Crop Protection 77 (2015) 74e86Contents lists available at ScienceDirect Crop Protection journal homepage: www.elsevier.com/locate/cropro Review Advancements in molecular marker development and their applications in the management of biotic stresses in peanuts Gyan P. Mishra*, T. Radhakrishnan, Abhay Kumar, P.P. Thirumalaisamy, Narendra Kumar, Tejas C. Bosamia, Bhagwat Nawade, Jentilal R. Dobaria Directorate of Groundnut Research, Post Box No. 05, Junagadh 362 001, Gujarat, India a r t i c l e i n f o a b s t r a c t Article history: Received 31 March 2015 Received in revised form 17 July 2015 Accepted 20 July 2015 Available online xxx Peanut is grown extensively in different parts of world, where various biotic and abiotic factors limit its productivity and quality. The major fungal biotic constraints to peanut production include rust (Puccinia arachidis Speg.), stem-rot (Sclerotium rolfsii), collar-rot (Aspergillus niger Van Teighem), afla-root (Aspergillus flavus), and late leaf spot (Phaeoisariopsis personata Ber. and M A Curtis), while viral disease constraints are peanut bud necrosis disease (PBND) caused by peanut bud necrosis virus (PBNV) and peanut stem necrosis disease (PSND) caused by tobacco streak virus (TSV). Since, only a few sources of resistance are available in cultivated peanut for some diseases, which has resulted in the limited success of conventional breeding programmes on disease resistance. Moreover, even marker assisted breeding in peanut is in the nascent stage and identification of some major quantitative trait loci (QTLs) for a few fungal disease resitance genes has only recently been reported. Substantial efforts are underway to develop PCR-based markers for the construction of high-density genetic linkage maps. This will enable the breeders to effectively pyramid various biotic stress resistance genes into different agronomically superior breeding populations, in a much shorter time. It is expected that the availability of various costeffective genomic resources (SNPs, whole genome sequencing, KASPar, GBS etc.) and more effective mapping populations (NAM, MAGIC etc.) in the coming years will accelerate the mapping of complex traits in peanut. This review provides an overview of the current developments and future prospects of molecular marker development and their applications for improving biotic-stress resistance in peanut crop. © 2015 Elsevier Ltd. All rights reserved. Keywords: Genomics Diseases and pests Marker assisted selection Linkage-mapping Transgenics 1. Introduction Peanuts (Arachis hypogaea L.), also known as groundnuts, are grown in more than 120 countries with different agro-climatic zones between latitudes 40 S and 40 N on approximately 21e24 M ha of land annually (Sarkar et al., 2014). It is cultivated predominantly by small farms under low input conditions and ranks third and fourth as a source of protein and edible oil, respectively (Bhauso et al., 2014). Several biotic stresses are known to limit peanut productivity, and their severity and extent of distribution vary with the cropping system, growing season, and region. Among biotic stresses, several diseases including rust (Puccinia arachidis Speg.), early leaf spot (ELS, Cercospora arachidicola), late leaf spot (LLS, Phaeoisariopsis personata Ber. and M A * Corresponding author. E-mail address:
[email protected] (G.P. Mishra). http://dx.doi.org/10.1016/j.cropro.2015.07.019 0261-2194/© 2015 Elsevier Ltd. All rights reserved. Curtis), and aflatoxin contamination by Aspergillus flavus and Aspergillus parasiticus are global constraints against peanut production (Subrahmanyam et al., 1984; Waliyar, 1991). Rust, stem-rot (Sclerotium rolfsii), collar-rot (Aspergillus niger Van Teighem), and leaf spots are also quite serious and together may cause the loss of 50e60% of pod yield in India (Dwivedi et al., 2003; Subrahmanyam et al., 1985). In the peanut growing regions, high yielding, welladapted cultivars contain multiple resistances to biotic stresses that can provide enhanced and sustainable peanut production (Dwivedi et al., 2003). The world's largest peanut germplasm collection with more than 15,000 accessions is housed at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in India (Gowda et al., 2013). These accessions have many differences in their vegetative, reproductive, physiological, and biochemical traits. The global Arachis gene pool possesses the source of resistance to many biotic stresses, including rust, ELS, LLS, Groundnut Rosette Disease [GRD, caused by a complex of three agents: groundnut G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 rosette virus (GRV), its satellite RNA (sat RNA), and a groundnut rosette assistor virus (GRAV)], Peanut Bud Necrosis Virus (PBND), A. flavus induced aflatoxin contamination, bacterial wilt (Ralstonia solanacearum), leafminer (Aproaerema modicella), Spodoptera, jassids (Empoasca kerri Pruthi), thrips (Frankliniella schultzei Trybom) and termites (Odontotermes sp.) (Rao et al., 2002; Basu and Singh, 2004; Amin et al., 1985; Rao et al., 2014). Since the 1960s, interspecific hybridization has received much attention in peanuts because several wild Arachis species show a very high level of resistance to many biotic stresses, such as rust, ELS, LLS, and stem rot (Holbrook and Stalker, 2003; Singh et al., 1984). However, success in transferring the resistance to cultivated peanuts has been limited mainly because of cross compatibility barriers, linkage drag, and long periods required for developing stable tetraploid interspecific derivatives (Wynne et al., 1991; Singh et al., 1997). Moreover, the partial and polygenic nature of biotic stresses makes the identification of resistant and susceptible lines very tedious using conventional screening techniques (Leal-Bertioli et al., 2009). Because of the frequent occurrence of multiple diseases, peanut yields are often significantly lower than their potential (Holbrook and Stalker, 2003). In the future, cultivars with multiple disease and pest resistances will be needed, which appears to be a very difficult endeavour for this crop species (Basu and Singh, 2004). Marker-assisted selection (MAS) offers great promise for improving the efficiency of conventional plant breeding (Janila et al., 2013), including the potential to pyramid resistance genes in peanuts (Mishra et al., 2009; Varshney et al., 2014; Pandey et al., 2012). For any molecular breeding program, assessment of genetic diversity and development of genetic linkage maps are two very important steps (Dwivedi et al., 2003). Abundant polymorphisms in wild Arachis species have been observed, but progress in the molecular breeding of cultivated peanuts is greatly constrained due to the low level of detectable molecular genetic variation (Mondal et al., 2005; Herselman, 2003; Raina et al., 2001; He and Prakash, 2001). Therefore, the use of more robust assays such as single nucleotide polymorphisms (SNPs), competitive allele-specific PCR (KASPar) and genotyping by sequencing (GBS) approaches are needed. However, cost-effective SNP genotyping platforms are not readily available for tetraploid peanuts, but a large number of robust markers such as SSRs and SNPs (including KASPar) would be valuable. SSRs are still considered the marker of choice in peanuts (Pandey et al., 2012), and a wide range of genotypes have been used for mapping (Table 1) of many important biotic and abiotic traits using SSR markers (Table 2). Despite being an important oilseed crop, very limited work in the area of molecular genetics and breeding of peanuts has been performed (Dwivedi et al., 2002; Raina et al., 2001). However, over the last decade, significant developments have been made in the use of various molecular approaches for biotic stress management in peanuts, and new efforts such as functional genomics are likely to play key roles in the future (Wang et al., 2011; Varshney et al., 2014; Gajjar et al., 2014). Recently, Kanyika et al. (2015) has 75 identified 376 polymorphic SSR markers in 16 African groundnut cultivars with a wide range of disease resistance. These identified markers can be used to improve the efficiency of introgression of resistance to multiple important biotic constraints into farmerpreferred varieties of Sub-Saharan Africa. In this review, we made an attempt to capture the recent updates in molecular marker development and their applications in the management of various biotic stresses in peanut. 2. Markers associated with rust and LLS resistance gene(s) Rust and leaf spots are economically very important foliar fungal diseases of peanuts that often occur together and not only reduce the yield but also adversely affect the fodder and seed quality (Subrahmanyam et al., 1985; Waliyar, 1991). Despite the economic importance of rust and LLS, very limited work has been carried out on hostefungus interaction, fungal genetic diversity, and physiological specialization (Mondal and Badigannavar, 2015). Several studies have emphasized the application of different types of molecular markers, construction of peanut linkage maps, or tagging of important agronomic traits, such as disease resistance (Wang et al., 2011; Gajjar et al., 2014). Recently, many DNA markers have been found to be putatively linked to rust and LLS resistance genes (Mondal et al., 2012a; Khedikar et al., 2010; Shoba et al., 2012; Sujay et al., 2012) (Table 2), a few of which have been validated and used in the breeding programme (Sujay et al., 2012; Gajjar et al., 2014; Varshney et al., 2014). Location of markers on the various linkage groups in Table 2, is derived after doing intensive meta-analysis of all the published literature, including the most comprehensive and consensus linkage maps available in peanut. Validation of other linked markers will accelerate the process of introgression of disease resistance into preferred peanut genotypes (Sujay et al., 2012; Gajjar et al., 2014). Near isogenic lines (NILs) developed for rust resistance were thoroughly screened with both foreground and background molecular markers (Yeri et al., 2014). For the identification of LLS resistance, Luo et al. (2005b) identified genes in the resistant genotype that were more highly expressed than in the susceptible genotype (in response to Cercosporidium personatum infection) by microarray analysis and validated them by real-time PCR. In a recombinant inbred line (RIL) population (VG 9514 TAG 24), two transposable element (TE) markers, TE 360 and TE 498, were found to be associated with the rust resistance gene. These two markers need further validation before they could be effectively applied for MAS of rust resistance in different backgrounds (Mondal et al., 2013). 3. Soil-borne fungal diseases and associated markers (Collar rot, Stem rot, Aspergillus spp., Bacterial wilt and Sclerotinia blight) Among soil-borne diseases, collar rot (A. niger) and stem-rot (S. rolfsii) are very important (Farr et al., 1989; Kolte, 1984). The search for peanut cultivars resistant to S. rolfsii originates all the way back Table 1 List of a few genotypes, used for mapping of various resistance gene(s) (Dwivedi et al., 2003; Shoba et al., 2012; Sujay et al., 2012). Traits Genotypes Early leaf spot Late leaf spot Rust Rosette disease Bacterial wilt Aflatoxin production ICG 405, ICG 1705, ICG 6284, TMV 2 GPBD 4, ICGV 99001, ICGV 99004, COG 0437, TAG 24, TMV 2 GPBD 4, ICGV 99003, ICGV 99005, TG 26, TMV 2 ICG 6323, ICG 6466, ICG 11044, JL 24 ICG 7893, ICG 15222, and Chico U 4-7-5, 55-437, J 11 76 G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 Table 2 SSR markers and its linkage group known to be associated to the rust and/or LLS resistance gene(s). S. No. Primers Linkage group Cross/genotypes Resistance Reference 1 2 seq3A01238a seq5D05274 a07 b07and a07 Rust Rust and LLS 3 4 seq16F01271 seq17F06152 b03 b04 ICGV 99003 TMV 2 TMV 2 COG 0437 (F2) and ICGV 99005 TMV 2 ICGV 99005 TMV 2 ICGV 99005 TMV 2 and 22 genotypes Rust Rust and LLS 5 seq13A07265 b01 ICGV 99005 TMV 2 and 22 genotypes Rust and LLS 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 seq2F05280 seq8E12200 seq16C06263 seq13A10250 seq2B10290 IPAHM103160 PM384100 PM137150 PM03168 PMc588183 PM375102 seq8D09190 GM1536410 GM2301137 GM2079418 PM50110 PM35124 b02 a01 b03 b04 b03 a03 and b03 e b06 a03 and b03 e a04 b10 and a09 b03 b03 b03 b05 a06 and b04 22 genotypes 22 genotypes 22 genotypes 22 genotypes 22 genotypes TAG 24 xGPBD 4 TMV 2 COG 0437 TMV 2 COG 0437 TMV 2 COG 0437 TMV 2 COG 0437 TMV 2 COG 0437 TAG 24 GPBD 4 TG 26 xGPBD 4 TG 26 xGPBD 4 TG 26 xGPBD 4 20 genotypes 20 genotypes Rust and LLS Rust resistance Rust Rust LLS Rust LLS LLS LLS LLS LLS LLS Rust Rust Rust Rust Rust and LLS 23 seq4A05 and gi56931710 a03 RILs from VG 9514 TAG 24 Varma et al., 2005 Shoba et al., 2012; Varma et al., 2005; Shirasawa et al., 2013 Varma et al., 2005 Varma et al., 2005; Mace et al., 2006; Shirasawa et al., 2013 Varma et al., 2005; Mace et al., 2006; Shirasawa et al., 2013 Mace et al., 2006; Shirasawa et al., 2013 Mace et al., 2006 Mace et al., 2006 Mace et al., 2006 Mace et al., 2006 Khedikar et al., 2010 Shoba et al., 2012 Shoba et al., 2012; Shirasawa et al., 2013 Shoba et al., 2012; Shirasawa et al., 2013 Shoba et al., 2012 Shoba et al., 2012 Sujay et al., 2012; Shirasawa et al., 2013 Sujay et al., 2012 Sujay et al., 2012 Sujay et al., 2012 Mondal and Badigannavar, 2010 Mondal and Badigannavar, 2010; Shirasawa et al., 2013 Mondal et al., 2012a a (F2) (F2) (F2) (F2) (F2) Rust Subscript numerical values are for linked band size. to 1918 (McClintock, 1918), but a high degree of resistance is yet to be found. Recently, Thirumalaisamy et al. (2014) has reported some sources for stem rot resistance in peanut, but the genetics of resistance and markers linked with the resistance gene(s) are still lacking. Thus, there is an urgent need to find molecular markers linked with the stem rot resistance QTLs, for its use in markerassisted breeding programme. Very few published reports pertaining to the molecular characterization of S. rolfsii are available. Variations in the internal transcribed spacer (ITS) regions have revealed 12 sub-specific groupings, some of which correlated with their mycelial compatibility groups (MCGs) (Harlton et al., 1995). Punja and Sun (1997) detected 68 MCGs while comparing 128 isolates of S. rolfsii from 36 host species collected from 23 geographic regions. Cilliers et al. (2000) found Amplified Fragment Length Polymorphism (AFLP) as a suitable technique for the assessment of genetic variability between isolates and MCGs of S. rolfsii. Genetic variability among the virulent isolates of S. rolfsii was studied using molecular techniques, such as RAPD, ITS-PCR and RFLP (Prasad et al., 2010). Several molecular markers associated with pod rot resistance and susceptibility in mutants and Giza5 peanut genotype were reported by Azzam et al. (2007) using RAPD markers, although these markers still need to be validated. A. flavus and A. parasiticus infect peanut seeds and produce aflatoxins, which are harmful to both domestic animals and humans (Waliyar et al., 2015; Singh et al., 2015a,b; Liu et al., 2014). The progress in peanut breeding for resistance to aflatoxin is slow due to the lack of a cost-effective method for resistance identification in breeding materials or segregating progeny (Lei et al., 2006). Barros et al. (2007) and Singh et al. (2015a,b) analysed Aspergillus isolates collected from peanut fields in Argentina and India using AFLP, where different levels of polymorphism in different groups of isolates were recorded. Guo et al. (2008) has identified up-regulation of 8 resistance-related genes for Aspergillus infection. Lei et al. (2006) reported an AFLP (E45/M53-440) converted SCAR marker (AFs-412) to be closely linked to resistance of A. flavus infection. Screening of isolates using gene-specific PCR was found to be quite effective for the identification of gene defects in A. flavus, which could be used as bio-control agents in peanut growing areas (Dodia et al., 2014). Moreover, to date, the genetic basis of S. rolfsi and A. flavus stress resistance traits in peanuts is not fully understood. Therefore, extensive efforts are required to first identify the resistance sources and then to find the markers associated with the resistance genes/QTLs for their future use in marker assisted breeding (Mishra et al., 2014). Bacterial wilt (R. solanacearum) is an important constraint to peanut production in several Asian and African countries, and planting of bacterial-wilt resistant cultivars is the most feasible method for disease control. Genetic diversity analysis using SSR and AFLP markers among selected peanut genotypes identified certain genotypes and primer combinations for developing mapping populations and breeding for high yield, resistant cultivars (Jiang et al., 2007a). In an attempt to understand the molecular mechanism of bacterial wilt resistance, 25 differentially expressed candidate genes were identified by studying the differences in gene expression between inoculated and control seeds. Confirmation of the functions of these genes needs to be validated through transgenic studies (Ding et al., 2012). For Sclerotinia blight (Sclerotinia minor) resistance, Kelly et al. (2010) characterized 96 US peanut mini-core collections using a resistance-associated SSR marker, and 39 accessions as new potential sources of resistance were identified. 4. Molecular studies on resistance to viral diseases (Groundnut rosette disease, PBND and PSND) Groundnut rosette disease is the most destructive viral disease of peanuts causing serious yield losses. Single recessive gene control for resistance to the aphid vector (Aphis craccivora) was observed in the breeding line ICG 12991, which was mapped 3.9 cM G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 from an AFLP marker on LG 01 (Herselman et al., 2004). Peanut bud necrosis disease (PBND) caused by peanut bud necrosis virus (PBNV) and vectored by Thrips (Vijayalakshmi et al., 1995) is a major viral disease of peanuts. In 2000, a new threat to peanuts emerged in the form of a viral disease named peanut stem necrosis disease (PSND) caused by the peanut stem necrosis virus (PSNV), which results in lethal necrosis (Rao et al., 2000). Tobacco streak virus (TSV) was found to be associated with the disease (Reddy et al., 2002). Despite several years of effort, a confirmed source of genetic resistance/tolerance to TSV has not been identified in the gene pool of cultivated peanuts. However, genetically engineered resistance has been actively investigated in recent years as an alternative to cope with this type of situation (Mehta et al., 2013). Kamdar et al. (2014) studied 115 resistant and one susceptible line to PBND using SSR, but no clear differentiation was observed. Similarly, SSR-based diversity analysis among 15 peanut genotypes (resistant and susceptible to PBND) grouped together based on their origin rather than PBND resistance (Srinivasaraghavan et al., 2012). In the future, the availability of more cost effective genomic resources, such as SNPs and whole genome sequencing, will hasten complex trait mapping efforts (especially for viral diseases) in this crop (Pandey et al., 2012). 5. Molecular studies on nematode resistance In many peanut production areas across the world, the peanut root-knot nematode causes significant economic losses (Holbrook and Stalker, 2003). Many sources of resistance were identified in the germplasm, and lot of molecular work has been performed to find the linked gene(s)/QTLs (Mishra et al., 2009). For the root-knot nematode (Meloidogyne arenaria), two dominant genes viz. Mae (restricted egg number) and Mag (restricted galling) conditioning resistance were identified, and a RAPD marker (Z3/265) was found to be linked to these genes (Garcia et al., 1996). Different types of DNA markers associated with root-knot nematode resistance were also identified (Burow et al., 1996; Garcia et al., 1996; Choi et al., 1999; Church et al., 2000; Wang et al., 2008a) and are currently being used for the development of resistant peanut cultivars. A DNA marker with 6% recombination frequency to the resistance gene has been developed to screen the segregating populations for nematode resistance (Chu et al., 2007). The RFLP marker R2430E was found to link to a locus for resistance of the peanut root-knot nematode M. arenaria (Neal) Chitwood race 1 (Pípolo et al., 2014). Genes controlling the resistance to nematodes were introgressed through interspecific hybridization and resulted in the release of the first nematode-resistant peanut cultivar COAN (Simpson and Starr, 2001). Other works on the development of nematode-resistant peanut cultivars are presented in other sections of this review. 6. Single nucleotide polymorphism (SNP) technologies for biotic stresses Recent developments in SNP technologies for peanuts have indicated that, in the near future, additional options may be available for the rapid identification of large numbers of polymorphic markers in peanuts (Kanazin et al., 2002; Khera et al., 2013). A single base pair extension (SBE) was found to be an efficient method for high-throughput SNP mapping in peanuts, and five candidate genes for resistance were identified on the genetic map (Alves et al., 2008). Recently, Khera et al. (2013) used a set of 96 informative SNPs to develop competitive allele-specific PCR (KASPar) assays in peanuts, designated as GKAMs (Groundnut KASPar Assay Markers), through which 90 GKAMs were validated for different biotic stresses. A comprehensive list of the various 77 markers associated with different diseases and pests is given in Table 3. 7. Advancements in linkage mapping Peanut is a self-pollinated allotetraploid (2n ¼ 4x ¼ 40, AABB) crop having ten basic chromosomes, harboring about 2813 Mb of DNA content (Arumuganatham, 1991). Peanut genome is nearly 20 times larger than that of Arabidopsis thaliana and is somewhat similar to Gossypium hirsutum and Zea mays. Variation in genome size among accessions of A. hypogaea (2n ¼ 4x ¼ 40) and Arachis duranensis (2n ¼ 2x ¼ 20) (Singh et al., 1996) and between A. hypogaea and A. monticola (Temsch and Greilhuber, 2000) has also been reported. The first RFLP-based genetic linkage map of peanuts was constructed using an F2 population (Halward et al., 1993). A list of a few classical and the most recent genetic linkage maps, including consensus maps, are given in Table 4. Compared to that of many other legume crops, the development of molecular markers in cultivated peanuts has progressed at a relatively slow pace. Although many markers have been developed in both wild and cultivated peanuts, the genetic linkage map is not yet saturated. There is a need to saturate the linkage map to provide sufficient markers for marker-assisted breeding (Dwivedi et al., 2003). Constant increases in peanut marker identities and linkage groups together with the availability of genome sequence data in the recent past have opened up the possibility of integrating new markers to some LGs and identifying closely linked markers (Mondal et al., 2012a). Efforts are currently underway for applying genomics to peanut biotic stress resistance breeding through mapping and MAS for different biotic stresses (Pandey et al., 2012). 8. QTL analysis for biotic stress resistance In peanuts, many markers were recently found to be associated with QTLs for various biotic stresses, namely, rust and LLS (Sujay et al., 2012; Mondal and Badigannavar, 2010), Cylindrocladium black-rot and ELS (Stalker and Mozingo, 2001), nematodes (Chu et al., 2007; Nagy et al., 2010), tomato spotted wilt virus (TSWV) (Qin et al., 2012), aphid vector of GRD (Herselman et al., 2004). The majority of the identified QTLs are not major and account for less than 10% of the phenotypic variation explained (PVE). Major QTLs identified for rust and LLS in the germplasm source (Khedikar et al., 2010; Sujay et al., 2012) and for nematode resistance (Nagy et al., 2010; Simpson, 2001) were of a wild species origin. In peanuts, candidate genome regions controlling disease resistance were identified by placing the 34 sequence-confirmed candidate disease resistance genes and 05 QTLs against LLS on the genetic map of the A-genome of Arachis. Upon grouping, these genes and QTLs were found to be present on the upper and lower regions of LG 04 and 02, respectively, indicating the prominence of these regions for imparting disease resistance (Leal-Bertioli et al., 2009). QTL analysis in a ‘Tifrunner GT-C20’-derived mapping population has identified 54 QTLs in the F2 map, including 02 for thrips, 15 for TSWV, and 37 for LS. However, in the F5 map, 23 QTLs could be identified, including 01 for thrips, 09 for TSWV, and 13 for LS. This is the first QTL study reporting novel QTLs for thrips, TSWV, and LS, which needs refinement in the future (Wang et al., 2013, 2014). Using RIL population (VG 9514 TAG 24), 13 main and 31 epistatic QTLs for total developmental period (TDP) were detected for bruchid resistance. Two years screening identified two common main QTLs, qTDP-b08 for TDP (57e82% PVE) and qAE2010/11-a02 for adult emergence (13e21% PVE) (Mondal et al., 2014). Shoba et al. (2013) reported Ah 4-26 and PM 384 as the closest markers for QTLs of 100 kernel weight and LLS severity, respectively. Because PMc 588 and Ah 4-26 are the flanking markers for 78 G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 Table 3 List of different markers associated with various biotic stresses. Markers Disease/Causal organism Reference RAPD RFLP AFLP AFLP AFLP SCAR RAPD AS-PCRa RAPD AFLP and SSR AFLP AFLP SSR RAPD and ISSR SSR ISSR SSR Microarray EST-SSR SNP TEa Nematode Nematode Bacterial wilt Rosette disease A. flavus A. flavus Pod-rot Nematode Rust Bacterial wilt Rust LLS Sclerotinia blight Rust and LLS Nematode Rust and LLS A. flavus A. flavus Rust Rust and Leaf spots Rust Garcia et al., 1996; Burow et al., 1996 Choi et al., 1999; Church et al., 2000 Jiang et al., 2003; Ren et al., 2008 Herselman et al., 2004 Lei et al., 2005 Lei et al., 2006 Azzam et al., 2007 Chu et al., 2007 Mondal et al., 2007 Jiang et al., 2007a; Jiang et al., 2007b Hou et al., 2007 Xia et al., 2007 Kelly et al., 2010 Mondal et al., 2008 Wang et al., 2008a Mondal et al., 2009 Hong et al., 2009 Guo et al., 2011 Mondal et al., 2012b Khera et al., 2013 Mondal et al., 2013 a TE: Transposable Element; AS-PCR: Allele Specific-PCR. Table 4 List some classical and latest genetic linkage maps. Populations Marker(s)/Loci Map distance (cM) References F2 Back Cross Arachis duranensis 02 RILs 02 RILs 10 RILs, 01 BC 03 RILs RFLP RFLP 1724 marker loci 324 marker loci 225 SSR 897 marker loci 3693 marker loci 1063.0 2210.0 1081.3 1352.1 1152.9 3863.6 2651.0 Halward et al., 1993 Burow et al., 2001 Nagy et al., 2012 Qin et al., 2012 Sujay et al., 2012 Gautami et al., 2012 Shirasawa et al., 2013 PM 384, they can therefore be used for marker-assisted breeding of LLS resistance. A genetic map derived from a SunOleic 97R NC94022 cross (Qin et al., 2012) was developed, and multiple phenotyping data have identified a total of 155 QTLs, of which, 01 and 03 major QTLs for TSWV and LLS resistance, respectively, were identified (Guo et al., 2013). A QTL region with 82.62% phenotypic variation for rust resistance (Sujay et al., 2012) was validated and introgressed in some susceptible varieties using a marker-assisted backcrossing (MABC) approach by employing four markers, namely IPAHM103, GM2079, GM1536 and GM2301 (Varshney et al., 2014). It is expected that multi-location testing of the promising introgressed lines will result in the identification of entries for its possible release as varieties with enhanced disease resistance. This result emphasized the utility of using markers for QTL selection through MAS for improving the rust resistance of any elite varieties (Varshney et al., 2014). To date, neither background nor genome-wide selection has been performed in peanuts, and this analysis must await the development of high-throughput, economical assays for a large number of markers (Holbrook et al., 2011). Details of some QTLs that have been identified to be associated with biotic stress-related traits in peanuts are given in Table 5. Identification of major QTLs for various biotic stress resistances in peanuts will enable efficient MABC for the development of resistant cultivars. Recently, 39 marker trait associations (MTAs) for A. flavus, ELS, LLS, and GRD were identified using genome wide association studies (GWAS). Of these MTAs, 01 was for Aspergillus (24.69% PV), 31 for GRD (10.25e39.29% PV), 06 for ELS (9.18e10.99% PV), and 01 for LLS (18.10% PV). It is expected that upon validation these MTAs may be deployed for marker-assisted improvement of peanut genotypes (Pandey et al., 2014). 9. Biotic stresses and gene expression studies (Transcriptome analysis, microRNAs, epigenetic regulation, microarrays) In cultivated peanuts, which do not have whole genome sequence information available yet, transcriptome data are an alternative source of information, and ESTs can be used to identify candidate genes (Pandey et al., 2012). During recent years, a wealth of genomic data has been generated in peanut by high throughput transcriptome sequencing (Chopra et al., 2014, 2015). However, the available transcriptome sequences are not complete; many have low N50 values, ranging from 500 to 750 bp (Guimar~ aes et al., 2012; Chopra et al., 2014). On the basis of gene annotations, Bosamia et al. (2015) has identified 2784 SSR containing sequences, of which, 2027 (72.81%) were annotated and assigned in 4124 gene ontology terms and 31.91% sequences were found to be associated with response to stimulus encompassing biotic as well as abiotic stresses. Transcriptome analysis of cDNA collections from Arachis stenosperma infected with C. personatum revealed a number of transcription factor families and defence-related genes. Additionally, the expression of five A. stenosperma resistance gene analogues (RGAs) and four retrotransposon (FIDEL-related) sequences were also analysed by qRT-PCR, which was used to design EST-SSRs of ~es et al., 2012). which 214 were shown to be polymorphic (Guimara Bertioli et al. (2003) generated 78 RGAs based on the nucleotidebinding site (NBS) regions from A. hypogaea and other wild G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 79 Table 5 List of QTLs identified for various biotic-stress related traits in peanut. Traits No of QTLs identified Phenotypic variance explained (PVE) % Reference LLS 28 10.07e67.8 Leaf rust Aspergillus flavus Bruchid resistance Aphid vector of rosette disease In F2 map TSWV Leaf spot Thrips In F5 map Thrips TSWV Leaf spot LLS TSWV LLS 13 6 13 8 54 (Total) 15 37 02 23 (Total) 01 09 13 05 01 03 2.54e82.62 6.2e22.7 13e82 1.18e76.16 e 4.40e34.92 6.61e27.35 12.14e19.43 e 5.86 5.20e14.14 5.95e21.45 4.2e43.8 16.7 12.42e20.59 Khedikar et al., 2010; Sujay et al., 2012 Khedikar et al., 2010; Sujay et al., 2012 Liang et al., 2009 Mondal et al., 2014 Herselman et al., 2004 Wang et al., 2013, 2014 relatives. A collection of peanut nucleotide binding site leucine-rich repeat (NBSeLRR) resistance gene candidates (RGCs) were identified by mining the GenBank databases (Radwan et al., 2010). Further, Yuksel et al. (2005) also isolated 234 RGAs based on the primer sequence information from NBS-LRR and LRR-‘Toll’-like motif (LRR-TM) classes. On the similar note, Proite et al. (2007) identified 35 putative non-redundant RGAs and 26 pathogenesis related ESTs from an accession of A. stenosperma, resistant to different foliar diseases. At present, a total of 281,754 ESTs are available for Arachis spp. on the NCBI website (www.ncbi.nlm.nih.gov, accessed January 24, 2015), of which the contribution of each species is as follows: A. hypogaea (205,442), A. duranensis (35,291), Aipaensis ipaensis (32,787), A. stenosperma (6264), Alberta magna (750), A. hypogaea subsp. fastigiata (745), A. appressipila (400) and A. diogoi (75). Many of these have been generated for the identification of biotic stress resistance genes (e.g., 21,777 ESTs were identified from developing seeds against Aspergillus infection (Guo et al., 2008), and 8000 ESTs from the root tissues of A. stenosperma resistant to M. arenaria (Proite et al., 2007). Guo et al. (2009) identified 17,376 ESTs from the leaves of TSWV and leaf spot resistant and susceptible cultivars, of which 5717 had unknown functions. In response to A. flavus infection under drought stress, 29 protein spots showing differential expression between resistant and susceptible cultivars were identified and further validated using RT-PCR analysis (Wang et al., 2010). In addition, some defense-related transcripts, such as putative oxalate oxidase (EU024476) and NBS-LRR domains, were also identified. Large numbers of available ESTs in the public databases were used for EST-SSR marker development. From 16424 unigenes, using MISA (MIcroSAtellite identification tool) search, a total of 2456 novel EST-SSR primer pairs were designed; of which 366 unigenes, having relevance to various stresses and other functions were PCR validated using a set of 11 diverse peanut genotypes (both resistant and susceptible to various diseases). Of these, 340 primer pairs yielded clear and scorable PCR products and 39 primer pairs exhibited polymorphisms which are of potential use for the resistance breeding programme (Bosamia et al., 2015). Out of 411 sorghum EST-SSR (SbEST-SSR) markers tested in peanuts, 39% could be successfully amplified, of which 14% showed polymorphism among resistant and susceptible cultivars for rust and LLS diseases (Savadi et al., 2012). Out of 259 EST-SSR markers, which were developed using A. hypogaea ESTs (NCBI database), SSR_GO340445 and SSR_HO115759 were found to be closely linked to the rust resistance gene (Mondal et al., 2012b). Chen et al. (2008a, 2008b, 2011) Leal-Bertioli et al., 2009 Guo et al., 2013 identified and cloned the resistance gene to TSWV and characterized two peanut oxalate oxidase genes. In response to A. flavus infection, many genes were found to be up-regulated in peanuts, of which PR-10 and pathogenesis-induced protein (PIP) genes were cloned (Xie et al., 2009a,b). Resveratrol imparts resistance in plants against both UV radiation and fungal infection; the gene that synthesizes resveratrol synthase has been cloned from peanuts, and expression analysis indicates that it is expressed in the root (Zhou et al., 2008; Han et al., 2010). Lipid transfer proteins (LTP), which were reported to be involved in disease resistance in plants, have also been cloned from peanuts (Zhao et al., 2009). Transcriptome analysis of the migratory plant parasitic nematode Ditylenchus africanus (peanut pod nematode) from mixed stages revealed the involvement of putative proteins in developmental and reproductive processes, as well as the role of unigenes in oxidative stress and anhydrobiosis (Haegeman et al., 2009). Eight differentially expressed genes were identified in A. stenosperma roots in response to M. arenaria infection using in silico ESTs and ~es et al., 2010, 2011). microarray analysis (Guimara From non-protein coding genes, microRNAs were transcribed by RNA polymerase II (Kim, 2005), and understanding of its functional and regulatory roles could open new windows for crop improvement including disease tolerance. Zhao et al. (2010) and Pan and Liu (2010) have identified 89 peanut miRNAs belonging to 14 new miRNA and 22 conserved miRNA families, which can provide the basis for peanut miRNA research for resistance to different stresses. Relationships between functional molecules and plant phenotypes can be studied more specifically using proteomics (Wang et al., 2011), and proteins that may play roles in aflatoxin resistance in imbedded peanut seeds have been discovered through proteomic studies (Wang et al., 2008b). In eukaryotes, epigenetic regulation is known to contribute to gene silencing and plays critical roles in development and genome defence against viruses, transposons, and transgenes (Lister et al., 2008; Gehring et al., 2006; La et al., 2011). It has been observed that bacterially infected plant tissue shows a net reduction in DNA methylation, which may affect the disease resistance genes responsible for surveillance against pathogens (Alvarez et al., 2010). An investigation regarding epigenetic regulation mechanisms of the peanut allergen gene Arah3 in developing peanut embryos demonstrated an association between the loss of histone H3 from the proximal promoter and high expression of Arah3 during embryo maturation (Fu et al., 2010). For better understanding and management of various biotic stresses in peanuts, there is an urgent 80 G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 need to determine the epigenetic regulatory mechanisms of different biotic stress resistant genes and promoters. For global gene expression profiling, microarray analysis is a powerful tool (Casson et al., 2005). Because a peanut gene chip is commercial unavailability, high-throughput gene expression analysis is currently very limited. However, peanut microarrays have been specifically designed to solve particular issues, such as the characterization of A. parasiticus infection-induced changes in gene expression and gene expression profiling in different peanut tissues (Luo et al., 2005a; Payton et al., 2009). Approximately 25,000 ESTs from cDNA libraries were constructed using the bacterial wilt resistant peanut leaf before and after bacterial infection (Huang et al., 2008). Shan et al. (2007) used soybean gene chips to analyse the differential gene expression of peanut varieties that are resistant and susceptible to A. flavus infection. Using microarray analysis, Guo et al. (2011) identified 62 genes in Aspergillus resistant peanut cultivars that were up-expressed in response to Aspergillus infection, and 22 putative resistance genes that were constitutively overexpressed. In addition to microarray-based gene expression analysis, the expression and regulation of individual genes has also been studied in peanuts (Wang et al., 2011). There is a need for the development of a comprehensive genome-scale platform for developing Aspergillus-resistant cultivars through targeted markerassisted breeding and genetic engineering. 10. Transgenic approach for biotic stress management (Fungal, viral, bacterial and insect-pest resistance) The lack of available resistance genes within crossable germplasms of peanuts necessitates the use of genetic engineering strategies to impart genetic resistance against various biotic stresses (Vasavirama and Kirti, 2012). Transgenic peanut lines possessing fungal resistance genes offer an alternative to traditional resistance and fungicide applications in managing fungal diseases (Chenault et al., 2005). Vasavirama and Kirti (2012) generated transgenic peanuts using a double gene construct with SniOLP (Solanum nigrum osmotin-like protein) and Rs-AFP2 (Raphanus sativus antifungal protein-2) genes under separate constitutive 35S promoters, which then showed enhanced disease resistance to LLS. Transgenic peanuts with rice chitinase-3 overexpression (with the CaMV 35S promoter) exhibited a resistance for leaf spot that was higher than that of the control, and a good correlation was observed between chitinase activity and fungal pathogen resistance (Iqbal et al., 2012). Similarly, peanuts transgenic for the chitinase gene (Rchit) from rice showed 2- to 14-fold higher chitinase activity than the wild type, and a significant negative correlation was observed between the chitinase activity and the frequency of infection to the three tested pathogens (A. flavus, LLS and rust) (Prasad et al., 2013). Transgenic peanut lines containing antifungal genes (rice chitinase and/or alfalfa glucanase), when evaluated for their reaction to Sclerotinia blight, showed varying degrees of resistance (Chenault et al., 2005). Significantly reduced lesion size was recorded in transgenic plants expressing a barley oxalate oxidase gene compared to the controls, which means that oxalate oxidase can confer enhanced resistance to Sclerotinia blight in peanuts (Livingstone et al., 2005). A non-heme chloroperoxidase gene (cpop) from Pseudomonas pyrrocinia, a growth inhibitor of mycotoxinproducing fungi, introduced into peanuts resulted in transgenic plants that showed inhibition of A. flavus hyphal growth and reduced aflatoxin contamination of peanut seeds (Niu et al., 2009). The epidemiology of PBNV is yet to be fully understood for peanut, including the search for linked markers for resistance gene(s) and the development resistant transgenic lines for its management. To this end, attempts have been made to develop transgenic peanuts expressing PBNV genes using viral coat protein (CP) genes (Satyanarayana et al., 1995). Evaluation of transgenic peanuts with CP genes showed that resistance could be achieved against PSND (Mehta et al., 2013). Transgenic peanut lines containing the CP gene of the peanut stripe virus (PStV) were less susceptible to PStV. TSWV has a broad host range, and it spreads through ubiquitous thrips. The nucleocapsid (N) protein gene of the lettuce isolate of TSWV was inserted into the peanut genome, which showed divergent levels of gene expression (Yang et al., 1998). Transgenic peanuts expressing the N protein of TSWV and subjected to natural infection of the virus under field conditions resulted in a significantly lower incidence of spotted wilt compared to that of non-transgenic lines (Yang et al., 2004). Increased insect tolerance of the transgenic plants was recorded when the cowpea trypsin inhibitor gene was transfected into peanuts (Xu et al., 2003; Zhuang et al., 2003). The transgenic lines developed against various diseases in peanuts are compiled and presented in Table 6, but to date no transgenic peanut cultivars have been released commercially. During the last decade, strong public opposition to genetically modified (GM) food crops, especially in European countries, are juxtaposed with issues such as freedom to operate related to patented technologies (Holbrook et al., 2011). However, during last two years, many patents have been approved in various countries for field trials of GM food crops. Two genetically modified types of corn, namely ‘TC1507’ and ‘SmartStax’ developed by the US companies Pioneer and Monsanto, respectively, won EU approval for their cultivation in EU countries in February of 2014 and November of 2013, respectively (Mcmanus, 2014). In India, the Union Ministry of Environment and Forests (MoEF) has approved field trials for GM food crops (rice, wheat, maize, castor and cotton) to determine their suitability for commercial production (Business Standard, 2014). Altogether, the possibility is good that various transgenic peanut crops will be used in the next few years. 11. Achievements and future prospects The dynamic challenges of peanut farming demand a quick response from breeders to develop new cultivars, a process that can be aided by the application of molecular markers (Chu et al., 2011). ‘NemaTAM’ is the first root-knot nematode-resistant peanut variety developed using the MABC approach in the USA (Simpson et al., 2003). The ‘Tifguard High O/L’ cultivar, with nematode resistance and a high oleic:linoleic acid (high O:L) ratio in seeds, was developed using Tifguard (nematode-resistant cultivar) as the recurrent female parent and Georgia-02C and Florida-07 (high O:L cultivars) as donor parents after three rounds of accelerated backcrossing using MAS (Chu et al., 2011). A QTL region explaining up to 82.62% of the phenotypic variation for rust resistance was introgressed from cultivar ‘GPBD 4’ into three rust susceptible varieties (ICGV 91114, JL 24 and TAG 24) through MABC using four markers (IPAHM103, GM2079, GM1536, GM2301). This has generated several promising introgression lines with enhanced rust resistance and higher yields. These linked markers may be used to improve rust resistance in peanut breeding programmes across the world (Varshney et al., 2014). Through validating LLS and rust resistance-linked markers in different peanut genotypes, six superior genotypes were identified. Moreover, three lines that are superior for productivity traits and equal for disease resistance to GPBD 4 (the resistant parent) are being included in variety release trials for multi-location evaluation (Sukruth et al., 2015). Gajjar et al. (2014) studied 22 SSR markers reportedly linked to rust and LLS disease resistance on 95 diverse genotypes for marker validation, from which 16 SSRs could be validated. G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 81 Table 6 Transgenics developed for various biotic stress resistances in peanut. Genes Resistance Reference Coat protein cry1AC Nucleocapsid (N) Cowpea trypsin inhibitor gene Coat protein Chitinase and glucanase Barley oxalate oxidase cry1EC cry1X cry1EC and Chi11 Coat Protein gene PStV Mustard defensin Chloroperoxidase (cpo-p) Rice chitinase-3 Rchit and CHI SniOLP and Rs-AFP2 Rice chitinase gene (Rchit) Coat protein cry1AcF cry8Ea1 Tfgd2-RsAFP2 fusion gene PBND Elasmopalpus lignoscellus Tomato spotted wilt virus Insect tolerance Peanut stripe potyvirus Sclerotinia blight Sclerotinia blight Spodoptera litura Helicoverpa armigera and Spodoptera litura Spodoptera litura and Phaeoisariopsis personata PStV LLS A. flavus Leaf spot Fusarium wilt and Cercospora arachidicola LLS A. flavus, LLS and rust PSND Spodoptera litura Holotrichia parallela ELS and LLS Satyanarayana et al., 1995 Singsit et al., 1997 Yang et al., 1998; Magbanua et al., 2000; Yang et al., 2004 Xu et al., 2003; Zhuang et al., 2003 Higgins et al., 2004 Chenault et al., 2005 Livingstone et al., 2005; Partridge-Telenko et al., 2011 Tiwari et al., 2008; Tiwari et al., 2011 Entoori et al., 2008 Beena et al., 2008 Hapsoro et al., 2008 Anuradha et al., 2008 Niu et al., 2009 Iqbal et al., 2012 Rohini and Sankara, 2001; Iqbal et al., 2011 Vasavirama and Kirti, 2012 Prasad et al., 2013 Mehta et al., 2013 Keshavareddy et al., 2013 Geng et al., 2013 Bala et al., 2015 Because of evolutionary selection pressure and their high genetic-diversity, wild peanut species are considered to be excellent sources of various disease resistance genes that remain underutilized (Stalker and Simpson, 1995). A dense genetic linkage map should enable breeders to effectively pyramid genes for various biotic stress resistances, such as rust, LLS, and nematode resistance, into agronomically superior lines in a much shorter time period than would be possible by conventional techniques (Gajjar et al., 2014). RILs are being developed to map various genes/QTLs underlying these traits. Currently, more than 14,000 SSR markers are available from different sources; however, substantial efforts are still required to develop sufficient PCR-based markers for the construction of a high-density genetic linkage map and for routine applications in the molecular breeding of peanuts (Mishra et al., 2014; Bosamia et al., 2015). The International Peanut Genome Initiative with a time line of 2012e2016 is working on different aspects of biotic stress management at the genome level, including screening peanut accessions for new sources of disease resistance, discovering new sources of disease resistance, identifying a core set of informative markers for their deployment in resistance breeding programmes, searching and validating markers that can be used in pre-breeding for disease and pest resistance, placing candidate genes for disease resistance on the Arachis genetic map, and identifying core sets of markers for QTLs associated with biotic stress resistance (http:// www.peanutbioscience.com/peanutgenomeinitiative.html). Nevertheless, the genomic progress made in peanuts over the last few years has been quite encouraging, and it is expected that a clearer genomic picture of peanuts will be available by the year 2016 for researchers to utilize. Recently, the International Peanut Genome Initiative (IPGI) has sequenced the genome of two wild species, A. duranensis (AA genome) and A. ipaensis (BB genome), supposedly the ancestral parents of cultivated peanut, which is an allotetraploid species. The hope is that the available sequence information will provide researchers with approximately 96 percent of all peanut genomic information and provide the molecular map needed to more quickly breed drought-resistant, disease-resistant, lower-input and higher-yielding varieties (http://www.icrisat.org/newsroom/newsreleases/icrisat-pr-2014-media13.htm; Mondal and Badigannavar, 2015). However, compared to other crops such as rice, soybeans and chickpeas, the ongoing molecular breeding programme for peanuts is relatively slow primarily due to low genetic diversity among the cultivated gene pool, introgression barriers between wild and cultivated lines, non-availability of genome sequence information until last year and inadequate funding. Because a draft sequence of the Arachis genome (AA and BB) is available, the expectation is that in the next few years the quality of peanuts will be improved through the use of modern biotechnological approaches (Janila et al., 2013). Ongoing research efforts across the world have not only resulted in better understanding of the peanut genome but also facilitated ongoing marker-assisted peanut breeding programs (Holbrook et al., 2011). The use of biotechnological interventions in peanut breeding for the development of resistance cultivars against various biotic stresses is quite promising. Despite substantial advancements in the biotic management strategies, the global peanut production is still threatened by a multitude of insect pests and diseases. The situation demands judicious blending of conventional and modern crop improvement technologies for more efficient and rapid tackling of these problems (Krishna et al., 2015). An outline of the tentative biotechnological interventions for peanuts is presented in Fig. 1. 12. Conclusions We have reviewed the recent biotechnological developments for the biotic stress management of peanut crops with special preference given to genomic approaches. The goal of these studies is to find more effective and economical high-throughput tools to manage various biotic stresses in peanuts. Conventional breeding along with phenotyping tools have largely been used in peanut improvement programs, and low genetic variability has been considered one of the major bottlenecks. Therefore, mutations were used to introduce variability, and wide-hybridizations were attempted to determine the variability from wild Arachis species. For the creation of new sources of genetic diversity, approaches that are being explored include the development of transgenics, TILLING (targeting-induced local lesions in genomes) populations and synthetic allotetraploids (Holbrook et al., 2011). Additionally, a few other robust mapping populations such as NAM (nested association mapping) and MAGIC (multi-parent advanced generation intercross) are being developed by various institutions working on peanut crops. To date, the genetic basis of many important traits in 82 G.P. Mishra et al. / Crop Protection 77 (2015) 74e86 Fig. 1. An outline of tentative biotechnological interventions proposed for the development peanut genotypes resistant to various biotic-stresses. peanuts is not fully understood, and molecular mapping strategies in cultivated peanut species for a few traits (e.g., rust, LLS, drought, etc.) have only recently been developed. The development of integrated comprehensive linkage maps allows for the identification of associated markers and QTLs more precisely on some of the linkage groups. Various genes and QTLs have been found to confer different biotic stress tolerances; one of the challenges in this area is to validate these gene(s)/QTLs on different backgrounds and to use them for marker-assisted breeding to develop resistant cultivars. Countries such as the USA, China, India, and Japan have used molecular breeding approaches to complement their ongoing peanut breeding programs over the last decade (Janila et al., 2013). Cultivars developed using transgenic technologies have not yet been released for commercial production, but several programs are working towards achieving this goal. Based on the reports from various labs across the world, it is expected that many peanut cultivars developed using a variety of biotechnological interventions are going to be released very soon. 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