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Heintz, J.

Publications and source records attributed to Heintz, J..

3 recordsLinked to original sources

The draft genome of the microscopic Nemertoderma westbladi sheds light on the evolution of Acoelomorpha genomes

BackgroundXenacoelomorpha is a marine phylum of microscopic worms that is an important model system for understanding the evolution of key bilaterian novelties, such as the nervous or excretory systems. Nevertheless, Xenacoelomorpha genomics has been restricted to the few species that either can be cultured in the lab or are centimetres long. Thus far, no genomes are available for Nemertodermatida, one of the phylums main clades and whose origin has been dated more than 400 million years ago. ResultsWe present the first nemertodermatid genome sequenced from a single specimen of Nemertoderma westbladi. Although genome contiguity remains challenging (N50: 48 kbps), it is very complete (BUSCO: 81.4%, Metazoa; 91.8%, Eukaryota) and the quality of the annotation allows fine-detail analyses of genome evolution. Acoelomorph genomes seem to be conserved in terms of the percentage of repeats, number of genes, number of exons per gene and intron size. In addition, a high fraction of genes present in both protostomes and deuterostomes are absent in Acoelomorpha. Interestingly, we show that all genes related to the excretory system are present in Xenacoelomorpha but Osr, a key element in the development of these organs and whose acquisition might explain the origin of the specialised excretory system. ConclusionsOverall, these analyses highlight the potential of the Ultra-Low Input DNA protocol and HiFi to generate high-quality genomes from single animals, even for relatively large genomes, making it a feasible option for sequencing challenging taxa, which will be an exciting resource for comparative genomics analyses.

evolutionary biology↗

Intra-individual changes in the frequency of mosaic loss of chromosome Y over time estimated with a new method

BackgroundMosaic loss of chromosome Y (LOY) is the most common somatic mutation and is associated with all-cause mortality, non-haematological cancers and Alzheimers disease among other outcomes. The predominant method used for estimating LOY is the intensity data generated by SNP-arrays, which is difficult to interpret due to its logarithmic scale. Here we describe a new way to convert the LOY mosaicism into a non-logarithmic scale, which instead represents the percentage of affected cells.\n\nMethodsWe compared three independent LOY readouts from matched samples, generated by SNP-array, whole genome sequencing and droplet digital PCR. The SNP-array standardization was derived from this comparison and was applied in analyses of serially collected samples from a large cohort of aging men. The sampling was performed up to five times, spanning up to 22 years.\n\nResultsWe observed a higher correlation between the LOY measurements from SNP-array and the two other readouts when using the standardized, instead of the logarithmic, SNP-array data. We also observed a pronounced intra-individual variation of changes in the frequency of LOY within individual males over time.\n\nConclusionsDescribing LOY measurements generated from SNP-arrays in percentage of cells without the Y chromosome makes comparisons to WGS and ddPCR measurements more precise and easier to interpret. This standardization could be applied to the vast amount of SNP-array data already generated in the scientific community, allowing further discoveries of LOY associated disease and outcomes. Additionally, the frequency of LOY in this study changed profoundly within men over time, likely as a result of aberrant clonal expansions.

genetics↗

SequencEnG: an Interactive Knowledge Base of Sequencing Techniques

Next-generation sequencing (NGS) techniques are revolutionizing biomedical research by providing powerful methods for generating genomic and epigenomic profiles. The rapid progress is posing an acute challenge to students and researchers to stay acquainted with the numerous available methods. We have developed an interactive online educational resource called SequencEnG (acronym for Sequencing Techniques Engine for Genomics) to provide a tree-structured knowledge base of 66 different sequencing techniques and step-by-step NGS data analysis pipelines comparing popular tools. SequencEnG is designed to facilitate barrier-free learning of current NGS techniques and provides a user-friendly interface for searching through experimental and analysis methods. SequencEnG is part of the project KnowEnG (Knowledge Engine for Genomics) and is freely available at http://education.knoweng.org/sequenceng/.

bioinformatics↗