Despite various methods for detecting and treating SARS-CoV-2, affordable and easily applicable solutions are still needed. Aptamers can potentially fill this gap. Here, we establish a workflow to identify aptamers that bind to the spike proteins of SARS-CoV-2, a process applicable to other targets as well. The spike protein is crucial for the virus’s entry into host cells. The aptamer development process for the spike protein’s receptor binding domain (RBD) begins with splitting the SARS-CoV-2’s genome into 40 nucleotide-long sequences, predicting their two-dimensional structure, and sorting based on the free energy. Selected oligomers undergo three-dimensional structure prediction and docking onto the viral spike protein’s RBD. Six RNA oligomers were identified as top candidates based on the RNA docking with the SARS-CoV-2 wild-type (WT) (Wuhan-Hu-1 strain) and Omicron variant BA.1 RBD and molecular dynamics simulations. Three oligomers also demonstrated strong predicted binding affinity with other SARS-CoV-2 variants, including BA.2, XBB.1.5, and EG.5, based on the protein–aptamer docking followed by stability evaluation using the MD simulations. The aptamer with the best fit for the spike protein RBD was later validated using biolayer interferometry. The process has resulted in identifying a single aptamer from a library of 29,000 RNA oligomers, which exhibited affinity in the submicromolar range and the potential to develop into a viral screen or therapeutic.

Cotton is an economically important crop. However, the yield gain in cotton has stagnated over the years, probably due to its narrow genetic base. The introgression of beneficial variations through conventional and molecular approaches has helped broaden its genetic base to some extent. The growth habit of cotton is one of the crucial factors that determine crop maturation time, yield, and management. This study used 44 diverse upland cotton genotypes to develop high-yielding cotton germplasm with reduced regrowth after defoliation and early maturity by altering its growth habit from perennial to somewhat annual. We selected eight top-scoring genotypes based on the gene expression analysis of five floral induction and meristem identity genes (FT, SOC1, LFY, FUL, and AP1) and used them to make a total of 587 genetic crosses in 30 different combinations of these genotypes. High-performance progeny lines were selected based on the phenotypic data on plant height, flower and boll numbers per plant, boll opening date, floral clustering, and regrowth after defoliation as surrogates of annual growth habit, collected over four years (2019 to 2022). Of the selected lines, 8×5-B3, 8×5-B4, 9×5-C1, 8×9-E2, 8×9-E3, and 39×5-H1 showed early maturity, and 20×37-K1, 20×37-K2, and 20×37-D1 showed clustered flowering, reduced regrowth, high quality of fiber, and high lint yield. In 2022, 15 advanced lines (F₈/F₇) from seven cross combinations were selected and sent for an increase to a Costa Rica winter nursery to be used in advanced testing and for release as germplasm lines. In addition to these breeding lines, we developed molecular resources to breed for reduced regrowth after defoliation and improved yield by converting eight expression-trait-associated SNP markers we identified earlier into a user-friendly allele-specific PCR-based assay and tested them on eight parental genotypes and an F₂ population.