Biology subjects

Heinzl, M.

Publications and source records attributed to Heinzl, M..

5 recordsLinked to original sources

bioRxiv2025

Programmatic design and editing of cis-regulatory elements

The development of modern genome editing and DNA synthesis has enabled researchers to edit DNA sequences with high precision but has left unsolved the problem of designing these edits. We introduce Ledidi, a computational method that rephrases the discrete design task of choosing which edits to make as an easily solvable continuous optimization problem. Ledidi can use any pre-trained deep learning model to guide the optimization, yielding an edited sequence that exhibits the desired outcome while explicitly minimizing the number of edits used. When applied in dozens of settings, we find that Ledidis designs can precisely control transcription factor binding, chromatin accessibility, transcription, and enhancer activity in silico. By using several deep learning models simultaneously, we design cell type-specific enhancers and experimentally validate them in cellulo. Finally, we introduce the concept of an "affinity catalog", where the design task is repeated multiple times across continuous variants of the design target. We demonstrate how these catalogs can be used to interpret deep learning models and the impact of starting template sequences, and also to design regulatory elements that control transcriptional dosage while maintaining cell type-specificity.

bioinformatics↗

bioRxiv2024

Mutations in ErbB2 accumulating in the male germline measured by error-corrected sequencing

Mutations in the male germline are a driving force behind rare genetic diseases. Driver mutations enjoying a selective advantage expand to mutant clusters within the aged testis and are thus overrepresented in sperm with age. Other kinds of driver mutations, occurring prepubescently, have been the focus of recent attention given their high occurrence rate independent of age. Here, we investigated the ErbB2 gene via error-corrected sequencing and detected a high percentage of missense mutations, including recurrent mutations, which were observed mainly in the tyrosine kinase domain with likely functional consequences, as we verified for a subset via biophysical methods. While these mutations increased with age, we found no evidence that they originated from mutational clusters in the aged testis, and young donors also showed an accumulation of driver mutations, suggesting that mutational enrichment is not exclusive to the sexually mature germline but can occur earlier during germline development, and are likely evenly distributed in the testis and stable in size.

genetics↗

bioRxiv2021

Discovery of an unusual high number of de novo mutations in sperm of older men using duplex sequencing

De novo mutations (DNMs) are an important player in heritable diseases and evolution. Of particular interest are highly recurrent DNMs associated with congenital disorders that have been described as selfish mutations expanding in the male germline, thus becoming more frequent with age. Here, we have adapted duplex sequencing (DS), an ultra-deep sequencing method that renders sequence information on both DNA strands; thus, one mutation can be reliably called in millions of sequenced bases. With DS, we examined [~]4.5 kb of the FGFR3 coding region in sperm DNA from older and younger donors. We identified sites with variant frequencies of 10-4 to 10-5, with an overall mutation frequency of the region of [~]6x10-7. Some of the substitutions were re-current and were found at a higher variant frequency in older donors than in younger ones, or exclusively, in older donors. Also, older donors harbored more mutations associated with congenital disorders. Other mutations were present in both age groups suggesting that these might result from a different mechanism (e.g., post-zygotic mosaicism). We also observed that independent of age, the frequency and deleteriousness of the mutational spectra was more similar to COSMIC than to gnomAD variants. Our approach is an important strategy to identify mutations that could be associated with a gain-of-function of the receptor tyrosine kinase activity, with unexplored consequences in a society with delayed fatherhood.

genetics↗

bioRxiv2019

Increased yields of duplex sequencing data by a series of quality control tools

Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences, and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics tool-set that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain PCR and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which result in unpaired families that do not form DCS. Finally, we also developed a tool called Variant Analyzer that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. We demonstrate that this tool identified false positive variants tagged by the tier-based classification. Furthermore, with this tool we can include reads without a family and check the reliability of the call, which increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

genomics↗

bioRxiv2018

Family reunion via error correction: An efficient analysis of duplex sequencing data

Duplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost--sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are, technically, thrown away. In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows \"reuniting\" these reads with their respective families increasing the output of the method and making it more cost effective. Additionally, we combine error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0, readily available through Galaxy, Bioconda, and as the source code.

bioinformatics↗