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DNA rearrangements are important in various contexts, such as in vertebrate immunity, and cancer genome instability. The single-celled eukaryoteOxytricha trifallaxundergoes massive and reproducible genome rearrangement during post-zygotic development, making it a compelling model organism to study DNA rearrangements. To date, computational tools for the extraction and analysis of rearrangement annotations lack transparency and rely on assumptions that may not hold for all analyzed data, leading to irreproducibility of results and loss of information through data filtering or misrepresentation.An implementation of a procedure for the annotation and analysis of DNA rearrangement as a web application is discussed and tested. The resulting annotations provide an improvement over previous annotations in the following manner. (a) SDRAP achieves more complete precursor-product mappings than previous software (b) the software allows for full transparency of all parameters used during the annotation and therefore facilitates reproducible results, and (c) this parameter transparency makes SDRAP suitable for comparison of genomic data from different sources, including cancer genomes.This work introduces a theoretical framework and software to systematically extract and analyze annotations from pairs of genome assemblies corresponding to precursor and product rearrangement data. The software makes no assumptions about the structure of the rearrangements, and permits the user to select parameters to suit the data.

RT-qPCR is the de facto reference method for detecting the presence of SARS-CoV-2 genomic material in infected individuals (1). Although RT-qPCR is inherently quantitative and despite SARS-CoV-2 viral loads varying by 10 orders of magnitude and therefore being potentially highly clinically informative, in practice SARS-CoV-2 RT-qPCR results are usually reported qualitatively as simply positive or negative. This is both because of the mathematical complexity of converting from Ct values to viral loads and because the same Ct value can correspond to orders-of-magnitude differences in viral load depending on the testing platform (2, 3, 4). To address this problem, here we present ct2vl, a Python package designed to help individual clinical laboratories, investigators, and test developers convert from Ct values to viral loads on their own platforms, using only the data generated during validation of those platforms. It allows any user to convert Ct values to viral loads and is readily applicable to other RT-qPCR tests. ct2vl is open source, has 100% code coverage, and is freely available via the Python Package Index (PyPI).IMPORTANCEUp to now, COVID-19 test results have been reported as positive vs. negative, even though “positive” can mean anywhere from 1 copy of SARS-CoV-2 virus per milliliter of transport media to over 1 billion copies/mL, with attendant clinical consequences. Democratizing access to this quantitative data is the first step toward its eventual incorporation into test development, the research literature, and clinical care.

Ciliates have two different types of nuclei per cell, with one acting as a somatic, transcriptionally active nucleus (macronucleus; abbr. MAC) and another serving as a germline nucleus (micronucleus; abbr. MIC). Furthermore,Oxytricha trifallaxundergoes extensive genome rearrangements during sexual conjugation and post-zygotic development of daughter cells. These rearrangements are necessary because the precursor MIC loci are often both fragmented and scrambled, with respect to the corresponding MAC loci. Such genome architectures are remarkably tolerant of encrypted MIC loci, because RNA-guided processes during MAC development reorganize the gene fragments in the correct order to resemble the parental MAC sequence. Here, we describe the germline organization of several nested and highly scrambled genes inOxytricha trifallax. These include cases with multiple layers of nesting, plus highly interleaved or tangled precursor loci that appear to deviate from previously described patterns. We present mathematical methods to measure the degree of nesting between precursor MIC loci, and revisit a method for a mathematical description of scrambling. After applying these methods to the chromosome rearrangement maps ofO. trifallaxwe describe cases of nested arrangements with up to five layers of embedded genes, as well as the most scrambled loci inO. trifallax.

It has been shown that alternating attachments of two types (species) of floating molecular (DNA based) tiles on a predesigned array that consists of communicating neighboring DNA tiles complementary to the floating tiles can dynamically simulate some types of cellular automata (CA). We show that the model can simulate any elementary one dimensional CA confirming the universal computational power of the model. We address the question of which design of the platform array provides communication across the whole plane. We show that for square tiles only the checkerboard arrangement of the two species can provide communication between any two tiles of the plane. On the other hand, there are an uncountable number of arrangements of two colors of hexagonal tiles on the plane which provide communication between any two tiles.