Vyshedskiy, B. | bioRxiv Science

bioRxiv2026

Positive germline selection of mtDNA mutations: evidence from the oocyte.

Purifying selection is the removal of detrimental mutations. Nuclear DNA mutations are purged by removing mutant individuals, embryos, or germline cells. Because mtDNA is present in numerous copies per cell, purifying selection of mtDNA mutations introduces an additional layer of complexity. The intracellular mutant fraction can change due to clonal expansion/reduction of mutant mtDNA molecules in germline cells. Different research groups have reported either negative (purifying), or positive (destructive) germline mtDNA selection. In this study, we use recently published high-fidelity data on mtDNA mutations in individual human oocytes from the Makova laboratory (Arbeithuber et al., 2025) to resolve this disagreement. To assess selection, we used the "selective expansion" metric St, which compares the average weighted rate of clonal expansion in a set of mutations tested for selection (e.g. non-synonymous mutations) to that of the set of synonymous mutations. We found that, on average, noncoding oocyte mutations in the control region expand faster than synonymous mutations, i.e., are under positive selection. Intriguingly, mutations in the coding region, the detrimental ones in particular, were also on average under positive selection. The prescence of average positive selection does not preclude purifying selection against individual mutations; it only indicates that positive selection dominates in aggregate mutational dynamics. Positive selection impacts the dynamics of de novo germline mutations that arise in primordial germ cells or oocytes and have not yet been inherited by the next generation. Contrastly, mutations that are passed to subsequent generations are under average purifying selection. We suggest that initial positive selection begets subsequent purifying selection by increasing intracellular mutant fractions to levels at which their deleterious effects become phenotypically apparent and can be efficiently removed.

genetics↗

bioRxiv2025

Analyzing long-read CRISPR experiments with CRISPRLungo

Long-read sequencing can characterize complex genome editing-induced DNA sequence changes such as large deletions, insertions, and inversions that are difficult to detect using short-read sequencing. However, PCR amplification and sequencing errors complicate accurate variant detection, and existing analysis tools are not optimized for gene editing specific allelic outcomes. Here we present CRISPRLungo, a computational pipeline specifically designed for long-read amplicon sequencing of gene edited samples. CRISPRLungo incorporates unique molecular identifier (UMI)-based error correction and statistical filtering to distinguish true editing events from background noise, enabling robust detection of small indels and structural variants. Through systematic benchmarking using simulated datasets, we demonstrate that CRISPRLungo outperforms existing approaches in both accuracy and read recovery. CRISPRLungo supports both Oxford Nanopore and PacBio platforms and identify previously undetected structural variant edits such as inversions in published CRISPR datasets. To demonstrate allele-specific edit quantification, we applied CRISPRLungo to analyze edited primary cells from a patient with harboring compound heterozygous SBDS mutations, accurately quantifying SBDS editing outcomes despite contaminating reads from the homologous SBDSP1 pseudogene. To maximize accessibility, we developed a fully client-side web application requiring no installation, making advanced long-read analysis accessible to researchers regardless of computational expertise. CRISPRLungo is freely available at https://github.com/pinellolab/CRISPRLungo with a user-friendly web interface available at https://pinellolab.github.io/CRISPRLungo.

bioinformatics↗

bioRxiv2023

A novel, wave-shaped profile of germline selection of pathogenic mtDNA mutations is discovered by bypassing a classical statistical bias.

The shift of the level of disease-causing mtDNA mutations (heteroplasmy) from mother to child is typically negatively correlated with the mothers heteroplasmy (Hm). In other words, mothers with low Hm tend to have children with a higher mutation level (Hch) than their own. In contrast, mothers with high Hm typically see a decrease in heteroplasmy in their children. This trend has been commonly interpreted as a result of a descending germline selection profile, i.e., positive selection at low Hm, gradually turning negative at high Hm. Here we demonstrate, however, that the negative correlation is mostly driven by RTM, or Regression To the Mean, a classical statistical bias. We further show that RTM can be nullified by using the average between the mothers and childs heteroplasmy, as a new variable, instead of the commonly used mothers heteroplasmy in blood. Additionally, we demonstrate that mother/child average is a better approximation of the actual germline heteroplasmy. Moreover, the elimination of RTM revealed a previously hidden wave-shaped HS-profile (positive mother-to-child shift at intermediate average mother-child heteroplasmy, decreasing towards high and low average heteroplasmy). In confirmation of this finding, we show that simulations that involve both wave-shaped HS-profile and RTM, reproduce the observed patterns of inheritance of mtDNA mutations in unprecedented detail. From the health care perspective, the uncovering of the wave-shaped HS-profile (and the removal of the RTM bias) are crucial for families affected by mtDNA disease. From the fundamental perspective, the wave- shaped profile offers a novel understanding of the dynamics of mtDNA in the germline and a novel potential mechanism that prevents the spread of detrimental mtDNA mutations in the population. SignificanceFrom the clinical perspective, the existence of wave-shaped selection may improve predictions and decisions for families affected by mtDNA diseases. From the fundamental perspective, it provides insight into the dynamics of general mtDNA mutations in the germline and in the population, as long as they follow wave-shaped selection profile. In Fig. 1, blue and red arrows represent the direction of expected changes of the heteroplasmy in a lineage with time/generations. With wave- shaped selection (Fig. 1B), a great majority of nascent low- fraction mutations are expected to converge back to zero and vanish. However, due to random intracellular genetic drift, some mutations will, occasionally, expand and enter the range of positive selection. Then they will be expanded by the selection to higher, detrimental levels, and become prone to downstream removal via death of highly mutated germ cells or inability of highly sick individuals to continue their lineage. In this way, the wave-shaped selection may help to prevent the spread of detrimental mutations in the population and in the species. In contrast, if the descending selection profile (Fig. 1A) was in effect, the nascent low heteroplasmy detrimental mutations would have been pushed to intermediate heteroplasmy levels where they will stay longer in hidden disease carriers enabling effective spread of mutation in the population. O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/568140v2_fig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1142cc0org.highwire.dtl.DTLVardef@186002aorg.highwire.dtl.DTLVardef@74d176org.highwire.dtl.DTLVardef@163ca6c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO (Graphic Summary) Pathogenic mtDNA mutations that cause a host of devastating inherited diseases are usually thought to follow an intriguing inheritance trend: Mothers with low levels of mutation (called mother heteroplasmy, Hm) tend to bear children with higher child heteroplasmy (Hch) then their own which constitutes positive Heteroplasmy Shift (HS=Hch-Hm). In contrast, mothers with high heteroplasmy Hm bear children with lower heteroplasmy Hc (negative HS). C_FIG

genomics↗