Enhancing SARS-CoV-2 surveillance through regular genomic sequencing in Spain: the RELECOV network

Citation: Vázquez-Morón, S.; Iglesias-Caballero, M.; Lepe, J.A.; Garcia, F.; Melón, S.; Marimon, J.M.; García de Viedma, D.; Folgueira, M.D.; Galán, J.C.; López-Causapé, C.; et al. Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network. Int. J. Mol. Sci. 2023,24, 8573. https://doi.org/ 10.3390/ ijms24108573 Academic Editor: Nitin Saksena Received: 8 March 2023 Revised: 25 April 2023 Accepted: 3 May 2023 Published: 10 May 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). International Journal of Molecular Sciences Article Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network Sonia Vázquez-Morón1,2,* , María Iglesias-Caballero 1, JoséAntonio Lepe 3, Federico Garcia 4,5 , Santiago Melón6, JoséM. Marimon 7, Darío García de Viedma 8, Maria Dolores Folgueira 9,10 , Juan Carlos Galán2,11 , Carla López-Causapé12, Rafael Benito-Ruesca 13 , Julia Alcoba-Florez 14, Fernando Gonzalez Candelas 2,15 , María de Toro 16 , Miguel Fajardo 17, Carmen Ezpeleta 18, Fernando Lázaro 19, Sonia Pérez Castro 20 , Isabel Cuesta 21, Angel Zaballos 22 , Francisco Pozo 1,2 , Inmaculada Casas 1,2,* and on behalf of RELECOV Network Members † 1Respiratory Viruses and Influenza Unit, National Centre for Microbiology, Instituto de Salud Carlos III, 28222 Majadahonda, Spain 2CIBER de Epidemiología y Salud Pública (CIBERESP), ISCIII, 28029 Madrid, Spain 3Microbiology Service, Hospital Universitario Virgen del Rocio, 41013 Sevilla, Spain 4 Microbiology Service, Hospital Universitario San Cecilio, Instituto de Investigación Biosanitaria Ibs. Granada, 18016 Granada, Spain 5CIBER de Enfermedades Infecciosas (CIBERINFEC), ISCIII, 28029 Madrid, Spain 6Microbiology Service, Hospital Universitario Central de Asturias, 33011 Oviedo, Spain 7Microbiology Service, Instituto de Investigación Sanitaria Biodonostia, Hospital Universitario Donostia, 20014 Donostia-San Sebastian, Spain 8 Microbiology Service, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain 9Microbiology Department, Hospital Universitario 12 de Octubre, Biomedical Research Institute imas12, 28041 Madrid, Spain 10 Department of Medicine, School of Medicine, Universidad Complutense, 28040 Madrid, Spain 11 Microbiology Service, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), 28034 Madrid, Spain 12 Microbiology Service, Hospital Universitario Son Espases, 07120 Palma de Mallorca, Spain 13 Microbiology Service, Hospital Clínico Universitario Lozano Blesa, Departamento de Microbiología, Facultad de Medicina, Instituto de Investigación Sanitaria de Aragón, Universidad de Zaragoza, 50009 Zaragoza, Spain 14 Microbiology Service, Hospital Universitario Ntra. Sra de Candelaria, 38010 Santa Cruz de Tenerife, Spain 15 Joint Research Unit Infection and Public Health FISABIO-University of Valencia, Institute for Integrative Systems Biology (I2SysBio), 46020 Valencia, Spain 16 Plataforma de Genómica y Bioinformática, Centro de Investigación Biomédica de La Rioja (CIBIR), 26006 Logroño, Spain 17 Microbiology Service, Hospital Universitario de Badajoz, 06080 Badajoz, Spain 18 Complejo Hospitalario de Navarra and Navarra De Servicios Y Tecnologías S A (NASERTIC), 31008 Pamplona, Spain 19 Microbiology Service, Hospital Universitario La Paz, 28046 Madrid, Spain 20 Microbiology Service, Complexo Hospitalario Universitario de Vigo, 36204 Vigo, Spain 21 Bioinformatics Unit, Unidades Centrales Científico Técnicas, Instituto de Salud Carlos III, 28222 Majadahonda, Spain 22 Genomics Unit, Unidades Centrales Científico Técnicas, Instituto de Salud Carlos III, 28222 Majadahonda, Spain *Correspondence: [email protected] (S.V.-M.); [email protected] (I.C.) † RELECOV Network Members is provided in Supplementary File S2. Abstract: Millions of SARS-CoV-2 whole genome sequences have been generated to date. However, good quality data and adequate surveillance systems are required to contribute to meaningful surveillance in public health. In this context, the network of Spanish laboratories for coronavirus (RELECOV) was created with the main goal of promoting actions to speed up the detection, analyses, and evaluation of SARS-CoV-2 at a national level, partially structured and financed by an ECDC-HERA-Incubator action (ECDC/GRANT/2021/024). A SARS-CoV-2 sequencing quality control assessment (QCA) was developed to evaluate the network’s technical capacity. QCA full panel results showed a lower hit rate Int. J. Mol. Sci. 2023,24, 8573. https://doi.org/10.3390/ijms24108573 https://www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2023,24, 8573 2 of 17 for lineage assignment compared to that obtained for variants. Genomic data comprising 48,578 viral genomes were studied and evaluated to monitor SARS-CoV-2. The developed network actions showed a 36% increase in sharing viral sequences. In addition, analysis of lineage/sublineage-defining mutations to track the virus showed characteristic mutation profiles for the Delta and Omicron variants. Further, phylogenetic analyses strongly correlated with different variant clusters, obtaining a robust reference tree. The RELECOV network has made it possible to improve and enhance the genomic surveillance of SARS-CoV-2 in Spain. It has provided and evaluated genomic tools for viral genome monitoring and characterization that make it possible to increase knowledge efficiently and quickly, promoting the genomic surveillance of SARS-CoV-2 in Spain. Keywords: SARS-CoV-2; genomic surveillance Spain; laboratory network RELECOV; VOCs; lineages; national QCA; mutation; phylogeny 1. Introduction On 30 January 2020, the World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) outbreak a public health emergency of international concern (PHEIC) [ 1 ]. One week later, the WHO recommended a surveillance approach based on, or similar to, the Global Influenza Surveillance and Response System (GISRS) that facilitates less resource-intensive monitoring [ 2 ]. Thus, from the beginning of the pandemic caused by SARS-CoV-2 [ 3 – 5 ], the frantic race to sequence this virus began, promoted by rapid technological development. This has led to the description of millions of genome sequences to date from the first SARS-CoV-2 complete genome published from a patient with severe respiratory syndrome on 26 December 2019 [4]. This large amount of information on the SARS-CoV-2 genome has aroused different nomenclature systems, genome repositories, and web servers allowing the exchange of molecular information as well as its analysis. Currently, three nomenclature systems, with their own scientific approaches, are used to classify and track SARS-CoV-2. The Global Initiative on Sharing All Influenza Data (GISAID) offers EpiCoV TM that includes a data repository, nomenclature system, and many tools for viral analysis [ 6 ]. Additionally, the NEXSTRAIN web server allows SARS-CoV-2 genome analyses and visualizations of the data [ 7 ]. In addition, the third nomenclature system is known as Pangolin which was developed for the implementation of a dynamic nomenclature for SARS-CoV-2. This has been described by Rambaut et al. and is known as “Pango lineage” [ 8 , 9 ]. This tool is used to assign lineages based on complete virus genome sequences, date of detection, and geographical location, allowing us to delve into the viral genome, and its evolution and transmission. However, this system has generated more than a thousand lineages, which constitute a great challenge for their follow-up in public health. In this sense, in May 2021, the WHO announced the assignment of simple names, easy to say and remember for the variants designated as of concern (VOCs) or interest (VOIs), using the Greek alphabet and arguing to avoid stigmatization generated by the relationship between the variant and the country where it was discovered and developing a global risk-monitoring framework [ 10 ]. SARS-CoV-2 and other coronaviruses evolve rapidly through point mutations as well as recombination, specifically in the spike region which is both a recombination and a mutation hotspot in coronaviruses [ 11 , 12 ]. SARS-CoV-2 evolution studies estimated a substitution rate of 0.5 × 10 −3 –1.1 × 10 −3 substitutions/site/year, corresponding to a rate of 1.3 to 2.8 substitutions/month for the whole genome, and the increases in substitution rates have been related to the emergence of new variants [ 13 ]. However, the spike region, in particular, accumulates mutations much faster than other regions. The emergence of the Omicron variant was a great example, because it accumulated an unusually high number of mutations in the spike region that was not observed previously with any other VOC [ 12 ], and led to evidence of a substantial reduction of the antibody neutralizing activity against Omicron [14]. Int. J. Mol. Sci. 2023,24, 8573 3 of 17 These viral characteristics showed the need to increase molecular knowledge related to the transmission and spread of the virus that could raise concern, which is essential for public health. In this sense, not only is the massive generation of data important, but these must be of good quality and linked to the establishment of an adequate surveillance system in order to contribute to meaningful actions in public health. In this regard, the WHO and European Centre for Disease Prevention and Control (ECDC) guidance on implementing genomic SARS-CoV-2 surveillance were released in January and May 2021, respectively [ 15 , 16 ]. On the other hand, on 17 February 2021, the European Commission proposed immediate action to prepare Europe for the growing threat of coronavirus variants under a new plan promoted by the program “Health Emergency Preparedness and Response Authority (HERA) Incubator” [ 17 ]. In Spain, the creation of a network of Spanish laboratories (RELECOV) for genomic surveillance of SARS-CoV-2 was a priority starting from January 2021 and it was reflected in the document “Strategy for the integration of sequencing in the surveillance of SARS-CoV-2” [ 18 ]. The RELECOV network was then officially structured under the ECDC/HERA/2021/024 project “Enhancing whole genome sequencing (WGS) and/or reverse transcription polymerase chain reaction (RT-PCR), national infrastructures, and capacities to respond to the COVID-19 pandemic in Spain”. The network, composed initially of 43 member institutions, including some regional nodes with regional networks or well-defined consortia. The RELECOV’s main objectives include promoting actions to speed up SARS-CoV-2 genomic virus detection, analyses, and evaluation in Spain. RELECOV’s efforts to date have been focused on improving and enhancing the SARS-CoV-2 genomic surveillance directed at the circulating virus in Spain, through establishing national quality controls for sequencing performance and methodology implementation, implementing genomic analyses and sharing of the obtained sequences, tracking mutations in the genome and, finally, performing phylogenetic analyses to characterize the sequenced viral genomes to provide a global context to the viruses circulating in Spain. These actions are essential given the potential scenarios for the rise to new pathogens or variants, highlighting the need to continue research on coronaviruses and especially genomic surveillance [19]. 2. Results 2.1. Surveillance of Virus from Sequences Deposited in GISAID by the RELECOV Network The first six months from the structuring of the RELECOV network were evaluated by monitoring viral circulation and the progress in sequence sharing in Spain. For this purpose, three periods were established to observe network’s activity over time: two quarterly periods comprised of 05.09.2021 to 05.12.2021 and 06.12.2021 to 08.03.2022, and their corresponding semi-annual period (05.09.2021 to 08.03.2022). RELECOV’s complete sequences deposited in GISAID in the period between 05.09.2021 and 05.12.2021 showed a spectrum of up to two hundred different lineages. The classification of the corresponding variants showed 1185 Alpha, 87 Beta, 18,272 Delta, 96 Gamma, 171 Mu, 2 Iota, 8 Omicron, 40 Lambda, 27 Eta, 1 Epsilon, 1 VUM (Variant Under Monitoring), 483 NA (Not applicable, lineages circulating before variant assignment started) 61 with an unassigned lineage, and 3 classified as recombinant (Table 1). The results showed that the Variant of Concern (VOC) with the highest circulation in Spain during this period was Delta, followed to a lesser extent by Alpha, which is consistent with the worldwide patterns at that time. Between 06.12.2021 and 08.03.2022, the virus genomes deposited in GISAID belonged to 172 different lineages, corresponding to the following variant classification: 72 Alpha, 2 Beta, 12,733 Delta, 4 Gamma, 15 Mu, 15,251 Omicron, 1 recombinant (XG), 49 NA, and 16 with an unassigned lineage (Table 2). For this period, the obtained results allowed us to monitor the co-circulation of the Omicron and Delta variants in similar proportions, as well as the quick spreading of the Omicron variant during this period. Int. J. Mol. Sci. 2023,24, 8573 4 of 17 Table 1. SARS-CoV-2 viral sequences from Spain deposited in GISAID between 05.09.2021 and 05.12.2021. Variant Number of Sequences Number of Lineages Alpha 1185 3 Beta 87 2 Gamma 96 9 Delta 18,272 126 Mu 171 3 Omicron 8 4 Lambda 40 2 2VUM 1 1 Eta 27 1 Epsilon 1 1 1NA 483 48 Unassigned lineage 61 NA Recombinant 3 NA Total 20,435 200 1NA: Not applicable (lineages without variant assignment). 2VUM: Variant Under Monitoring. Table 2. SARS-CoV-2 viral sequences from Spain deposited in GISAID between 06.12.2021 and 08.03.2022. Variant Number of Sequences Number of Lineages Alpha 72 2 Beta 2 2 Delta 12,733 107 Gamma 4 2 Mu 15 3 Omicron 15,251 48 Unassigned lineage 16 NA Recombinant 1 NA 1NA 49 8 Total 28,143 172 1NA: Not applicable (lineages without variant assignment). The aggregated data for a semi-annual period (05.09.2021 to 08.03.2022) showed that viral sequences deposited in GISAID corresponded to 263 different lineages. In terms of variant classification, we found 1257 sequences belonging to Alpha, 89 Beta, 31,005 Delta, 27 Gamma, 1 Epsilon, 27 Eta, 40 Lambda, 186 Mu, 15,259 Omicron, 4 recombinant, 532 NA, 1 VUM, and 77 sequences with an unassigned lineage. The analysis also allowed us to observe sequences deposited during the study period but corresponding to prior dates, which demonstrates the network boost in data exchange. During 2020, an elevated percentage of virus circulation without variant assignment was observed since this nomenclature system was announced by the WHO in May 2021 [ 20 ]. Moreover, there was a high percentage of the Delta variant circulating in 2021 and a high percentage for the Omicron variant in the two first months of 2022 in Spain. Other variants such as Beta, Mu, Lambda, and Gamma circulated in Spain in smaller proportions during 2021 (Figure 1). The monthly based analysis for the semi-annual period data (05.09.2021 to 08.03.2022) showed co-circulation of the main VOCs and their replacement in Spain. These data highlight the co-circulation of Alpha and Delta variants during June and July 2021, with Delta becoming the dominant variant in August 2021. The co-circulation of Delta and Omicron variants in December 2021 was also detected, concluding with the replacement of Delta by Omicron in February 2022 (Figure 2) reflecting similar dynamics for Alpha, Delta, and Omicron time course distributions in all submitted sequences to GISAID until 15.03.2022 (Supplementary File S3 and Supplementary Figure S1). Moreover, comparing the data by dividing the semi-annual period by quarter (05.09.2021– 05.12.2021 and 06.12.2021–08.03.2022), an increase of 36% in the number of deposited viral Int. J. Mol. Sci. 2023,24, 8573 5 of 17 sequences from Spain in GISAID was observed, which demonstrates data sharing improvement over time. Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 5 of 18 nomenclature system was announced by the WHO in May 2021 [20]. Moreover, there was a high percentage of the Delta variant circulating in 2021 and a high percentage for the Omicron variant in the two first months of 2022 in Spain. Other variants such as Beta, Mu, Lambda, and Gamma circulated in Spain in smaller proportions during 2021 (Figure 1). Figure 1. Percentage of sequences corresponding to different variants by year. SARS-CoV-2 viral sequences from Spain shared in GISAID between 05.09.2021 and 08.03.2022. NA: not applicable (lineages without variant assignment). VUM: Variant Under Monitoring. The monthly based analysis for the semi-annual period data (05.09.2021 to 08.03.2022) showed co-circulation of the main VOCs and their replacement in Spain. These data highlight the co-circulation of Alpha and Delta variants during June and July 2021, with Delta becoming the dominant variant in August 2021. The co-circulation of Delta and Omicron variants in December 2021 was also detected, concluding with the replacement of Delta by Omicron in February 2022 (Figure 2) reflecting similar dynamics for Alpha, Delta, and Omicron time course distributions in all submitted sequences to GISAID until 15.03.2022 (Supplementary File S3 Supplementary Figure S1). 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2020 2021 2022 Alpha Beta Delta Épsilon Eta Gamma Lambda Mu NA Ómicron Recombinant Unassigned lineage VUM Figure 1. Percentage of sequences corresponding to different variants by year. SARS-CoV-2 viral sequences from Spain shared in GISAID between 05.09.2021 and 08.03.2022. NA: not applicable (lineages without variant assignment). VUM: Variant Under Monitoring. Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 6 of 18 Figure 2. Time course of variants in Spain between 05.09.2021 and 08.03.2022 by month (sequences shared in GISAID). NA: Not applicable (lineages without variant assignment). VUM: Variant Under Monitoring. Moreover, comparing the data by dividing the semi-annual period by quarter (05.09.2021–05.12.2021 and 06.12.2021–08.03.2022), an increase of 36% in the number of deposited viral sequences from Spain in GISAID was observed, which demonstrates data sharing improvement over time. 2.2. Tracking Changes in Delta and Omicron Variants To track changes in Delta and Omicron variants, we checked all lineage-defining mutations, considered as non-synonymous substitutions or deletions that occur in >75% of sequences within a lineage or its sublineages according to their definition on the web portal outbreak.info [21]. 2.2.1. Delta Variant The analyses of lineage-defining mutations corresponding to 248 Delta lineages and sublineages available until July 2022 were checked. The analyses showed a total of 441 mutations described for this set corresponding to the Delta variant, of which 14 were present in more than 98% of lineages and sublineages. These mutations were: ORF1b (P314L, G662S, and P1000L); S (T19R, T452R, T478K, D614G, and P681R); ORF3a (S26L); M (I82T); N (D63G, R203M, and D377Y); and ORF8 (S84L). The mutations present in all lineages and sublineages were: T19R, T478K, and D614G in S, I82T in M, and S26L in ORF3a. 2.2.2. Omicron Variant The analysis for the Omicron variant included a total of 205 lineages and sublineages available until October 2022. A total of 343 mutations were present in this set, with the most frequent being: ORF1a (P3395H and T3255I); ORF1b (P314L and I1566V); S (G142D, G339D, S373P, S375F, S447N, T478K, E484A, Y505H, D614G, H655Y, N679K, P681H, N764K, D796Y, Q954H, and N969K), E (T19I); M (Q19E and A63T); ORF8 (S84L); and N (P13L, R203K, and G204R). However, only the mutations in ORF1a (T3255I and P3395H), S (D614G, H655Y, N679K, D796Y, Q954H, and N969K), and M (A63T) were present in all lineages and sublineages belonging to the Omicron variant. These results showed that 27 mutations were present in more than 95% of lineages/sublineages belonging to the 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% January February March April May June July August September October November December January February March 2021 2022 Alpha Beta Delta Épsilon Eta Gamma Lambda Mu NA Ómicron Figure 2. Time course of variants in Spain between 05.09.2021 and 08.03.2022 by month (sequences shared in GISAID). NA: Not applicable (lineages without variant assignment). VUM: Variant Under Monitoring. Int. J. Mol. Sci. 2023,24, 8573 6 of 17 2.2. Tracking Changes in Delta and Omicron Variants To track changes in Delta and Omicron variants, we checked all lineage-defining mutations, considered as non-synonymous substitutions or deletions that occur in >75% of sequences within a lineage or its sublineages according to their definition on the web portal outbreak.info [21]. 2.2.1. Delta Variant The analyses of lineage-defining mutations corresponding to 248 Delta lineages and sublineages available until July 2022 were checked. The analyses showed a total of 441 mutations described for this set corresponding to the Delta variant, of which 14 were present in more than 98% of lineages and sublineages. These mutations were: ORF1b (P314L, G662S, and P1000L); S(T19R, T452R, T478K, D614G, and P681R); ORF3a (S26L); M(I82T); N(D63G, R203M, and D377Y); and ORF8 (S84L). The mutations present in all lineages and sublineages were: T19R, T478K, and D614G in S, I82T in M, and S26L in ORF3a. 2.2.2. Omicron Variant The analysis for the Omicron variant included a total of 205 lineages and sublineages available until October 2022. A total of 343 mutations were present in this set, with the most frequent being: ORF1a (P3395H and T3255I); ORF1b (P314L and I1566V); S(G142D, G339D, S373P, S375F, S447N, T478K, E484A, Y505H, D614G, H655Y, N679K, P681H, N764K, D796Y, Q954H, and N969K), E(T19I); M (Q19E and A63T); ORF8 (S84L); and N(P13L, R203K, and G204R). However, only the mutations in ORF1a (T3255I and P3395H), S(D614G, H655Y, N679K, D796Y, Q954H, and N969K), and M(A63T) were present in all lineages and sublineages belonging to the Omicron variant. These results showed that 27 mutations were present in more than 95% of lineages/sublineages belonging to the Omicron variant, but only 9 were present in all of them, and most mutations were located in the Sgene. In this analysis, we also observed that the Delta lineages/sublineages had three times more defined lineage mutations (441) than Omicron (161) until July 2022. We suggest that this difference might be associated with the circulation period of each variant until the moment of analysis (Delta: October 2020 to July 2022 and Omicron: November 2021 to July 2002) and could be related to the number of infections, giving rise to a greater evolution of Delta reflected in the changes established as determinants of lineages. A posterior analysis on October 2022 revealed an increase to 342 lineage-defining mutations of Omicron lineages/sublineages, confirming its evolution over time. 2.3. Quality Control Assessment for SARS-CoV-2 Sequencing (QCA) The QCA of SARS-CoV-2 sequencing was performed between 22.12.2021 and 28.01.2022. In total, 37 out of the 38 RELECOV network participants (97.4%) reported their results for the quality control assessment. Obtaining and sequencing of inactivated and lyophilized SARS-CoV-2 samples was carried out and assessed by the Reference Laboratory, Respiratory Virus and Influenza Unit of the National Centre for Microbiology (CNM), Carlos III Health Institute before dispatch, in order to obtain the correct results for the assignment of lineage and variant for each sample. The sample details for the QCA are shown in Table 3. In regard to the library preparation kits, the most used by the participants were the DNA prep Tagmentation (35.14%), Nextera XT, and SeqCovid kits (10.81% each for the latter two) on the Illumina platform which was used by 70.27% of the participants. The Ion ampliseq kit for Chef DL8 (8.10%) on the Ion Torrent platform was used by 27.03% of the participants. The overall results obtained by the RELECOV members, who were individually designated by a unique and random code anonymized, are shown in Figure 3. Int. J. Mol. Sci. 2023,24, 8573 7 of 17 Table 3. Characteristics of the samples and results of the 37 RELECOV network participants reporting results in the QCA. Sample Variant Lineage Variant Lineage Number of Correct Results (%) Number of Correct Results (%) #1 Alpha B.1.1.7 37 (100) 36 (97.30) #2 Beta B.1.351 37 (100) 37 (100) #3 1NA A.28 36 (97.30) 36 (97.30) #4 Mu B.1.621 37 (100) 37 (100) #5 Gamma P.1 37 (100) 34 (91.89) #6 Delta AY.9.2 37 (100) 33 (89.19) #7 Delta AY.43 14 (37.83) 11 (29.73) #8 Delta AY.94 36 (97.30) 31 (83.78) #9 Delta AY.94 37 (100) 32 (86.49) #10 Delta AY.43 37 (100) 37 (100) 1NA: Not applicable. The complete hit rates (percentage of assignment) for variant and lineage were 37.8% and 13.51%, respectively, and the correct assignment of both variant and lineage was low 13.51% (5/37). We identified a potential problem with one of the QCA samples, due to a failure in the RNA lyophilization procedure therefore, batches of tubes corresponding to this specific sample were not homogeneous. For analysis of results, hit rates were recalculated without considering that specific sample. After removing this sample, the global results generated a complete correct assignment rate of 94.59% for variant and 64.86% for lineage. In addition, performing a disaggregated analysis by QCA sample, the variant and lineage assignments were above 95% and 85%, respectively, regardless of the described problem with one sample. These results highlight the inherent complexity of comparing lineage assignments from a number of laboratories using different sequencing technologies and bioinformatic pipelines to generate the consensus SARS-CoV-2 sequences. 2.4. Reference SARS-CoV-2 Phylogenetic Analysis Implementation The phylogenetic analyses were performed in order to establish a reference matrix and tree containing worldwide sequences including different lineages and variants as a tool for surveillance purposes. A phylogenetic analysis was carried out using FastTree [ 22 ] and IQ-TREE 2 [ 23 ] from the FASTA files corresponding to 713 worldwide (76 countries and territories) viral sequences retrieved from GISAID using the NCBI Sequence NC_045512.2 as the reference genome for SARS-CoV-2. This analysis revealed the same clusters described by the WHO for variant assignments comprising different lineages and sublineages (Figure 4). An additional analysis using the sequence of the Sgene (Figure 5) showed that variant clusters were consistent in both trees. As expected, viral evolution was better resolved using the complete viral genome for this analysis. However, the information provided by the Sgene must be taken into consideration in view of the results obtained for variant classifications. Int. J. Mol. Sci. 2023,24, 8573 8 of 17 Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 8 of 18 Figure 3. Results for variant (green) and lineage (blue) assignments in ten samples for the RELECOV network participants. 9 9 9 10 8 9 10 9 9 9 9 9 9 9 10 9 9 9 9 9 10 8 9 10 10 9 9 9 10 10 9 10 10 10 10 10 10 9 9 9 9 7 7 10 9 9 9 8 8 9 9 7 8 9 8 9 9 9 6 9 9 9 9 9 9 9 10 9 10 9 8 9 10 10 012345678910 COD_2101 COD_2102 COD_2103 COD_2104 COD_2105 COD_2106 COD_2107 COD_2108 COD_2109 COD_2110 COD_2111 COD_2112 COD_2113 COD_2114 COD_2115 COD_2116 COD_2117 COD_2119 COD_2120 COD_2121 COD_2122 COD_2123 COD_2124 COD_2125 COD_2126 COD_2127 COD_2129 COD_2131 COD_2132 COD_2134 COD_2135 COD_2136 COD_2137 COD_2139 COD_2140 COD_2141 COD_2143 Figure 3. Results for variant (green) and lineage (blue) assignments in ten samples for the RELECOV network participants. Int. J. Mol. Sci. 2023,24, 8573 9 of 17 Int. J. Mol. Sci. 2023, 24, x FOR PEER REVIEW 10 of 18 Figure 4. Phylogenetic tree, showed as cladogram, of the 713 worldwide (76 countries and territories) complete viral genomes retrieved from GISAID and NCBI NC_045512.2 SARS-CoV-2. Each colour represents a cluster associated with a specific variant identified by WHO. Nodes values: SH- aLRT/UFBoot (ultrafast bootstrap) supports. Figure 4. Phylogenetic tree, showed as cladogram, of the 713 worldwide (76 countries and territories) complete viral genomes retrieved from GISAID and NCBI NC_045512.2 SARS-CoV-2. Each colour represents a cluster associated with a specific variant identified by WHO. Nodes values: SH-aLRT/UFBoot (ultrafast bootstrap) supports. Int. J. Mol. Sci. 2023,24, 8573 16 of 17 18. Ministerio de Sanidad. Integración de la Secuenciación Genómica en la Vigilancia del SARS-Cov-2. 2021. 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