A hybrid pipeline for reconstruction and analysis of viral genomes at multi-organ level

Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

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“…DS1 : 2 compilations of FASTQ data, namely, a human virome (Virome) [ 88 ] and ancient DNA from a Denisova individual (Denisova) [ 89 ];…”

Section: Resultsmentioning

confidence: 99%

Efficient DNA sequence compression with neural networks

2020

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“…Each animal or plant host individual becomes the equivalent of a single culture. One challenge of applying our approach in this context, of course, is that the environment inside of a multicellular organism introduces considerable tissue heterogeneity that can give rise to different dynamics and evolution in different parts of the organism ( 27 , 30 , 31 ). An additional challenge for our continuous-time estimation lies in our model’s assumption that the selective cost of the transgene is tied to microbial growth rate.…”

Section: Discussionmentioning

confidence: 99%

Methods for measuring the evolutionary stability of engineered genomes to improve their longevity

et al. 2021

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Diverse applications rely on engineering microbes to carry and express foreign transgenes. This engineered baggage rarely benefits the microbe and is thus prone to rapid evolutionary loss when the microbe is propagated. For applications where a transgene must be maintained for extended periods of growth, slowing the rate of transgene evolution is critical and can be achieved by reducing either the rate of mutation or the strength of selection. Because the benefits realized by changing these quantities will not usually be equal, it is important to know which will yield the greatest improvement to the evolutionary half-life of the engineering. Here, we provide a method for jointly estimating the mutation rate of transgene loss and the strength of selection favoring these transgene-free, revertant individuals. The method requires data from serial transfer experiments in which the frequency of engineered genomes is monitored periodically. Simple mathematical models are developed that use these estimates to predict the half-life of the engineered transgene and provide quantitative predictions for how alterations to mutation and selection will influence longevity. The estimation method and predictive tools have been implemented as an interactive web application, MuSe.

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“…We then compared the viral DNA findings of the frozen samples with those of the formalin-fixed (both FF and FFPE). From the total of 29 positive hits for viral DNA found in the frozen tissues of the four individuals, by day 1 the total virus positivity was 23 in both the FF and FFPE groups and moderately decreased along longer incubation times (FF: 24,18,17,19,16,and FFPE: 23,19,19,18,20 for days 2, 4, 6, 8 and 10, respectively). The increase in the number of FN calls from day 2 to day 10 was more consistent in the FF group, extracted with standard tissue kit, than in the FFPE group, extracted with dedicated FFPE protocol, although not statistically significant (FF: p-value 0.22 and FFPE: p-value 0.61).…”

Section: Viral Dna Detection In Frozen Controls and Formalin-fixed Sa...mentioning

confidence: 95%

“…The viral genomic sequences were reconstructed using alignment-based and de novo assembly with TRACESPipe [18]. Precisely, the adapter sequences were trimmed using Trimmomatic by removing content from an adapters' list, with a maximum mismatch that allowed a full match of 2.…”

Section: Ngs Data Analysismentioning

confidence: 99%

Detection of Low-Copy Human Virus DNA upon Prolonged Formalin Fixation

Mielonen

Pratas

Hedman

et al. 2022

Viruses

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Formalin fixation, albeit an outstanding method for morphological and molecular preservation, induces DNA damage and cross-linking, which can hinder nucleic acid screening. This is of particular concern in the detection of low-abundance targets, such as persistent DNA viruses. In the present study, we evaluated the analytical sensitivity of viral detection in lung, liver, and kidney specimens from four deceased individuals. The samples were either frozen or incubated in formalin (±paraffin embedding) for up to 10 days. We tested two DNA extraction protocols for the control of efficient yields and viral detections. We used short-amplicon qPCRs (63–159 nucleotides) to detect 11 DNA viruses, as well as hybridization capture of these plus 27 additional ones, followed by deep sequencing. We observed marginally higher ratios of amplifiable DNA and scantly higher viral genoprevalences in the samples extracted with the FFPE dedicated protocol. Based on the findings in the frozen samples, most viruses were detected regardless of the extended fixation times. False-negative calls, particularly by qPCR, correlated with low levels of viral DNA (<250 copies/million cells) and longer PCR amplicons (>150 base pairs). Our data suggest that low-copy viral DNAs can be satisfactorily investigated from FFPE specimens, and encourages further examination of historical materials.

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A hybrid pipeline for reconstruction and analysis of viral genomes at multi-organ level

Cited by 19 publications

References 42 publications

Efficient DNA sequence compression with neural networks

Efficient DNA sequence compression with neural networks

Methods for measuring the evolutionary stability of engineered genomes to improve their longevity

Detection of Low-Copy Human Virus DNA upon Prolonged Formalin Fixation

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