Identification and genomic profiling of a cotton leafroll dwarf virus isolate from Brownfield, TX

Abstract

Background:

Cotton leafroll dwarf virus (CLRDV), a member of the Polerovirus genus, is an emerging pathogen that threatens global cotton (Gossypium hirsutum) production. Since its first detection in Alabama in 2017, CLRDV has spread rapidly to several states of the United States of America, including Texas.

Methods:

In 2024, symptomatic cotton plants were collected from Brownfield, Texas. Total RNA was extracted, and RT-PCR was performed to amplify the viral genome and sequenced. The complete sequence (5,838 bp) was obtained and compared with existing CLRDV genomes from the U.S.

Results:

The Brownfield isolate displayed typical CLRDV genome features but also showed genetic differences compared to isolates from neighboring regions. Phylogenetic analysis indicated regional diversification, possibly due to environmental pressures or host cultivar variability.

Conclusion:

This study highlights the presence and evolution of CLRDV in Texas and neighboring states. Ongoing surveillance and development of resistant cotton cultivars are essential to mitigate yield losses.

1 Introduction

Cotton (Gossypium hirsutum L.) stands as one of the world’s most valuable fiber crops, grown in over 80 countries and serving as a cornerstone of the global textile industry (1). During the 2023–2024 season, worldwide cotton production exceeded 24.67 million metric tons, equivalent to 113.29 million bales (1 bale = 480 pounds) (2). The United States plays a significant role in global production, ranking fourth with approximately 14.41 million bales, around 12% of the global total, and contributing nearly $6.62 billion to the national economy by cotton export (3). Within the U.S., Texas dominates national production with approximately 3.2 million hectares under cultivation, followed by Georgia, Arkansas, Mississippi, North Carolina, and Alabama. Cotton cultivation in the U.S. faces persistent threats from a range of biotic stresses, including pests and pathogenic organisms such as bacteria, fungi, nematodes, and viruses. In 2023, biotic stresses alone contributed to a 7.4% reduction in yield nationwide, resulting in an estimated loss of approximately 1.4 million bales (4). Although viral diseases currently contribute minimally to an overall yield loss of about 2,994 bales, the increasing spread of viruses such as cotton leafroll dwarf virus (CLRDV) raises concern for future outbreaks and economic consequences (4).

CLRDV, a member of the Polerovirus genus within the Solemoviridae family, was initially identified in Africa in 1949 and has since been reported in parts of Asia and South America (5). The virus was first detected in the U.S. in 2017 in Alabama (6) and has now been confirmed in at least 14 cotton-growing states, including Georgia, Mississippi, and Texas (7). Its prevalence is variable, with incidence rates ranging from below 1% to over 20%, depending on the region (5, 8–14). The first genomic insights of CLRDV in the U.S. emerged from partial sequences obtained in Alabama by Avelar, et al. (6), followed by a complete genome sequence from a Georgia isolate by Tabassum, et al. (13). Cotton leafroll dwarf virus (CLRDV) poses a growing challenge to cotton production across the U.S., yet critical gaps remain in our understanding of its genetic landscape. Although its incidence has increased in recent years, there is a need for more sequenced genome data to identify genetic variation and population structure of CLRDV strains affecting U.S. cotton fields. Moreover, uncovering new viral isolates and obtaining their full-length genome sequences are essential steps toward understanding how the virus evolves, adapts, and spreads. Such insights are not only vital for accurate diagnostics and targeted disease management but also for guiding resistance breeding efforts aimed at safeguarding cotton crops against emerging viral threats.

Building on this foundation, the present study aims to detect new CLRDV isolates and obtain their full-length sequence from the Brownfield, Texas samples. To achieve these objectives, symptomatic cotton leaf samples were systematically collected from commercial fields and subjected to amplification of the full-length sequence. Further, the comparative analyses with previously reported CLRDV sequences enabled the identification of nucleotide variations and phylogenetic relationships among isolates. These approaches collectively contribute to a more comprehensive understanding of CLRDV evolution and distribution in a major cotton-producing region of the southern United States. Our findings enhance the current understanding of CLRDV genetic diversity and provide valuable aid to support the development of effective monitoring strategies and the breeding of resistant cotton cultivars.

2 Materials and methods

2.1 Sample collection

During the 2024 growing season, leaf and petiole samples were collected from a commercial field located at Brownfield, Texas. The samples collected from cotton plants exhibiting symptoms indicative of CLRDV infection (5) which ranged from mild chlorosis to severe stunting and leaf curling (Figures 1A-F). To preserve RNA integrity, samples were flash-frozen in liquid nitrogen immediately after collection and stored at -80°C until further processing.

Figure 1

2.2 RNA extraction and reverse transcription-PCR

Total RNA was isolated from symptomatic leaf and petiole tissue using the Spectrum™ Plant Total RNA Kit (Sigma-Aldrich, St. Louis, MO, USA), following the manufacturer’s instructions. To eliminate potential genomic DNA contamination, the RNA was treated with RNase-free DNase I (Qiagen, USA). Complementary DNA (cDNA) was synthesized using the GoScript™ Reverse Transcriptase cDNA Synthesis Kit (Promega, USA) and a gene-specific reverse primer (Table 1). The reverse transcription protocol involved the denaturation of RNA and gene-specific reverse primer at 70°C for 5 minutes, followed by the immediate addition of the RT master mix and incubation at 42°C for 90 minutes to ensure optimal primer annealing and cDNA synthesis. PCR amplification was conducted using primer pairs JL0067-JL0068 and JL0063-JL0068, targeting conserved regions of the viral movement and coat protein genes for diagnostic detection of CLRDV (13, 15). To amplify a longer genomic fragment spanning partial ORF1 and ORF3 regions (~2132 nt), the JL0100-JL0068 primer pair was employed. Amplicons were sequenced using Oxford Nanopore sequencing, which was carried out by Plasmidsaurus (https://plasmidsaurus.com/). The resulting sequences were aligned using NCBI’s BLASTn tool and BioEdit (16).

2.3 Full-length sequence amplification and sequencing

Further, for the full-length CLRDV sequence amplification, a strategic primer design approach was implemented based on multiple sequence alignment (MSA). Coding sequences from closely related CLRDV strains were retrieved from the NCBI Virus database based on the alignment with an amplified 2.1 kb partial fragment. These sequences were aligned using ClustalW with default settings to identify conserved regions, particularly at the 5′ and 3′ termini of the target open reading frame (17). Regions with ≥90% conservation were selected as candidate primer binding sites. SnapGene version 8.0.3 was used to design 4 pairs of primer sets within these regions. These primers were used to amplify the full-length CLRDV sequence in 4 overlapping fragments using RT-PCR reaction using Phusion High-Fidelity DNA Polymerase (Thermo Scientific, USA), and PCR products were sequenced at Plasmidsaurus (https://plasmidsaurus.com/) using the Oxford nanopore technique. All four fragments were assembled after removing the overlapped region to get the full-length sequence. Viral coding regions were predicted using SnapGene’s import feature function (SnapGene Version 8.0.3) from the annotation GFF3 file of the closest aligned sequences.

2.4 Sequence alignment and phylogenetic analysis

Phylogenetic relationships of amplified sequence in this study (accession number: PV548928) and existing full-length CLRDV sequences retrieved from the NCBI Virus database (https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/virus?SeqType_s=Nucleotide&VirusLineage_ss=Cotton%20leafroll%20dwarf%20virus,%20taxid:312295) were analyzed using the phangorn R package (18) after the multiple sequence alignment with the msa package (19). Sequences were aligned using the ClustalW algorithm with default substitution parameters (20). The aligned sequences were converted into phyDat format for phylogenetic inference. Model selection was performed using the modelTest function in the phangorn R package, and the best-fit evolutionary model (TIM2e+G(4)+I) was selected based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) (18). A maximum likelihood (ML) tree was inferred using the pml_bb function under the selected model. Node support was assessed via 1000 bootstrap replicates using the bootstrap.pml function with nearest-neighbor interchange (NNI) optimization. The resulting phylogenetic tree was midpoint rooted and visualized using the plotBS function with ultrafast bootstrap values. Tip labels were color-coded based on the geographic origin of the state to highlight the spatial distribution of viral lineages. A consensus network was constructed using the consensusNet function with a 20% threshold to display topological variation among bootstrap replicates.

Pairwise nucleotide sequence comparisons were conducted between the CLRDV isolate identified in this study (accession number: PV548928) and previously reported CLRDV genome sequences retrieved from the NCBI Virus database (accession numbers: OK185946, OK185945, OQ107471, PP556773, PP556772, PP556774, OK185941, OQ107470, OK185944, OK185943, OK185942, MN872302, OM687235), which were identified from Texas and surrounding regions. The ORFs 0–5 sequence alignment was performed using ClustalW, and pairwise distance was calculated using the dist.DNA function of the Ape R package was plotted using the pheatmap R package (21).

2.5 Amino acid sequence analysis

A multiple sequence alignment (MSA) was carried out using MAFFT (22), followed by the computation of site-specific conservation scores via the bio3d package in R (23) to explore the evolutionary dynamics and functional conservation among the aligned protein sequences. A maximum likelihood tree was also constructed using amino acid alignment using IQTree-3.0.0 (24). To characterize the putative proteins encoded by the complete CLRDV genome, amino acid sequences were analyzed using MEME Suite with default parameters for the identification of conserved motifs (25).

3 Results

3.1 New CLRDV isolate from Brownfield, Texas, identified by RT-PCR and sequencing

In this study, we identified an unreported viral isolate from cotton samples collected in Brownfield, Texas. Initial detection was achieved using PCR amplification, which revealed diagnostic bands of expected sizes 312 bp and 432 bp (Figure 1G). The partial CLRDV sequence of a 2,173 bp amplicon was obtained using primer pair JL0100 and JL0068 (Figure 1G, Supplementary Table S1), which shares the highest similarity with known CLRDV isolates from Oklahoma, Kansas, and Texas (GenBank accessions: OM687235.2 and PP556774.1) (26). Further, the full-length CLRDV genome was obtained by amplifying and sequencing four overlapping fragments. Assembly of these fragments yielded a complete genome sequence of 5838 nt, which represents a typical CLRDV isolate (Figure 1H). Sequence analysis revealed a 90.58%-99.69% identity with previously reported CLRDV genomes (Supplementary Table S2). The assembled sequence was submitted to NCBI under accession number PV548928, which was used in all subsequent analysis.

3.2 Sequence analysis reveals genetic variation among CLRDV isolates

Since the first identification of CLRDV, 834 CLRDV-related sequences have been deposited in the NCBI Virus Database, including 60 complete or near-complete genomes of these; 50 full-length sequences originate from U.S. samples, including the isolate identified in this study (PV548928) (27). Supplementary Figure S1 illustrates the geographic spread of both complete and partial CLRDV sequences in the USA, specifically showing their detected states of origin as submitted to NCBI. In order to establish the relationship of the identified CLRDV isolate from Brownfield, Texas, with previously identified CLRDV isolates, a phylogenetic analysis was conducted using the Maximum Likelihood (ML) approach. The full-length genome sequence obtained (5838nt) was aligned with a set of CLRDV isolates having full-length sequences from various geographical regions retrieved from the NCBI virus database. Multiple sequence alignment was performed using ClustalW, showing the variation among the sequences from samples collected from Texas and neighboring states (Supplementary Figure S2). The phylogenetic tree was constructed in the best-fit evolutionary model (TIM2e+G(4)+I), which was determined to be the best-fitting substitution model based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) with 1,000 bootstrap replicates. The resulting ML tree revealed that the Brownfield isolates clustered within a clade comprising isolates from the southern Great Plains region of the United States (Figure 2A). Within this clade, the Brownfield isolate showed the closest evolutionary relationship to the CLRDV isolate EC4 (GenBank: OM687235.2), which was previously identified in cotton samples collected from Oklahoma. To find the variation among the regional population, we reconstructed the phylogenetic tree with isolates identified in Texas and neighboring states (Figure 2B).

Figure 2

To assess the genetic relationships among CLRDV isolates, a pairwise distance matrix was generated using full-length genome sequences. The resulting heatmap (Figure 2C) illustrates the genetic divergence among 14 CLRDV isolates from Texas and neighboring states (Oklahoma, Arkansas, and Louisiana). The color scale represents nucleotide divergence, with blue indicating high similarity (low genetic distance) and red representing greater divergence. The Brownfield isolate (PV548928) clustered closely with isolates from Oklahoma (OM687235), Lubbock (PP556773), and San Angelo (PP556774), showing minimal genetic divergence (dark blue). This suggests a high degree of sequence conservation and possible regional movement or common ancestry among these isolates. In contrast, isolates from College Station (MN872302), Rapides Parish, LA (OQ107470), and Arkansas (OQ107471) displayed greater divergence (red shades), indicating broader genetic variation across geographical regions. These findings support the existence of region-specific CLRDV lineages and highlight the close genetic similarity of the Brownfield isolate with other West Texas variants (Figure 2C, Supplementary Table S3).

3.3 Conservation and motif analysis of aligned protein-coding sequences

To further characterize the identified CLRDV isolate from Brownfield, Texas, we performed a detailed amino acid sequence analysis of the predicted viral proteins encoded by the sequenced genome. We translated the coding regions into their corresponding amino acid sequences using the nucleotide sequence data. The translation was carried out using the standard genetic code, and the individual open reading frames (ORFs) were identified based on the known genome organization of CLRDV. A multiple sequence alignment (MSA) was constructed using MAFFT. Further, the maximum likelihood tree constructed from amino acid alignments suggested the variation between sequences of CLRDV identified from a small geographical region, i.e. Texas and surrounding areas (Figure 3A). The computation of site-specific conservation scores, ranging from 0 (completely variable) to 1 (fully conserved), were assigned to each residue position bsed on the degree of sequence similarity at that site (Figure 3B). Conversely, multiple dips with scores below 0.4 reflect variable or evolutionarily flexible segments, potentially associated with surface loops, linker regions, or domains undergoing adaptive evolution. Further, we performed de novo motif discovery using the MEME Suite to pinpoint specific sequence elements that are recurrently conserved. This analysis uncovered ten highly significant motifs (E-values ranging from 7.08e^-242 to 8.49e^-242) shared among the analyzed sequences (Figure 3C). All motifs were reproducibly detected across the 14 viral isolates examined, including newly identified isolates and others, underscoring their likely evolutionary retention and biological importance. The consensus sequences of the motifs spanned 20 to 50 nucleotides, and several displayed notable features consistent with regulatory or structural roles. For example, Motif 1 (AGATAACTCAGTAGCTTGTTATAGCAGGAGCTCTTAA) and Motif 4 (AACAATTTTGGAACAGTTTTTCTCGAGATCTGAAATCA) were among the most broadly distributed and positionally conserved, suggesting their potential function as core regulatory elements or essential protein-binding sites. Repetitive motifs such as Motif 5 and Motif 7 exhibited features resembling G-rich tracts or tandem repeats, often implicated in RNA secondary structure formation or transcriptional control mechanisms. Overall, the combination of high conservation scores and consistently recurring motifs provides compelling evidence for the presence of functionally constrained domains and regulatory elements within these viral protein-coding regions. The strong statistical support (E-values < 1e^-241) further emphasizes that these motifs likely contribute to conserved molecular functions such as replication, transcription regulation, or host interaction. At the same time, the variation in sequences suggests the evolution of the CLRDV genome under environmental pressure.

Figure 3

4 Discussion

CLRDV, the probable causative agent of Cotton Blue Disease, is becoming an increasing threat to cotton production in various regions, including the southeastern United States, parts of South America, and Africa (5). The virus is primarily transmitted by the cotton aphid (Aphis gossypii). Early-stage infections of CLRDV often go unnoticed due to their latent and asymptomatic nature, making early detection and intervention particularly challenging. Management strategies for CLRDV are hindered by several factors, including the absence of resistant cotton varieties and the aphid’s high reproductive rate, adaptability, and increasing resistance to chemical insecticides (28, 29). In addition, the virus’s ability to survive in alternate hosts, including weeds and volunteer cotton plants, enables it to overwinter and reemerge during the growing season, further complicating control efforts (30). Moreover, specific mutations in viral genes, such as P0, which plays a role in viral pathogenicity and suppression of host RNA silencing, have been identified as key targets for diagnostic advancements (31). Advances in genomic sequencing have provided new insights into the virus’s spread and evolution, offering opportunities to better understand and address CLRDV (32). Genome sequencing data are crucial for assessing genetic diversity among CLRDV strains in different regions, enabling the tracking of viral movement, detection of emerging virulent variants, and the development of more precise molecular diagnostic tools. Thus, combining genome-based surveillance with traditional agricultural practices and breeding initiatives offers a promising approach to more effectively manage CLRDV.

The high bootstrap value (>90%) associated with the phylogenetic grouping of certain isolates suggests a strong genetic similarity and a recent common ancestry between these strains. This close relationship implies that the EC4-like variant may have spread quickly, or that the isolates detected in Brownfield underwent mutations, possibly through aphid-mediated transmission or human activities, such as the movement of infected plant material. Detection of this isolate in Brownfield (TX) aligns with statewide reports of CLRDV circulation across commercial cotton fields and raises concerns that the virus may be more widespread than currently known. Moreover, genomic data from retrospective studies indicate CLRDV has been cryptically circulating in the U.S. since at least 2006, underscoring the potential genetic diversity yet to be uncovered (32). Although the sequence variation among isolates remains limited, this highlights the need for ongoing genomic surveillance to detect novel variants before they attain wider distribution. Further, the amino acid changes observed in the viral sequences provide important insights into potential viral adaptations (13, 33). Phylogenetic reconstruction using Maximum Likelihood methods demonstrated that CLRDV isolates form geographically distinct clades, indicating regional adaptation (34–36). The fact that isolates from the Brownfield cluster together suggests that local environmental pressures or varying resistance traits among cotton cultivars may be selecting for specific viral variants. Moreover, coordinated studies from sentinel plots across the U.S. cotton belt highlight cultivar-specific variation in disease incidence and severity, reinforcing the hypothesis that host resistance shapes viral evolution (35, 36). Collectively, these findings support the idea that regional environmental factors and cultivar composition are driving local adaptation of CLRDV, enhancing the virus’s ability to persist and spread. Ongoing monitoring of viral evolution and transmission dynamics is essential for understanding the virus’s adaptation to local conditions and for developing effective, region-specific management strategies and diagnostic tools.

5 Conclusion

Despite its economic importance, knowledge regarding the genetic diversity of CLRDV and the evolutionary forces shaping its variability remains limited. This study underscores the nucleotide diversity in relatively conserved sequences among closely related CLRDV isolates, primarily driven by mutations and recombination events in a small area. The amino acid sequence analysis of the new CLRDV isolate from Brownfield, Texas, highlighted both conserved and variable regions across the viral genome. The identified amino acid substitutions in the movement protein suggest potential implications for the virus’s ability to spread within cotton plants, warranting further investigation into their functional significance. Ongoing surveillance and functional studies of these amino acid changes are crucial for understanding CLRDV spread dynamics and developing more effective management strategies. These insights will aid in developing molecular diagnostic tools, strengthening resistance breeding, and improving epidemiological monitoring of CLRDV in the U.S. and South America. Further research should focus on virus transmission, genome variation, recombination, host interactions, and the role of aphid vectors in viral evolution.

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