Whole Exome Sequencing
Whole Exome Sequencing - Related Videos
08:22
A Novel Strategy Combining Array-CGH, Whole-exome Sequencing and In Utero Electroporation in Rodents to Identify Causative Genes for Brain Malformations
0 Views •
2017
Periventricular nodular heterotopia (PNH) is the most common form of malformation of cortical development (MCD) in adulthood but its genetic basis remains unknown in most sporadic cases. We have recently developed a strategy to identify novel candidate genes for MCDs and to directly confirm their causative role in vivo.
08:53
Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma
0 Views •
Cited by 9 •
2017
Here, we describe a combined flow cytometric cell sorting and low-input, next-generation library construction protocol designed to produce high-quality, whole-exome data from the Hodgkin Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (CHL).
08:57
Amplicon Sequencing using the Long-Read Sequencing Technologies
0 Views •
2025
This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.
07:30
Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
0 Views •
Cited by 19 •
2020
This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.
02:02
Cis-regulatory Sequences
0 Views •
2020
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
FAQs
Fragmentation first creates DNA pieces that can be processed for selective enrichment. A capture step then concentrates sequences from exons, while next-generation sequencing generates reads from the enriched material. Computational alignment places those reads against a reference genome, enabling subsequent variant detection and interpretation. Each stage helps convert a complex DNA sample into relevant sequence information.
Broad coverage matters when a patient’s clinical features do not identify one likely gene. Examining exonic regions across nearly all genes allows the analysis to look beyond an initial candidate and consider multiple possible genetic explanations. This is particularly useful for rare inherited disorders and conditions whose genetic basis may involve more than one gene or a complex pattern.
Instead of restricting analysis to a preselected candidate, this method surveys coding regions across nearly all genes. That broader scope can be valuable when clinical findings do not point clearly to one gene, because the analysis is not limited at the outset to a single suspected explanation. It therefore supports investigation of genetically complex conditions as well as rare inherited disorders.
Detection identifies DNA variants, but interpretation connects those findings with their possible relevance to health and disease. That distinction matters because sequencing produces genomic information that still requires evaluation before it can inform a medical question. In practice, interpretation turns variant calls into evidence that can support diagnosis or research.
In clinical medicine, the method can support diagnosis of rare inherited disorders when the responsible genetic change is not apparent from clinical features alone. It also helps investigate genetically complex conditions, where a narrow candidate-focused approach may not capture the relevant possibilities. Its value is greatest when clinicians need broad genomic evidence to explore an uncertain diagnosis.
The resulting variant information can support research into disease mechanisms and treatment responses. By examining coding changes across nearly all genes, investigators can study genetically complex conditions without limiting the work to one preselected gene. This links sequence analysis with questions about how disease develops and how genetic findings relate to responses to treatment.