RESUMEN
A comprehensive SARS-CoV-2 genomic surveillance programme that integrates logistics, laboratory work, bioinformatics, analytics, and timely reporting was deployed through a public-private partnership in the city of Bengaluru, Karnataka in India. As a result, 12461 samples have been sequenced and reported to the Karnataka State public health officials as time-sensitive, decision support during the last one year and uploaded in global public databases in a timely manner. This programme has developed an analytics platform for studying SARS-CoV-2 sequences and their epidemiological context. Continuous sequencing effort enabled timely detection of emergence of Omicron variant in India and the subsequent spread of the same and its sub-lineages with more logistic growth (BA.10, BA.12 and BA.5) in Bengaluru. Our data also helped to provide timely information on variants to determine which of the Variants of Concern tracked globally, were observed in Bengaluru, ensuring targeted efforts and reducing unwarranted fear. This effort highlights the importance of, and the urgent need to, increase genomic surveillance to support the states with limited sequencing and bioinformatics capacity. We describe the development and deployment of this end-to-end solution for genomic surveillance of SARS-CoV-2 in the city of Bengaluru.
RESUMEN
BACKGROUND: Dried blood spots (DBS) are a relatively inexpensive source of nucleic acids and are easy to collect, transport, and store in large-scale field surveys, especially in resource-limited settings. However, their performance in whole-genome sequencing (WGS) relative to that of venous blood DNA has not been analyzed for various downstream applications. METHODS: This study compares the WGS performance of DBS paired with venous blood samples collected from 12 subjects. RESULTS: Results of standard quality checks of coverage, base quality, and mapping quality were found to be near identical between DBS and venous blood. Concordance for single-nucleotide variants, insertions and deletions, and copy number variants was high between these two sample types. Additionally, downstream analyses typical of population-based studies were performed, such as mitochondrial heteroplasmy detection, haplotype analysis, mitochondrial copy number changes, and determination of telomere lengths. The absolute mitochondrial copy number values were higher for DBS than for venous blood, though the trend in sample-to-sample variation was similar between DBS and blood. Telomere length estimates in most DBS samples were on par with those from venous blood. CONCLUSION: DBS samples can serve as a robust and feasible alternative to venous blood for studies requiring WGS analysis.