Nanopore long-read next-generation sequencing for detection of mitochondrial DNA large-scale deletions.

Front Genet

Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.

Published: June 2023

Primary mitochondrial diseases are progressive genetic disorders affecting multiple organs and characterized by mitochondrial dysfunction. These disorders can be caused by mutations in nuclear genes coding proteins with mitochondrial localization or by genetic defects in the mitochondrial genome (mtDNA). The latter include point pathogenic variants and large-scale deletions/rearrangements. MtDNA molecules with the wild type or a variant sequence can exist together in a single cell, a condition known as mtDNA heteroplasmy. MtDNA single point mutations are typically detected by means of Next-Generation Sequencing (NGS) based on short reads which, however, are limited for the identification of structural mtDNA alterations. Recently, new NGS technologies based on long reads have been released, allowing to obtain sequences of several kilobases in length; this approach is suitable for detection of structural alterations affecting the mitochondrial genome. In the present work we illustrate the optimization of two sequencing protocols based on long-read Oxford Nanopore Technology to detect mtDNA structural alterations. This approach presents strong advantages in the analysis of mtDNA compared to both short-read NGS and traditional techniques, potentially becoming the method of choice for genetic studies on mtDNA.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10344361PMC
http://dx.doi.org/10.3389/fgene.2023.1089956DOI Listing

Publication Analysis

Top Keywords

next-generation sequencing
8
mitochondrial genome
8
mtdna
8
structural alterations
8
mitochondrial
6
nanopore long-read
4
long-read next-generation
4
sequencing detection
4
detection mitochondrial
4
mitochondrial dna
4

Similar Publications

Article Synopsis
  • The emergence of Next Generation Sequencing (NGS) technology has transformed clinical diagnostics, providing extensive microbiome data for personalized medicine.
  • Despite its potential, microbiome data's complexity and variability pose challenges for traditional statistical and machine learning approaches, including deep learning.
  • The paper presents a novel feature engineering technique that combines two data feature sets, significantly improving the Deep Neural Network's performance in colorectal cancer detection, raising the Area Under the Curve (AUC) from 0.800 to 0.923, thus enhancing microbiome data analysis and disease detection capabilities.
View Article and Find Full Text PDF

The extent of functional sequences within the human genome is a pivotal yet debated topic in biology. Although high-throughput reverse genetic screens have made strides in exploring this, they often limit their scope to known genomic elements and may introduce non-specific effects. This underscores the urgent need for novel functional genomics tools that enable a deeper, unbiased understanding of genome functionality.

View Article and Find Full Text PDF

Purpose: To examine the association between blastocyst morphology and chromosomal status utilizing pre-implantation genetic testing for aneuploidy (PGT-A).

Methods: A single-center retrospective cohort study including 169 in-vitro fertilization cycles that underwent PGT-A using Next Generation Sequencing (2017-2022). Blastocysts were morphologically scored based on Gardner and Schoolcraft's criteria.

View Article and Find Full Text PDF

Objective: Endometrial cancers can be classified into 4 molecular sub-groups: (1) POLE mutated (POLEmut), (2) mismatch repair deficiency/microsatellite-instable (MMRd/MSI-H), (3) TP53-mutant or p53 abnormal (p53abn), and (4) no specific mutational profile (NSMP). Although molecular classification is increasingly applied in oncology, its role in guiding fertility-sparing treatments for endometrial cancer remains unclear. This study examines the prognostic role of molecular classification in fertility-sparing treatment and its potential to guide treatment decisions.

View Article and Find Full Text PDF

Telomemore enables single-cell analysis of cell cycle and chromatin condensation.

Nucleic Acids Res

January 2025

Laboratory for Molecular Infection Medicine Sweden (MIMS), Umeå University, Biomedicinbyggnaden 6K och 6L, Umeå universitetssjukhus, 901 87, Umeå, Sweden.

Single-cell RNA-seq methods can be used to delineate cell types and states at unprecedented resolution but do little to explain why certain genes are expressed. Single-cell ATAC-seq and multiome (ATAC + RNA) have emerged to give a complementary view of the cell state. It is however unclear what additional information can be extracted from ATAC-seq data besides transcription factor binding sites.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!