Byron Galindo Ornelas

Mr. Byron Galindo Ornelas

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Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Journal Article
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José Francisco Muñoz-ValleJosé Francisco Muñoz-Valle
José Francisco Muñoz-Valle
AVAlberto-Antony Venancio-Landeros
Alberto-Antony Venancio-Landeros
RSRocío Sánchez-Sánchez
Rocío Sánchez-Sánchez
KRKaren Reyes-Díaz
Karen Reyes-Díaz
BOByron Galindo Ornelas
Byron Galindo Ornelas
OGOctavio-Patricio García-González
Octavio-Patricio García-González
SARS-CoV-2 variants surveillance is a worldwide task that has been approached with techniques such as Next Generation Sequencing (NGS); however, this technology is not widely available in developing countries because of the lack of equipment and limited funding in science. An option is to deploy a RT-qPCR screening test which aids in the analysis of a higher number of samples, in a shorter time and at a lower cost. In this study, variants present in samples positive for SARS-CoV-2 were identified with a RT-qPCR mutation screening kit and were later confirmed by NGS. A sample with an abnormal result was found with the screening test, suggesting the simultaneous presence of two viral populations with different mutations. The DRAGEN Lineage analysis identified the Delta variant, but there was no information about the other three mutations previously detected. When the sequenced data was deeply analyzed, there were reads with differential mutation patterns, that could be identified and classified in terms of relative abundance, whereas only the dominant population was reported by DRAGEN software. Since most of the software developed to analyze SARS-CoV-2 sequences was aimed at obtaining the consensus sequence quickly, the information about viral populations within a sample is scarce. Here, we present a faster and deeper SARS-CoV-2 surveillance method, from RT-qPCR screening to NGS analysis.