Tapping panel dryness (TPD), a complex physiological syndrome associated with the rubber tree (Hevea brasiliensis Muell. Arg.), causes cessation of latex drainage upon tapping and thus threatens rubber production. Rubber tree virus 1 (RTV1) is a novel positive-sense single-stranded RNA virus from the Betaflexiviridae (genus Capillovirus), which has been established to cause TPD. MicroRNAs (miRNAs) play an important role in the interplay between viruses and host cells. In this study, we identified the rubber tree genome-encoded miRNAs and their therapeutic targets against RTV1. We applied computational algorithms to predict target binding sites of rubber tree miRNAs potentially targeting RTV1 RNA genome. Mature rubber-tree miRNAs are retrieved from the miRBase database and are used for hybridization of the RTV1 genome. A total of eleven common rubber-tree miRNAs were identified based on consensus genomic positions. The consensus of four algorithms predicted the hybridization sites of the hbr-miR396a and hbr-miR398 at common genomic loci (6676 and 1840), respectively. A miRNA-regulatory network of rubber tree was constructed with the RTV1— ORFs using Circos, is illustrated to analyze therapeutic targets. Overall, this study provides the first computational evidence of the reliable miRNA–mRNA interaction between specific rubber tree miRNAs and RTV1 genomic RNA transcript. Therefore, the predicted data offer valuable evidence for the development of RTV1-resistant rubber tree in the future. Our work suggests that similar computational host miRNA prediction strategies are warranted for identification of the miRNA targets in the other viral genomes.

More than 3 years have passed since the outbreak of COVID-19 and yet, the origin of the causal virus SARS-CoV-2 remains unknown. We examined the evolutionary trajectory of SARS-CoV-2 by analyzing non-redundant genome sets classified based on six closely linked mutations. The results indicated that SARS-CoV-2 emerged in February 2019 or earlier and evolved into three main haplotypes (GL, DS, and DL) before May 2019, which then continued to evolve in parallel. The dominant haplotype GL had spread worldwide in the summer (May to July) of 2019 and then evolved into virulent strains in December 2019 that triggered the global pandemic, whereas haplotypes DL and DS arrived in China in October 2019 and caused the epidemic in China in December 2019. Therefore, haplotype GL neither originated in China nor from the viral strains that caused the epidemic in China. Accordingly, considering data solely from China would be inadequate to reveal the mysterious origin of SARS-CoV-2, emphasizing the necessity of global cooperation.

Sugarcane Bacilliform Virus (SCBV) is considered an economically the most damaging pathogen for sugarcane production worldwide. Three ORFs are characterized in a single molecule of circular, ds-DNA genome of the SCBV, encoding for hypothetical protein (ORF1), DNA binding protein (ORF2) and Polyprotein (ORF3). The study was aimed to predict and comprehensively evaluate sugarcane miRNAs for the silencing of SCBV genome using in-silico algorithms. Computational methods were used for prediction of candidate miRNAs from sugarcane ( S. officinarum L.) to silence the expression of SCBV genes through translational inhibition by mRNA cleavage. Mature sugarcane miRNAs were retrieved and were assessed to hybridization with the SCBV genome. A total of fourteen potential candidate miRNAs from sugarcane were computed by all the algorithms used for the silencing of SCBV. A consensus of three algorithms predicts hybridization sites of sof-miR159e at common locus 5534. The miRNA-mRNA interaction was estimated by computing free-energy of miRNA-mRNA duplex using RNAcofold algorithm. Regulatory network of predicted candidate miRNAs of sugarcane with SCBV ORFs, generated using Circos, identify novel targets. Consequently, detecting and discarding inefficient amiRNAs prior to cloning would help suppressed mutants faster. The efficacy of predicted candidate miRNAs was evaluated to test the survival rate of the in vitro amiRNA-mediated effective badnaviral silencing and resistance in sugarcane cultivars.

Pandanus amaryllifolius is a valuable aromatic crop widely cultivated in tropical forest understories. Here, A telomere-to-telomere, gap-free genome assembly of the Chinese cultivar ‘Taishan Banlan’ was generated, and the molecular basis underlying shading-mediated regulation of leaf aroma biosynthesis was elucidated for the first time through integrated genomic, transcriptomic, and metabolomic analyses. Volatile metabolomics identified 1599 volatile organic compounds in leaf tissue, with terpenoids as the primary contributors to leaf aroma. Shading modulated the aroma quality of P. amaryllifolius primarily via terpenoid biosynthesis, yielding aroma profiles dominated by sweet, fruity, green, and woody notes. Integrated transcriptomic profiling revealed that terpenoid biosynthesis is co-regulated by structural genes in the MVA/MEP pathways, TPS family members, and key transcription factors, which collectively modulate the biosynthesis and accumulation of the three core differential terpenoids. Our findings provide valuable resources for the targeted genetic improvement and efficient cultivation optimization of P. amaryllifolius .

The global COVID-19 pandemic has lasted for three years since its outbreak, however its origin is still unknown. Here, we analyzed the genotypes of 3.14 million SARS-CoV-2 genomes based on the amino acid 614 of the Spke (S) and the amino acid 48 of NS8 (nonstructural protein 8), and identified 16 linkage haplotypes. The GL haplotype (S_614G and NS8_48L) was the major haplotype driving the global pandemic and accounted for 99.2% of the sequenced genomes, while the DL haplotype (S_614D and NS8_48L) caused the pandemic in China in the spring of 2020 and accounted for approximately 60% of the genomes in China and 0.45% of the global genomes. The GS (S_614G and NS8_48S), DS (S_614D and NS8_48S) and NS (S_614N and NS8_48S) haplotypes accounted for 0.26%, 0.06%, and 0.0067% of the genomes, respectively. The main evolutionary trajectory of SARS-CoV-2 is DS→DL→GL, whereas the other haplotypes are minor byproducts in the evolution. Surprisingly, the newest haplotype GL had the oldest time of most recent common ancestor (tMRCA), which was May 1 2019 by mean, while the oldest haplotype had the newest tMRCA with a mean of October 17, indicating that the ancestral strains that gave birth to GL had been extinct and replaced by the more adapted newcomer at the place of its origin, just like the sequential rise and fall of the delta and omicron variants. However, they arrived and evolved into toxic strains and ignited a pandemic in China where the GL strains did not exist at the end of 2019. The GL strains had spread all over the world before they were discovered, and ignited the global pandemic, which had not been noticed until the pandemic was declared in China. However, the GL haplotype had little influence in China during the early phase of the pandemic due to its late arrival as well as the strict transmission controls in China. Therefore, we propose two major onsets of the COVID-19 pandemic, one was mainly driven by the haplotype DL in China, the other was driven by the haplotype GL globally.