Enhancing germplasm utilization to meet specific user

ARTICLE

Plant Genetic Resources Newsletter, 2003, No. 136: 14-22

Enhancing germplasm utilization to meet specific user needs through interactive stratified core selections

v. Mahalakshmi 1 , T.J.L. van Hintum2 and R. Ortiz3181 1/nternationa/ Crops Research Institute for the Semi-Arid Tropics (lCRISAT), Patancheru, 502324 Andhra Pradesh, India 2Centre for Genetic Resources (The Netherlands), PO Box 16, 6700 AA Wageningen, Netherlands 31nternationallnstitute of Tropical Agriculture (/ITA), PMB 5230, Oyo Road, Ibadan, Nigeria. Email: [email protected]

Summary

Resume

Resumen

Enhancing germ plasm utilization to meet specific users' needs through interactive stratified core selections The large collection of landraces of sorghum, pearl millet, pigeonpea, chickpea and groundnut held at ICRISAT represents a challenge for the maintenance of both the accessions and the information documented for this germplasm. These collections are often the result of collecting missions and specific research programmes that may result in over-representation of certain materials. Core collections improve the sampling while selecting accessions from a germplasm collection. However, static core collections, which are a priori selected by the curator, are often of limited use to the users of the genebank who are interested in a specific trait or domain. The current revolution in information technology makes it possible for users to make such selections themselves on the Web. This article reports use of stratified selection methodology that allows the user to choose the domain of interest. The size of the stratified selection can be chosen to be between 1 and 10% of the total collection size. The user can choose the selection algorithms based on either the proportional or logarithmic sampling strategy. The system selects a minimum of one entry per group to ensure the representation of small groups. This approach provides the users with more focused selection of the germplasm with the diversity of the trait of interest than core collections. Furthermore, it shows how the current developments in the information and communication technology can be used to improve utilization of plant genetic resources.

Encouragement de I'utilisation du materiel genetique pour repondre aux besoins specifiques des utilisateurs par des selections stratifiees interactives dans des collections temoins La conservation des accessions et de l'information relative au materiel genetique des grandes collections de varietes locales de sorgho, mil chandelle, pois d' Angole, pois chiche et arachide de l'ICRISAT constitue un defi. Ces collections ont souvent ete constituees dans Ie cadre de missions de collecte et de programmes specifiques de recherche, aboutissant parfois aune surrepresentation de certains materiels. Les collections temoins ameIiorent l'echantillonnage tout en selectionnant les accessions apartir d'une collection de materiel genetique. Cependant, les collections temoins statiques, choisies a priori par Ie conservateur, sont souvent d'un interet limite pour les utilisateurs de la banque de genes, qui se concentrent sur un caractere ou un domaine specifique. La revolution actuelle des techniques de l'information rend ce choix possible par les utilisateurs eux-memes via Internet. Cet article presente l'utilisation d'une methode de selection stratifiee qui permet a l'utilisateur de choisir Ie domaine qui l'interesse. La taille de la selection stratifiee peut etre fixee entre 1 et 10 % de l'ensemble de la collection. L'utilisateur peut effectuer la selection par des algorithmes bases sur une strategie d' echantillonnage logarithmique ou proportionnel. Le systeme choisit un minimum d'une entree par groupe pour permettre la representation de petits groupes. Cette approche permet al'utilisateur d'effectuer une selection du materiel genetique plus ciblee sur la diversite du caractere d'interet par rapport a l'utilisation des collections temoins. En outre, l'article montre comment les developpements actuels des techniques de l'information et de la communication peuvent servir a ameliorer l'utilisation des ressources phytogenetiques.

Acrecentar la utilizaci6n del germoplasma para satisfacer las necesidades de los usuarios mediante colecciones nucleo estratificadas EI tamafio de las colecciones de sorgo, milo, friiol de palo, garbanzo y mani conservadas en el banco de germoplasma del ICRISAT es un reto para el mantenimiento de las entradas y la informacion. Estas colecciones suelen resultar de misiones de busqueda de recursos geneticos 0 de programas de investigaci6n, 10 que puede provocar una sobre-representaci6n de ciertos materiales. EI muestreo meiora cuando las entradas de una colecci6n de germoplasma se seleccionan en las colecciones nucleo. Sin embargo, las colecciones nucleo seleccionadas a priori por el curador pueden ser poco utiles para los usuarios del banco de germoplasma que esten interesados solo en una caracteristica particular 0 un tema especifico. La revoluci6n de la informatica permite a los usuarios seleccionar por si mismos a traves de Internet. Este articulo muestra el empleo de una metodologia de selecci6n estratificada que permite al usuario escoger el tema de su interes. Se escoge el rango de la selecci6n estratificada entre ell y 10% de la colecci6n total. EI usuario escoge algoritmos de acuerdo a una estrategia de muestreo propordonal 0 logaritmica. EI sistema selecdona como minimo una entrada por grupo, para asegurar la representaci6n de grupos pequefios. Este procedimiento permite una selecci6n localizada del germoplasma buscado meior que usando la colecci6n nucleo. Esto demuestra igualmente c6mo pueden usarse los avances en la informatica y la tecnologia de la comunicaci6n para utilizar meior los recursos fitogeneticos.

Key words: chickpea, core collection, germplasm utilization, groundnut, pearl millet, pigeonpea, sorghum, stratified selection

Introduction Germplasm collections of major crop plants continue to grow in number and size around the world. When agriculture became intensive there was concern of losing genetic diversity forever, and the world community decided

to support collection and conservation of the germplasm of major cultivated crops. Today, however, the return for these investments is being assessed by the use of these germplasm resources in breeding programmes. The very large size and

Plant Genetic Resources Newsletter, 2003, No. 136

heterogeneous nature of germplasm collections can hinder the efforts to increase their use in plant improvement. These germplasm collections are often a result of historical events and arbitrary decisions, collecting missions and specific research programmes resulting in over-representation of certain material, whereas other types of material can be under-represented (Grenier et a1. 2000a, b). Core collections (Frankel and Brown 1984; Brown 1989a, b; van Hintum et a1. 2000) which represent "with a minimum of repetitiveness, the genetic diversity of crop species and its wild relatives" were proposed to enhance the use of germplasm held in the collections. The core collection should contain about 10% of the total number of accessions, such that it represents the possible diversity in the collection. Many genebank curators have been following this idea and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) has also assembled core collections to reflect the diversity in its mandate crops (Grenier 2000; Upadhyaya et a1. 2001; see crops pages at http://www.icrisat.org/text/research/grep/ homepage.htm). These are collections created to represent the existing collection based on the available information. A core collection is often of limited use to the clients of the genebank who are not interested in the entire diversity but rather are more interested in accessions meeting a specific diversity in a trait of interest or domain. Subsampling the core collection for specific traits such as disease resistance to identify new sources of resistance is a common procedure (Miklas et a1. 1999). Recent developments in recombinant DNA technology have sharpened the interest of plant molecular biologists and plant breeders in genetic resources for specific diversity (Tatineni et a1. 1996; Dean et a1. 1999). Thus, the needs of molecular plant breeders have given added impetus to the designation of specific stratified collections. Stratified core selection, which has its origin in the concepts defined by Brown and Frankel (1984), facilitates the users' focusing on selecting germplasm with the diversity of the trait of interest (van Hintum 1999). The information on the accessions held in the germplasm banks of the Consultative Group on International Agricultural Research (CGIAR) is at http://www.singer.cgiar.org. Here we describe a computerbased stratified core selector and its advantages in enhancing the use of the germplasm and the associated information. The stratified core selector allows users to create focused selection of the germplasm with a broad representation of the diversity in the domain of interest.

Material and methods The germplasm collection of sorghum, pearl millet, chickpea, pigeonpea and groundnut, maintained at ICRISAT under an agreement signed with FAO-CGIAR, includes in excess of 111 000 accessions. A large majority of these have been characterized and evaluated for various traits of interest. This information is available at http:/ / www.icrisat.cgiar.org/text/research/grep/homepage.htm or http://www.singer.cgiar.org.

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The term 'accession' in this article refers to any sample in the whole collection, while 'entry' refers to any accession selected for inclusion in the selected core. The procedure for any selection to represent the desired variability includes the following steps (van Hintum et a1. 2000): 1. Identification of accessions in the domain. 2. Dividing the domain into distinct groups. 3. Defining number of entries per distinct group. 4. Allocating entries to each group in the core subset. In the core collection the curator fixes all these steps a priori. In the stratified core selector, described earlier by van Hintum (1999), the user can define the domain (step 1), and the number of entries to be included in the stratified core selection (step 3), allowing for example the selection of 20 early European butterhead lettuces with maximal diversity.

Domain Domain is defined as any set of germplasm with a specific trait or purpose, such as disease resistance or seed size, or combination of traits such as time to flowering and grain mould resistance. The user can choose from the list of traits available in the database.

Group The division of a domain in genetically distinct groups depends on the nature of the trait for which the domain was defined. Traits are either qualitative (seed colour, flower colour, texture, country of origin) or quantitative (days to flowering, stem height, leaf width) in nature. The stepwise division of groups of a qualitative nature can easily be accomplished, as they are by nature distinct. Quantitative traits can be divided into groups based on the distribution and range value for the trait among the accessions. The choice of the number of groups in such cases is left to the user from a minimum of 5 to a maximum of 20 classes.

Number of accessions or sample size The decision to make in any core subset is its size, and this depends on its purpose. The program allows the user to choose between a minimum (1 %) and a maximum (10%) size for the domain trait of interest.

Selection of entries in the group Before selecting the entries in each group, it is necessary to determine the number of entries for each group. This number will depend on the sampling strategy used. The two strategies provided to the user are proportional and logarithmic. In proportional random sampling (P), the domain is first divided into nonoverlapping groups or strata (as described under groups) and a defined proportional size for the core is assigned for each group. The entries in each group are then selected at random. This approach is based on the assumption that the variation between groups is higher and is of greater

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Plant Genetic Resources Newsletter, 2003, No. 136

interest than the variation within groups. Such stratification will increase the efficiency with the right choice of sample sizes for each group. Because of these desirable properties, both statistical and biological, the variability (diversity) in the trait of interest will be retained in the same proportion in both the core and the original. The argument against this strategy is that if rare alleles occur in smaller groups or genetic variation is negatively related to group size (i.e. larger groups having lower variation compared with smaller groups), they will not be represented in the core. In such cases the logarithmic (L) strategy, in which the representation of each group in the core is in proportion to the logarithm of the number of accessions in that group (Brown 1989), is appropriate. Improving the core choice requires an understanding of the genetic diversity of the trait in the entire collection and it is left to the user to pick the appropriate strategy. The number of entries in each group is determined based on the sampling strategy chosen by the user. Basic statistical parameters (minimum, maximum, mean and standard deviation) for the selected traits and the diversity index (Shannon and Weaver 1949) are presented along with the sample size in each group to enable the user to take decisions on the sample size and group size. The entries are then allocated randomly from the accessions in each group and either the entire stratified core selection or individual group members are displayed to the user on request. This list provides the list of accessions in the chosen group by the country of origin. The other option is a simple list that provides the user with individual entries in each group and the values for the traits chosen for stratification. Other related information on each entry from the source tables is also made available through on-line request. Users can choose individual entries from each group and make their own stratified core selection. The entire core entries can also be selected and the request for seeds to the ICRISAT genebank curator can be made on-line.

the user receives the list of accessions in the stratified core selection meeting the required criteria via email. The user can choose the accession from this list and submit a seed request to the germplasm curator. The programming language, Microsoft ASpTM, has no compilation requirement, but an interpreter, i.e. Personal Web Server (PWS) or Internet Information Server (lIS), is required to run the program. A copy of the program with a sample database is available on request, with instructions for the user including the required modifications to connect to their database.

Output The program is interactive and users have the option of selecting the traits of interest for stratification, number of accessions, the method of sampling and the number of groups in the case of quantitative traits (Figure 2). The output is the accessions arranged based on their country of origin. The statistical parameters and distribution parameters for the selected traits from the entire collection and the stratified core selection are also given. For other quantitative traits,

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DeSign and development of the system The current revolution in information technology allows the curators of a genebank to build systems with which users can interact and make their own selections. The structure of the program and dataflow is presented in Figure 1. The crop databases contain all the relevant information on the germplasm accessions. The primary table is the passport table containing all the relevant information on the collection and origin of the accession. The characterization and other evaluation data are added as they become available. The passport information forms the 'master information' to which other information is linked. The choice for the database platform was Microsoft SQL 7.0™. The program was developed with Microsoft ASPTM and tested for compatibility with the two most widely used browsers, namely, Netscape and Internet Explorer. Due to the very large size of the databases it is possible that certain queries and options might take too long a time to process on-line with the currently available hardware. Therefore, the option to submit a request off-line is also provided, wherein

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Plant Genetic Resources Newsletter, 2003, No. 136

the statistical parameters (minimum, maximum, average, number of accessions and standard deviation) in the entire collection and the stratified core selection are also presented for ready reference for the user to make a decision on the sample (Figure 3).

Results and discussion The stratified core selection program is available from ICRISAT's e-GREP crop pages at http://www.icrisat.org/ text/ research/ grep /homepage.htm. The user can select the trait of interest from the list of traits for which information is available. If further stratification is required, a trait from the stratification list can be selected. The number of accessions that contain the information for the selected trait(s) and the minimum and maximum sample size for the core subset are displayed, and the user can choose the desired sample size and the sampling strategy. In the case of quantitative traits the number of groups between 5 (the default) and 20 can be selected (Figure 2). As the class intervals are whole numbers, the number of possible grouping levels is based on the range,

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and the program automatically determines the maximum value for grouping. The required logic is built into the system such that the user is prompted when the required criteria are not met or selected. When the user selects the entire stratified core selection option, the list of accessions from the stratified core selection by country of origin and the statistics for the other available variables from the entire and the stratified core selection are displayed. Details for each accession in the stratified list are available to the user in simple format options. The user has the option to select the accessions of choice for adding to the seed list and then to request the seeds from the ICRISAT genebank curator. For qualitative traits (e.g. flower colour in chickpea or panicle shape in pearl millet), which fall into distinct and separate groups, sampling strategies may not be of importance. However, the purpose of the stratified core selection will determine the sampling strategy even in these cases. Diversity can be maximized in the core collection by using logarithmic sampling (Tables 1 and 2). Chickpea (a predominantly self-pollinated crop) and pearl millet (an outcrossing crop) are used to illustrate the results. Where

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