Majallah-i ḥifāẓat-i giyāhān (Jun 2016)

Identification and Molecular Analysis of Bean common mosaic virus (BCMV) and Bean common mosaic necrosis virus (BCMNV) in Mazandaran Province

  • Z. Moradi,
  • M. Mehrvar,
  • E. Nazifi

DOI
https://doi.org/10.22067/jpp.v30i1.41631
Journal volume & issue
Vol. 30, no. 1
pp. 143 – 150

Abstract

Read online

Introduction: Among legume crops, common bean (Phaseolus vulgaris L.) is one of the most important worldwide crops, because of its cultivation area and nutritional value. The closely related potyviruses Bean common mosaic virus (BCMV) and Bean common mosaic necrosis virus (BCMNV) are the most common and most destructive viruses that infect common beans throughout the world. The viruses induced similar symptoms in numerous bean genotypes, including mosaic, leaf distortion, stunting, and lethal necrosis. Like all potyviruses, BCMV and BCMNV have non-enveloped flexuous filamentous virions of 750 nm long and 11–13 nm wide, which encapsidate a single-stranded, positive-sense RNA molecule of approximately 10,000 nt long. Both are naturally transmitted by aphids in a non-persistent manner and by seed, which explains their worldwide distribution. These viruses are major constraints on bean production and can cause serious crop losses. Mazanadaran province in north of Iran is one of the major producing areas of legumes, so identification of these viruses is a concern. However, so far, no studies have been done with these viruses in this province. The aim of this research was to study the existence of BCMV and BCMNV in research areas and determining of their phylogenetic relationship. Polymerase chain reaction (PCR) with degenerate primers for conserved sequences of the viral genomes has facilitated the rapid detection of many potyviruses and enabled partial genomic sequencing. In the absence of complete genomic sequences of potyviruses, CI-coding region is more suitable for diagnostic and taxonomy purposes, rather than the coat protein (CP) usually used. The CI gene most accurately reflects the taxonomic status according to the complete ORF. Materials and Methods: From July to September 2013 and 2014, a total of 50 leaf samples of beans showing virus symptoms were collected from different bean fields in Mazandaran province. Total RNA was extracted from all samples. The RT-PCR assay was performed using potyvirus degenerate primers corresponding to the virus CI gene. Expected PCR products of 680 bp were purified from 1% agarose gels using the Gel Recovery kit, then cloned into the pTG19-T vector and sequenced. Sequences were compared to data available in GenBank. Phylogenetic tree for grouping based on nucleotide sequences was constructed by MEGA 5.1 software program using neighbor-joining method. Multiple alignments of the nucleotide and amino acid sequences were carried out using the Clustal W and DNAMAN7 software. Results and Discussion: Using potyvirus degenerate primers CI F/R, an amplicon of the expected size (680 bp) was generated from 13 plant samples. Specific amplification using the potyvirus degenerate primers in infected samples, but not from healthy samples, confirmed the presence of a potyvirus. The most typical symptoms in positive samples were mosaic, mottling, rugosity, leaf distortion and necrosis. Two selected PCR positive samples were cloned into the pTG19-T vector, sequenced and submitted to BLASTn to identify the best matching sequences recorded in GenBank. BLASTn analysis of the sequenced data revealed that the PCR-amplified fragments belonged to Bean common mosaic virus (Cowpea) and Bean common mosaic necrosis virus (White bean). Phylogenetic tree based on multiple sequence alignment of 680 nt of CI gene divided all BCNMV isolates into two groups: I and II. Members of each group were divided into two subgroups: A, B. Isolates in subgroup IA included three isolates from China and two isolate from Indonesia. Iranian isolate (BCMV-MAZ) was classified in the group IB with RU1M isolate (USA). Group II included a wide range of Chinese isolates and also one isolate from USA, Germany, India and South Korea. Phylogenetic analysis by comparing the 680 bp of CI gene sequences showed that all BCMNV sequences can be placed into two groups: Only TN1 isolate (USA) was classified in group I. Group II included 2 subgroups A, B. Iranian isolate (BCMNV-MAZ) with NL8 isolate (USA) were classified in the subgroup IIA. Isolates in group IIB included a number of USA isolates and one isolate from the UK. Isolate of BCMV-MAZ (from Sari) showed the highest (96.8% - 98.7%) and the lowest (79.5%-91.6%) nucleotide and amino acid sequence identity with RU1M isolate (USA) and Habin1 (Korea), respectively. Also BCMNV-MAZ (from Jouybar) displayed the highest (97.8%) and the lowest (96.9%) nucleotide sequence identity with NL-3 K, NL5 and NL8, respectively. This isolate was 97.7 % identical with other isolates of the BCMNV at the amino acid identity level. Conclusions: BCMV and BCMNV are widespread in almost all bean growing areas of Iran and often present in the mixture. In this study, for the first time we reported the occurrence of BCMV and BCMNV in common beans in Mazandaran province based on the RT-PCR, and CI gene analyses, and determining their phylogenetic relationship with other isolates of these viruses available in the GenBank. Primary detection was performed by using CI F/R degenerate primer based on the potyvirus CI gene motifs I and V. Since the sequence identity of CI gene is higher when compared to that of the CP gene and is involved in helicase activity during replication, the use of CI is more accurate in defining orders in potyvirus taxonomy and in evolutionary relationships. Due to ease in the spread of these viruses by seed and vectors, detection of such viruses has a crucial role in the control of these diseases. The data obtained in this study will be beneficial to improve control strategies for these viruses in Iran. Study on the distribution of BCMV and BCMNV will be useful for breeders to incorporate virus resistance into bean cultivars, where any or both of the two viral species occur.

Keywords