Morphological and Molecular Screening of Soybean Genotypes against Yellow Mosaic Virus Disease

Soybean [Glycine max (L.) Merrill] is one of the major legume crops in the world, providing an abundant source of oil, protein, macronutrients and minerals (Clemente and Cahoon, 2009). It is nutritionally precious for human and animal consumption as it contains 36.6 g of protein, 19.9 g of total fat, 30.2 g of carbohydrate, 9.3 g of dietary fiber and 15.7 mg of iron per 100 g of seeds. India occupied 4^th position in terms of global soybean production area, 11 million ha and 5^th in production (11 million metric tons) after United States, Brazil, Argentina and China (USDA, 2018-19). In India Madhya Pradesh, Maharashtra, Rajasthan, Karnataka and Andhra Pradesh are major soybean-growing states that contribute 96% of production in decreasing order of production. Ninety-nine per cent area under soybean is rainfed (Sky Met Whether Services, 2017). The growth and productivity of soybean are adversely affected by many biotic factors. Among them, viruses are the most notorious agent of yield losses of soybean in India. Yellow Mosaic Disease  of the leguminous crops causes an estimated annual loss of US$300 million (Varma et al., 1992). Among legumes, soybean is an economically important crop in which YMD causes 15-75% yield loss (Sharma et al., 2014).
       
Progress of yellow mosaic virus (YMV) resistance breeding in soybean is often impeded by the difficulties in identification of resistant plants. Since YMV is carried by whitefly and the distribution of whitefly may not be uniform in the field, selection may end up in picking plants with pseudo-resistance (disease escape), if proper screening approach is not followed. Selection through some indirect approaches such as gene linked-molecular marker (s) may offer help in overcoming the inaccuracies of field screening and greatly facilitates the development of YMV resistant genotypes. Among different molecular markers, microsatellites are highly preferred owing to their higher level of polymorphism, co-dominance nature, chromosome-specificity as well as reliability. In soybean, SSR markers have been used to identify YMV resistance gene linked markers (Kumar et al., 2015). However, the markers need validation for effective application in marker-assisted selection (MAS) for YMV resistance with regional adoption and higher yielding genotypes. During the present investigation an effort has been made to screen resistant genotypes against YMV based on disease indexing and SSR markers that may be used as parents in crossing programmes to breed varieties resistant against YMV in future by using conventional or molecular breeding approaches.

The field experiment was conducted during Kharif and Rabi 2018-19 with two replications in randomized block design in the field and the laboratory work has been carried out at the Plant Molecular Biology Laboratory, Department of Plant Molecular Biology and Biotechnology, College of Agriculture, Rajmata Vijayaraje Scindia Agricultural University, Gwalior, Madhya Pradesh, India.
 
Source of biological materials
 
Fifty-three accessions of soybean (Table 1) were obtained from authentic sources and grown in field for virus indexing. The seeds was obtained from College of Agriculture, JNKVV, Jabalpur, RAK, College, Sehore and Zonal Agricultural Research Station, Morena, RVSKVV, Gwalior, M.P., India. Fresh leaves samples were collected for the genomic DNA extraction for SSR markers analysis.
 

 
Screening of genotypes against YMV in field
 
A set of 53 soybean genotypes was selected for testing reaction against YMV disease in field condition (Fig 1). For this purpose, the genotypes were grown in RBD design in 3-meter-long rows with spacing of 30 cm from row-to-row and 5-7 cm from-plant-to-plant in the experimental field. In order to ensure proper spread of the disease and to maintain uniform pressure of it across the field, spreader rows of highly susceptible genotype JS335 was grown as boarder rows and considered as positive control for screening of soybean genotypes. The crop was grown following standard package-of-practices to get a good crop stand. Scoring of YMV disease reaction was performed. The score has been assigned as per disease symptoms appeared in the leaves and growth pattern observation. The data on disease severity was recorded using 0-9 rating scale (Mayee and Datar, 1986). In this method the point scale (0 to 9) is divided into 6 categories for screening of genotype for disease resistance. General interpretation of the scale is as follows:
 


Disease severity has been calculated by using following formula:
                                                                                                         
Molecular analysis
 
A total of 20 SSR molecular markers for YMV were used for genetic diversity analysis. Primers were obtained from Imperial Life Sciences Pvt. Ltd. Gurgaon, Haryana, India. Genomic DNA was isolated using protocol proposed by Saghai-Maroof et al., (1984) with minor modifications. Extracted DNA was quantified using Nanodrop by measuring the absorbance at 260nm and 280nm. After quantification, the DNA was diluted with distilled water. The final concentration of DNA obtained to be used for PCR was 25 ng µl^-1. The amplification of genomic DNA was carried out in a 0.2 ml PCR tube containing 10x PCR buffer, 1.4 mM MgCl₂, 100µM dNTPs, 5pM each primer (forward and reverse) and 1U Taq DNA polymerase. PCR conditions were initial denaturation at 94°C for 4 minutes, denaturation at 94°C for 30 sec, annealing at 55-60°C (according to the primer) for 30 sec, elongation at 72°C for 45 sec and final elongation at 72°C for 5 minutes.  Amplified products were resolved on 2.5% agarose gel using electrophoresis for the generation of microsatellite fingerprints. The products were visualized by ethidium bromide staining and final gel picture documented with gel documentation system.

In the present study screening of the fifty-three soybean genotypes against YMV disease resistance has been performed (Fig 1). Various research works on the effect of yellow mosaic diseases in soybean were carried out previously (Karthikeyan et al., 2004; Gupta and Chouhan, 2005; Salem et al., 2009). In this study, JS335 was taken as a control for phenotypic as well as molecular analysis due to its higher susceptibility against YMD. The result is presented in Table 2; during Kharif 2018, maximum virus infection were recorded in RVS 2001-4 (36.00) followed by JS 97-52 (35.30), AMS 2014-4 (27.00), JS 335 (25.90), VLS-94 (22.90), KDS-992 (22.70), PS-1092 (21.80), JS20-71 (20.10), PS-1613(19.10), RC-132(4.50), SKF-SPS-11(3.90), RC (3.40), RSC10-52 (3.10), EC 457286 (1.20), RVS 76 (1.00), NRC-130 (0.90), SP-37 (0.90), NRCSL-1 (0.80), SL-1123 (0.80), SL 1068(0.70), NRC-86 (0.60), MACSNRC-1575 (0.60), MACS725 (0.50), JS 20-69 (0.40), RVS 2207-6 (0.40), RVS-14 (0.40), RVS2011-35 (0.30), MACS 15-20 (0.20), RVS 18 (0.10),  RVS-24(0.10) and JS 20-94 (0.10), while  YMV disease free germplasm lines were recorded JS 20-98, JS 95-60, JS 20-84, AGS 111, NRC 127, KDS 980, G-29, RSC 10-70, RSC 10-71, NRC-2, MACS-58 (0.00). During Rabi 2018-19, maximum virus infection were recorded in RVS 2001-04 (23.90) followed by JS 97-52 (20.23), AMS 2014-4 (20.70), KDS-992 (19.10), JS 335 (18.80), VLS-94 (16.30), PS-1613 (13.50), PS-1092 (12.90), JS20-71 (12.20), SKF-SPS-11(3.50), NRC-132 (3.30), NRC-125 (1.60), EC457286 (1.50), RSC10-52 (1.30), NRC-134 (1.20), NRC76 (0.60), SL 1068 (0.60), NRC-130 (0.50), NRC-86 (0.40), MACSNRC-1575 (0.20) and MACS-1520 (0.20), while many genotypes were found free  from virus infection as score was recorded (0.00).
 

 

       
Out of 53 genotypes, 12 entries viz., JS 20-84, AGS 111, JS 20-98, NRC127, KDS980, G-29, RSC-10-70, RSC-10-71, NRC-2, MACS-15-20, MACS-58 and JS 95-60 were found highly resistant (Table 2). Twenty six  genotypes viz., JS 20-29, JS 20-69, JS 20-94, JS 20-116, JS 20-34, RVS 2007-6, RVS 2011-35, RVS -14, RVS -24, RVS -18, NRC- 76, NRC -86, NRC- 130, NRC -131, NRC -147, AMSMBC -18, AMS-100-39, MACS 1520, MACSNRC-1575, SL -1123, SL-1068, MACS725, SP 37, NRC SL-1, RVS 76 and MACS - 1520 showed resistant reaction. Among above twenty six genotypes, two of them (JS20-69 and JS20-34) have been reported moderately resistant against yellow mosaic virus recently (Silodia et al., 2018). Six genotypes have been found moderately resistant viz., RSC-10-52, EC457286, NRC -125, NRC-132, NRC-134 and SKF-SPS -11. Seven genotypes viz., JS 20-71, PS 1092, PS 1613, MS 2014-1, KDS 992, VLS -94, JS 93-05 showed moderately susceptible reaction and only three genotypes have been found to show highly susceptible reaction viz., JS 335, RVS 2001-04 and JS 97-52 (Fig 2).
 

       
In a similar field study conducted by Pancheshwar et al., (2016) to screen 72 soybean genotypes against YMV disease a total of 40 genotypes namely CAT 87, JS 98-79, JS 20-05, JS 20-24, JS 20- 29,JS 20-69, JS 20-74, JS 20-76, JS 20-82, JS 20-90, JS 20-98, JS (IS) 90-5-12-1, PK 885, PK 1225, PS 1466, PS 1539, PS 1540, SPC 175, SL 96, SL 517, SL 710, SL 744, SL 799, SL 900, SL 955, UPSM 534, PK 515, PS 1225, PS 1584, GSDL 7, GSDL 49, GSDL 57, GSDL 82, PK 416, PS 564, PS 19, PS 1573, SL 958, SL 983 and PSB 13-15 exhibited highly resistance. While, 16 genotypes viz., B 327 B1664 CAT 783 DS 2410 HIMSO 1681 JS 99-72 JS 20-21 JS 20-30, JS 20-73 JS 20-77 NRC 56 PK 768 PS 1518 RVS 2002-4 SL 738 and PSB 13-16 showed moderately resistant response. Similar studies on the field evaluation of yellow mosaic diseases have been performed by several workers and various characteristics of pathogen like symptoms development on hosts, their allocation and transmission are well documented (Haq et al., 2010; Srivastava and Prajapati, 2012; Govindhan et al., 2014; Silodia et al., 2018). Evaluation of crops against YMV has been done by several researchers (Pandya et al., 1977; Ganapathy et al., 2003; Silodia et al., 2018).
       
In the present study, evaluation of the soybean genotypes against YMV disease under field condition demonstrated the presence of variations against YMV disease. This suggests the requirement for constant screening of crop varieties against such diseases. It will be helpful to select better genotypes against YMV disease. Koranne and Tyagi (1985) also evaluated 88 soybean genotypes in the field to select YMV resistant genotypes. Baruah et al., (2014) examined 44 soybean genotypes against yellow mosaic virus (YMV). In their study, after field screening two highly resistant varieties (DS 9712 and DS9814) and one highly susceptible variety JS335 were identified.
 
Molecular markers analysis
 
It is reported that YMV resistance in soybean is governed by single dominant (Bhattacharyya et al., 1999) and two recessive (Singh and Mallick, 1978) genes. This indicates that the genetics of YMV resistance in soybean is not much clear. There are contradictory reports on the genetic nature of Yellow mosaic virus resistance. It has become imperative to find out the true nature of YMV resistance in soybean. Exploitation of SSR markers for molecular analysis in relation to different traits have been reported in soybean (Tomar et al., 2011; Sahu et al., 2012; Tripathi and Khare, 2016). Attempts have also been made to identify DNA markers linked to YMV resistance in soybean crop. Yadav et al., (2015) performed whole genome sequencing approach for YMV susceptible and resistant soybean varieties to find the genomic regions linked with resistance gene. A single nucleotide polymorphism (SNP) was reported in their study with a possible linkage with YMV resistance gene. Kumar et al., (2015) also reported two markers (Satt301 and GMHSP179) with possible association with yellow mosaic disease in soybean. We also included above said markers in the present study but unfortunately, we didn’t get good quality amplification with all soybean genotypes taken. So, both markers were not considered. The previously reported linkages by above said researchers have not been validated in mapping population. Perhaps due to this reason no other reports are available on use of such markers in development of YMV resistance soybean varieties through marker assisted selection. Due to not-availability of accurately linked SSR markers to YMV resistance in soybean we tried new SSR markers for the present study.
       
In our study, a total of twenty YMV linked SSR markers were tried to amplify soybean genotypes. Among them only ten SSR markers were found to be able to successfully amplify all soybean genotypes. Out of ten, eight markers (Table 3) amplified two alleles with an average of 1.8 alleles per locus. This indicates very narrow genetic basis of the genotypes taken for the study. Similarly, Rani et al., (2016) identified genetic basis of 41 soybean genotypes varying in resistance against yellow mosaic virus using 58 simple sequence repeat primers. An average of 2.41 alleles per locus was detected in their study. The present investigation revealed the highest genetic diversity (0.4785) with Satt554 while lowest genetic diversity (0.037) with Satt308. Similarly polymorphism information content (PIC) was highest (0.364) in Satt554 and lowest (0.0363) in Satt308 among all polymorphic markers (Table 3).


       
In UPGMA cluster analysis, soybean genotypes were grouped into two clusters one minor and one major (Fig. 3). Minor cluster contained only four genotypes namely: AMS100-99, JS20-116, MACS-1520 and NRC-2. Major cluster contained 49 genotypes and this cluster was further divided into two groups. Major group contained 48 genotypes while minor group had a single genotype VLS-94. Major group was divided into two subgroups one minor and one major. Minor group consisted of thirteen genotypes viz: AGS-111, NRC-192, NRC-190, RVS2007-6, RVS-24, NRC-191, RVS2001-4, NRC-125, SL-1068, JS335, NRC134, PS-1092 and RVS-14 and major subgroup contained thirty-five soybean genotypes. Major subgroup further divided into two portions one minor and one major. Minor portion contained single genotype, viz: JS20-29, while major portion contained thirty-four genotypes, namely : KDS980, MACSNRC-1575, JS20-84, JS20-94, G-29, NRC-127, RSC-10-52, RSC-10-70, SL-1123, AMSMBC-18, JS95-60, AMS-MS-58, JS20-34, RVS-18, SP-37, JS20-71, JS97-52, KDS-992, NRC-86, JS20-34, JS20-98, MACS-1520, NRC-147, NRC-SL-1, PS-1613, RVS-76, MACS725, AMS2014-1, RSC-10-71, EC-45-7286, NRC-76, SKF-SPS-11, JS93-05 and RVS2011-35. The clustering was based on genetic similarity among soybean genotypes revealed during SSR analysis. Most of the genotypes were grouped according to their place of origin such as JS20-84 and JS20-94, RSC-10-52 and RSC-10-70, JS20-71 and JS97-52, JS20-69 and JS20-98, NRC-147 and NRC-SL-1. Among all the genotypes, JS20-69 and VLS-94 formed separate subgroups for each of them. This indicated their genetic variability from rest of the genotypes.
       


In field condition 11 genotypes were found to be highly resistant and 26 were resistant including JS 20-29, JS 20-69 and JS 20-98. Similarly in molecular analysis these genotypes showed their genetic distance from rest of the genotypes. In dendrogram JS 20-69 and JS 20-98 grouped together however JS 20-29 formed a separate group. This indicates the correlation between field data and molecular marker data. Inclusion of more numbers of microsatellite markers may be beneficial to for identification of more YMV resistant genypes.

In conclusion, out of fifty-three, 11 genotypes were found to be highly resistant, 26 resistant, 6 moderately resistant, 4 moderately susceptible, 3 susceptible, while three genotypes namely: JS335, JS 97-52 and RVS 2001-4 showed highly susceptible expression of the YMV disease during virus indexing at field level. The significance of the findings of this study is that it would pave the way for YMV resistance breeding in soybean. Because, transferring genes from wild relatives comes with penalty of linkage drag (Ram et al., 1984). The resistant genotypes identified in this study are principally released varieties. Use of such improved varieties as donor of resistance will exclude the problem of linkage drag; rather it might contribute some useful genes to the recipient genotypes. The improved genotypes with YMV resistance would stand as barrier against spread of the disease to newer areas and thus it can boost production and productivity of soybean in the country.