# Ct Value from RT-qPCR Can Predict SARS-CoV-2 Virus Assembly and Lineage Assignment Success
## 4 Discussion  
Although we originally performed our study with a focus on the identification of potential novel biomarkers resulting from human transcriptome and metacranscriptome analysis of samples from COVID-19 patients with different severity of the disease, here, we reported dependency of SARS-CoV-2 genome assembly and lineage assignment on Ct value from diagnostic RT-qPCR. This work is a collateral output of the complex research but is an independent and specifically focused part of it and a brief report of this finding. Exploring the relationship between RT-qPCR Ct value and further analysis of data on the virus would be logical (through higher viral load leading to more viral reads in the dataset), and it certainly was questioned before; however, here we confirmed and described this relationship in a specific experimental design for a metacranscriptomic study. This means that RNA sequencing of human tissue from COVID-19 patients containing viral reads between those of humans and bacteria was analyzed instead of using the standard procedure for genome assembly with viral RNA isolation. We performed multiple steps of data analysis to achieve the observation. First, assembly of the genome was necessary. There are various assemblers fit for this job. The benchmarking study by [PERSON] and [PERSON] (2022) recommends SPAdes, IDBA, and ABySS out of the eight assemblers they tested [17]. We tested the performance of SPAdes our  
Figure 1: Dot plot graph showing relationship between SARS-CoV-2 assembly success (NG50 value) and RT-qPCR Ct value. Here, we can see 3 highlighted zones—the green zone under Ct value \(<\) 25, where all samples were assembled into a complete genome, and the grey zone between Ct values of 25 and 30 where genomes were assembled completely, fragmented, or assembly failed. None of the samples over Ct value 30 were assembled into the SARS-CoV-2 genome. selves, trying various strategies as well as Trinity, which was not compared by [PERSON] and [PERSON] (2022). These results are about to be published as \"Possibilities of assembling whole genome of clinically relevant pathogens directly from clinical samples sequenced as metatranscriptomic data\" ([PERSON] et al., 2023). For presenting results here, we chose the best-performing assembly strategy. It was observed that samples with a Ct value under 25 were always assembled, samples between Ct values of 25 and 30 were in a kind of grey zone--where assembly might be successful, but not always--and samples over a Ct value of 30 were never successfully assembled. Previously published studies have shown that the use of different approaches for SARS-CoV-2 genome sequencing is capable, although targeted resequencing (either amplicon or hybridization-based) with subsequent full genome assembly involved were working horses when it comes to massively applied diagnostic and epidemiologic surveillance studies. Additionally, short- as well as long-read sequencing solutions were used with an acceptable ratio when it comes to turn-around times, throughput, and cost-effectiveness of such testing [6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18]. However, when it comes to the research potential with the focus not only on diagnostics but also complex study of viral infection and local and potentially global host reaction, the most relevant strategy is the metatranscriptomic analysis starting directly from clinical samples. With this approach, the host transcriptome, microbiome, as well as viral genome could be analyzed in parallel if there is enough of the viral genome; in addition, a full viral genome could be assembled. In a comprehensive study by [PERSON] et al. of complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serial dilutions of a cultured isolate as well as clinical samples covering a range of sample types and viral loads were analyzed and, in the case of metatranscriptomic analyses, similar findings as in our study were reported.