita,

Nkhoma,

Dzobo

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

Investigating the human genome is vital for identifying risk factors and devising effective therapies to combat genetic disorders and cancer. Despite the extensive knowledge of the "light genome”, the poorly understood "dark genome" remains understudied. In this study, we integrated data from 20,412 protein-coding genes in Pharos and 8,395 patient-derived tumours from The Cancer Genome Atlas (TCGA) to examine the genetic and pharmacological dependencies in human cancers and their treatment implications. We discovered that dark genes exhibited high mutation rates in certain cancers, similar to light genes. By combining the drug response profiles of cancer cells with cell fitness post-CRISPR-mediated gene knockout, we identified the crucial vulnerabilities associated with both dark and light genes. Our analysis also revealed that tumours harbouring dark gene mutations displayed worse overall and disease-free survival rates than those without such mutations. Furthermore, dark gene expression levels significantly influenced patient survival outcomes. Our findings demonstrated a similar distribution of genetic and pharmacological dependencies across the light and dark genomes, suggesting that targeting the dark genome holds promise for cancer treatment. This study underscores the need for ongoing research on the dark genome to better comprehend the underlying mechanisms of cancer and develop more effective therapies.

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“…Identifying and targeting these differentially essential genes would mean hitting the cancerous cells avoiding the healthy ones. Although the most investigated, cancer is not the only disease for which the individuation and characterisation of EGs is of great interest [12,13]. A crucial issue concerning the prediction of EGs is the labelling process.…”

Section: Introductionmentioning

confidence: 99%

HELP: A computational framework for labelling and predicting human common and context-specific essential genes

Granata,

Maddalena,

Manzo

et al. 2024

Preprint

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Machine learning-based approaches are particularly suitable for identifying essential genes as they allow the generation of predictive models trained on features from multi-source data. Gene essentiality is neither binary nor static but determined by the context. The databases for essential gene annotation do not permit the personalisation of the context, and their update can be slower than the publication of new experimental data. We propose HELP (Human Gene Essentiality Labelling & Prediction), a computational framework for labelling and predicting essential genes. Its double scope allows for identifying genes based on dependency or not on experimental data. The effectiveness of the labelling method was demonstrated by comparing it with other approaches in overlapping the state-of-the-art EG annotations, where HELP demonstrated the best compromise between false and true positive rates. The gene attributes, including multi-omics and network embedding features, lead to high-performance prediction of EGs while confirming the existence of essentiality nuances.

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Essential genes from genome-wide screenings as a resource for neuropsychiatric disorders gene discovery

Cited by 6 publications

References 46 publications

Shedding Light on the Dark Genome: Insights into the Genetic, CRISPR-based, and Pharmacological Dependencies of Human Cancers and Disease Aggressiveness

Shedding Light on the Dark Genome: Insights into the Genetic, CRISPR-based, and Pharmacological Dependencies of Human Cancers and Disease Aggressiveness

Shedding light on the dark genome: Insights into the genetic, CRISPR-based, and pharmacological dependencies of human cancers and disease aggressiveness

HELP: A computational framework for labelling and predicting human common and context-specific essential genes

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