from Frontline Genomics by Megan Hickland
Genomic data are an excellent source of novel disease biomarkers and targets. In fact, genetically validated targets are twice as likely to achieve FDA approval (King et al. 2019). The next-generation sequencing (NGS) technology that underlies these discoveries is now commonplace in many research labs. Validation of target expression by RNA sequencing (bulk-RNA-seq) is also common once a gene of interest is identified. However, in a mixed population of cells, biomarkers and targets of interest are expressed at varying levels – bulk-RNA-seq is only capable of reporting on the average gene expression. As a result, important differences in gene expression as a function of cell type or location may be missed by researchers.
(read more…)
from Frontline Genomics by Megan Hickland
Genomic data are an excellent source of novel disease biomarkers and targets. In fact, genetically validated targets are twice as likely to achieve FDA approval (King et al. 2019). The next-generation sequencing (NGS) technology that underlies these discoveries is now commonplace in many research labs. Validation of target expression by RNA sequencing (bulk-RNA-seq) is also common once a gene of interest is identified. However, in a mixed population of cells, biomarkers and targets of interest are expressed at varying levels – bulk-RNA-seq is only capable of reporting on the average gene expression. As a result, important differences in gene expression as a function of cell type or location may be missed by researchers.
(read more…)
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from Frontline Genomics by Megan Hickland
Genomic data are an excellent source of novel disease biomarkers and targets. In fact, genetically validated targets are twice as likely to achieve FDA approval (King et al. 2019). The next-generation sequencing (NGS) technology that underlies these discoveries is now commonplace in many research labs. Validation of target expression by RNA sequencing (bulk-RNA-seq) is also common once a gene of interest is identified. However, in a mixed population of cells, biomarkers and targets of interest are expressed at varying levels – bulk-RNA-seq is only capable of reporting on the average gene expression. As a result, important differences in gene expression as a function of cell type or location may be missed by researchers.
(read more…)
Related Posts
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Worm’s radical transformation shows metamorphosis can change the functions of cells
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Scientists map dormant cancer cells’ hideouts, opening new targets for treatment
Soluble signals released by neighboring cells direct how the human kidney is built
Genetics influence how cancer arises – and how it evolves
RNA-based testing uncovers extraordinary diversity in mutations driving lung cancer
Study offers new insights into why ex-smokers remain at elevated risk of lung disease
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