scholarly journals Comprehensive analysis of RNA-seq and whole genome sequencing data reveals no evidence for SARS-CoV-2 integrating into host genome

2021 ◽  
Author(s):  
Yu-Sheng Chen ◽  
Shuaiyao Lu ◽  
Bing Zhang ◽  
Tingfu Du ◽  
Wen-Jie Li ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Comprehensive Analysis ◽  
Host Genome ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Rna Seq ◽  
Sequencing Data

scholarly journals Comprehensive analysis of RNA-seq and whole genome sequencing data reveals no evidence for SARS-CoV-2 integrating into host genome

2021 ◽  
Author(s):  
Yu-Sheng Chen ◽  
Shuaiyao Lu ◽  
Bing Zhang ◽  
Tingfu Du ◽  
Wen-Jie Li ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rna Virus ◽  
Comprehensive Analysis ◽  
Host Genome ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Rna Seq ◽  
Sequencing Data ◽  
Infected Cells

SARS-CoV-2, as the causation of severe epidemic of COVID-19, is one kind of positive single-stranded RNA virus with high transmissibility. However, whether or not SARS-CoV-2 can integrate into host genome needs thorough investigation. Here, we performed both RNA sequencing (RNA-seq) and whole genome sequencing on SARS-CoV-2 infected human and monkey cells, and investigated the presence of host-virus chimeric events. Through RNA-seq, we did detect the chimeric host-virus reads in the infected cells. But further analysis using mixed libraries of infected cells and uninfected zebrafish embryos demonstrated that these reads are falsely generated during library construction. In support, whole genome sequencing also didn't identify the existence of chimeric reads in their corresponding regions. Therefore, the evidence for SARS-CoV-2's integration into host genome is lacking.

scholarly journals Whole genome sequencing reveals high differentiation, low levels of genetic diversity and short runs of homozygosity among Swedish wels catfish

Heredity ◽  
2021 ◽  
Author(s):  
Axel Jensen ◽  
Mette Lillie ◽  
Kristofer Bergström ◽  
Per Larsson ◽  
Jacob Höglund
Keyword(s):  
Genetic Diversity ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Peripheral Populations ◽  
Whole Genome ◽  
Runs Of Homozygosity ◽  
Sequencing Data ◽  
Isolated Populations ◽  
Native Populations

AbstractThe use of genetic markers in the context of conservation is largely being outcompeted by whole-genome data. Comparative studies between the two are sparse, and the knowledge about potential effects of this methodology shift is limited. Here, we used whole-genome sequencing data to assess the genetic status of peripheral populations of the wels catfish (Silurus glanis), and discuss the results in light of a recent microsatellite study of the same populations. The Swedish populations of the wels catfish have suffered from severe declines during the last centuries and persists in only a few isolated water systems. Fragmented populations generally are at greater risk of extinction, for example due to loss of genetic diversity, and may thus require conservation actions. We sequenced individuals from the three remaining native populations (Båven, Emån, and Möckeln) and one reintroduced population of admixed origin (Helge å), and found that genetic diversity was highest in Emån but low overall, with strong differentiation among the populations. No signature of recent inbreeding was found, but a considerable number of short runs of homozygosity were present in all populations, likely linked to historically small population sizes and bottleneck events. Genetic substructure within any of the native populations was at best weak. Individuals from the admixed population Helge å shared most genetic ancestry with the Båven population (72%). Our results are largely in agreement with the microsatellite study, and stresses the need to protect these isolated populations at the northern edge of the distribution of the species.

scholarly journals Identification of individuals by trait prediction using whole-genome sequencing data

2017 ◽  
Vol 114 (38) ◽  
pp. 10166-10171 ◽  
Author(s):  
Christoph Lippert ◽  
Riccardo Sabatini ◽  
M. Cyrus Maher ◽  
Eun Yong Kang ◽  
Seunghak Lee ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Predictive Accuracy ◽  
Large Fraction ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Demographic Information ◽  
Personal Privacy ◽  
Sequencing Data ◽  
Legal Implications

Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.

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