| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T99 |
0-23 |
Sentence |
denotes |
Bioinformatics analysis |
| T100 |
24-273 |
Sentence |
denotes |
S protein reference sequences for SARS-CoV-1, SARS-CoV-2, batRaTG13, Middle East respiratory syndrome (MERS) and human common-cold coronaviruses 229E, NL63, OC43 and HKU1 were downloaded from the National Center for Biotechnology Information (NCBI). |
| T101 |
274-555 |
Sentence |
denotes |
A multiple sequence alignment was created with multiple alignment using fast Fourier transform (MAFFT) using the slow but accurate L-INS-I parameter settings [24] and the alignment curated, cut to the target region 1029–1192 (SARS-CoV-1 numbering) and visualised with Jalview [25]. |
| T102 |
556-883 |
Sentence |
denotes |
We used Molecular Evolutionary Genetics Analysis (MEGA) X [26] to calculate the number of amino-acid differences for all sequence pairs in the alignment of the mAb target region and the full S protein normalised by the length of the aligned sequence of the respective reference protein to obtain per cent amino acid identities. |
| T103 |
884-1079 |
Sentence |
denotes |
To determine SARS-CoV-2 sequence diversity in the S protein within the current pandemic, 230 human and environmental viral sequences were downloaded from GISAID’s EpiCoV database on 1 March 2020. |
| T104 |
1080-1220 |
Sentence |
denotes |
We gratefully acknowledge the authors, originating and submitting laboratories of the sequences on which this part of the research is based. |
| T105 |
1221-1267 |
Sentence |
denotes |
The list is detailed in Supplementary Table 1. |
| T106 |
1268-1379 |
Sentence |
denotes |
The nt sequences were searched with basic local alignment search tool (BLAST)X against the reference S protein. |
| T107 |
1380-1533 |
Sentence |
denotes |
174 hits covered the full length of the S protein and amino-acid mutations were counted and tabulated using a custom Perl script (Supplementary Table 2). |
