caratterizzazione ed utilizzo delle risorse genetiche

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Plant Genetic Resources: Characterization and Utilization

Special issue on the 2nd International Symposium on “Genomics of Plant Genetic

Resources”, 24 – 27 April 2010, Bologna, Italy

Guest editors

Roberto Tuberosa

Andreas Graner

Rajeev K. Varshney

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Plant Genetic Resources

Characterization and Utilization

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Plant Genetic Resources

Characterization and Utilization

Genomics of plant genetic resources: an

introduction

Roberto Tuberosa

1

*, Andreas Graner

2

and Rajeev K. Varshney

3 1

Department of Agroenvironmental Science and Technology, Viale Fanin 44, 40127

Bologna, Italy,2Leibniz Institute of Plant Genetics and Crop Plant Research (IPK),

Corrensstraße 3, D-06466 Gatersleben, Germany and3International Crops Research

Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad 502 324, Andhra Pradesh, India

This special issue of Plant Genetic Resources has assembled 52 short articles selected among the over 350 oral and poster communications presented during the 2nd International Symposium on Genomics of Plant Gen-etic Resources (GPGR2; www.GPGR2.com) held in Bologna, Italy, from April 24 to 27, 2010. The second edition of GPGR2, co-organized by Bioversity International, the Leibniz Institute of Plant Genetics and Crop Plant Research and the University of Bologna, followed the first edition organized in 2005 by the Chinese Academy of Agricultural Science in Beijing, China.

The overall objective of GPGR2 was to critically evalu-ate how the levalu-atest advances in genomics platforms and resources have enhanced our capacity to investigate plant genetic resources and harness their potential for improving crop productivity and quality. The unifying picture that emerges from the articles collected in this issue shows the increasingly pivotal role of genomics for characterizing germplasm collections, best managing genebanks, elucidating plant functions and identifying superior alleles at key loci for the selection of improved genotypes. In this brief introduction, we present an over-view of the main topics covered and have included additional references to provide some further reading opportunities to the interested reader who wishes for a more comprehensive overview of the merits and limi-tations of genomics-based approaches.

The first group of articles (from page 155 – 184) offers a glimpse of the tools, platforms and resources currently available to investigate the structural and functional diversity present in both the coding and non-coding regions of the plant genome. This complexity, largely

inaccessible until recently, is now receiving increasing attention in view of its importance in the regulation of quantitative trait expression. Structural variability (e.g. copy number variations and/or indels) in what, as a reflection of our past ignorance, was often referred to as ‘junk DNA’ has instead been shown to be an important driver of phenotypic variability (Magalhaes et al., 2007; Salvi et al., 2007). Operationally, the new paradigm has been set by next generation sequencing (NGS) and bioin-formatics, quickly adopted as the gold standard required to deliver an exhaustive, accurate characterization of DNA variation, the discovery of single nucleotide poly-morphisms (SNPs) in massive number (Akhunov et al., 2009; Varshney et al., 2009) and the analysis of synteny (Bolot et al., 2009). The cost of sequencing has already fallen dramatically and keeps dropping, thus allowing for the direct analysis of large sets of accessions at a frac-tion of the cost of such an operafrac-tion just a few short years ago. NGS is also becoming the preferred choice for tran-scriptome profiling (Forrest and Carninci, 2009; Tamura and Yonemaru, 2010). Unlike microarray platforms (Gupta et al., 2008; Pietsch et al., 2009), NGS offers the distinct advantage of being able to report on changes across the entire transcriptome, including in rare tran-scripts. The power and benefits of NGS are particularly evident in species such as apple, potato or maize that suffer from low linkage disequilibrium while enjoying a high level of polymorphism, two features which require a highly detailed analysis at the DNA level to identify haplotype diversity in germplasm collections. A level of genetic resolution sufficient to validate candidate genes and, in some cases, even identify causal polymorphisms can be attained by association mapping, an approach increasingly adopted to dissect the genetic basis of target traits (Ersoz et al., 2007; Rafalski, 2010). Genome-wide association mapping greatly benefits from the

* Corresponding author. E-mail: roberto.tuberosa@unibo.it

qNIAB 2011

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Plant Genetic Resources: Characterization and Utilization (2011) 9(2); 151–154 doi:10.1017/S1479262111000700

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utilization of genome-wide SNP genotyping (Waugh et al., 2009). Compared with other classes of molecular markers, SNPs are amenable to high-throughput automation at a relatively low cost (Edwards et al., 2009). Although SNPs are already routinely utilized in a number of important crops (e.g. rice, barley and maize; McNally et al., 2009; Hayden et al., 2010; Yan et al., 2010), con-siderable work is still required to establish suitable platforms in polyploid species such as wheat, in view of the additional difficulties caused by the presence of

homoeologous loci (Ganal and Ro¨der, 2007; Berard

et al., 2009; Trebbi et al., 2011).

The second group of articles (from page 185 – 280) deals with one of the most difficult challenges faced by genebank managers, namely the characterization of germplasm collections. Over the past two decades, mol-ecular profiling has greatly improved the accuracy of this characterization (Glaszmann et al., 2010), particu-larly in the so-called ‘orphan’ species, which have been largely neglected also due to the lack of the

means to properly investigate their biodiversity

(Varshney et al., 2010). An accurate characterization at the genomic level is a fundamental step required for (1) a more cost-efficient management of germplasm collections, both in situ and ex situ, (2) understanding phylogenetic relationships among species (Bolot et al., 2009), (3) the assembly of core collections suitable for association mapping studies (Maccaferri et al., 2011) and (4) assessing genetic similarity among accessions sharing common ancestors (Maccaferri et al., 2007).

The third group of articles (from page 281 – 360) pre-sents examples on how genomics-based approaches can provide information useful for crop improvement programmes by providing the breeder with effective indirect selection schemes. In particular, a number of articles (from page 324 – 351) deal with the improvement of crop quality and nutritional value, a topic of great interest in countries where malnutrition – the so-called ‘hidden hunger’ – is rampant as a consequence of an unbalanced diet. To address this problem, programmes such as HarvestPlus (www.harvestplus.org) are exploit-ing both natural and artificially induced variation to increase the iron, zinc and provitamin A content in crops. For the genomics-based improvement of crops for resistance to abiotic and biotic stresses, the generation challenge programme (GCP; www.generationcp.org) has developed a valuable molecular marker toolkit which provides easy access to existing information on molecular markers used in breeding programmes. Additionally, the GCP’s genotyping support service offers cost-efficient genotyping services, both for fingerprinting and the anal-ysis of genetic diversity, as well as for molecular breed-ing. The most significant results achieved by the GCP through the application of genomics approaches have

been summarized in two recent articles (Glaszmann et al., 2010; Varshney et al., 2010) and some examples are also presented in this special issue. The adoption of genomics-assisted breeding has considerably enhanced the effectiveness of breeding programmes and the response to selection (Varshney et al., 2005; Varshney and Tuberosa, 2007; Xu, 2010). Marker-assisted selection (MAS) is now routinely included in many breeding pro-grammes, particularly for traits controlled by major loci (Ejeta and Knoll, 2007; Gupta and Langridge, 2010). This notwithstanding, MAS for complex quantitative traits (e.g. drought tolerance) remains a highly challenging undertaking, mainly because so much of the variation for these traits is under the control of many genes, where the contribution of each is too small to allow their ready identification and so justify the implementation of an MAS breeding strategy (Collins et al., 2008). Nonethe-less, some major loci which affect yield per se (i.e. not linked to phenology) across a broad range of environ-ments have been described (Maccaferri et al., 2008; Yadav et al., 2011). When major loci that affect organ growth (e.g. leaf size) and yield components (e.g. seed number and seed weight) are identified, modelling the effects of the relevant quantitative trait loci (QTLs) in response to environmental cues should provide a highly effective approach for predicting yield performance across different environmental conditions (Parent et al., 2010; Tardieu and Tuberosa, 2010). From a breeding standpoint, an interesting alternative to phenotypic selec-tion for improving yield per se is provided by genome-wide selection, which is increasingly being adopted for the improvement of those major crops where SNP platforms allow for a cost-effective, high-throughput profiling of large populations (Bernardo, 2009).

Over the past decade, genomics has ushered in novel approaches which have produced a quantum leap in our ability to characterize and utilize plant genetic resources (Tuberosa et al., 2002; Varshney et al., 2005; Ribaut et al., 2010; Yano and Tuberosa, 2009; Langridge and Fleury, 2011). Overall, molecular profiling suggests that the diver-sity stored in genebanks has been only marginally tapped into so far. Cloning of the key genes which underlie agronomically valuable traits will allow breeders to mine genebank collections much more effectively for novel alleles (Salvi and Tuberosa, 2007). Cloning will also pro-vide perfect MAS markers and the opportunity to identify novel alleles via TILLING in mutant collections (Talame` et al., 2008; Sestili et al., 2010). Importantly, when access to genes is hampered by low recombination, genetic engineering will facilitate the transfer of these cloned genes, especially when sourced from wild relatives. In this regard, recent progress regarding site-specific recom-bination may open the door to further improve plant per-formance through the replacement of distinct alleles.

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Meeting the challenges posed by climate change and the fast increasing demand for food, feed, fibre and fuel will require an acceleration of the rate of crop improve-ment, which in some key crops (e.g. wheat) has wor-riedly started to slow down (Tester and Langridge, 2010). Achieving higher gains from selection will require enlarging the pool of genetic resources and exploiting wild relatives of crops (Feuillet et al., 2008; Kovach and McCouch, 2008) to identify superior alleles not yet uti-lized in the cultivated gene pool. This brief introduction and the articles of this special issue clearly show that genomics of plant genetic resources is having a tangible impact on the way genebanks are being managed and how germplasm collections are being exploited to improve crop performance.

Acknowledgements

The GPGR2 organizers thank the sponsors (for a complete list, see the congress website at www.GPGR2. com/sponsors.html) for their generous financial support and all participants for their contributions to the scientific programme of the Congress.

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Berard A, Le Paslier MC, Dardevet M, Exbrayat-Vinson F, Bonnin I, Cenci A, Haudry A, Brunel D and Ravel C (2009) High-throughput single nucleotide polymorphism genotyping in wheat. (Triticum spp.). Plant Biotechnology Journal 7: 364 – 374.

Bernardo R (2009) Genomewide selection for rapid intro-gression of exotic germplasm in maize. Crop Science 49: 419 – 425.

Bolot S, Abrouk M, Masood-Quraishi U, Stein N, Messing J, Feuillet C and Salse J (2009) The ‘inner circle’ of the cereal genomes. Current Opinion in Plant Biology 12: 119–125.

Collins NC, Tardieu F and Tuberosa R (2008) Quantitative trait loci and crop performance under abiotic stress: where do we stand? Plant Physiology 147: 469 – 486.

Edwards KJ, Reid AL, Coghill JA, Berry ST and Barker GLA (2009) Multiplex single nucleotide polymorphism (SNP)-based genotyping in allohexaploid wheat using padlock probes. Plant Biotechnology Journal 7: 375 – 390.

Ejeta G and Knoll JE (2007) Marker-assisted selection in

sorghum. In: Varshney RK and Tuberosa R (eds)

Genomics-assisted Crop Improvement, vol. 2. Houten: Springer, pp. 187 – 206.

Ersoz ES, Yu J and Buckler ES (2007) Applications of linkage dis-equilibrium and association mapping. In: Varshney RK and Tuberosa R (eds) Genomics-assisted Crop Improvement, Vol. 1: Genomics Approaches and Platforms. Houten: Springer, pp. 97 – 120.

Feuillet C, Langridge P and Waugh R (2008) Cereal breeding takes a walk on the wild side. Trends in Genetics 24: 24 – 23.

Forrest ARR and Carninci P (2009) Whole genome transcriptome analysis. RNA Biology 6: 107 – 112.

Ganal MW and Ro¨der MS (2007) Microsatellite and SNP markers

in wheat breeding. In: Varshney RK and Tuberosa R (eds) Genomics-assisted Crop Improvement, Vol. 2: Genomics Applications in Crops. Houten: Springer, pp. 1 – 24. Glaszmann JC, Kilian B, Upadhyaya HD and Varshney RK (2010)

Accessing genetic diversity for crop improvement. Current Opinion in Plant Biology 13: 167 – 173.

Gupta PK and Langridge P (2010) Marker-assisted wheat breed-ing: present status and future possibilities. Molecular Breeding 26: 145 – 161.

Gupta PK, Rustgi S and Mir RR (2008) Array-based high-through-put DNA markers for crop improvement. Heredity 101: 5 –18. Hayden MJ, Tabone TL, Nguyen TM, Coventry S, Keiper FJ, Fox RL, Chalmers KJ, Mather DE and Eglinton JK (2010) An informative set of SNP markers for molecular characteris-ation of Australian barley germplasm. Crop and Pasture Science 61: 70 – 83.

Kovach MJ and McCouch SR (2008) Leveraging natural diversity: back through the bottleneck. Current Opinion in Plant Biology 11: 193 – 200.

Langridge P and Fleury D (2011) Making the most of ‘omics’ for crop breeding. Trends in Biotechnology 29: 33 – 40. Maccaferri M, Sanguineti MC, Xie C, Smith JSC and Tuberosa R

(2007) Relationships among durum wheat accessions. II. A comparison of molecular and pedigree information. Genome 50: 385 – 399.

Maccaferri M, Sanguineti MC, Corneti S, Ortega JLA, Ben Salem M, Bort J, DeAmbrogio E, del Moral LFG, Demontis A, El-Ahmed A, et al. (2008) Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability. Genetics 178: 489 – 511.

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Genomics of plant genetic resources:

past, present and future

Kyujung Van

1

, Dong Hyun Kim

1

, Jin Hee Shin

1

and Suk-Ha Lee

1,2

*

1

Department of Plant Science and Research Institute for Agriculture and Life Sciences,

Seoul National University, Seoul 151-921, Korea and2Plant Genomics and Breeding

Institute, Seoul National University, Seoul 151-921, Korea

Abstract

Plant genetic resources (PGR) include cultivars, landraces, wild species closely related to cultivated varieties, breeder’s elite lines and mutants. The loss of genetic diversity caused by the practice of agriculture and the availability of genetic information has resulted in a great effort dedicated to the collection of PGR. Prior to the advent of molecular profiling, accessions in germplasm collections were examined based on morphology. The development of molecu-lar techniques now allows a more accurate analysis of molecu-large collections. Next-generation sequencing (NGS) with de novo assembly and resequencing has already provided a substantial amount of information, which warrants the coordination of existing databases and their integration into genebanks. Thus, the integration and coordination of genomic data into genebanks is very important and requires an international effort. From the determination of phenotypic traits to the application of NGS to whole genomes, every aspect of genomics will have a great impact not only on PGR conservation, but also on plant breeding programmes.

Keywords:

genomics; germplasm collection; next-generation sequencing; plant genetic resources

Introduction

Plant genetic resources (PGR) began to establish around 1993 as a consequence of growing concerns about bio-diversity, its conservation and genetic erosion. Although the rate of population growth is slowing down, global food production is still a major challenge for the future of mankind (Hoisington et al., 1999; Hammer, 2003; Gepts, 2006). Therefore, securing PGR for future gener-ations has become a priority not only in developing countries but also in the entire world. The development and application of molecular techniques and genomics have dramatically improved the characterization and deployment of PGR. This review surveys the past and current status of the application of genomics to the PGR characterization and discusses future directions.

Early impact of genomics on PGR

The advent of agriculture made possible by domestication greatly affected the diversity of crops (Gepts, 2006). The voyages of Christopher Columbus marked the earliest recorded acquisition of new plant resources, and, ever since, collected plants have been conserved in botanical gardens and herbaria (Short, 2003). The rediscovery of Mendel’s law in the early 20th century helped the dramatic increase in agricultural productivity, although the overall genetic diversity decreased as a result of modern agri-cultural practices. Fearing genetic erosion, the world community increased the effort to better evaluate PGR in genebanks (Hoisington et al., 1999).

The characterization of PGR by comparisons of plant morphology, such as yield, colour, texture, taste, etc., is the simplest and easiest approach (Gilbert et al., 1999; Hoisington et al., 1999). In addition to these qualitative/ quantitative phenotypic traits, pedigree analysis and geographical distribution are also helpful for measuring

* Corresponding author. E-mail: sukhalee@snu.ac.kr

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genetic diversity (Hammer, 2003). A renewed impetus towards PGR characterization was made possible by the development of modern molecular techniques.

Current status of plant genomics

The genetic diversity of major crops has been declining through domestication and the introduction of modern plant breeding (Tanksley and McCouch, 1997; Hyten et al., 2009). To prevent the genetic vulnerability of crops and to preserve valuable genetic resources, it needs to collect, preserve, examine and utilize germplasm effectively. The concept of the core set was proposed to minimize replicates and ensure the representation of the maximum genetic diversity of the entire germplasm collection (Frankel, 1984; Brown, 1989; van Hintum, 1999). Phenotyping was the traditional criteria for germplasm evaluation; however, currently, these evalu-ations are changed to genotyping by molecular markers (Tanksley and McCouch, 1997).

Genetic markers are powerful tools for genetic map-ping, and molecular markers are highly polymorphic, easily detected and unaffected by the environment (Andersen and Lubberstedt, 2003). Various molecular markers have been developed, such as restriction fragment length polymorphisms, randomly amplified polymorphic DNA, simple sequence repeats, amplified fragment length polymorphisms and single nucleotide polymorphisms (SNPs) (Gupta et al., 2001), which are used for the construction of genetic and physical maps. These markers are applied in plant breeding for quanti-tative trait loci (QTLs) mapping, map-based cloning, marker-assisted selection, etc. (Moose and Mumm, 2008). Previously, genome-sequencing projects depended on Sanger sequencing methods. Recently, introduction of next-generation sequencing (NGS) technologies into plant breeding programmes has enabled the acquisition of high-throughput sequence data inexpensively in a short time (Morozova and Marra, 2008). However, the de novo assembly of plant genomes using NGS with short-read length is not yet adequate because most plant genomes are large and harbour long repeat sequences (Varshney et al., 2009). Thus, NGS technol-ogies are applied for the resequencing of species for which a complete reference genome sequence exists and are actively used for high-throughput genotyping of up to a million SNP markers in Arabidopsis and several polyploidy crops (Rostoks et al., 2006; Weber et al., 2007; Hyten et al., 2008; Akhunov et al., 2009; Yan et al., 2010). Genome-wide SNP genotyping is a powerful tool for association mapping and evolutionary studies (Akhunov et al., 2009). Furthermore, SNP markers can be used more effectively when combined with genotypes and

haplotypes (Hamblin et al., 2007; Yan et al., 2010). This multiplexed genotyping technology facilitates the effective examination and selection of germplasms by unravelling novel and potentially agronomically useful alleles (Tanksley and McCouch, 1997). The QTL mapping of soybean rust was successfully conducted by SNP gen-otyping using the GoldenGate assay (Hyten et al., 2009). These NGS technologies and the massively developed genome-wide markers are also applied for the construc-tion of high-density maps and genetic diversity analysis (Gupta et al., 2008).

Future directions

A wealth of genetic resources in Arabidopsis and other model species have promoted great advances in plant science. Furthermore, whole genome sequencing pro-jects involving more than 20 plants will be completed in the near future (Gupta et al., 2008). With the improve-ment in sequencing techniques, more genetic resources, including the sequences, will be available in the future. Second (next) generation sequencers – Illumina’s GA, Roche’s 454 and Applied Biosystems’ SOLiD – have gen-erated large amounts of short DNA sequence reads. These have been updated to produce longer read lengths and greater amounts of sequence reads. Currently, sev-eral companies are attempting to introduce a new sequencing machine, which will be called third gener-ation sequencing (Rusk, 2009). Helicos Biosciences developed a true single molecule sequencer that sequenced the virus M13 genome by an amplification-free method (Harris et al., 2008). Pacific Biosciences developed a single molecular real-time sequencing machine, based on an assessment of the temporal order of incorporation of fluorescently labelled nucleotides, which can produce reads longer than 1 kb (Eid et al., 2009). Oxford Nanopore’s sequencer is designed to avoid amplification or labelling by detecting a direct elec-trical signal (Clarke et al., 2009). Despite dramatic improvements in sequencing speed and capacity, third generation sequencers will not completely replace the previous sequencing methods. Frequent use by research-ers will likely reveal not only the benefits but also the limitations of these new techniques. Similar to the use of second generation sequencers together with ABI 3730, new sequencers will also be used with earlier technologies.

Until several years ago, whole genome plant sequen-cing projects were limited to model species. However, de novo sequencing and assembly are now easier due to longer reads and lower costs, which in the past few years has allowed for much greater sequencing depth. In addition to de novo genome sequencing, the whole

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genome sequence variations in 1001 accessions of Arabidopsis were analyzed in 2008 (Weigel and Mott, 2009). Furthermore, in rice, a high-throughput method for genotyping recombinant populations was developed (Huang et al., 2009). Third generation sequencers could be also used for detection of sequence variation, associ-ations between important agronomic traits and gene identification in regulatory networks by ChIP-chip and ChIP-seq protocols.

Presently, bioinformatics is the major bottleneck for a more complete exploitation of the information of genetic resources that is rapidly accumulating. The integration and organization of the available genomic resources to facilitate their use by researchers are therefore important. It could be a similar concept to that of an ‘omic space’ comprising a comprehensive omic planes (Toyoda and Wada, 2004). Several integrated databases, such as the arabidopsis information resource (Arabidopsis), Gramene (rice) and SoyBase (soybean), provide genetic maps, genomic sequences, gene predictions, expressed sequence tags, marker data, QTLs, repetitive sequences, etc. One of the most significant contributions of the comprehensive genomic resources is that it provides a benefit to researchers who want to start new experiments or compare related information.

Acknowledgements

This work was supported by a grant from the BioGreen 21 Project (code no. 20080401034010), Rural Develop-ment Administration, the Republic of Korea. S.-H. Lee is grateful for the Senior Visiting Fellowship provided by the Institute of Advanced Studies at the University of Bologna, Italy.

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Genomic tools for the analysis of genetic

diversity

J. Antoni Rafalski*

DuPont Agricultural Biotechnology Group and Pioneer Hi-Bred International, Wilmington, DE 19880-0353, USA

Abstract

We now understand that many different types of DNA structural polymorphisms contribute to functional diversity of plant genomes, including single nucleotide polymorphisms, inser-tions of retrotransposons and DNA transposons, including Helitrons carrying pseudogenes, and other types of insertion – deletion polymorphisms, many of which may contribute to the phenotype by affecting gene expression through a variety of mechanisms including those involving non-coding RNAs. These polymorphisms can now be probed with tools such as array comparative genomic hybridization and, most comprehensively, genomic sequencing. Rapid developments in next generation sequencing will soon make genomic sequencing of germplasm collections a reality. This will help eliminate an important difficulty in the esti-mation of genetic relationships between accessions caused by ascertainment bias. Also, it has now become obvious that epigenetic differences, such as cytosine methylation, also contribute to the heritable phenotype, although detailed understanding of their transgenerational stability in crop species is lacking. The degree of linkage disequilibrium of epialleles with DNA sequence polymorphisms has important implications to the analysis of genetic diversity. Epigenetic marks in complete linkage disequilibrium (LD) with DNA polymorphisms do not add additional diversity information. However, epialleles in partial or low LD with DNA sequence alleles constitute another layer of genetic information that should not be neglected in germplasm analysis, especially if they exhibit transgenerational stability.

Keywords:

comparative genomic hybridization; epigenetic; haplotype; next generation sequencing; single nucleotide polymorphism

Introduction

Thirty years ago Botstein et al. (1980) introduced the method of constructing genetic maps with DNA markers, known as restriction fragment length polymorphisms (RFLP). This development revolutionized genetic mapping and the analysis of diversity. Subsequent methodological advances, such as development of simple sequence repeat markers (SSRs), random amplification of poly-morphic DNA (RAPD) (Williams et al., 1990) and amplified fragment length polymorphisms (AFLP) (Zabeau and Voss, 1993), were enabled by the development of polymerase

chain reaction. Development of single nucleotide

polymorphism (SNP)-based markers brought a new level of resolution to the analysis of genetic diversity and for most applications superseded other genetic marker cat-egories. More recently, DNA sequencing of partial or com-plete genomes from multiple individuals has expanded our understanding of the range of intraspecific genetic variation encountered in higher plants (Fu and Dooner, 2002; Yang and Bennetzen, 2009). With the rapid decline in the cost of DNA sequencing and new technological developments, it is certain that genome sequencing of germplasm collection will become accessible, eliminating biases present in existing genotyping methodologies, although it will also impose a significant data analysis overhead, necessitating increased investment in bioinfor-matics. The proposed 1001 Arabidopsis genomes project

* Corresponding author. E-mail: j-antoni.rafalski@cgr.dupont.com

qNIAB 2011

ISSN 1479-2621

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(http://1001genomes.org/about.html) is a sign of things to come. Beyond DNA sequence, there is a renewed interest in the epigenetic marks, such as cytosine methylation, dec-orating DNA and chromatin, and potentially influencing the phenotype. We have discussed the impact of these developments on the analysis of genetic diversity.

Intraspeciﬁc diversity and the phenotype

Genomic sequencing of diverse genotypes in several plant species demonstrated that in addition to SNPs and SSR polymorphisms, extensive intraspecific differences include large insertions/deletions frequently composed of highly repetitive sequences such as retrotransposons and DNA transposons (Wang and Dooner, 2006), and in some cases also genes (Belo´ et al., 2009; Springer et al., 2009). For example, the complement of disease resistance genes may differ between accessions (Chin et al., 2001; Yahiaoui et al., 2009). Sequences that do not code for proteins may nevertheless affect the phenotype, by sup-plying enhancers or promoters to nearby genes, or code for small RNAs, which affect expression of other genes by a variety of mechanisms (Chen, 2009). Pseudo-genes, which in maize are frequently generated by Heli-tron transposons, are sometimes transcribed in sense or antisense direction, also affecting gene expression phe-notype (Yang and Bennetzen, 2009).

If these types of polymorphisms are in linkage disequilibrium with genetic markers used for germplasm characterization (predominantly SNPs and SSRs), then no additional information other than marker genotype is needed to reflect correctly the underlying genetic relation-ships of accessions. However, if linkage disequilibrium (LD) between markers for germplasm fingerprinting and genic or non-genic large indel polymorphisms breaks down rapidly, direct genotyping of these differences may be necessary by DNA sequencing or other methods such as array comparative genomic hybridization (Belo´ et al., 2009; Springer et al., 2009). This is likely to occur in the case of variants, which occurred recently on the back-ground of pre-existing haplotype pattern.

An important issue not always appreciated in the germ-plasm analysis context is the prevalence of ascertainment bias, which occurs when polymorphic loci are identified (ascertained) in one collection of germplasm, but used to evaluate diversity in another set (Clark et al., 2005). For example, a collection of SNP loci identified in a set of cultivated lines will not correctly represent poly-morphic loci present in unadapted accessions, leading to incorrect estimates of genetic distances in the latter set of germplasm. Many polymorphic loci in the non-adapted accessions will not be represented in the SNP collection developed from adapted germplasm, and,

in turn, some alleles common in adapted material may be rare in non-elite accessions. As a result, genetic distances determined in the ascertainment population may be lengthened in comparison with those in the non-ascertained population (Fig. 1). It is difficult to ident-ify a priori an appropriate collection of germplasm for ascertainment (marker discovery), given unbalanced representation of different types of germplasm in many collections. Perhaps, the most appropriate unbiased methodology for germplasm fingerprinting is genotyping by genomic sequencing.

The sequencing technology is rapidly approaching the stage where it will become a cost-effective tool for genotyping (Edwards and Batley, 2009; Varshney et al., 2009). A number of accessions will be simultaneously sequenced in each lane of the instrument, after appropri-ate encoding. Depending on the size of the genome, some form of reduced representation analysis (Yuan et al., 2003) will probably be necessary to focus the effort on non-repetitive fraction of the genome.

Perspective on epigenotyping of germplasm

It is well established that epigenetic variation encoded by DNA base modifications such as 5-methylcytidine affects phenotype in animals and plants (Peaston and Whitelaw, 2006; Henderson and Jacobsen, 2007; Chandler and Alleman, 2008). Some of the epialleles in plants are

Teosinte accessions

Maize

Fig. 1. An example of ascertainment bias. SNP markers

ascertained in elite maize inbred collection were used to fingerprint a set of maize and teosinte lines. Genetic dis-tances between maize lines appear much lengthened with respect to those between teosinte accessions, which are fore-shortened. Using unbiased genotyping method eliminates this disparity. Data courtesy of Stan Luck (Pioneer Hi-Bred).

J. A. Rafalski 160

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remarkably stable and affect important plant character-istics (Cubas et al., 1999). It is therefore reasonable to propose that a complete characterization of a germplasm accession or a breeding stock should involve not only the description of the genotype but also of the epigenotype. It has recently been demonstrated that recursive selection for a yield component in canola results in plants that are genetically identical but can be distinguished by DNA methylation differences and exhibit significant differences in yield (Hauben et al., 2009). The tools for comprehensive epigenotyping are available and involve

chemical deamination of m5C to U followed by DNA

sequencing, enabling single base resolution across the whole genome, albeit at considerable expense (Lister and Ecker, 2009; Lister et al., 2009; Wang et al., 2009). The high throughput sequencing technology, especially rapidly

developing single molecule sequencing (Edwards

and Batley, 2009), promises to enable comprehensive epigenotyping of germplasm collections in the coming years. Currently, several options exist for epigenotyping of a subset of the genome, for example by excluding repetitive fraction of the genome (Peterson et al., 2002) or capturing specific sequences of interest (Hodges et al., 2009).

Conclusions

Rapid technological developments are changing our understanding of genetic diversity, by allowing increas-ingly dense genotyping and identification of types of genetic polymorphisms that were previously not easily accessible to molecular analysis. In the next few years, another step change will occur with the availability of inexpensive genomic sequencing and development of tools for direct probing of epigenetic layer of information (Flusberg et al., 2010). These developments will further enable the understanding of relationship between haplo-type defined at the sequence level and phenotypic expression, through the use of association mapping and genome prediction techniques. To fully exploit these developments, we need to better understand the extent of linkage disequilibrium in the germplasm of interest.

Acknowledgements

I appreciate many discussions with Scott Tingey and with all of my professional colleagues at DuPont/Pioneer Hi-Bred Int.

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Maize inbreds exhibit high levels of copy number variation (CNV) and presence/absence variation (PAV) in

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Varshney RK, Nayak SN, May GD and Jackson SA (2009)

Next-generation sequencing technologies and their

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J. A. Rafalski 162

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Long terminal repeat retrotransposon Jeli

provides multiple genetic markers for

common wheat (Triticum aestivum)

Nataliya V. Melnikova*, Fedor A. Konovalov and

Alexander M. Kudryavtsev

Vavilov Institute of General Genetics, Moscow, Russia

Abstract

The recombinant inbred line mapping population Opata85 £ Synthetic W7984 was used to map Jeli long terminal repeat retrotransposon insertion sites in the hexaploid wheat genome. Sequence-specific amplified polymorphism technique was applied to reveal Jeli insertions. Jeli was found to provide multiple genetic markers for common wheat. Our marker system revealed A-genome Jeli insertions, and therefore can be used for targeted analysis of the A genome.

Keywords:

long terminal repeat retrotransposons; molecular mapping; sequence-specific amplified polymorphism; Triticum aestivum L.

Introduction

Retrotransposons, also called class I transposable

elements, are mobile genetic elements that undergo repli-cative transposition through reverse transcription of RNA intermediates (Kumar and Bennetzen, 1999). Retrotran-sposons are the major components of cereal genomes that are largely located in repetitive DNA (Barakat et al., 1997). Polymorphic retrotransposon insertions can be used as a molecular marker system for genetic studies in plant species (Ellis et al., 1998; Queen et al., 2004). One of the most popular transposon-based marker methods is the sequence-specific amplified polymorph-ism (SSAP) technique (Waugh et al., 1997) that was designed to analyse the insertion polymorphism of high copy number long terminal repeat (LTR) retrotranspo-sons in plant genomes. SSAP techniques can be powerful experimental genomic tools that can be applied to molecular mapping, marker-assisted selection, diversity analysis and evolutionary studies.

Materials and methods

The recombinant inbred line (RIL) mapping population Opata85 £ Synthetic W7984 was used to map Jeli LTR retrotransposon (gypsy-like family) insertions in common wheat (Triticum aestivum L.) genome. Total DNA was extracted from individual plants by using hexadecyltrimethylammonium bromide protocol (Torres et al., 1993) with minor modification. SSAP analysis was performed, as described by Konovalov et al. (2010). Six primer combinations were used to amplify the DNA sequences between the Jeli LTRs and Taq I

restriction sites. The LTR primer sequence 50

-CCC-TAGGAACATAGCTTCATCA-30 was based on the Jeli

sequence TREP3458 obtained from the International Triticeae Mapping Initiative Triticeae Repeat Sequence Database (Wicker et al., 2002). To reduce the number of amplification products, two to three selective bases

were added to the 30 ends of the LTR primers (AC,

AG, CTG, GAC, GGA and TC). The PCR reaction pro-ducts were separated by electrophoresis in a polyacryl-amide sequencing gel using a 38 £ 50 cm Bio-Rad SequiGen GT cell and visualised using silver staining. The polymorphic SSAP markers were mapped within a framework of known restriction fragment length

* Corresponding author. E-mail: mnv-4529264@yandex.ru

qNIAB [2011]. This is a work of the U.S. Government

and is not subject to copyright protection in the United States. ISSN 1479-2621

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polymorphism markers (http://www.graingenes.org/). The marker presence/absence data were analyzed using MAPMAKER 3.0 (Lander et al., 1987). A logarithm of odds score threshold of 5.0 was used to detect genetic linkage. Markers that were not assigned into linkage groups were discarded.

Results and discussion

Polymorphic Jeli insertions represented by SSAP bands were scored in a RIL mapping population Opata85 £ Synthetic W7984 (Fig. 1). The total number of SSAP bands for the six primer combinations was 316 with a mean of 52.7 bands/primer combination. The number of polymorphic bands was 65, ranging from 5 (selective bases CTG) to 18 (selective bases AG) with a mean

of 10.8. The polymorphism level (proportion of poly-morphic bands in the total number of bands) for Jeli observed in our study was 0.18, which was close to the polymorphism level of the markers based on the retrotransposons Tar1 and TAGERMINA, but higher than that of the markers based on Thv19 and BARE-1/Wis-2-1A elements (Queen et al., 2004). Seventeen of the 65 markers could not be assigned into linkage groups, and therefore, were discarded; thus, 48 markers were placed on the chromosome maps. The number of SSAP markers mapped on each chromosome varied from zero (chromosomes 1D, 4D, 5D and 7D) to six (chromosome 2A) markers/chromosome.

The mapping experiments demonstrated approxi-mately the same general distribution of Jeli markers between the three wheat genomes as the nulli-tetrasomic analysis had revealed earlier (Konovalov et al., 2010): 30 insertion sites in the A genome (63%); 14 in the B genome (14%) and 4 in the D genome (4%). The A-genome preference of the Jeli polymorphic insertions was revealed by our marker system. Such an unequal distribution of the retrotransposon-based markers could be explained by a burst of Jeli amplification in the diploid A-genome donor (Triticum urartu Thum. ex Gandil.) with lower retrotransposition activity in the B and D genome donors (Konovalov et al., 2010) that led to a higher copy number of Jeli itself in the A genome; another alternative involves possible differ-ences in the LTR sequdiffer-ences of the Jeli lineages from the A, B and D genomes that could result in preferable primer annealing at the Jeli copies from the polyploid wheat genome A.

Tight clustering of Jeli markers was observed in some cases (chromosomes 1B, 2A, 4A, 5A and 6A). Some clustering of BARE-1/Wis-2-1A markers on the linkage map has been shown (Queen et al., 2004). SSAP marker clustering may be because of cases wherein one polymorphic change is scored as two markers (e.g. if an single-nucleotide polymorphism at a restric-tion site changes the SSAP band length) or by clustering of the retrotransposons themselves, but a more detailed investigation is needed to confirm this hypothesis.

The SSAP system based on the Jeli retrotransposon provides multiple genetic markers for common wheat. Our marker system preferably revealed A-genome Jeli insertions, and therefore can be used for targeted analysis of the A genome in evolutionary studies, genetic mapping, polymorphism screening and marker-assisted selection. The number of Jeli insertion sites that can be revealed by different primer/restriction enzyme com-binations can be estimated as being at least several hundreds. It may also be a promising A-genome identi-fication tag when used as a probe in fluorescent in situ hybridization analyses.

M O S 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Fig. 1. Jeli-based SSAP marker (LTR primer with selective

bases AG) segregation in an Opata85 £ Synthetic W-7984 mapping population. M, 10-bp DNA ladder; O, Opata85; S, Synthetic W7984.

N. V. Melnikova et al. 164

caratterizzazione ed utilizzo delle risorse genetiche

Plant Genetic Resources: Characterization and Utilization

Special issue on the 2nd International Symposium on “Genomics of Plant Genetic

Resources”, 24 – 27 April 2010, Bologna, Italy

Guest editors

Roberto Tuberosa

Andreas Graner

Rajeev K. Varshney

Plant Genetic Resources

Characterization and Utilization

journals.cambridge.org/pgr

Plant Genetic Resources

Characterization and Utilization

Contents

Genomics of plant genetic resources: an

introduction

Roberto Tuberosa

*, Andreas Graner

and Rajeev K. Varshney

Acknowledgements

References

Genomics of plant genetic resources:

past, present and future

Kyujung Van

, Dong Hyun Kim

, Jin Hee Shin

and Suk-Ha Lee

*

Abstract

Keywords:

Introduction

Early impact of genomics on PGR

Current status of plant genomics

Future directions

Acknowledgements

References

Genomic tools for the analysis of genetic

diversity

J. Antoni Rafalski*

Abstract

Keywords:

Introduction

Intraspeciﬁc diversity and the phenotype

Perspective on epigenotyping of germplasm

Conclusions

Acknowledgements

References

Long terminal repeat retrotransposon Jeli

provides multiple genetic markers for

common wheat (Triticum aestivum)

Nataliya V. Melnikova*, Fedor A. Konovalov and

Alexander M. Kudryavtsev

Abstract

Keywords:

Introduction

Materials and methods

Results and discussion