Artemisia L. is among the most diverse and medicinally important genera of the plant family Asteraceae. Discrepancies arise in the taxonomic classification of Artemisia due to the occurrence of multiple polyploidy events in separate lineages and its complex morphology. The discrepancies could be resolved by increasing the genomic resources. A. scoparia is one of the most medicinally important species in Artemisia. In this paper, we report the complete chloroplast genome sequence of Artemisia scoparia. The genome was 151,060 bp (base pairs), comprising a large single copy (82,834 bp) and small single copy (18,282 bp), separated by a pair of long inverted repeats (IRa and IRb: 24,972 bp each). We identified 114 unique genes, including four ribosomal RNAs, 30 transfer RNAs, and 80 protein-coding genes. We analysed the chloroplast genome features, including oligonucleotide repeats, microsatellites, amino acid frequencies, RNA editing sites, and codon usage. Transversion substitutions were twice as frequent as transition substitutions. Mutational hotspot loci included ccsA-ndhD, trnH-psbA, ndhG-ndhI, rps18-rpl20, and rps15-ycf1. These loci can be used to develop cost-effective and robust molecular markers for resolving the taxonomic discrepancies. The reconstructed phylogenetic tree supported previous findings of Artemisia as a monophyletic genus, sister to the genus Chrysanthemum, whereby A. scoparia appeared as sister to A. capillaris.

Background: Cotton leaf curl disease (CLCuD) is a disease of cotton caused by begomoviruses, leading to a drastic loss in the annual yield of the crop. Pakistan has suffered two epidemics of this disease leading to the loss of billions in annual exports. The speculation that a third epidemic of CLCuD may result as consequence of the frequent occurrence of Tomato leaf curl New Delhi virus (ToLCNDV) and Cotton leaf curl Kokhran Virus-Burewala Strain (CLCuKoV-Bu) in CLCuD infected samples, demand that the interactions taking between the two viruses be properly evaluated. This study is designed to assess virus-virus interactions at the molecular level and determine the type of co-infection taking place. Methods: Based on the amino acid sequences of the gene products of both CLCuKoV-Bu and ToLCNDV, protein structures were generated using different software, i.e., MODELLER, I-TASSER, QUARKS, LOMETS and RAPTORX. A consensus model for each protein was selected after model quality assessment using ERRAT, QMEANDisCo, PROCHECK Z-Score and Ramachandran plot analysis. The active and passive residues in the protein structures were identified using the CPORT server. Protein–Protein Docking was done using the HADDOCK webserver, and 169 Protein–Protein Interaction (PPIs) were performed between the proteins of the two viruses. The docked complexes were submitted to the PRODIGY server to identify the interacting residues between the complexes. The strongest interactions were determined based on the HADDOCK Score, Desolvation energy, Van der Waals Energy, Restraint Violation Energy, Electrostatic Energy, Buried Surface Area and Restraint Violation Energy, Binding Affinity and Dissociation constant (K_d). A total of 50 ns Molecular Dynamic simulations were performed on complexes that exhibited the strongest affinity in order to validate the stability of the complexes, and to remove any steric hindrances that may exist within the structures. Results: Our results indicate significant interactions taking place between the proteins of the two viruses. Out of all the interactions, the strongest were observed between the Replication Initiation protein (Rep) of CLCuKoV-Bu with the Movement protein (MP), Nuclear Shuttle Protein (NSP) of ToLCNDV (DNA-B), while the weakest were seen between the Replication Enhancer protein (REn) of CLCuKoV-Bu with the REn protein of ToLCNDV. The residues identified to be taking a part in interaction belonged to domains having a pivotal role in the viral life cycle and pathogenicity. It maybe deduced that the two viruses exhibit antagonistic behavior towards each other, and the type of infection may be categorised as a type of Super Infection Exclusion (SIE) or homologous interference. However, further experimentation, in the form of transient expression analysis, is needed to confirm the nature of these interactions and increase our understanding of the direct interactions taking place between two viruses.