ISSN 1614-2942, Volume 6, Number 4 This article was published in the above mentioned Springer issue. The material, including all portions thereof, is protected by copyright; all rights are held exclusively by Springer Science + Business Media. The material is for personal use only; commercial use is not permitted. Unauthorized reproduction, transfer and/or use may be a violation of criminal as well as civil law. Tree Genetics & Genomes (2010) 6:613–625 DOI 10.1007/s11295-010-0276-z Author's personal copy OPINION PAPER The emerging role of genomic tools in mulberry (Morus) genetic improvement Kunjupillai Vijayan Received: 7 September 2009 / Revised: 5 December 2009 / Accepted: 26 January 2010 / Published online: 23 February 2010 # Springer-Verlag 2010 Abstract Mulberry (Morus L) is one of the economically important trees that have a long history of extensive cultivation in Asia. Mulberry leaf is the sole food for the silkworm Bombyx mori; hence, the sustainability of the sericulture industry is dependent on the continuous supply of nutritious mulberry leaf. Genetic improvement of mulberry for leaf yield, leaf nutritional contents, and adaptability has great socioeconomical importance because the sericulture is the backbone of rutal economy in several Asian countries. Much effort has been made on germplasm collection, characterization, and varietal development through conventional methods. However, the complexity of important agronomic traits, the substantial lag time between germination and sexual maturity, the absence of inbred lines, and the outbreeding nature of mulberry delay the genetic improvement via conventional breeding techniques. In this postgenomic era, having the next generation sequencing facilities in its fold, it is possible to integrate modern genomic tools with conventional breeding techniques to dissect the complex traits into their individual components to gain better control over them. In mulberry, such efforts are lacking. This paper, therefore, summarizes the current position of genetic and genomics research in mulberry and discusses the directions for future research, utilizing the emerging technologies in molecular markers, association genetics, quantitative trait locus mapping, transcriptomics, metabolomics, marker-assisted selection breeding, and transgenesis. Keywords Association mapping . Metabolomics . Mulberry . Trancriptomics . Sericulture . QTL mapping Introduction Mulberry (Morus L; Moraceae) is a fast-growing deciduous woody perennial tree belonging to the family Moraceae. Mulberry has tremendous economic importance in most of the developing countries in Asia, where sericulture is an important industry. The silkworm Bombyx mori L. exclusively feeds the leaf of mulberry, and hence, the sustainability of sericulture heavily depends on the productivity of high-quality mulberry leaves. Mulberry is also used as animal fodder because it is highly nutritious, palatable, and digestible (70–90%; Sanchez 2000a, b). Fruits of mulberry are used for human consumption either as fresh fruit or in the form of various confectionary products such as jam, marmalade, frozen desserts, pulp, juice, paste, ice cream, and wine (Soufleros et al. 2004; Yua et al. 2008). In spite of this high commercial importance, very little effort has been made to harness the benefits of the recent technological advancements in plant genomics for mulberry genetic improvement. Therefore, this article is intended to provide an overview of the genomic tools that are suitable for enhancing the productivity and adaptability in mulberry. Origin, distribution, and cytology Communicated by: E. Dirlewanger. K. Vijayan (*) Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan 115, Republic of China e-mail: kvijayan01@yahoo.com Mulberry originated in the northern hemisphere, particularly in the Himalayan foothills, and later it spread into the tropics of the southern hemisphere (Hou 1994; Benavides et al. 1994). Today, it is present in all regions between 50° N lat. and 10° S lat. (Yokoyama 1962), from sea level to 614 Author's personal copy altitudes as high as 4,000 m (Machii et al. 1999; Tutin 1996), which include Asia, Europe, North and South America, and Africa. Although the taxonomy of mulberry is yet to be resolved fully, according to the widely accepted classification of Koidzumi (1917), the genus Morus is divided into two sections, the Dolichostylae (long style) and the Macromorus (short style), and each section is again divided into two groups namely Papillosae and Pubescentae, based on the nature of stigmatic hairs. A total of 24 species and one subspecies are recognized in this classification (Table 1). Currently, however, more than 68 species are widely recognized (Datta 2000). Out of which, only a few species such as Morus alba, Morus indica, Morus bombycis, Morus latifolia, and Morus multicaulis are cultivated for leaves to feed the silkworm while another species, Morus nigra, is cultivated for its fruits. Cytologically, mulberry exhibits different ploidy levels. Most of the cultivating species are diploids (2x, 2n=28). But triploids (3x, 3n=42; M. bombycis), tetraploids (4x, 4n=56; Morus laevigata, Morus cathayana, and Morus boninensis), hexaploids (6x, 6n=84; Morus serrata and Morus tiliaefolia), octoploids (8x, 8n=112; M. cathayana), and docosaploids (22x, 22n=308; M. nigra) (Basavaiah et al. 1989) and even haploids (M. notabilis) with 14 chromosomes are also available in nature (Maode et al. 1996). Phenotypic and genotypic variations Owing to the great economic importance, large numbers of mulberry germplasm accessions have been maintained in several countries. For instance, China, India, Japan, Korea, and Bulgaria have, respectively, more than 1,860, 1,120, 1,375, 615, and 140 germplasm accessions (FAO 2003; Machii et al. 1999; Pan 2000; Tzenov 2002; Tikader and Dandin 2006; Tikader et al. 2009). Since information on phenotypic and genotypic variability is vital for effective utilization of germplasm accessions for long-term improvement of leaf yield, leaf quality, adaptation, and resistance to pests and diseases, efforts have continuously been made to characterize and evaluate germplasm accessions. Evaluations based on traits related to growth, development, leaf yield, leaf quality, and adaptability to various agroclimatic conditions (Banerjee et al. 2007; Bindroo et al. 1996; Machii et al. 1997, 2000; Rajan et al. 1997; Suryanarayana et al. 2002; Tikader et al. 2003; Tikader and Kamble 2008a, 2009; Vijayan et al. 1999a, b) and screening for tolerance to abiotic and biotic stresses (Sujathamma and Dandin 1998; Susheelamma and Jolly 1986; Susheelamma et al. 1990; Yadav et al. 1993; Vijayan et al. 2003, 2004a) revealed the presence of considerable genetic variability among the germplasm accessions. Based on the genetic distance estimated with different statistical methods, the germplasm accessions were grouped into Tree Genetics & Genomes (2010) 6:613–625 Table 1 Mulberry species recognized by Koidzumi (1917) Sl. no. Species 1 2 3 4 5 6 7 8 M. M. M. M. M. M. M. M. bombycis Koidz. alba L. indica L. kagayamae Koidz. boninensis Koidz. atropurpurea Roxb. laevigata Wall. formosensis Hotta 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 M. M. M. M. M. M. M. M. M. M. M. M. M. M. M. M. mesozygia Stapf. cathayana Hemsl. microphylla Bickl. rabica Koidz. latifolia Poir. acidosa Griff. rotundiloba Koidz. notabilis C. K. Schn. nigriformis Koidz. serrata Roxb. nigra L. rubra L. celtidifolia Kunth tiliaefolia Makino macroura Miq. multicaulis Perr. different clusters, and utilizing this information, parental selections were made for different breeding programs (Machii et al. 1997, 2000; Rajan et al. 1997; Vijayan et al. 1999a, b; Tikader et al. 2003; Tikader and Kamble 2008a, 2009). Highly heritable morphological characters were documented and utilized for the development and registration of varieties (Rao 2003; Vijayan et al. 1997a, c). However, phenotypic evaluation has several limitations as most of the agronomically important traits that are used for evaluations vary greatly depending upon the developmental stages and environmental conditions, and collection of data is time consuming, laborious, and expensive and is influenced by human bias. Therefore, molecular markers, which are highly polymorphic, multiallelic, nonepistatic, neutral, and insensitive to environment influence, have been used for genetic evaluation of mulberry germplasm resources. However, most of these molecular markers that have been used for mulberry genetic resource assessment are of anonymous types such as random amplification of polymorphic DNA (RAPD; Bhattacharya and Ranade 2001; Chatterjee et al. 2004; Lou et al. 1998; Srivastava et al. 2004; Xiang et al. 1995; Zhao and Pan 2004), amplified fragment length polymorphism (AFLP; Botton et al. 2005; Kafkas et al. 2008; Sharma et al. 2000; Wang and Yu 2001), and intersimple sequence repeats (ISSR; Tree Genetics & Genomes (2010) 6:613–625 Author's personal copy Awasthi et al. 2004; Vijayan and Chatterjee 2003; Vijayan 2004; Vijayan et al. 2004b, c, 2005, 2006a, b; Zhao et al. 2006). Nonetheless, these studies further confirmed the high genetic diversity among the accessions. Recently, more reliable, robust, codominant, and better informative markers such as simple sequence repeats (SSR) markers have been developed in mulberry (Agarwal et al. 2004; Zhao et al. 2005). A list of the 16 SSR primers along with their nucleotide sequences and related information is available in Tikader et al. (2009). Thus, a number of proven marker systems are now available for mulberry germplasm assessment. Using these marker systems, effective assessments of mulberry germplasm to identify genetically distant accessions with desirable traits can be made to assist the breeders for selection of parents. In the meantime, efforts can also be made to develop single-nucleotide polymorphism (SNP) markers in mulberry, as these are the abundant markers present in any genome (Collins et al. 1997). Hence, SNP can make genotyping more effective and faster than any other marker systems. Owing to the current impetus on mulberry genomic research, large numbers of expressed sequence tags (ESTs) from mulberry have been started to be deposited in GenBank (Lal et al. 2009; Zhao 2008; Sajeevan et al. unpublished). Presently, nearly 1,366 ESTs from healthy and stresssubjected plants of M. alba and M. indica are available. Using these ESTs, new markers such as SNPs and SSRs can be developed. Likewise, attempts can also be devoted to develop SNPs from ISSR and RAPD markers that are associated with valuable phenotypic traits through locusspecific amplification and comparative resequencing from multiple individuals (Rieder et al. 1998;). Recently, chloroplast genome of mulberry (M. indica cv. K2) has been completely sequenced (Ravi et al. 2006). This 158,484-bp circular DNA contains two identical inverted repeats of 25,678 bp each, separating a large single-copy region of 87,386 bp and a small single-copy region of 19,742 bp. The sequence information on the cpDNA can be of much use to develop suitable polymerase chain reaction (PCR) primers for phylogenetic assessments, evolutionary investigations (Cruzen et al. 1993), and bar coding of mulberry species (CBOL plant working group 2009). Furthermore, information on the complete sequence of chloroplast DNA has great potential for manipulating the photosynthetic efficiency of mulberry through genetic engineering because a large number genes involved in the process of photosynthesis are located in the chloroplast. Trait improvement through conventional breeding In mulberry, leaf is the primary product and, therefore, leaf productivity was the principal trait targeted by most of the breeding schemes. Leaf productivity is a multifactorial trait 615 that depends on a number of quantitative traits such as plant height, number of branches, leaf retention capacity, nodal length, leaf size and weight, total biomass, etc. (Bindroo et al. 1990; Sahu et al. 1995; Tikader and Kamble 2008a, 2009; Vijayan et al. 1997b). The other important traits that have been targeted by the mulberry breeders are the adaptability, resistance to pests and diseases, tolerance to abiotic stresses like drought, salinity, and cold, higher vegetative propagation ability, better leaf quality, and better coppicing ability. Coppicing ability is important in tropical sericulture zones where silkworms are reared four to five times per year, and to feed the silkworms with fresh leaves, mulberry is pruned regularly for four to five times per year to obtain juvenile shoots. Since mulberry is a crosspollinated perennial plant with high heterozygosity and long juvenile period, traditional breeding methodologies mostly relied on the production of F1 hybrids (Das 1984). F1 hybrids are obtained either through controlled crossing or by collecting open-pollinated seeds from selected female parents. Intensive within-family selection and clonal propagation were adopted to multiply superior hybrids. Once a hybrid with desirable traits is identified, it is mass multiplied for further assessment. Based on its performance in multilocation trials, varieties suitable for a particular agroclimatic zone is selected and released for filed cultivations (Fig. 1). Mulberry varieties are multiplied clonally (planting stem cuttings) to capture the additive and nonadditive variations. Using these breeding methods, leaf productivity has been increased significantly. Major silk-producing countries like China and India have released a number of mulberry cultivars for commercial exploitation (Tikader et al. 2009; Vijayan 2009). In spite of the large germplasm collections, breeders so far have exploited only a few accessions mostly from M. alba and a few other species closely related to it (Tikader and Kamble 2008b), leaving huge genetic resources unutilized. This reduced genetic base makes them susceptible to disease epidemics and reduces the chance of their further improvement using new combinations of genes (Tikader and Dandin 2007). This limited use of germplasm resources is mainly due to the paucity of information on the genetic control of most of the agronomically important traits. Thus, it is difficult to transfer desirable traits from the unadapted genotypes to the elite lines. Introgression of characters from wild relatives to the elite breeding line is, often, accompanied by undesirable traits that are difficult to be removed because of their close physical linkage with the desired traits, a phenomenon called linkage drag. In order to get rid of these undesired traits, back crossings are to be made for several generations. Mulberry being a tree crop with long juvenile period, back crossing for many generations is highly time consuming and laborious and is almost prohibitive. Similarly, no inbred lines or doubled haploid lines are available to study the Author's personal copy 616 Promising cultivars/land races Germplasm evaluation 4-5 yrs Parental selection Hybridization and seed collection the complexity of most of these traits to increase the productivity and nutritional quality of the leaves and the adaptability of the mulberry for sustaining the sericulture industry. (Controlled crossing/Open pollination) 4-5 yrs Genomic research in mulberry Seedling nurseries Seedling assessment/ Progeny row Trials (Growth and branching, leaf yield) Primary Yield Trials with selections from PRT (Growth, leaf yield, incidence of pests and diseases) 5-6 yrs Final Yield Trails with selections from PYTs 5-6 yrs (Growth, leaf yield, propagation efficiency, incidence of pests and diseases, bioassay) Variety for that specific region Tree Genetics & Genomes (2010) 6:613–625 Multi Location Trials with selections from FYT by regional research stations under a breeding institute 5-6 yrs (Growth, leaf yield, adaptability, incidence of pests and diseases under different cultural conditions of that zone) All India Coordinated Trials with outstanding selections from different breeding Institutes 5-6 yrs (Growth, leaf yield, adaptability, incidence of pests and diseases under different agro-climatic conditions) Registration, mass multiplication and variety release 1-2 yrs Fig. 1 Developmental stages of new mulberry varieties through conventional breeding genetic controls on important agronomic traits. Therefore, except a few crossability, heritability, and combining ability studies (Dandin et al. 1987; Dwivedi et al. 1989; Tikader and Dandin 2001; Vijayan et al. 1997a, 2008), no effort was made to understand the genetic control of major growth and adaptability traits. The major challenges, thus, faced by the mulberry breeders, such as (1) understanding the basis of heterosis and prediction of hybrid performance, (2) identification of useful genetic factors in divergent populations or lines, (3) introgression of desired traits with minimal linkage drag, (4) understanding the genotype by environment interaction, remain unresolved. In order to resolve these problems, proper understanding on (a) the number of genetic factors (loci) influencing the expression of the traits, (b) the chromosomal location of these loci, (c) the relative size of the contribution of individual loci to trait expression, (d) pleiotropic effects, (e) epistatic interactions among genetic factors, and (f) variation of expression of individual factors in different environments are required. This necessitates the integration of recent advances in genomic research with conventional breeding techniques to dissect Thus, it is evident that growth-related traits play a significant role in leaf productivity and adaptations in mulberry. Understanding on these traits through genomic approach is essential to tackle them effectively and efficiently. Although much advancement has been made in silkworm genomic research, the same could not be achieved in mulberry. However, in many tree species like Eucalyptus (Gratapaglia and Kirst 2008), Pinus (Pot et al. 2006), and Populus (Rae et al. 2006) both forward and reverse genomic approaches were proven their worth in elucidating genes involved in the expression of different traits and chemical pathways. Generally, in forward genomics, existing phenotypic traits are analyzed to identify the underlying genetic variations whereas in reverse genomic manipulation of specific gene through transgenic technologies such as insertional mutagenesis, overexpression of genes, and RNA interference (RNAi) and miRNA approaches is used to study the gene–trait relationship. Reverse genomic methods are, however, mostly species specific, expensive, and transgenic or only transiently disrupt gene functions. Forward genomic approaches, thus, seem to be well suited for mulberry as considerable phenotypic variation is present in the natural populations for the important traits like leaf yield, leaf quality, and adaptability. The commonly used technologies in forward genomics are genotyping, genetic mapping, discovery of quantitative trait loci (QTL), association mapping, positional cloning and sequencing, functional genomics, and the recently introduced metabolomics. The following sections will deal with some of these tools and their possible applications to resolve specific problems in mulberry. Genetic linkage mapping Mulberry breeding thus far focused on improvement of leaf yield and its component characters through selection on phenotypes. This selection method, based on phenotype of the principle character and its components, has achieved a certain level of genetic gain as evidenced from the higher leaf yield presently obtained from improved cultivars (Tikader et al. 2009; Vijayan 2009). Further improvement on the rate of genetic gain, particularly for the complex traits such as growth rate, leaf size, delayed leaf senescence, Tree Genetics & Genomes (2010) 6:613–625 Author's personal copy propagation efficiency, resprouting, and survival, can be achieved through indirect selection on trait-linked molecular markers. Furthermore, in mulberry, most of the component traits of leaf yield were found under the control of both additive and nonadditive gene actions (Misilamani et al. 2000; Vijayan et al. 1997a, c, 2008). Hence, capturing the nonadditive genetic variation through clonal propagation offers a potential method for considerably improving the yield potential in mulberry. Therefore, molecular markers tightly linked to traits of importance, identified through genetic linkage mapping, would be a powerful tool for accelerating the varietal developments in mulberry. In most of the plants, genetic linkage maps are constructed from segregating populations such as F2, backcrosses, doubled haploids, recombinant inbred lines, and near-isogenic lines. However, in outbreeding heterozygous perennial crops like mulberry, such populations are generally not available and are difficult to develop due to the high genetic load and the long generation period. Hence, linkage maps in tree crops are generally developed from F1 progenies, either full sibs or half sibs, using “pseudo-testcross strategy” (Grattapaglia and Sederoff 1994). The assumption behind this method is that in a cross between two heterozygous parents the dominant markers heterozygous in one parent and null in the other will segregate in a 1:1 ratio in the progeny (Grattapaglia and Sederoff 1994). Different software packages are available for constructing linkage maps using information from such crosses (Table 2). Although this method is simple and is applicable for any type of maker systems, it suffers from the limitation that maps are individual specific and cannot be aligned or integrated. Therefore, linkage maps for every elite breeding line have to be developed. Nevertheless, it is possible to integrate the maps if multiallelic codominant markers such as microsatellite markers are used. Nonetheless, linkage mapping through pseudotestcross strategy is well established in several tree plants 617 like Eucalyptus, Populus, etc. (Grattapaglia and Sederoff 1994; Thamarus et al. 2002; Zhang et al. 2004). However, in mulberry, only a single map was reported (Venkateswarlu et al. 2006), and it was constructed with RAPD, ISSR, and SSR markers. The average map distances of 15.75 cM for the female and 18.78 cM of the male parents clearly suggest that the markers in this map are sparsely distributed. Thus, the linkage information generated from this map has very limited utility in identifying markers–trait association. Therefore, attempts must be made urgently to develop linkage maps with densely distributed polymorphic markers such as AFLP, SSR, and SNPs. In this regard, it is important to note that comparative genome analyses in many crop plants have shown that gene content and orders are often highly conserved at the map level across many species. For instance, a comparative genomic analysis revealed that all common markers in Eucalyptus grandis and Eucalyptus globulus were collinear, and little evidence was found for gross chromosomal rearrangements (Myburg et al. 2003). Similarly, extensive synteny was found between the linkage maps of maritime pine and loblolly pine (Chagne et al. 2003) and between loblolly pine and Douglas fir (Krutovsky et al. 2004). Results from these studies suggest that comparative genome analysis between even distantly related species can generate useful information on genome evolution and location of homologous chromosomal regions that harbor important traits. Such approach can be used in mulberry to get more information from the great advancement made on genetic linkage analyses in other tree crops like Eucalyptus, Populus, Ficus, apple, cacao, etc. QTL discovery Given the polygenic nature of most of the economically important traits in mulberry, it is essential to map the QTLs Table 2 Some of the useful softwares for linkage and QTL mappings Software Availability Reference MAPMAKER http://www.broad.mit.edu/ftp/distribution/software/ mapmaker3/ http://www.genome.wi.mit.edu/genome_software http://www.kyazma.nl/index.php/mc.JoinMap/ http://www.inra.fr/mia/T/CarthaGene/ http://www-genome.wi.mit.edu/genome_software http://carlit.toulouse.inra.fr/MCQTL/ http://www.mapqtl.nl https://www.uni-hohenheim.de/plantbreeding/software/ http://qtl.cap.ed.ac.uk/ http://statgen.ncsu.edu/qtlcart/cartographer.html http://www.qgene.org/ Lander et al. (1987) JOINMAP CARTHAGENE MAPMAKER-QTL MCQTL MAPQTL PLABQTL QTLExpress QTL cartographer Qgene Stam (1993) de Givry et al. (2005) Lander and Botstein (1989) Jourjon et al. (2005) Van Ooijen (2004) Utz and Melchinger 1995 Seaton et al. (2002) Basten et al. (1998) Nelson (1997) Author's personal copy 618 for these traits. QTL mapping has been started to be viewed as a powerful tool to dissect the complex traits into their components (Grattapaglia et al. 2009). Recent reports on the genetic architecture of QTLs in interspecific hybrids of trees (Table 3) revealed that QTL mapping is effective for growthrelated traits in all the major tree plants (Grattapaglia et al. 1996). In many such studies, the major effect of QTLs explained about 10–30% of phenotypic variations (Vaillancourt et al. 1995; Byrne et al. 1997; Rae et al. 2008; Novaes et al. 2009). Encouraged by the results of these QTL mappings in trees, mulberry breeders in India and China have taken up QTL mapping in a big way. For instance, in India, the Central Silk Board, Bangalore, with the financial support from the Department of Biotechnology (DBT), Government of India, has taken up research projects aiming to map QTLs for leaf production, vegetative propagation water use efficiency, epicuticular wax formation, and resistance to pest and diseases, which are implemented at various research institutes. Tree Genetics & Genomes (2010) 6:613–625 The basic method of discovering a QTL is based on the degree of covariation between markers and phenotypic traits. Several different approaches like single marker approach (Coffman et al. 2003), interval mapping (Lander and Botstein 1989), and composite interval mapping (Zeng 1994) are used for identifying QTLs. A number of software packages are also available for detecting QTLs and many are freely available (Table 2). Regarding the QTLs in tree species like mulberry, pseudo-testcross mapping strategy detects only those QTLs for which one or both parents are heterozygous and are not masked either by dominance (Groover et al. 1994) or by the environment in which the phenotyping is carried out (Bradshaw 1996). Lin and Ritland (1996) are of the opinion that selective genotyping might decrease the power of mapping multiple linked QTLs. The number of independent measurement per line and the number of lines used for analysis have great influence on the outcome of QTL mapping (Hansen et al. Table 3 A brief summary of the quantitative trait loci (QTL) mapping and association mappings (LD) in tree species Plant Character studied Results References Apple Apple Cacao Fruit quality Biotic stress Yield and growth QTL mapping QTL mapping LD mapping Kenis et al. (2008) Stoeckli et al. (2008) Marcano et al. (2009) Coconut Eucalyptus Eucalyptus Eucalyptus Eucalyptus Eucalyptus Douglas fir Pinus Pinus Pinus Pinus Pinus Pinus Pinus Populus Populus Populus Populus Wax components Propagation Growth Biotic stress resistance Chemical compounds against herbivory Wood properties Growth Biotic stress resistance Growth Growth Wood density Wood density Carbon assimilation Abiotic stress tolerance Bud phenology Bud phenology Carbon assimilation Abiotic stress tolerance QTL mapping QTL mapping eQTL QTL mapping QTL mapping QTL mapping QTL mapping LD mapping QTL mapping LD mapping QTL mapping LD mapping LD mapping LD mapping QTL mapping LD mapping QTL mapping QTL mapping Riedel et al. (2009) Marques et al. (2005) Krist et al. (2004) Freeman et al. (2008a) Freeman et al. (2008b) Freeman et al. (2009) Ukrainetz et al. (2008) Neale (2007) Pot et al. (2006) Yu et al. (2006) Pot et al. (2006) Gonzalez-Martinez et al. (2007) Gonzalez-Martinez et al. (2008) Gonzalez-Martinez et al. (2008) Rae et al. (2006) Hall et al. (2007) Rae et al. (2007) Street et al. (2006) Populus Populus Populus Sweet cherry White spruce White spruce White spruce Abiotic stress tolerance Growth Adventitious root growth Fruit size Biotic stress resistance Abiotic stress resistance Bud phenology eQTL QTL mapping QTL mapping QTL mapping LD mapping LD mapping LD mapping Street et al. (2006) Rae et al. (2008) Zhang et al. (2009b) Zhang et al. (2009a) Namround et al. (2008) Namround et al. (2008) Namround et al. (2008) Tree Genetics & Genomes (2010) 6:613–625 Author's personal copy 2008). Since most populations have a large number of QTLs with small effects that can combine to cause significant effect, it is important to increase replicated measures from large collections of lines. Furthermore, considering the caveat from Beavis (1998) that high heterozygosity and experimental designs may lead to overestimation of the magnitude of QTLs, adequate precautions are essential while mapping QTLs in mulberry. Another critical factor that can affect the success of QTL mapping in mulberry is the phenotyping. Phenotyping requires correct definition of traits, environmental measurements, experimental design, and proper recording of data and method of analysis. Expression quantitative trait locus mapping A QTL identified through the aforementioned approaches may have genomic regions with several hundred genes (Salvi and Tuberosa 2005). Thus, it is difficult to determine which gene(s) is responsible for the variation in the trait, for which extensive cloning and sequencing are required (Mackay 2001). System biology approaches such as transcriptomics has shown that modifications in gene regulation cause wide phenotypic variations in natural populations (Gilad et al. 2008; Hansen et al. 2008). Thus, mapping of QTLs that control the transcript level of gene expression, called expression QTL (eQTL) mapping or systems genetics, helps us understand the relationship between the genome and the transcriptome. Generally, two types of eQTLs are recognized, cis-QTLs and trans-QTLs. cis-QTLs are due to polypmorphism in or closer to the gene that codes for the mRNA product and, thus, are likely to represent structural genes, while transQTLs are due to polymorphism located elsewhere in the genome but control the transcription of the interested gene and, thus, are likely to be transcription regulator(s). The major difference of eQTL mapping from traditional QTL mapping is the ability to analyze thousands of traits at a time to find the QTL responsible for the variations (Chesler 2007). In order to achieve the full potential of eQTL mapping, it is necessary to develop highly saturated maps like those with SNP markers (Gilad et al. 2008). Several software packages are freely available, with which eQTLs can be identified from repository genomic data. EQTL EXPLORER is one such soft ware available from http://web.bioinformatics.ic.ac.uk/eqtlexplorer. The success (Table 3) of eQTL mapping in Eucalyptus and Populus (Krist et al. 2004) suggests that eQTL is much suited to mulberry for identification of genes responsible for adaptability, pathogen resistance, and early leaf senescence and leaf nutritional qualities. 619 Metabolomic QTL mapping The nutritional status of mulberry leaf has a high impact on the cocoon quality as mature silkworms use more than 70% of the leaf protein for synthesizing the silk proteins, fibroin, and sericin. (Fukuda et al. 1959). Nutritional status of mulberry leaf can be improved by integrating genetic and metabolic approaches. Metabolic profiling facilitates understanding of plant metabolic networks (Fernie and Schauer 2008). Pathway-based approaches have been found useful in identifying the genetic determinants of crop compositional quality. These approaches have identified several mQTLs in tomato (Schauer et al. 2006, 2008), Cucumis (Alba et al. 2005), and sesame (Laurentin et al. 2008). The most commonly used technologies for metabolic profiling are mass spectrometry and nuclear magnetic resonance (NMR). Different types of mass spectrometry are available. Of which, gas chromatography–mass spectrometry, gas chromatography–time-of-flight mass spectrometry, liquid chromatography–mass spectrometry, capillary electrophoresis–mass spectrometry, and Fourier transform–ion cyclotron resonance–mass spectrometry are most widely used. NMR uses magnetic nuclei of atoms after application of a constant magnetic field. NMR has the advantage of being used for assessing living cells; it provides subcellular information, and it is easier to drive atomic information for flux modeling from NMR than from mass-spectrometrybased approaches (Fernie and Schauer 2008). Considering the great potentials of mQTL mapping, it can be adopted for improving the leaf quality in mulberry to enhance the silk productivity per unit area, which will have a great impact on the sustainability of sericulture. Association mapping Association mapping or linkage disequilibrium (LD) mapping is an emerging technique in plants, though it was well established in human. Association mapping differs from traditional linkage mapping in many aspects (Table 4); it exploits the historical and evolutionary recombination events rather than the limited recombinations available in biparental mapping populations (Nordborg and Tavaré 2002). LD mapping uses the genetic diversity present in natural populations to identify molecular markers that are tightly linked to complex phenotypic traits on the basis of significant allele frequency differences between individuals with the phenotype of interest (“cases”) and a set of unrelated control individuals (Pritchard et al. 2000). Based on the nature of the study, LD mapping can be categorized into candidate gene association mapping and genome-wide association mapping (Zhu et al. 2008). Candidate gene association mapping relates polymorphisms in selected Author's personal copy 620 Tree Genetics & Genomes (2010) 6:613–625 Table 4 Major differences between biparental linkage mapping and association mapping Linkage mapping Association mapping Family-based Pedigree data are essential Recombination from only 2–3 generations is available Parental lines must be genotypically and phenotypically divergent and must be compatible Mapping population is to be developed Information on a single genetic background is available High-resolution mapping requires large population Alleles are screened only in pairs in diploids Less prone to false positive Population-based Pedigree data are not essential Recombination from many generation is available No parents candidate genes with phenotypic variation for specific traits whereas genome-wide association mapping or gene scan surveys genetic variation in the whole genome to locate genes or narrow regions that have significant statistical connections to various complex traits (Zhu et al. 2008). Many computer softwares can be used for visualizing linkage disequilibrium (Table 5). Association mapping has already proven its efficiency in many tree plants (Table 3). Detection of gene–trait associations for important growth traits like phenology, disease resistance, drought resistance, and wood properties in those trees suggest the suitability of association mapping in mulberry, though it has not been attempted in mulberry. Marker-assisted selection breeding Variety development in mulberry based on phenotypic characters needs large-scale multienvironmental testing Table 5 Commonly available softwares for visualization of linkage disequilibrium Natural populations are used Information from a large genetic back ground is available Natural population is large Large number of alleles may be present in a single locus Highly prone to false positive due to population structure and admixture of populations (Fig. 1). In addition, mulberry needs at least 3–4 years to become well established to be able to express important agronomic traits properly. For appropriate statistical analysis, data have to be recorded in all the seasons for a minimum of 3 years. Thus, field testing of a large number of progenies of mulberry requires huge space, time, labor, and money. Therefore, assistance from environmentally insensitive, selectively neutral, and less expensive and more time-saving methods like molecular marker-assisted selection (MAS) techniques can be used for accelerating mulberry breeding as it is easier, faster, nondestructive, and cheaper than the phenotypic assessment, especially for complex traits which are expensive to assess (Koebner and Summers 2003). The most important requirement for MAS is molecular markers that are tightly linked to traits of interest (Collard et al. 2005). If there is a marker linked tightly to a particular phenotype, then one can select the phenotype indirectly based on the presence or absence of the marker on a gel or on autoradiogram, depending on the Software Available from GOLD http://www.sph.umich.edu/csg/abecasis/GOLD GRR GOLDsurfer HAPLOPAINTER HAPLOT HaploView HaploVisual JLIN LDheatmap LDMAP Marker PowerMarker SNPanalyzer TASSEL http://www.sph.umich.edu/csg/abecasis/GRR/ http://www.umbio.com http://haplopainter.sourceforge.net/html/ManualIndex.htm http://info.med.yale.edu/genetics/kkidd/programs.html http://broad.mit.edu/mpg/haploview/index.php http://www.cs.helsinki.fi/u/prastas/haplovisual/ http://www.genepi.com.au/projects/jlin http://stat-db.stat.sfu.ca:8080/statgen/research/LDheatmap http://cedar.genetics.soton.ac.uk/pub/PROGRAMS/LDMAP http://www.gmap.net/marker http://statgen.ncsu.edu/powermarker/index.html http://www.istech.info/istech/board/login_form.jsp http://www.maizegenetics.net Tree Genetics & Genomes (2010) 6:613–625 Author's personal copy marker system (Hospital 2009), because the banding patterns indirectly reveal the presence or absence of a specific chromosomal segment which carries the desired alleles (Varshney et al. 2004). Although tightly linked markers for phenotypic traits through genetic mapping have not been identified in mulberry, using multiple regression analysis on germplasm accessions, several molecular markers associated with many important agronomic and biochemical characters have been identified (Vijayan and Chatterjee 2003; Vijayan et al. 2006a, 2009; Kar et al. 2007). After appropriate validations, these markers can initially be employed for MAS breeding in mulberry. Genetic transformation system Reverse genomic tools such as insertional mutagenesis, overexpression of genes, and RNAi are increasingly being used for dissection of complex traits in trees. Insertional mutants with suppressed or activated target genes are used for identifying phenotypes (Busov et al. 2005). Overexpression of dominant genes in transgenic plants leads to visible phenotypic changes and it has been shown in trees (Grattapaglia et al. 2009). RNAi is another powerful tool that has been developed recently for validating gene function in the context of plant developments. The essence of RNAi is the delivery of doublestranded RNA into the plant to induce a sequence-specific RNA degradation mechanism that effectively silences targeted gene (Waterhouse and Helliwell 2003). For elucidating genes involved in many biochemical pathways, this methods appear to be very promising (Capell and Christou 2004). In order to apply these technologies in mulberry, an efficient transformation system is a prerequisite. Bhatnagar et al. (2002, 2003) have developed an efficient Agrobacterium-mediated transformation system for the mulberry. Using this transformation system, a glycinin gene AlaBlb, an oryzacystatin gene OC (Wang et al. 2003), and a barley HVA1 gene (Lal et al. 2008) were successfully incorporated into the mulberry genome. Thus, an efficient genetic transformation system in mulberry is ready for the breeders to take advantage of. Overexpression of genes and reverse genetics are also promising options to study the trait–gene relationships in mulberry. However, transgenesis of a highly cross-pollinated plant like mulberry should be done with great caution. In this regard, it is important to note that chloroplast genetic engineering has been viewed as a safer method of transgenic plant development as, unlike nuclear genes, transgenes in the chloroplast DNA have little chances of dissemination through cross-pollination. 621 Conclusion and perspectives Given the astonishing speed with which the current genomic research is progressing due to the revolutionary technological advancements in various fields of biology especially in DNA sequencing and bioinformatics, it is easy to envisage that studies of trait–gene associations will become as simple as doing a PCR amplification reaction in a well-equipped laboratory. Indeed, it is true that the genomic research in mulberry has not been developed as much as that in silkworms. Therefore, mulberry breeders could not get much benefit from the tremendous achievements made in plant genomic research. Nonetheless, considering the developed marker technology, large genetic resources, and trained manpower, it is envisaged that deployment of the emerging genomic tools discussed in this article would be applied soon for resolving the major bottlenecks in mulberry breeding such as germplasm evaluations, parental selections, progeny analyses, introgression of traits from unadapted genotypes and species to elite breeding lines. The efficient transformation system available for mulberry is another tool that can be used for improving mulberry via genetic engineering. Side-by-side efforts can also be made for developing adequate number of mapping populations from well-planned crosses, evolving efficient phenotyping methodologies, discovering and validating SNP markers, and developing more ESTs. These resources are essential for the successful application of the emerging genomic tools in mulberry to enhance its productivity and adaptability for sustaining a vibrant sericulture industry in Asia. References Agarwal R, Hendre UD, PS SA, Singh L (2004) Isolation and characterization of six novel microsatellite markers for mulberry (Morus indica). Mol Ecol Notes 4:477–479 Alba R, Payton P, Fei Z, McQuinn R, Debbie P, Martin GB, Tanksley SD, Giovannoni JJ (2005) Transcriptome and selected metabolite analyses reveal multiple points of ethylene control during tomato fruit development. Plant Cell 17:2954–2965 Awasthi AK, Nagaraja GM, Naik GV, Kanginakudru S, Thangavelu K, Nagaraju J (2004) Genetic diversity in mulberry (genus Morus) as revealed by RAPD and ISSR marker assays. BMC Genet 5:1, available at http://www.biomedcentral.com/1471-2156/5/1 Banerjee R, Roychowdhuri S, Sau H, Das BK, Ghosh P, Saratchandra B (2007) Genetic diversity and interrelationship among mulberry genotypes. J Genet Genomics 34:691–697 Basavaiah, Dandin SB, Rajan MV (1989) Microsporogenesis in Hexaploid Morus serrata Roxb. Cytologia 54:747–751 Basten CJ, Weir BS, Zeng Z-B (1998) QTL cartographer a reference manual and tutorial for QTL mapping. Department of Statistics North Carolina State University, Raleigh Beavis WD (1998) QTL analyses: power, precision, and accuracy. In: Patterson AH (ed) Molecular dissection of complex traits. CRC, Boca Raton, pp 145–162 622 Author's personal copy Benavides JE, Lachaux M, Fuentes M (1994) Efecto de la aplicación de estiércol de cabra en el suelo sobre la calidad y producción de biomasa de Morera (Morus sp.). In: Benavides JE (ed) Arboles y arbustos forrajeros en América Central, vol II. CATIE, Turrialba, pp 495–514 Bhatnagar S, Kapur A, Khurana P (2002) Evaluation of parameters for high efficiency gene transfer via particle bombardment in Indian mulberry, Morus indica cv. K2. Indian J Expt Biol 40:1387–1392 Bhatnagar S, Kapur A, Khurana P (2003) Evaluation of parameters for high efficiency gene transfer via Agrobacterium tumefaciens and production of transformants in Indian mulberry, Morus indica cv. K2. Plant Biotechnol 21:1–8 Bhattacharya E, Ranade SA (2001) Molecular distinction among varieties of Mulberry using RAPD and DAMD profiles. BMC Plant Biol 3:1, Available at http://www.biomedcentral.com/14712229/1/3 Bindroo BB, Tikku AK, Pandit RK (1990) Variation of some metric traits in mulberry varieties. Indian For 116:320–324 Bindroo BB, Fotadar RK, Dhar A (1996) Propagation of mulberry under subtropical conditions. Indian Silk 34:11–15 Botton A, Barcaccia G, Cappellozza S, Tos RD, Bonghi C, Ramina A (2005) DNA fingerprinting sheds light on the origin of introduced mulberry (Morus spp.) accessions in Italy. Genet Resour Crop Evol 52:181–192 Bradshaw HD Jr (1996) Molecular genetics of Populus. In: Stettler RF, Bradshaw HD Jr, Heilman PE, Hinckley TM (eds) Biology of Populus and its implications for management and conservation. NRC, Ottawa, pp 183–199 Busov VB, Brunner AM, Meilan R, Filichkin S, Ganio L, Gandhi S, Strauss SH (2005) Genetic transformation: a powerful tool for dissection of adaptive traits in trees. New Phytol 167:9–18 Byrne M, Murrell JC, Owen JV, Williams ER, Moran GF (1997) Mapping of quantitative trait loci influencing frost tolerance in Eucalyptus nitens. Theor Appl Genet 95:975–979 CBOL plant working group (2009) A DNA barcode for land plants. Proc Natl Acad Sci USA 106:12794–12797 Capell T, Christou P (2004) Progress in plant metabolic engineering. Curr Opin Biotech 15:148–153 Chagne D, Brown G, Lalanne C, Madur D, Pot D, Neale D, Plomion C (2003) Comparative genome and QTL mapping between maritime and loblolly pines. Mol Breed 12:185–195 Chatterjee SN, Nagaraja GM, Srivastava PP, Naik G (2004) Morphological and molecular variation of Morus laevigata in India. Genetica 39:1612–1624 Chesler EJ (2007) Combining quantitative trait and gene-expression data. In: Barnes MR (ed) Bioinformatics for genetics: a bioinformatics primer for the analysis of genetic data. Wiley, Chichester, pp 389–402 Coffman CJ, Doerge RW, Wayne ML, McIntyre LM (2003) Intersection tests for single marker QTL analysis can be more powerful than two marker QTL analysis. BMC Genet 4:10 Collard BCY, Pang ECK, Jahufer MZZ, Brouwer JB (2005) An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: the basic concepts. Euphytica 142:169–196 Collins FS, Guyer MS, Chravarti A (1997) Variations on a theme: cataloging human DNA sequence variation. Science 128:1580– 1581 Cruzen MB, Arnold ML, Carney SE, Wollenberg KR (1993) cpDNA inheritance in interspecific crosses and evolutionary inference in Louisiana Irises. Am J Bot 80:344–350 Dandin SB, Kumar R, Ravindran S, Jolly MS (1987) Crossability studies in mulberry. Indian J Seric 26:1–4 Das BC (1984) Mulberry varieties, exploitations and pathology. Sericologia 24:369–372 Tree Genetics & Genomes (2010) 6:613–625 Datta RK (2000) Mulberry cultivation and utilization in India. FAO Electronic conference on mulberry for animal production (Morus-L). http://www.fao.org/DOCREP/005/X9895E/ x9895e04.htm#TopOfPage de Givry S, Bouchez M, Chabrier P, Milan D, Schiex T (2005) CARTHAGENE: multipopulation integrated genetic and radiated hybrid mapping. Bioinformatics 21:1703–1704 Dwivedi NK, Suryanarayana N, Susheelamma BN, Sikdar AK, Jolly MS (1989) Interspecific hybridization studies in mulberry. Sericologia 29:147–149 FAO (2003) Conservation status of sericultural germplasm resources in the world-1. Conservation status of mulberry (Morus spp.) genetic resources in the world. Food and Agricultural Organization of the United Nation (FAO), FAO Corporate Document Repository, Rome, Compiled by Kee-Wook Sohn. http://www. fao.org/DOCREP/005/AD107E/AD107E00.HTM Fernie AR, Schauer N (2008) Metabolomics-assisted breeding: a viable option for crop improvement? Trends Genet 25:39–48 Freeman JS, Potts BM, Vaillancourt RE (2008a) Few Mendelian genes underlie the quantitative response of a forest tree, Eucalyptus globules, to a natural fungal epidemic. Genetics 178:563–571 Freeman JS, O’Reilly-Wapstra JM, Vaillancourt RE, Wiggins N, Potts BM (2008b) Quantitative trait loci for key defensive compounds affecting herbivory of Eucalyptus in Australia. New Phytol 178:846–851 Freeman JS, Whittock SP, Potts BM, Vaillancourt RE (2009) QTL influencing growth and wood properties in Eucalyptus globules. Tree Genet Genome 5:713–722. doi:10.1007/s11295-009-0222-0 Fukuda T, Sudo M, Matuda M, Hayashi T, Kurose T, Florrin YHM (1959) Formation of silk protein during the growth of silkworm larvae Bombyx mori L. In: Proceeding of the 4th Intl. Cong. Biochemistry (Insect) vol. 12, pp 90–112 Gilad Y, Rifkin SA, Pritchanrd JK (2008) Revealing the architecture of gene regulation: the promise of eQTL studies. Trends Genet 24:408–415 Gonzalez-Martinez SC, Wheeler NC, Ersoz E, Nelson CD, Neale DB (2007) Association genetics in Pinus taeda L. I. wood property traits. Genetics 175:399–409 Gonzalez-Martinez SC, Huber D, Ersoz E, Davis JM, Neale DB (2008) Association genetics in Pinus taeda L. II. Carbon isotope discrimination. Heredity 101:19–26 Grattapaglia D, Sederoff R (1994) Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudotestcross: mapping strategy and RAPD markers. Genetics 137: 1121–1137 Gratapaglia D, Kirst M (2008) Eucalyptus applied genomics: from gene sequences to breeding tools. New Phytol 179:911–929 Grattapaglia D, Bertolucci FLG, Penchel R, Sederoff R (1996) Genetic mapping of quantitative trait loci controlling growth and wood quality traits in Eucalyptus grandis using a maternal half-sib family and RAPD markers. Genetics 144:1205–1214 Grattapaglia D, Plomion C, Krist M, Sedroff RR (2009) Genomics of growth traits in forest trees. Curr Opin Plant Biol 12:1–9 Groover A, Devey M, Fiddler T, Lee J, Megra WR, Mitchet-Olds T, Herman B, Vujere S, Williams C, Neale D (1994) Identification of quantitative trait loci influencing wood specific gravity in an out bred pedigree of loblolly pine. Genetics 138:1293– 1300 Hall D, Luquez V, Garcia VM, St Onge KR, Jansson S, Ingvarsson PK (2007) Adaptive population differentiation in phenology across a latitudinal gradient in European aspen (Populus tremula L.): a comparison of neutral markers, candidate genes and phenotypic traits. Evolution 61:2849–2860 Hansen BG, Halkier BA, Kliebenstein DJ (2008) Identifying the molecular basis of QTLs: eQTLs add new dimension. Trends Plant Sci 13:72–77 Tree Genetics & Genomes (2010) 6:613–625 Author's personal copy Hospital F (2009) Challenges for effective marker-assisted selection in plants. Genetics 136:303–310 Hou YJ (1994) Mulberry breeding. Sericulture Department, Zhejiang Agriculture University, Hangzhou, p 4 Jourjon MF, Jasson S, Marcel J, Ngom B, Mangin B (2005) MCQTL: multi-allelic QTL mapping in multi-cross design. Bioinformatics 21:128–130 Kafkas S, Ozgen M, Dogan Y, Ozcan B, Ercisli S, Serce S (2008) Molecular characterization of mulberry accessions in Turkey by AFLP markers. J Am Soc Hortic Sci 133:593–597 Kar PK, Srivastava PP, Awasthi AK, Raje Urs S (2007) Genetic variability and association of ISSR markers with some biochemical traits in mulberry (Morus spp.) genetic resources available in India. Tree Genet Genomes 4:75–83 Kenis K, Keulemans J, Davey MW (2008) Identification and stability of QTLs for fruit quality traits in apple. Tree Genet Genomes 4:647–661 Koebner RMD, Summers W (2003) 21st century wheat breeding: plot selection of plate detection? Trends Biotechnol 21:59–63 Koidzumi G (1917) Taxonomy and phytogeography of the genus Morus. Bull Seric Exp Station Tokyo (Japan) 3:1–62 Krist M, Myburg A, De Leon JPG, Krist ME, Scott J, Sederoff R (2004) Coordinated genetic regulation of growth and lignin revealed by quantitative trait locus analysis of cDNA microarray data in an interspecific backcross of Eucalyptus. Plant Physiol 135:2368–2378 Krutovsky KV, Troggio M, Brown GR, Jermstad KD, Neale DB (2004) Comparative mapping in the Pinaceae. Genetics 168:447–461 Lal S, Gulyani V, Khurana P (2008) Over expression of HVA1 gene from barley generates tolerance to salinity and water stress in transgenic mulberry (Morus indica). Transgenic Res 17:651–663 Lal S, Ravi V, Khurana JP, Khurana P (2009) Repertoire of leaf expressed sequence tags (ESTs) and partial characterization of stress-related and membrane transporter genes from mulberry (Morus indica L.). Tree Genet Genome 5:359–374 Lander ES, Botstein D (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199 Lander ES, Green P, Abrahamson J, Barlow A, Daly MJ, Lincoln SE, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174–181 Laurentin H, Ratzinger A, Karlovsky P (2008) Relationship between metabolic and genomic diversity in sesame (Sesamum indicum L.). BMC Genomics 9:250 Lin JZ, Ritland K (1996) The effects of selective genotyping on estimates of the proportion of recombination between linked quantitative trait loci. Theor Appl Genet 93:1261–1266 Lou CF, Zhang YZ, Zhou JM (1998) Polymorphisms of genomic DNA in parents and their resulting hybrids in mulberry Morus. Sericologia 38:437–445 Machii H, Koyama A, Yamanouchi H, Katagiri K (1997) Manual for the characterization and evaluation of mulberry genetic resources. Misc Publ Natl Inst Seric Entomol Sci 22:105–124 Machii H, Koyama A, Yamanouchi H (1999) A list of genetic mulberry resources maintained at National Institute of Sericultural and Entomological Science. Misc Publ Natl Seric Entomol Sci 26:1–77 (in Japanese) Machii H, Koyama A, Yamanouchi H, Matsumoto K, Kobayashi S, Katagiri K (2000) A list of morphological and agronomical traits of mulberry genetic resources. Misc Publ Natl Inst Seric Entomol Sci 29:1–307 Mackay TFC (2001) The genetic architecture of quantitative traits. Annu Rev Genet 35:303–339 623 Maode Y, Zhonghuai X, Lichun F, Yifu K, Xiaoyong Z, Chengjun J (1996) The discovery and study on a natural haploid Morus notabilis Schneid. Acta Sericol Sin 22:67–71 Marcano M, Morales S, Hoyer MT, Courtois B, Risterucci AM, Fouet O, Pugh T, Cros E, Gonzalez V, Dagert M, Lanaud C (2009) A genome wide admixture mapping study for yield factors and morphological traits in a cultivated cocoa (Theobroma cacao L.) population. Tree Genet Genomes 5:329–337 Marques CM, Carocha VJ, deSa ARP, Oliveira MR, Pires AM, Sedroff R, Borralho NMG (2005) Verification of QTL linked markers for propagation traits in Eucalyptus. Tree Genet Genomes 1:103–108 Misilamani S, Reddy AR, Sarkar A, Sreeniva BT, Camle CK (2000) Heritability and genetic advance of quantitative traits in mulberry (Morus spp.). Indian J Seric 39:16–20 Myburg AA, Griffin AR, Sederoff RR, Whetten RW (2003) Comparative genetic linkage maps of Eucalyptus grandis, Eucalyptus globulus and their F(1) hybrid based on a double pseudo-backcross mapping approach. Theoret Appl Genet 107:1028–1042 Namround MC, Beaulieu J, Juge N, Laroche J, Bousquet J (2008) Scanning the genome for gene single nucleotide polymorphisms involved in adaptive population differentiation in white spruce. Mol Ecol 17:3599–3613 Neale DB (2007) Genomics to tree breeding and forest health. Curr Opin Genet Dev 17:539–544 Nelson JC (1997) QGENE: software for marker-based analysis and breeding. Mol Breed 3:239–245 Nordborg M, Tavaré S (2002) Linkage disequilibrium: what history has to tell us. Trends Genet 18:83–90 Novaes E, Osorio L, Drost DR, Miles BL, Boaventura-Novaes CRD, Benedict C, Dervinis C, Qibin Yu Q, Sykes R, Davis M, Martin TA, Peter GF, Kirst M (2009) Quantitative genetic analysis of biomass and wood chemistry of Populus under different nitrogen levels. New Phytol 182:878–890 Pan YL (2000) Progress and prospect of germplasm resources and breeding of mulberry. Acta Sericol Sin 26:1–8 Pot D, Rodrigues JC, Rozenberg P, Chantre G, Tibbits J, Cahalan C, Pichavant F, Plomion C (2006) QTLs and candidate genes for wood properties in maritime pine (Pinus pinaster Ait). Tree Genet Genomes 2:10–24 Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000) Association mapping in structured populations. American J Hum Genet 67:170–181 Rae AM, Ferris R, Tallis MJ, Taylor G (2006) Elucidating genomic regions determining enhanced leaf growth and delayed senescence in elevated CO2. Plant Cell Environ 29:1730–17741 Rae AM, Tricker PJ, Bunn SM, Taylor G (2007) Adaptation of tree growth to elevated CO2: quantitative trait loci for biomass in Populus. New Phytol 175:59–69 Rae AM, Pinel MPC, Bastien C, Sabatti M, Street NR, Tucker J, Dixon C, Marron N, Dillen SJ, Taylor G (2008) QTL for yield in bioenergy Populus: identifying GxE interactions from growth at three contrasting sites. Tree Genet Genomes 4:977–112 Rajan MV, Chturvedi HK, Sarkar A (1997) Multivariate analysis as an aid to genotypic selection for breeding in mulberry. Indian J Seric 36:111–115 Rao A (2003) Conservation status of mulberry genetic resources in India. In: Conservation status of sericulture germplasm resources in the world - I. Conservation status of mulberry (Morus spp.) Genetic resources in the world. Compiled by Kee-Wook Sohn. http://www.fao.org/docrep/005/ad107e/ad107e0m. htm#TopOfPage Ravi V, Khurana JP, Tyagi AK, Khurana P (2006) The chloroplast genome of mulberry: complete nucleotide sequence, gene organization and comparative analysis. Tree Genet Genomes 3:49–59 624 Author's personal copy Riedel M, Riederer M, Becker D, Herran A, Kullaya A, Arana-López G, Peña-Rodríguez L, Billotte N, Sniady V, Rohde W, Ritter E (2009) Cuticular wax composition in Cocos nucifera L.: physicochemical analysis of wax components and mapping of their QTLs onto the coconut molecular linkage map. Tree Genet Genomes 5:53–69 Rieder MJ, Taylor SL, Tobe VO, Nickerson DA (1998) Automating the identification of DNA variations using quality-based fluorescence re-sequencing: analysis of the human mitochondrial genome. Nucleic Acids Res 26:967–973 Sahu PK, Yadav BRD, Saratchandra B (1995) Evaluation of yield components in mulberry germplasm varieties. Acta Botanica 23:191–197 Salvi S, Tuberosa R (2005) To clone or not to clone plant QTLs: present and future challenges. Trends Plant Sci 10:297–304 Sanchez MD (2000a) World distribution and utilization of mulberry, potential for animal feeding. FAO Electronic conference on mulberry for animal production (Morus-L). http://www.fao.org/ DOCREP/005/X9895E/x9895e02.htm Sanchez MD (2000b) Mulberry: an exceptional forage available almost worldwide. World Animal Review 93(1), FAO, Rome Schauer N, Semel Y, Roessner U, Gur A, Balbo I, Carrari F, Pleban T, Perez-Melis A, Bruedigam A, Kopka J, Willmitzer L, Zamir D, Fernie AR (2006) Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat Biotechnol 24:447–454 Schauer N, Semel Y, Balbo I, Steinfath M, Repsilber D, Selbig J, Pleban T, Zamir D, Fernie AR (2008) Mode of inheritance of primary metabolic traits in tomato. Plant Cell 20:509–523 Seaton G, Haley CS, Knott SA, Kearsey M, Visscher PM (2002) QTL Express: mapping quantitative trait loci in simple and complex pedigrees. Bioinformatics 18:339–340 Sharma A, Sharma R, Machii H (2000) Assessment of genetic diversity in a Morus germplasm collection using fluorescencebased AFLP markers. Theor Appl Genet 101:1049–1055 Soufleros EH, Mygdalia AS, Natskoulis P (2004) Characterization and safety evaluation of the traditional Greek fruit distillate ‘‘Mouro’’ by flavor compounds and mineral analysis. Food Chem 86:625– 636 Srivastava PP, Vijayan K, Awasthi AK, Saratchandra B (2004) Genetic analysis of Morus alba through RAPD and ISSR markers. Indian J Biotechnol 3:527–532 Stam P (1993) Construction of integrated genetic linkage maps by means of a new computer package: JoinMap. Plant J 3:739–744 Stoeckli S, Mody K, Gessler C, Patocchi A, Jermini M, Dorn S (2008) QTL analysis for aphid resistance and growth traits in apple. Tree Genet Genomes 4:833–847 Street NR, Skogstrom O, Sjodin A, Tucker J, Rodriguez-Acosta M, Nilsson P, Janson S, Taylor G (2006) The genetics and genomics of drought response in Populus. Plant J 48:321–341 Sujathamma P, Dandin SB (1998) Evaluation of mulberry genotypes for propagation parameters. Indian J Seric 37:133–136 Suryanarayana N, Rao RDM, Reddy MP (2002) Genetic divergence in mulberry (Morus spp.). Indian J Seric 41:2–11 Susheelamma BN, Jolly MS (1986) Evaluation of morphophysiological parameters associated with drought resistance in mulberry. Indian J Seric 25:6–14 Susheelamma BN, Jolly MS, Giridhar K, Sengupta K (1990) Evaluation of germplasm genotypes for drought resistance in mulberry. Sericologia 30:327–341 Thamarus KA, Groom K, Murrell J, Byrne M, Moran GF (2002) A genetic linkage map for Eucalyptus globulus with candidate loci for wood, fibre, and floral traits. Theor Appl Genet 104:379–387 Tikader A, Dandin SB (2001) Breeding behaviour of some wild mulberry. Indian Silk 40:9–10 Tree Genetics & Genomes (2010) 6:613–625 Tikader A, Dandin SB (2006) Maintenance and utilization of mulberry (Morus spp.) genetic resources. In: Proceedings of the Reports at the International Jubilee Scientific Conference Problems of maintenance and Utilization of Mulberry and Silkworm Genetic Resources, Sept, 25–2 9, 2006, Vratsa, Bulgaria Tikader A, Dandin SB (2007) Pre-breeding efforts to utilize two wild Morus species. Curr Sci 92:1072–1076 Tikader A, Kamble CK (2008a) Studies on variability of indigenous mulberry germplasm on growth and leaf yield. Pertanika J Trop Agric Sci 31:163–170 Tikader A, Kamble CK (2008b) Mulberry wild species in India and their use in crop improvement – a review. Australian J Crop Science 2:64–72 Tikader A, Kamble CK (2009) Development of core collection for perennial mulberry (Morus spp.) germplasm. Pertanika J Sci Technol 17:43–51 Tikader A, Rao AA, Thangavelu K (2003) Genetic divergence in exotic mulberry (Morus spp.) germplasm. Sericologia 43:495– 501 Tikader A, Vijayan K, Kamble CK (2009) Conservation and management of mulberry germplasm through biomolecular approaches—a review. Biotechnol Mol Biol Rev 3:92–104 Tutin GT (1996) Morus L. In: Tutin GT, Burges NA, Chater AO, Edmondson JR, Heywood VH, Moore DM, Valentine DH, Walters SM, Webb DA (eds) Flora Europa, Psilotaceae to Platanaceae, vol 1, 2nd edn. Cambridge University Press, Australia Tzenov PI (2002) Conservation status of mulberry germplasm resources in Bulgaria. Paper contributed to expert consultation on promotion of global exchange of sericulture germplasm satellite session of XIXth ISC Congress, September 21st–25th Bangkok, Thailand. http://www.fao.org/DOCREP/ 005/AD107E/ ad107e01.htm Ukrainetz NK, Ritland K, Mansfield SD (2008) Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families. Tree Genet Genomes 4:159–170 Utz HF, Melchinger AE (1995) PLABQTL: a computer program to map QTL. Version 1.0. Institute of plant breeding, seed science and population genetics. University of Hohenheim, Stuttgart Vaillancourt RE, Pottis BM, Mamson A, Eldrige T, Reid JB (1995) Using RAPDs to detect QTLs in an interespecific F2 hybrid of Eucalyptus. In: Potts BM, Borralho NMG, Reid JB, Cromer RN, Tibbits WN, Raymond CA (eds) Eucalyptus plantations: improving fibre yield and quality. CRCTHF-IUFRO Conference. (19th–24th February, 1995, Hobart, Australia). CRC for Temperate Hardwood Forestry, vol. 1, pp 430–431 Van Ooijen JW (2004) MapQTL ® 5, software for the mapping of quantitative trait loci in experimental populations. Kyazma BV, Wageningen Varshney A, Mohapatra T, Sharma RP (2004) Molecular mapping and marker assisted selection of traits for crop improvement. In: Srivastava PS, Narula A, Srivastava S (eds) Plant biotechnology and molecular markers. Kluwer, Dordrecht, pp 289–330 Venkateswarlu M, Raje Urs S, Nath BS, Shashidhar HE, Maheswaran M, Veeraiah TM, Sabitha MG (2006) A first genetic linkage map of mulberry (Morus spp.) using RAPD, ISSR, and SSR markers and pseudo testcross mapping strategy. Tree Genet Genomes 3:15–24 Vijayan K (2004) Genetic relationships of Japanese and Indian mulberry (Morus spp.) revealed by DNA fingerprinting. Plant Sys Evol 243:221–232 Vijayan K (2009) Approaches for enhancing salt tolerance in mulberry (Morus L). Plant Omics 2:41–59 Tree Genetics & Genomes (2010) 6:613–625 Author's personal copy Vijayan K, Chatterjee SN (2003) ISSR profiling of Indian cultivars of mulberry (Morus spp.) and its relevance to breeding programs. Euphytica 131:53–63 Vijayan K, Chauhan S, Chakraborti DNK, SP RBN (1997a) Leaf yield component combining abilities in mulberry (Morus spp). Euphytica 98:47–52 Vijayan K, Tikader A, Das KK, Chakraborti SP, Roy BN (1997b) Correlation studies in mulberry (Morus spp.). Indian J Genet Breed 57:455–460 Vijayan K, Das KK, Chakraborti SP, Roy BN (1997c) Heterosis for leaf yield and related characters in mulberry. Indian J Genet Plant Breed 583:369–374 Vijayan K, Das KK, Doss SG, Chakraborti SP, Roy BN (1999a) Genetic divergence in indigenous mulberry. Indian J Agric Sci 69:851–853 Vijayan K, Sahu PK, Chakraborti SP, Roy BN (1999b) Evaluation of tetraploid germplasm varieties for triploid breeding in Mulberry. Indian J Genet Plant Breed 59:515–522 Vijayan K, Chakraborti SP, Ghosh PD (2003) In vitro screening of axillary buds for salinity tolerance in mulberry genotypes. Plant Cell Rep 22:350–357 Vijayan K, Chakraborti SP, Ghosh PD (2004a) Screening of Mulberry (Morus spp.) for salinity tolerance through in vitro seed germination. Indian J Biotechnol 3:47–51 Vijayan K, Awasthi AK, Srivastava PP, Saratchandra B (2004b) Genetic analysis of Indian mulberry varieties through molecular markers. Hereditas 141:8–14 Vijayan K, Srivastava PP, Awasthi AK (2004c) Analysis of phylogenetic relationship among five mulberry (Morus) species using molecular markers. Genome 47:439–448 Vijayan K, Nair CV, Chatterjee SN (2005) Molecular characterization of mulberry genetic resources indigenous to India. Genet Resour Crop Evol 52:77–86 Vijayan K, Srivastava PP, Nair CV, Tikader A, Awasthi AK, Raje Urs S (2006a) Molecular characterization and identification of markers associated with leaf yield traits in mulberry using ISSR markers. Plant Breed 125:298–301 Vijayan K, Tikader A, Kar PK, Srivastava PP, Awasthi AK, Thangavelu K, Saratchandra B (2006b) Assessment of genetic relationships between wild and cultivated mulberry (Morus) species using PCR based markers. Genet Resour Crop Evol 53:873–882 Vijayan K, Chakraborti SP, Doss SG, Ghosh PD, Ercisli S (2008) Combining ability for morphological and biochemical characters in mulberry (Morus spp.) under salinity stress. Int J Indust Entomol 16:67–74 Vijayan K, Nair CV, Chatterjee SN (2009) Diversification of mulberry (Morus indica var. S36)—a vegetatively propagated tree species. Caspian J Env Sci 7:23–30 625 Wang ZW, Yu MD (2001) AFLP analysis of genetic background of polyploid breeding materials of mulberry. Acta Sericologic Sin 27:170–176 Wang H, Lou C, Zhang Y, Tan J, Jiao F (2003) Preliminary report on Oryza cystatin gene transferring into mulberry and production of transgenic plants. Acta Sericologic Sin 29:291–294 Waterhouse PM, Helliwell CA (2003) Exploring plant genomics by RNA-induced gene silencing. Nat Rev Genet 4:29–38 Xiang Z, Zhang Z, Yu M (1995) A preliminary report on the application of RAPD in systematics of Morus alba. Acta Sericol Sin 21:203–207 Yadav DBR, Sukumar J, Prasad KV (1993) Screening of potential resistance in the mulberry to leaf spot (Cercospora moricola) disease. Sericologia 33:81–90 Yokoyama T (1962) Synthesized science of sericulture. Japan, pp 39–46 Yu Q, Li B, Nelson C, McKeand S, Batista V, Mullin T (2006) Association of the cad-n1 allele with increased stem growth and wood density in full-sib families of loblolly pine. Tree Genet Genomics 2:98–108 Yua XH, Liua H, Tong L (2008) Feeding scenario of the silkworm Bombyx mori, L. in the BLSS. Acta Astronautica 63:1086–1092 Zeng Z-B (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468 Zhang D, Zhang Z, Yang K, Li B (2004) Genetic mapping in (Populus tomentosa × Populus bolleana) and P. tomentosa Carr. using AFLP markers. Theoret Appl Genet 108:657–662 Zhang B, Tong C, Yin T, Zhang X, Zhuge Q, Huang M, Wang M, Wu R (2009a) Detection of quantitative trait loci influencing growth trajectories of adventitious roots in Populus using functional mapping. Tree Genet Genomes 5:539–552 Zhang G, Sebolt AM, Sooriyapathirana SS, Wang D, Bink MCAM, Olmstead JW, Iezzoni AF (2009b) Fruit size QTL analysis of an F1 population derived from a cross between a domesticated sweet cherry cultivar and a wild forest sweet cherry. Tree Genet Genomes. doi:10.1007/s11295-009-0225-x Zhao W (2008) Full-length cDNA library construction and analysis of the expressed sequence tags (ESTs) of young mulberry shoots. Postdoctoral report 8. Nanjing University, China Zhao W, Pan Y (2004) Genetic diversity of genus Morus revealed by RAPD markers in China. Int J Agric Biol 6:950–954 Zhao W, Miao X, Jia S, Pan Y, Huang Y (2005) Isolation and characterization of microsatellite loci from the mulberry, Morus L. Plant Sci 16:519–525 Zhao W, Zhou Z, Miao X, Wang S, Zhang L, Pan Y, Huang Y (2006) Genetic relatedness among cultivated and wild mulberry (Moraceae: Morus) as revealed by inter-simple sequence repeat (ISSR) analysis in China. Can J Plant Sci 86:251–257 Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20