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Chia (Salvia hispanica L.) is one of the most popular nutrition-rich foods and pseudocereal crops of the family Lamiaceae. Chia seeds are a rich source of proteins, polyunsaturated fatty acids (PUFAs), dietary fibers, and antioxidants. In this study, we present the assembly of the chia reference genome, which spans 303.6 Mb and encodes 48,090 annotated protein-coding genes. Our analysis revealed that ~42% of the chia genome harbors repetitive content, and identified ~3 million single nucleotide polymorphisms (SNPs) and 15,380 simple sequence repeat (SSR) marker sites. By investigating the chia transcriptome, we discovered that ~44% of the genes undergo alternative splicing with a higher frequency of intron retention events. Additionally, we identified chia genes associated with important nutrient content and quality traits, such as the biosynthesis of PUFAs and seed mucilage fiber (dietary fiber) polysaccharides. Notably, this is the first report of in-silico annotation of a plant genome for protein-derived small bioactive peptides (biopeptides) associated with improving human health. To facilitate further research and translational applications of this valuable orphan crop, we have developed the Salvia genomics database (SalviaGDB), accessible at https://salviagdb.org.

Genomic surveillance has emerged as a critical monitoring tool during the SARS-CoV-2 pandemic. Wastewater surveillance has the potential to identify and track SARS-CoV-2 variants in the community, including emerging variants. We demonstrate the novel use of multilocus sequence typing to identify SARS-CoV-2 variants in wastewater. Using this technique, we observed the emergence of the B.1.351 (Beta) variant in Linn County, Oregon, USA, in wastewater 12 days before this variant was identified in individual clinical specimens. During the study period, we identified 42 B.1.351 clinical specimens that clustered into 3 phylogenetic clades. Eighteen of the 19 clinical specimens and all wastewater B.1.351 specimens from Linn County clustered into clade 1. Our results provide further evidence of the reliability of wastewater surveillance to report localized SARS-CoV-2 sequence information.

SARS-CoV-2 variant proportions in a population can be estimated through genomic sequencing of clinical specimens or wastewater samples. We demonstrate strong pairwise correlation between statewide variant estimates in Oregon, USA, derived from both methods (correlation coefficient 0.97). Our results provide crucial evidence of the effectiveness of community-level genomic surveillance.