Genome Assembly Experts - Was RaTG13 Fraudulently Constructed?
I like to make our readers be aware of the Chinese publications from where the claim that the virus came from bat originated. The key sequence to understand the origin of Covid is RaTG13, which you can download from here. You can also download the raw data files from NCBI SRA (SRX7724752 and SRX8357956).
Two preprints (here and here ) claimed that it was impossible to reconstruct RaTG13 from the submitted SRA data. I know that many genome assembly experts read this blog. Would you be able to verify the claims? I do not think you need heavy-duty genome assembly tools to assemble a viral genome.
Comments from the above preprints -
To this date, the most critical piece of evidence on the purposed “natural origin” theory of SARS-CoV-2, was the sequence known as RaTG13, allegedly collected from a single fecal sample from Rhinolophus Affinis. Understanding the provenance of RaTG13 is critical on the ongoing debate of the Origins of SARS-CoV-2. However, this sample is allegedly “used up” and therefore can no longer be accessed nor sequenced independently [1], and the only available data was the 3 related Genbank accessions: MN996532.1, SRX7724752 and SRX8357956.
The raw data of BtCoV/RaTG13Contained multiple anomalies that signifies that the original sample could not have contained enough RNA template for the extraction of a complete viral genome as in MN996532.1 Furthermore, many of these anomalies points toward the fraudulent use of a mixed DNA library, rather than genuine mRNA, for the sequencing of SRX7724752, evident by the presence of widespread A-T ligation of unrelated dsDNA fragments that can only happen if the same library preparation process have been ran on dsDNA instead of ssRNA. which would constitute Academic fraud.
Readers should also note that the authors of the Chinese papers got caught flat out lying about when they sequenced RaTG13, and they issued a late “addendum” to their claim that they did not have the sequence prior to 2020. You can find the details in this paper by Rossana Segreto and Yuri Deigin.
