De novo Genome Assembly and Single Nucleotide Variations for Soybean Mosaic Virus Using Soybean Seed Transcriptome Data

Investigating Variability in Viral Presence and Abundance across Soybean Seed Development Stages Using Transcriptome Analysis

Plant transcriptomes offer a valuable resource for studying viral communities (viromes). In this study, we explore how plant transcriptome data can be applied to virome research. We analyzed 40 soybean transcriptomes across different growth stages and identified six viruses: broad bean wilt virus 2 (BBWV2), brassica yellow virus (BrYV), beet western yellow virus (BWYV), cucumber mosaic virus (CMV), milk vetch dwarf virus (MDV), and soybean mosaic virus (SMV). SMV was the predominant virus in both Glycine max (GM) and Glycine soja (GS) cultivars. Our analysis confirmed its abundance in both, while BBWV2 and CMV were more prevalent in GS than GM. The viral proportions varied across developmental stages, peaking in open flowers. Comparing viral abundance measured by viral reads and fragments per kilobase of transcript per million (FPKM) values revealed insights. SMV showed similar FPKM values in GM and GS, but BBWV2 and CMV displayed higher FPKM proportions in GS. Notably, the differences in viral abundance between GM and GS were generally insignificant based on the FPKM values across developmental stages, except for the apical bud stage in four GM cultivars. We also detected MDV, a multi-segmented virus, in two GM samples, with variable proportions of its segments. In conclusion, our study demonstrates the potential of plant transcriptomes for virome research, highlighting their strengths and limitations.

Multi-omics assisted breeding for biotic stress resistance in soybean

Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.

Evolution and Phylogeny of Soybean Mosaic Virus Based on 143 Complete Genomes

Soybean mosaic virus (SMV) of the genus Potyvirus is an important virus in cultivated soybeans. Here, we obtained 7 SMV genomes from soybean germplasms using RNA sequencing and conducted a comprehensive evolutionary and phylogenetic study of 143 SMV genomes derived from 10 plant species and 12 countries. The phylogenetic tree we constructed using coding DNA sequences revealed the existence of nine clades of SMV isolates/strains. Recombination analysis revealed 76 recombinant events and 141 recombinants in total. Clades 1 and 3 contain the most common SMV pathotypes, including G1 through G7, which are distributed worldwide. Clade 2 includes several Chinese SMV pathotypes. The SMV isolates were further divided into two groups. The SMV isolates in the first group, including clades 8 and 9, were identified from Pinellia and Atractylodes species, whereas those in the second group (clades 1 through 7) were mostly found in cultivated soybeans. The SMV polyprotein undergoes positive selection, whereas most mature proteins, except for the P1 protein, undergo negative selection. The P1 protein of SMV isolates in group 1 may be highly correlated with host adaptation. This study provides strong evidence that recombination and plant hosts are powerful forces driving the genetic diversity of the SMV genome.

A metagenomic study of DNA viruses from samples of local varieties of common bean in Kenya

Common bean (Phaseolus vulgaris L.) is the primary source of protein and nutrients in the majority of households in sub-Saharan Africa. However, pests and viral diseases are key drivers in the reduction of bean production. To date, the majority of viruses reported in beans have been RNA viruses. In this study, we carried out a viral metagenomic analysis on virus symptomatic bean plants. Our virus detection pipeline identified three viral fragments of the double-stranded DNA virus Pelargonium vein banding virus (PVBV) (family, Caulimoviridae, genus Badnavirus). This is the first report of the dsDNA virus and specifically PVBV in legumes to our knowledge. In addition two previously reported +ssRNA viruses the bean common mosaic necrosis virus (BCMNVA) (Potyviridae) and aphid lethal paralysis virus (ALPV) (Dicistroviridae) were identified. Bayesian phylogenetic analysis of the Badnavirus (PVBV) using amino acid sequences of the RT/RNA-dependent DNA polymerase region showed the Kenyan sequence (SRF019_MK014483) was closely matched with two Badnavirus viruses: Dracaena mottle virus (DrMV) (YP_610965) and Lucky bamboo bacilliform virus (ABR01170). Phylogenetic analysis of BCMNVA was based on amino acid sequences of the Nib region. The BCMNVA phylogenetic tree resolved two clades identified as clade (I and II). Sequence from this study SRF35_MK014482, clustered within clade I with other Kenyan sequences. Conversely, Bayesian phylogenetic analysis of ALPV was based on nucleotide sequences of the hypothetical protein gene 1 and 2. Three main clades were resolved and identified as clades I-III. The Kenyan sequence from this study (SRF35_MK014481) clustered within clade II, and nested within a sub-clade; comprising of sequences from China and an earlier ALPV sequences from Kenya isolated from maize (MF458892). Our findings support the use of viral metagenomics to reveal the nascent viruses, their viral diversity and evolutionary history of these viruses. The detection of ALPV and PVBV indicate that these viruses have likely been underreported due to the unavailability of diagnostic tools.