Mitochondrial mutations are increasingly recognised as informative endogenous genetic markers that can be used to reconstruct cellular clonal structure using single-cell RNA or DNA sequencing data. However, identifying informative mtDNA variants in noisy and sparse single-cell sequencing data is still challenging with few computation methods available. Here we present an open source computational tool MQuad that accurately calls clonally informative mtDNA variants in a population of single cells, and an analysis suite for complete clonality inference, based on single cell RNA, DNA or ATAC sequencing data. Through a variety of simulated and experimental single cell sequencing data, we showed that MQuad can identify mitochondrial variants with both high sensitivity and specificity, outperforming existing methods by a large extent. Furthermore, we demonstrate its wide applicability in different single cell sequencing protocols, particularly in complementing single-nucleotide and copy-number variations to extract finer clonal resolution.
Traditional carrier screening has been utilized for the detection of carriers of genetic disorders. Since a comprehensive assessment of the carrier frequencies of recessive conditions in the Southern Chinese population is not yet available, we performed a secondary analysis on the spectrum and carrier status for 315 genes causing autosomal recessive disorders in 1543 Southern Chinese individuals with next-generation sequencing data, 1116 with exome sequencing and 427 with genome sequencing data. Our data revealed that 1 in 2 people (47.8% of the population) was a carrier for one or more recessive conditions, and 1 in 12 individuals (8.30% of the population) was a carrier for treatable inherited conditions. In alignment with current American College of Obstetricians and Gynecologists (ACOG) pan-ethnic carrier recommendations, 1 in 26 individuals were identified as carriers of cystic fibrosis, thalassemia, and spinal muscular atrophy in the Southern Chinese population. When the >1% expanded carrier screening rate recommendation by ACOG was used, 11 diseases were found to meet the criteria in the Southern Chinese population. Approximately 1 in 3 individuals (35.5% of the population) were carriers of these 11 conditions. If the 1 in 200 carrier frequency threshold is used, and additional seven genes would meet the criteria, and 2 in 5 individuals (38.7% of the population) would be detected as a carrier. This study provides a comprehensive catalogue of the carrier spectrum and frequency in the Southern Chinese population and can serve as a reference for careful evaluation of the conditions to be included in expanded carrier screening for Southern Chinese people.
Mitochondrial mutations are increasingly recognised as informative endogenous genetic markers that can be used to reconstruct cellular clonal structure using single-cell RNA or DNA sequencing data. However, there is a lack of effective computational methods to identify informative mtDNA variants in noisy and sparse single-cell sequencing data. Here we present an open source computational tool MQuad that accurately calls clonally informative mtDNA variants in a population of single cells, and an analysis suite for complete clonality inference, based on single cell RNA or DNA sequencing data. Through a variety of simulated and experimental single cell sequencing data, we showed that MQuad can identify mitochondrial variants with both high sensitivity and specificity, outperforming existing methods by a large extent. Furthermore, we demonstrated its wide applicability in different single cell sequencing protocols, particularly in complementing single-nucleotide and copy-number variations to extract finer clonal resolution. MQuad is a Python package available via https://github.com/single-cell-genetics/MQuad.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.