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Proc. 11th ISTRC-AB Symp. Kinshasa, DR Congo. 4-8 October, 2010

167

Bioinformatics resources for application of molecular breeding in orphan root crops

Melaku GedilInternational Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria Email: [email protected]

AbstractModern breeding of root and tuber staple food crops is the most practical strategy to address the challenges of small holding farmers in developing nations. The rapid advance of genomics technologies can enable breeders to design cost-effective and efficient breeding strategies by exploiting the ability of molecular plant breeding to increase favorable gene action and efficiency of selection. The rapid growth of sequencing and genotyping technology and the parallel growth of bioinformatics and online biological resources can successfully be harnessed for innovative breeding approach to accelerate the process of variety development. Root crop scientists in developing countries, however, are not in a position to utilize the existing tools due to lack of information on the existence or the usefulness of such tools. In view of moving towards molecular breeding, we indicate web based, free access, integrated resources for building basic bioinformatics skills. Selected online resources for self-paced tutorials and other skill building opportunities are outlined. Particular emphasis was made to comparative genomics techniques to develop genomic resources for molecular breeding. The first step towards variant discovery is the mining of data in public databases. Subsequently the retrieved data would be analyzed to compare nucleotides, perform similarity search, deduce protein sequences, and understand the function of the protein. The ultimate goal is to identify and validate nucleotide variants associated with key traits for development of user-friendly molecular markers. It should be noted that investment in bioinformatics capacity building is more affordable and feasible in light of accessibility of cutting edge Information and Communication Technology (ICT) in all corners of the world. To gain the benefit of genomics and bioinformatics, African research institutions should consider investing in human resources and infrastructure development in addition to forging strong partnerships with advanced research institutes.

Keywords: Bioinformatics; cassava; molecular breeding; genomics; genotyping; marker

Why Bioinformatics? The rapid advance of genomics technologies can successfully be harnessed to address the challenges of small holding farmers in developing countries by enabling plant breeders to design cost-effective and efficient breeding strategies by exploiting the ability of molecular plant breeding to increase favorable gene action and efficiency of selection. The ever increasing amount of genomic resources necessitates that plant scientists be equipped with fundamental genomic analysis tools for genomics assisted crop improvement. The role of bioinformatics as a pivotal tool for molecular breeding is growing steadily, particularly in identification of nucleotide variants associated with key traits. In this paper an outline of basic bioinformatics skills to utilize selected public databases and integrated resources as well as online resources for self-paced tutorials and other skill building opportunities were presented.

The most important components of molecular breeding are genomics and bioinformatics.

Bioinformatics is broadly defined as the development and application of computational tools to acquire, store, organize, retrieve, and analyze large amount of biological information. � It is an integral part of molecular biology and

pivotal tool for molecular breeding� Key tool to harness genomics technologies for

efficient breeding strategies� Enables innovative genome-wide marker

discovery (SSR, SNP)� Widely used for functional or Gene-targeted

marker development� Orphan crops with little DNA sequence

information can be studied through comparative genomics methods

Developing Genomic Resources for Molecular Breeding The first step towards variant discovery is the mining of data in public databases. The retrieved data would be used to:• Align and compare sequences• Perform similarity search• Deduce protein sequences• Identify domains/motifs/active sites• Understand the function of the protein.

The ultimate goal is to identify and validate nucleotide variants associated with key traits for development of user-friendly molecular markers.


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Sequence retrieval and manipulation

Sequence alignment

Phylogenetics

Similarity search

Basic Skills in Bioinformatics 'Bioinformatics-Lite'

1. Search for a sequence of interest begins with keywords, accession number, gene name, species name, etc. The Entrez search engine at NCBI, in addition to retrieving sequences, returns pre-computed lists of data elements such as related sequences, gene, protein, taxonomy, and others. Search can be performed in all databases or restricted to nucleotide in the drop down menu. The result can be displayed in different format or downloaded, the most common format being FASTA.

2.Sequence alignment is the prerequisite of virtually all forms of sequence analysis ranging from search, to assembly, and to phylogenetics. Various algorithms have been developed to produce optimal alignment, a topic which is beyond the scope of this paper. Two examples of widely used open access softwares, namely BioEdit (Hall, 1999), and MEGA (Tamura et al. 2007), are freely downloaded and installed with easy-to-understand user's manual. A pair of sequences or multiple sequences saved, for example in FASTA format, can be used as an input. However, sequence alignment can also be done on the web at one of the resources listed in this review (e.g. EMBL-EBI) using the ClustalW program or other methods.

3.Phylogenetic analysis is the basis of taxonomical and evolutionary studies. In the context of this paper, phylogenetic analysis is performed to cluster multiple sequences based on genetic distances. This is a broad topic and a subject of 100s of articles and books. A deluge of tools and web services can also be found online (e.g.Http://evolution.genetics.washington.edu/phylip/software.html). For beginners, stand alone programs such as MEGA can do excellent job of phylogeny tree construction. In addition, web services such as EMBL-EBI provide similar tools.

4.Sequence comparison is essential for under-standing evolutionary relationship between genes. The most common and widely used similarity search tool is BLAST (Best Local Alignment Search Tool (Ye et al. 2006). BLAST is a set of programs used to compare a nucleotide or protein

query sequence to all of the available sequence databases. NCBI and EBI provide many different types of BLAST. Information on how to access BLAST services on WWW, choosing the right type of BLAST, interpreting BLAST results, how to do batch BLAST jobs, and others can be found at NCBI-BLAST home page(Http://blast.ncbi.nlm.nih.gov/Blast.cgi).

5. There are several applications in which primer

designing is required for marker development. Such cases include, but not limited to, retrieved sequences containing simple sequence repeats suitable for SSR marker development. Orphan crops lack sequence information in which comparative genomics approaches such as homologous sequences are used to design degenerate primers, or re-sequence the gene of interest. The most widely used program for primer designing is PRIMER 3.0(http://frodo.wi.mit.edu/primer3/) with several versions of web interface. The web-site provides user-friendly web interface and user manual describing the underlying principle of the program.

6.The major areas of high-end bioinformatics include the development of databases and algorithms for multiple sequence alignment, analysis and annotation of various types of microarray platforms, high-density oligonucl-eotide chips, variety of mass spectrometry, and diverse platforms of next generation sequencing.

Primer design

Advanced Skills


169

Computer savvy researchers who aspire to become bioinformatics tool developer should consider learning a scripting language program such as Perl (community web site: http://www.cpan.org/). Some genomics tasks such as discovery of SNPs or SSR in thousands of sequences, filtering sequences with the target motif and designing assay reagent (e.g. primer), filtering the result of BLAST, and annotation of thousands of EST sequences is a daunting job. Programming skill allows automation of such large scale and complex jobs.

Databases and Resources In parallel with the advances in genomic technologies that are churning out astronomical data, numerous databases and tools are being developed, making it difficult, for an average biologist, to choose from. A good starting point could be the collection of molecular biology databases published in the journal Nucleic Acid Research, the latest (at the time of the conference) being volume 38, Database issue (http://www.oxfordjournals.org/nar/database/c/).


170

Comprehensive and Integrated Biological Data

NCBI and EMBL provide access to a

comprehensive and integrated collection of

biological data worldwide. Such integrated system

is particularly useful for beginners as it eliminates

the need for formatting input/output data for

various interrelated suites of applications.


171

Web Tools and SoftwareMost popular and basic tools and services

Issue and online Database Collection: a community of data resources", Nucl. Acids Res., 38:D1-D4

Gedil , M. 2010. “Tailoring Bioinformatics for the Genetic Improvement of Orphan Crops” Afri Tech Dev Forum 6:34-43

Hall,T.A. (1999) "BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT", Nucl. Acids. Symp. Ser., 41, 95-98.

L a r r i n u a , I M a n d S B B e l m a r. 2 0 0 9 "Bioinformatics and Its Relevance to Weed Science", Weed Science, 56:297-305

Rhee,S.Y., J.Dickerson, and D.Xu. (2006) "Bioinformatics and its applications in plant biology", Annu. Rev. Plant Biol. 57:335-360

Tamura,K., J.Dudley, M.Nei, and S.Kumar. (2007) "MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0", Mol. Biol. Evol., 24, 1596-1599.

Ye,J., S.McGinnis, and T.L.Madden. (2006) "BLAST: improvements for better sequence analysis", Nucleic Acids Res, 34, W6-W9.

Online Bioinformatics Learning ResourcesSuggested Online resources for self-paced tutorials and other skill building opportunities:1. NCBI Tra in ing and Tu to r i a l s :

http://www.ncbi.nlm.nih.gov/guide/training-tutorials/

2. Free Bioinformatics Educational Resource 2Can Support Portal EBI (http://www.ebi.ac.uk/2can/home.html)

3. Ensembl tutorials and other help documentation for Ensembl at :http://www.ensembl.org/info/website/tutorials/index.html

4. Open Access literature, books, manuals, lecture notes, slides (via Google scholar; Scirus.com; Lab pages; wikipedia; university web sites)

Most current researchers who use Bioinformatics in their day-to-day work trained themselves. Numerous free bioinformatics educational resources are available.

African Scientists can tap into advances in communication technology for cyber-learning capitalizing on the widely available ITC gadgets such as computers, mobile phones, and other wireless devices to access free available educational resources.

Key References Armstead et al. 2009. “Bioinformatics in the

orphan crops", Brief Bioinform, 10:645-653

Cochrane,G.R., and M.Y.Galperin. (2010) "The 2010 Nucleic Acids Research Database


172

adaptation aux systèmes culturaux et alimentaires, lui confèrent un rôle de premier plan dans les efforts d'allègement de la crise alimentaire et de la pauvreté en Afrique subsaharienne. Les racines tubéreuses de manioc se prêtent à une gamme de procédés de transformation, aboutissant à des sous-produits alimentaires variés (Segnou, 2002). Le manioc constitue ainsi la source de calorie la plus sûre et la moins chère en zone tropicale (Daniel et Boher, 1988).

En Côte d'Ivoire, le manioc occupe le deuxième rang des cultures vivrières, après l'igname, avec une production estimée à 2,34 millions de tonnes en 2007 (Anonyme, 2009). Il y est cultivé essentiellement pour ses racines tubéreuses qui sont transformées en de multiples produits dérivés dont les plus répandus sont l'attiéké, le foutou, le placali, la farine, l'amidon et le gari.

Toutefois, en Côte d'Ivoire, sous l'action des producteurs qui abandonnent souvent des variétés qui ne répondent pas à leurs exigences, des feux de brousse, des maladies et ravageurs, le manioc et les espèces sauvages apparentés ont tendance à disparaître.

Pour limiter l'ampleur des effets néfastes de perte des ressources génétiques, la conservation de celles-ci s'avère indispensable. Dans l'optique d'une utilisation rationnelle des ressources génétiques en conservation, des travaux de caractérisations morphologique, agronomique, enzymatique et moléculaire sont conduits afin de déterminer les classes homogènes, de déceler les doublons et de définir des groupes d'accessions ayant le maximum possible de traits génétiques ou agromorphologiques en commun.

En effet, des travaux de caractérisation morphophysiologique, réalisés par Fleming et Rogers (1970) puis Rogers et Appan (1973), Zoundjihékpon (1986) puis par N'zué (2007), ont montré qu'à partir des caractères qualitatifs observés ou quantitatifs mesurés, il est possible de regrouper les ressources génétiques de manioc en plusieurs classes. Il en est de même pour les travaux de caractérisation agromorphologique conduits par Willemen et al. (2007), Elias et al. (2000) puis par Mckey et al. (2001). Or, la collection de manioc dont dispose la Côte d'Ivoire n'a pas encore fait l'objet de caractérisation agronomique ni moléculaire, pour déceler les variétés performantes et les doublons éventuels.

L'objectif général de la présente étude, est la contribution à la productivité du manioc. De façon spécifique, elle vise à déterminer des groupes variétaux homogènes au sein de la collection en

Caractérisation agronomique des ressources génétiques du manioc (Manihot esculenta Crantz) conservées dans la collection vivante de la Côte d'ivoire

1 1 1N'Zué B. , Djédji C. , Zohouri G.P. , Niamké 2 2 1 1S. , Ndjatchi A. , Dibi K.E. et Ochou O.G.

1Centre National de Recherche Agronomique (CNRA), www.cnra.ci2 Université de Cocody-Abidjan

RésuméLe manioc (Manihot esculenta Crantz) occupe en Côte d'Ivoire, le deuxième rang des productions vivrières, après l'igname, avec une production annuelle de 2,34 millions tonnes. Les ressources génétiques du manioc sont conservées in vivo en stations depuis une quarantaine d'années par les instituts de recherche dont le CNRA. Cependant, la caractérisation agronomique de ces ressources génétiques n'avait pas encore été réalisée. Dans ce contexte, des travaux relatifs à la caractérisation agronomique ont été conduits de 2003 à 2005 en Côte d'Ivoire. Le matériel végétal était constitué de 265 accessions caractérisées selon six caractères agronomiques. Les travaux ont permis de regrouper les accessions en 4 classes homogènes. La classe 1, de type 91/02322 est composée de 82 % de variétés améliorées qui sont caractérisées par une faible incidence de la mosaïque et une élévation de la production moyenne en racines tubéreuses par plant tandis que la classe 4, de type Toussin, est constituée d'au moins 80 % de cultivars traditionnels qui sont caractérisés par une forte incidence de la mosaïque, un goût doux et une bonne cuisson.

Mots-clés : Manioc, Manihot esculenta, accession, caractérisation agronomique.

IntroductionLe manioc (Manihot esculenta Crantz) est une plante pérenne appartenant à la famille des Euphorbiaceae. Il est l'une des principales plantes à racines amylacées, et constitue la troisième source d'hydrate de carbone dans les tropiques, derrière le riz et le maïs (Anonyme, 2008). Son importante production, sa disponibilité à toutes les périodes de l'année, sa tolérance aux conditions extrêmes de stress pédoclimatiques et son


173

Observations et mesures effectuées Les observations ont porté sur les descripteurs suivants (tableau 1) : � l'incidence de la mosaïque africaine est le

rapport du nombre de plants ayant au moins une feuille présentant le symptôme de la maladie sur le nombre de plants total par parcelle ; elle est exprimée en % et a été obtenue, 4 mois après plantation ;

� le poids moyen des racines tubéreuses, exprimés en kg / racines tubéreuses, est le rapport du poids des racines tubéreuses d'une accession sur le nombre de racines tubéreuses ;

� la production moyenne en racines tubéreuses par plant, exprimés en kg / plant, est le rapport du poids des racines tubéreuses d'une accession sur le nombre de plant ;

� le taux de matière sèche, exprimé en %, est le rapport du poids sec sur le poids frais après séchage à l'étuve ; un échantillon de 4 racines tubéreuses a été prélevé de manière aléatoire dans chaque parcelle lors de la récolte ; ces racines, pelées, ont été découpées en petites rondelles d'environ 3 g chacune ; des tas, constitués de 200 g chacun , ont été étalés sur papier aluminium et séchés à l'étuve à 100 °C pendant 24 h ; le poids de matière sèche obtenu a été alors rapporté au poids frais;

� la cuisson et le goût ont été appréciés suite à des tests de dégustation ; des échantillons de racines tubéreuses, prélevés dans chaque parcelle, ont été pelées et mises à cuire dans l'eau ; ensuite, une appréciation individuelle a été faite sur la cuisson et le goût par 3 personnes volontaires ; les échelles de notation ont été définies comme suit : bonne = 1, moyenne = 2, mauvaise = 3, pour la cuisson ; doux = 1, neutre = 2, amer = 3, pour le goût.

champ, par des descripteurs agronomiques.

Matériel et Méthodes

Présentation pédoclimatique du site d'étude La région d'Abidjan, qui est le site d'étude, est localisée au Sud de la Côte d'Ivoire dans la forêt dense humide. Les sols sont de type ferralitique fortement desaturés sous forte pluviométrie (Monnier, 1979). Les sables tertiaires sont des dépôts détritiques sablo-argileux ou sableux. Leur teneur en argiles dépasse rarement 30 %. Le régime pluviométrique comporte deux saisons pluvieuses (avril à juillet et octobre à novembre) et deux saisons sèches (décembre à mars et août à septembre). Le climat de cette région de basse Côte d'Ivoire se caractérise par une pluviosité moyenne annuelle de l'ordre de 2000 mm (Ndabalishye, 1995). Les températures minimale et maximale sont respectivement de 22,6°C et 29,8°C sous abri (Zoundjihekpon, 1986).

Les travaux ont été conduits à la station de recherche du CNRA à Adiopodoumé, dans la région d'Abidjan.

Matériel végétal� Le matériel végétal qui a servi à la

caractérisation agronomique est constitué de265 accessions appartenant à l'espèce M. esculenta. Ces accessions proviennent de la collection du CNRA et sont composées de :

� 130 cultivars locaux collectés par l'ex-ORSTOM (aujourd'hui IRD), l'ex-IDESSA, la COSCA et le CNRA ;

� 74 clones améliorés localement par l'ex-ORSTOM, l'ex-IRAT, l'ex-IDESSA et le CNRA ;

� 51 variétés d'origines étrangères ;� 10 accessions d'origine inconnue.

Méthodes

Dispositifs expérimentauxLes 265 accessions ont été plantées en bandes. Chaque clone a été planté en deux lignes de 5 plants chacune avec des écartements de 0,80 m entre lignes et 0,80 m entre plants. Les accessions ont été séparées de 1 m. Les bandes étaient distantes de 1,50 m. Les boutures ont été plantées horizontalement en septembre 2003 sur sol labouré, pour la première plantation et novembre 2004 pour la deuxième plantation. L'entretien a été réduit au sarclage et aux remplacements des pieds et des clones manquants. La récolte des parcelles a eu lieu 11 mois après plantation.


174

Tableau 1 : Caractères mesurés et observés sur les accessions de manioc

- Incidence des maladies en saison pluvieuse, 4 mois après (mosaïque)

-Poids moyens des racines tubéreuses

- Production moyenne en racines tubéreuses par plant

- Taux de matière sèche (TMS)

-Cuisson (bonne, moyenne,Mauvaise)

- Goût (doux, neutre, amer) après cuisson

Mosa

Pmoyt

Pmoyp

TMS

Cuis

Gout

absence = 0présence = 1

kg/racines tubéreuses

kg/plant

%

bonne = 1, moyenne = 2, mauvaise = 3

doux = 1neutre = 2amer = 3

Descripteurs Code Notation / Unité

Les trois premiers axes principaux retenus ont servi à faire ressortir des groupes homogènes à l'aide de la classification ascendante hiérarchique.

Analyses StatistiquesUne analyse en composantes principales (ACP) suivie d'une classification ascendante hiérarchique (CAH) a été réalisée avec le logiciel XLSTAT-PRO version 7.5 1995-2000 (Fahmy, 1999). La classification ascendante hiérarchique (CAH) a permis à la fois de classer les accessions et d'analyser les degrés d'affinité entre celles-ci. Elle a aussi permis de dénombrer les classes et d'indiquer leur composition, à partir des axes principaux retenus et du niveau de dissimilarité.

Résultats

Mise en évidence des paramètres les plus discriminants de la collectionL'analyse en composantes principales (ACP) a permis de regrouper les variables selon les trois premiers axes principaux (F1, F2 et F3) représentatifs. Ces trois premiers axes principaux représentent 77 % de la variation totale (tableau 2).Pour un axe donné, les variables qui ont les plus forts coefficients sont celles qui contribuent le plus à la formation de cet axe. En se basant sur les contributions des variables (tableau 3) et la corrélation entre les variables (tableau 4), les trois axes principaux sont caractérisés comme suit (figures 1, 2 et 3) :�· l'axe 1 (F1) représente 39,51 % de la variation

totale et est caractérisé par la production moyenne en racines tubéreuses par plant (Pmoyp) et la cuisson (cuis) ; les variables Pmoyp et cuis sont positivement corrélées entre elles, ce qui signifie que, lorsque la production moyenne par plant est élevée, la cuisson devient mauvaise selon l'échelle de notation.

�· l'axe 2 (F2) représente 23,71 % de la variation totale ; il est défini par le taux de matière sèche (Tms) et le goût ; il existe une corrélation négative entre le taux de matière sèche et le goût; cela suppose que, l'augmentation du taux de matière sèche s'accompagne du goût doux selon l'échelle de notation.

· l'axe 3 (F3), constitué par 13,48 % de la variation totale, est défini par le poids moyen des racines tubéreuses (Pmoyt) et la mosaïque (Mosa) ; les variables Mosa et Pmoyt sont négativement corrélées entre elles, ce qui signifie que, lorsque l'incidence de la mosaïque est élevée, le poids moyen des racines tubéreuses diminue. Cela montre que, l'influence de la mosaïque a eu un effet significatif sur le poids moyen des racines tubéreuses.


175

Tableau 4: Matrice de corrélations des caractères étudiés

Mosa Pmoyt Pmoyp Tms Cuis Gout

Mosa

Pmoyt

Pmoyp

Tms

Cuis

Gout

1

-0,295

-0,499

-0,055

-0,317

-0,170

-0,295

1

0,605

-0,038

0,119

0,154

-0,499

0,605

1

-0,061

0,347

0,209

-0,055

-0,038

-0,061

1

-0,364

-0,333

-0,317

0,119

0,347

-0,364

1

0,460

-0,170

0,154

0,209

-0,333

0,460

1

F1 F2 F3

Mosa 17,303 9,393 32,715

Pmoyt

16,304

14,871 35,729

Pmoyp

26,234

11,076 2,157

Tms

5,272

34,789 17,877

Cuis

20,289

12,353 11,061

Gout

14,598

17,518 0,461

Tableau 2 : Valeurs propres des axes principaux

Tableau 3 : Contributions des variables (%) a la formation des axes principaux

F1 F2 F3 F4 F5 F6

Valeur propre

2,371

1,423

0,809

0,614

0,465

0,318

Variance (%)

39,514 23,716

13,488

10,230

7,753

5,300

39,514

63,230

76,718

86,948

94,700

100,000Cumule (%)

En gras, valeurs significatives (hors diagonale) au seuil alpha=0,050 (test bilateral)

2.2. Classification des accessions de la collection�La classification ascendante hiérarchique (CAH), réalisée sur les trois premiers axes principaux, ont mis en évidence des groupes homogènes d'accessions au sein de la collection de manioc. Au total 4 classes d'accessions (figure 4) ont été révélées en tenant compte d'un niveau de dissimilarité de 85. Les effectifs des classes selon la CAH sont établis comme suit : classe 1 (70 accessions), classe 2 (49 accessions), classe 3 (54 accessions), classe 4 (92 accessions). Ainsi, la classe 4 a eu le plus grand effectif avec 92 accessions alors que la classe 2, la plus faible, ne renferme que 49 accessions. Les caractéristiques des classes ainsi définies se présentent comme suit :� la classe 1, groupe Ay3 ou 91/02322, est composé de 70 access ions qu i son t essentiellement améliorées ; celles-ci ont une bonne tolérance à la mosaïque faible et présente une production moyenne par plant élevée ;

� la classe 2, type TA8, est constituée de 49 clones qui sont majoritairement améliorés ; elle regroupe les clones à taux de matière sèche faible ;� la classe 3, type 359 ou Zoglo5, renferme 54 accessions qui sont majoritairement améliorées ; elle renferme les clones à production moyenne en racines tubéreuses par plant et le poids moyen des racines tubéreuses faibles ;

� la classe 4, groupe Kokob7 ou Toussin, est composée de 92 accessions qui sont essentiellement traditionnelles ; celles-ci présentent en commun le goût doux, une bonne cuisson et la mosaïque élevée.

,


176

Variables (axes F1 et F3 : 53,00 %)

Mosa Pmoyt

Pmoyp

TmsCuis

Gout

-1

-0,5

0

0,5

1

-1 -0,5 0 0,5 1

-- axe F1 (39,51 %) -->

Figure 2 : Représentation des variables

dans le plan principal (F1, F3)


Mosa Pmoyt

Pmoyp

TmsCuis

Gout

-1

-0,5

0

0,5

1

-1 -0,5 0 0,5 1

-- axe F2 (23,72 %) -->

Figure 3 : Représentation des variables dans le plan principal (F2, F3)

Figure 4: Dendrogramme montrant 4 classes génotypiques révélées avec un niveau de dissimilarité 85.

Dendrogramme

0

34

68

102

136

170

204

Dis

sim

ilar

ite

DiscussionLa caractérisation agronomique des accessions de la collection de manioc en Côte d'Ivoire a permis d'identifier les descripteurs les plus discriminants. Ceux-ci ont contribué à la formation de 3 axes principaux qui représentent 77 % de la variation totale. Les 265 accessions ont été regroupées en 4


PmoytPmoyp

CuisGout

0,5 1

-- axe F1 (39,51 %) -->

Figure 1 : Représentation des variables

dans le plan principal (F1, F2

Mosa

Tms

-1

-0,5

0

0,5

1

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des caractères

consulté 11/09/2009Daniel J.F and Boher B. (1988), Epiphytic phase of

Xanthomonas campestris pathovar manihotis on aerial of cassava. Agronomie tropicale, 5, 111-116.

Elias M ., Panaud O. and Robert T. (2000), Assessment of genetic variability in a traditional cassava (Manihot esculenta Crantz) farming system using AFLP marker, Heredity, 85, 219-230.

agronomiques est parfois très forte, et qu'elle peut être responsable d'erreur d'identification pour des individus appartenant à des variétés très semblables.

Conclusion et perspectivesLa présente étude, réalisée à la station expérimentale du CNRA à Adiopodoumé, a consisté à caractériser les accessions de la collection du manioc par des descripteurs agronomiques. La caractérisation agronomique de la collection a permis de les regrouper en 4 classes selon les 6 descripteurs utilisés.

La classe 1 de type Ay3 ou 91/02322 est caractérisée par une faible incidence de la mosaïque et une forte production par plant. Elle est composée essentiellement de variétés améliorées provenant de la Côte d'Ivoire et de l'IITA. La classe 3 de type 359 ou Zoglo5 a été composée de clones à rendements en racines tubéreuses faibles. La classe 4 de type Kokob7 est constituée de cultivars collectés en Côte d'Ivoire, à goût doux, à bonne cuisson et à forte incidence de la mosaïque.

En perspectives, il serait nécessaire de réaliser une étude de caractérisation de la collection par des marqueurs moléculaires en vue de compléter les caractérisations morphologiques et agronomiques. Le but visé est de déceler les doublons et rendre la gestion de la collection plus efficace et rationnelle.

RemerciementsNous voudrions témoigner notre profonde gratitude à Messieurs KOUADIO Krah, DAHA Alphonse et YAO Brou André, techniciens sur le Programme Plantes à Racines et Tubercules du CNRA pour leurs contributions à la présente étude.

Références bibliographiquesAnonyme (2008),

http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567#ancor consulté 05/09/2009

Anonyme (2009), http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567#ancor:

différentes classes.La classe 1 de type Ay3 ou 91/02322 est à

faible incidence de la mosaïque et à forte production par plant. Elle est composée essentiellement de variétés améliorées provenant de la Côte d'Ivoire et de l'IITA. La classe 2 de type TA8 renferme les clones à taux de matière sèche faible. La classe 3 de type 359 ou Zoglo5 a les rendements en racines tubéreuses faibles. La classe 4 de type Kokob7 est constitué de cultivars collectés en Côte d'Ivoire, est à goût doux, à bonne cuisson et à forte incidence de la mosaïque.

Après avoir utilisé 9 caractères agronomi-ques, Zoundjihékpon (1986) a pu définir 6 classes de cultivars de manioc dont quatre classes étaient caractérisées par les descripteurs agronomiques tandis que les deux autres faisaient intervenir des caractères de l'appareil reproducteur dans leur définition. Ainsi, les quatre classes obtenues, avec les descripteurs agronomiques, sont en conformité avec le nombre de classes obtenu par Zoundjihékpon.

La classe 1 représentée essentielle-ment par les variétés améliorées, a montré une résistance à la mosaïque. Cette résistance des variétés améliorées qui peut s'expliquer par le fait que lors de leurs créations, ces génotypes aient bénéficié d'un effort de sélection contre la mosaïque. Cependant, selon N'zué (2007), la résistance des variétés à cette maladie étant souvent limitée dans le temps, il convient d'extraire les plants de manioc atteints de la maladie dans le champ ou de renouveler le matériel végétal de plantation auprès des instituts de recherche.

Les résultats obtenus indiquent aussi que, les variétés de la classe 4 pourraient être d'utilisations multiples, surtout grâce à leur goût doux et à leur aptitude à la bonne cuisson. Les variétés ayant ces caractéristiques sont destinées prioritairement à la préparation du foutou qui est un mets répandu en Côte d'Ivoire. Les mêmes observations ont été faites par N'zué (2007) et par Lefèvre (1988). Par ailleurs, l'incidence de la mosaïque africaine a été plus élevée au niveau de cette classe, qui était essentiellement composée de cultivars tradi-tionnels. Cette forte sensibilité des cultivars pourrait baisser les rendements conformément aux observations de Theberge (1985) et de Marquette (1973). En effet, selon ces auteurs, la mosaïque africaine est l'une des causes principales de la faiblesse des rendements.

Par ailleurs, selon Mckey et al. (2001), la caractérisation d'une collection par des descrip-teurs agronomiques paraît peu efficace. En effet, ces auteurs révèlent que la variabilité intravariétale


177

indicators. Genet resour. Crop Evol, 54, 1595-1612.

Zoundjihékpon J. (1986). Etude de la variabilité morphophysiologique et enzymatique de cultivars de Manihot esculenta

eCrantz. Thèse de doctorat 3 cycle. FAST, Université nationale de Côte d'Ivoire. 120p.

Fahmy T. (1999), XLSTAT 4.0. Copyright Dr Thierry Fahmy, 1995-1999. Addinsoft, Paris. PP 1-10.

Fleming H.S. and Rogers D.J. (1970), A Classification of Manihot esculenta, Crantz using the information carrying content of a character as a measure of its classificatory rank. Proceedings of the

nd2 International Symposium on Tropical Root and Tuber Crops, Hawaii, August, 1970. PP 66-70.

Lefèvre F. (1988), Ressources génétiques et amélioration du manioc, Manihot esculenta Crantz, en Afrique. Thèse de Doctorat Ingénieur. INAPG. France.9 Novembre 1988.144p.

Marquet te J . (1973) , Expérimentat ion Agronomique, région Maritime et des Savanes, Année 1974. 80p.

Mckey D., Emperaire L ., Elias M., Pinton F. et Robert T. (2001), Gestions locales et dynamiques régionales diversité variétale du manioc en Amazonie. Genet. Sel. Evol,33, 465-490.

Monnier Y. (1979), Les sols. In : Les Atlas jeune Afrique : la Côte d'Ivoire, Jeune Afrique, Ed., Paris. PP 20-21.

Ndabalishye I. (1995), Agriculture vivrière Ouest-africaine à travers le cas de la Côte d'Ivoire. Monographie. Bouaké, Institut des savanes. 383p.

N'Zué B. (2007), Caractérisation morphologique, sélection variétale et amélioration du taux de multiplication végétative chez le manioc Manihot esculenta Crantz (Euphorbiaceae). Thèse de Doctorat unique. Ufr. Biosciences , Université de Cocody-Abidjan.127p.

Rogers J. D. and Appan, S.G. (1973), Manihot , manitotoides (Euphorbiaceae). New York, Etats-Unis, Hafner Press, Flora Neotropica Monography n°13, 272p.

Segnou J. (2002), Développement végétatif et potentiel de rendement chez le manioc. Tropiculture, 20, 161-164.

Theberge R.L. (1985), Common African pests and diseases of cassava, yam, sweet potato and cocoyam. Ibadan, IITA. 108 p.

Willemen L., Scheldeman X., Cabellos VS., Salazar SR and Guarina L. (2007), Spatial patterns of diversity and genetic erosion of traditionna cassava ( Manihot esculenta Crantz) in the Peruvian Amazon: An evaluation of socio-economic and environmental a


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showed good association when tested on 40 elite lines. Two markers SSRY20 and SSRY76 were found to be the closest to any R-gene because their primers were found 58kb downstream and 49.3kb upstream respectively of the closest R-gene. In an effort to improve phenotyping for reliable marker-trait association, an expected inverse correlation of cycle threshold (Ct) values to viral quantities was obtained after real time PCR thereby establishing it as a veritable tool for this purpose. Candidate markers could provide useful information for identification of resistance genes for development of gene-targeted molecular markers for molecular breeding of cassava.

Keywords: SSR, Marker, molecular breeding, cassava, mosaic disease, real time PCR

IntroductionThe most important threat to cassava production in sub-Saharan Africa (SSA) is the cassava mosaic disease (CMD). The disease results in substantial root yield loss between 20% and 90% in cassava fields in SSA (Hahn et al., 1980). Epidemic outbreaks result in up to 100% yield loss (Jennings, 1994). The CMD is caused by cassava infecting begomoviruses (CMBs, genus Begomovirus, family Geminiviridae). Six of the eight CMBs reported to cause CMD worldwide, have been documented in SSA (Patil and Fauquet, 2009).

They are: African cassava mosaic virus (ACMV), East African cassava mosaic virus (EACMV),

East African cassava mosaic Cameroon virus (EACMCV), East African cassavamosaic Malawi

virus (EACMMV), East African cassava mosaic Zanzibar virus (EACMZV) and South African

cassava mosaic virus (SACMV). In addition, EACMV-UG, a recombinant virus between ACMV and EACMV was attributed to CMD-pandemics in East Africa. These virus species are transmitted by the whitefly, Bemisia tabaci biotype A. A Biotype B of the vector (B. argentifolia) was recently found in the Americas (Polston et al., 1997) but it is not yet implicated for any type of CMD.

The need to overcome the problems associated with conventional crop breeding has necessitated efforts to develop molecular markers for rapid and efficient selection of genotypes with desirable traits. Resistance was observed in the Nigerian cassava landraces (Legg and Fauquet, 2004). Molecular markers can be an indispensable tool to hasten the process of selection of resistance sources for marker-assisted introgression (Okogbenin, 2007). This study therefore verifies

Development and validation of genomic tools for marker-assisted breeding of cassava mosaic disease resistance in cassava (Manihot esculenta)

Melaku Gedil, Gerald Otti, Lovina Enok, P. Lava KumarInternational Institute of Tropical Agriculture, PMB 5320, Ibadan, NigeriaEmail:[email protected]; Website: http://molecularbreeding.iita.org

AbstractIn a bid to fast-track the process of selection of cassava (Manihot esculenta Crantz) genotypes resistant to the cassava mosaic disease (CMD), caused by whitefly-transmitted begomoviruses, a number of molecular markers have been developed to map resistance genes. The simple sequence repeat (SSR) markers, NS158 and SSRY28 and a sequence-characterized amplified region (SCAR) marker, RME-1 have been previously reported to be linked to a CMD2 gene. Other unpublished sources also implicate NS169 and SSRY235 markers as being linked to CMD resistance traits. This study, therefore, aims to verify and validate the utility of these markers including three others - SSRY20, SSRY76 and SSRY238 in marker-assisted selection (MAS) and to test the utility of certain novel approaches in facilitating the use of gene-targeted molecular markers in MAS. It also aims to validate tools for enhancing reliability of marker-trait association. The utility of the markers for MAS were verified by determining their levels of association to CMD resistance in two mapping populations, 1M and 23M and forty elite clones using bulk-segregant analysis (BSA) and simple marker-trait correlation. Candidate R-genes were identified by selecting genes annotated with characteristic resistance domains following sequence homology search of primer sequences of the SSR and SCAR markers on cassava genomic sequences using phytozome (www.phytozome.net). After analyzing all markers, NS158, SSRY28 and RME-1 were found to exhibit significant association to CMD resistance in 1M and 23M populations, both of which involve TME 3 as source of resistance, with percentage association levels of 74%, 75% and 70%, respectively, at a resistance range of 1=R<2 and 88%, 89% and 83% when a disease score of 2 is considered resistant. The tested molecular markers, particularly NS158 and SSRY238


179

respectively (Lokko et al., 2005). An average CMD score was calculated for each genotype from CMD scores taken for three consecutive months. The same field scoring method was used to evaluate the elite cassava lines.

DNA Extraction: Genomic DNA was extracted from each genotype of the 1M and 23M populations and the elite genotypes using a high-throughput method optimized in our laboratory. Method involves dry extraction following grinding of liquid N -treated cassava leaves in the 2

GENO/GRINDER 2000 machine (BT & C incorporated, Lebanon, New Jersey) with a capacity of one hundred and ninety two samples per extraction run.

PCR amplification: All eight markers were amplified in the elite line samples while only polymorphic markers were amplified in the mapping populations. A Touch-down (TD60) program written in a PTC-200 thermal cycler machine was utilized.

Genotyping: Segregation patterns of the SSR markers on the 1M and 23M populations were evaluated by genotyping on 2.0% superfine resolution (SFR) agarose gel. Four microliters of PCR products for each marker was mixed with 1 ìl of loading dye and subjected to agarose gel electrophoresis at 80V.

Bulk Segregant Analysis: Parents of the two mapping populations were screened with all eight primers. Primers showing polymorphism between the parents of a population were selected and used to screen bulks of resistant and susceptible genotypes of that population. Resistant and susceptible bulks for the 1M and 23M mapping populations were generated by pooling 1 ìl each of working DNA dilution from ten resistant and ten susceptible genotypes. Bulk samples showing similar banding patterns with the corresponding parent were opened and the segregation patterns of the markers in both populations were evaluated by PCR and gel electrophoresis in order to establish association.

In silico methods: Forward and reverse primers of the candidate markers under study were used to mine cassava genomics resources with the aim of finding resistance genes existing within or around the marker locus. These primers were used as query sequences for a BLAST search on the draft cassava genome (www.phytozome.net/cassava).

the utility of a collection of eight molecular markers (7 SSR and 1 SCAR), for marker-assisted breeding (MAB). Five of these markers (NS158, SSR28, RME-1, SSR235, and NS159) have been reported by other investigators to be genetically linked to a putative new source of CMD resistance namely CMD2 (Akano et al., 2002, CIAT, 2004). Result obtained from this study is therefore aimed at verifying this reported linkage of the five markers to any resistance gene not only in the published source of the resistance (TME3), but also in other elite genotypes. It is also expected to provide a basis as well as set the pace for the identification of the actual genes conferring resistance to TME3 and other resistant cassava genotypes using in silico technique (Gedil, 2009). The successful application of the genomic tools used in the study, to the achievement of these objectives would validate their utility in discovery of gene-targeted markers for molecular breeding of CMD resistance in cassava.

Materials and Methods

Plant Materials: 1M and 23M mapping populations of Cassava, Manihot esculenta, derived from TME3 x TME117 and TME3 x 30555, respectively, as well as forty elite cassava lines were used.

Molecular Markers: Seven simple sequence repeat (SSR) markers, SSRY20, SSRY76, SSRY235, SSRY28, NS158, and NS169 as well as one sequence characterized amplification region (SCAR) marker, RME-1 were used. For Real Time PCR, CMBRepF and ACMVRep-R were used as forward and reverse primers (Alabi et al., 2008), respectively, for PCR-based detection of ACMV.

Field Evaluation: Two mapping populations were established in IITA station, Ibadan, Nigeria, for two consecutive seasons, 2007 and 2008. All treatment rows were adjacent to a spreader row of CMD-affected cassava infested with whiteflies. Phenotypic scores of both populations were taken at a month interval with first score taken 4 weeks after planting based on the five-point CMD scoring method developed in IITA (IITA, 1990). Genotypes without obvious symptoms of CMD were scored as 1. Those with mild chlorotic patterns were scored 2 while those with strong mosaic distortions affecting the entire leaf were scored 3. Scores 4 and 5 are given to genotypes with severe mosaic distortion and shrinking affecting up to 2/3rd and 4/5th of the entire leaves,


180

of phenotype and genotype to in silico genomics. Results were obtained for in silico analysis of eight markers, their association levels to CMD resistance in two populations and forty elite lines, and for the amplification of ACMV sequence in representative cassava genotypes using real time PCR. All molecular markers used in the study were tested for their levels of association to CMD resistance in TME3 and non-TME3 sources. This involved determining the correlation of genotyping derived CMD scores and phenotyping-derived CMD scores in percentage values. Table 1 shows the association level of each marker as an average value of their levels of association with the 1M and 23M each grown in the two planting seasons, 2007 and 2008.

Real Time PCR: Real Time PCR was done by using the SYBR green pcr core reagent kit from Applied Biosystem (www.apliedbiosystems.com). The kit consists of 10X SYBR Green buffer, 25 mM MgCl 250 units AmpliTaq Gold and 100 2,

units AmpErase Uracil N-Glycosylase. Total reaction volume was 25ìl and included the above reagents with 5 ìM CMBRepF (forward) primer, 5 ìM ACMVRep-R (reverse) primer and 50 ng genomic DNA.

Results and Discussion

A multi-pronged approach was employed to verify the usefulness of the candidate markers. This ranges from the gene-tagging techniques of bulk-segregant analysis (BSA) and simple correlation


181

Table1: Average percentage association of candidate markers to CMD resistance, from genotyping and phenotyping data compared for two growing seasons.

primer 1M 2007

(%)

1dR<2

1M 2007

(%) max.

R score 2

23M 2007

(%)1dR<2

23M 2007

(%) max

R score 2

1M 2008

(%)1dR<2

1M 2008

(%) max

R score 2

23M 2008

(%)1dR<2

23M 2008

(%) max

R score 2

% Average

Associat ion

1dR<2

% Average

Association

max R

score 2

NS158 84.2 92.1 77.7 80 63.5 90.3 70.9 90.7 74.1 88.3

SSRY28 86.9 94.8 75.5 77.8 67.2 93.6 73.9 88.3 75.9 88.6

SSRY235 63.5 71.1 31.1 37.8 57.5 71.0 41.2 27.9 48.3 52.0

NS1 69 86.9 94.8 33.7 40 63.5 93.6 58.8 34.8 60.7 65.8

RME-1 73.7 81.6 84.5 84.5 48.7 74.2 71.6 93.0 69.6 83.3

SSRY20 47.2 52.8 61.8 67.6 43.5 50.0 42.9 45.7 48.9 54.0

SSRY238 47.4 61.1 - - 62.5 71.0 - - 55.0 66.1

marker depends on the definition of resistance and factors that influence resistance phenotype (e.g. type of begomovirus species). Genotypic scores for the 1M and 23M populations were taken based on the segregation pattern of the parent alleles in the progenies. Molecular markers used had size polymorphism in both parents where both were either homozygous or one was heterozygote sharing an allele with the other parent apart from its own distinct allele (Fig. 1). Progenies are therefore scored as either resistant or susceptible based on the parent allele they have inherited. Genotypes having allele(s) of the resistant parent were scored as resistant while those having allele(s) of the susceptible parent were scored as susceptible.

Table 2 presents the association levels of the eight markers in a panel of forty elite lines. It shows that all of the markers had good association with CMD resistance (with association levels =70). Severity score is based on the symptom exhibited at the time of evaluation. This would not preclude plants recovering from prior more severe infection. More genetic investigations are required to discern resistance and recovery mechanisms and the underlying genetic factors.

The association level of each marker to any of the populations is determined by the proportion of the entire population whose phenotypes correspond with the genotypes generated with the marker. For instance, score 77.7% for 23M population (grown in the 2007 season) at the resistance score range, 1=R<2 imply that 77.7% of the entire population has same CMD status phenotypically and genotypically.

In all the mapping populations utilized in the study, the candidate markers - NS158, RME-1 and SSRY28 exhibited at least 70% association with the phenotype when a score of 2 was considered as resistant (Table1). This is consistent with the reported close linkage of the markers to the CMD2 gene believed to control CMD resistance in TME3, the source of resistance (Akano et al., 2002). Phenotyping at the range, 1=R<2 also showed that these three markers have the highest association levels though RME-1 has an association level slightly below 70%. (Table1). Three markers, NS158, SSRY28 and RME-1 showed good association (=70%) at resistance threshold of 2 consistent with their reported close linkage to CMD2 as against two markers (NS158 and SSRY28) which showed good association when the score range 1=R<2 are considered resistant. This result suggests that the determination of association to CMD resistance of a molecular


182

Figure1. Agarose gel picture showing PCR analysis of SSR20 on 1M population. Lanes 1 and 2 represent the parents, TME3 and TME117 respectively. Samples in reamining lanes are progenies.

In silico analysis

BLAST search on the draft cassava genome (www.phytozome.net) using primer sequences of all eight markers showed that only two, primers of SSRY20 and SSRY76 markers exist on the same scaffold as gene(s) with resistant annotation (Table 3). This suggests that they may be associated to a resistance source other than that already identified in TME3 i.e. the CMD2 gene (Akano et al, 2002) since both markers were not found associated with this source. However, having been found in close proximity to candidate R-genes and being associated to resistance in the elite lines, both markers could lead to the identification of resistance genes in non-TME3 sources for design of functional gene-based markers for marker-assisted selection.

For each marker, the genotype scores were obtained on the basis of observed recurring fragment size common to all resistant elites and a different recurring fragment size common to all susceptible lines. Again, the genotype scores of all tested markers have a significant correlation to the phenotype scores across the elite lines. By implication, each of the markers might be linked to a resistance gene common to all the elite lines. However, all the eight markers may not be commonly linked to a resistance gene as they are not all on the same genetic group or chromosome. For instance, SSRY20 and NS158 are on different linkage groups (Okogbenin, 2006) and would therefore be linked to different resistance genes. This would imply that a single elite line may have more than one resistance locus. However, only an elaborate study on the genetics of resistance would resolve the number of genes controlling resistance in the various resistance sources.


183

Primers tested % false positives % false negatives % association

NS158 12.5 7.5 80.0

SSRY28 15.0 7.5 77.5

SSRY235 0.0 30.0 70.0

NS169 17.5 7.5 75.0

RME-1 10 17.5 72.5

SSRY20 0.0 24.3 76.7

SSRY76 5.4 24.3 70.3

SSRY238 10.8 8.1 81.1

Table2. Summary of percentage false positives and negatives as well as percentage association to CMD resistance in elite lines.

Table3. Summary of primer BLAST alignment results on phytozome.

Real Time PCRCMD is a complex disease, with multiple viruses associated in various regions, mixed infection of ACMV and EACMV-like viruses are frequent. It is important, therefore, to understand the performance of a resistant genotype infected with various species of CMD-causing begomoviruses either singly or in mixed infection. This requires application of methods to detect and quantify the different species / strains of the begomovirus(es) in the test plant and its influence on phenotype and CMD severity. With this rationale, we have initiated a real time PCR-based method for a better understanding of the impact of single and/or mixed infections and virus load (concentration) on genetic mechanism of CMD resistance in a given genotype and to assess the robustness of marker-trait linkage. Methods are being standardized using viral genomes. For instance, a genomic sequence of ACMV was amplified using the SYBR green method of real time PCR. Amplification with 5 ìM forward and reverse primer resulted in an efficiency of 86.2% with quantification by the standard curve method (Fig.2). The efficiency value is valid despite falling outside the 90%-100% range (Dorak, 2010). While the current data is not sufficient to draw conclusion, it signifies the importance of the approach. At the moment, we are considering a Taqman based real-time assay for better data.


184

Fig.3. Amplification plot for 18 1M genotypes, 5 standards and one no-template control (NTC). Samples, standards and the negative control (NTC) were amplified in triplicates.

Fig.2. Standard curve of Cycle threshold (Ct) against quantity. Standards are serial dilutions of 100ng TME117.

Primer ID Phytozome Hit Hit Score E-value Candidate R Gene around Hit

Position of R Gene relative to hit*

SSRY20 Nuclear pore complex

46.4 1.40E-05 Ser/Thr protein kinase

58kb downstream

SSRY76 Epilepsy Holoproscencephaly-like protein

41 5.80E-04 TIR domain 122.7kb downstream

SSRY76 Epilepsy Holoproscencephaly-like protein

41 5.80E-04 LRR domain 49.3kb upstream

*The proximity of each marker to a candidate resistance gene is specified as the genomic distance in kilobases (kb) of the position of alignment of its primer (phytozome hit) to the nearest gene with resistance annotation (candidate R-gene) on the same scaffold. Downstream refers to the 3' direction of sequence while upstream means to the 5' direction of sequence.

and effective marker-aided breeding of CMD resistance.

ConclusionMolecular markers have the potential for application in marker-assisted selection (MAS) and for identification of gene-based functional markers for reliable marker-aided molecular breeding of CMD resistance. However, their effective application to MAS depends on the accurate understanding of mechanisms of resistance and precise phenotyping. CMD is a complex disease caused by single or mix of different begomovirus species. Symptom severity is influenced by the time of infection and synergistic interaction between the virus species. Therefore, phenotyping should be complemented with determination of virus or viruses in the case of mixed infection, and their relative abundance in the host. Quantification of viral sequences by real time PCR is a tool of choice for fulfilling both conditions. Little is known about the mechanism of resistance as some varieties exhibit recovery from initial infection. While it is presumed that there are several sources of resistance to CMD, the most commonly used ones were attributed to CMD1 (TMS series) and CMD2 (TME series), although a thorough genetic investigation to determine the number of genes and their relationship remains pending. Several molecular markers have been developed to tag both types of resistance. Selection of precise markers linked to CMD resistance is necessary to improve the precision and speed of cassava improvement programs targeted for Africa. Our on-going program on marker validation would not only contribute to this process, but also determines the precise resistance mechanism.

ReferencesAkano, O.; Dixon, O.; Mba, C.; Barrera, E.;

Fregene, M. (2002). Genetic mapping of a dominant gene conferring resistance to cassava mosaic disease. Theor App I Genet 105:5215252

Alabi, O.J., Kumar, P.L. and Naidu, R.A. (2008). Multiplex PCR method for the detection of African cassava mosaic virus and East African cassava mosaic Cameroon virus in cassava. Journal of Virological Methods 154:111-120

Gedil, M.A. (2009). Tailoring Bioinformatics for the Genetic Improvement of Orphan Crops. ATDF Journal 6:34-43.

Hahn, S.K.; Howland, A.K.; Terry, E.R. (1980).

The inverse relationship between the two quantities implies that susceptible genotypes with high CMD scores reach threshold earlier hence their smaller Ct values. This observation is significant because it validates the applicability of real time PCR to achieving accurate phenotyping by accurate quantification of viral load. Beyond this, real time PCR can amplify sequences unique to each strain of cassava mosaic virus using specific qPCR primers and probes. Future studies, using the technique will resolve the effect of species/strain, mixed infection and virus load on genotype response. These will ensure an accurate


185

Non-specific amplification was checked by running a melt-curve analysis. A single peak was obtained indicating the absence of non-specific amplification (Fig.4).

Fig.4. Melt curve analysis showing specific amplification of ACMV sequences.

An inverse relationship was obtained when cycle threshold (Ct) was plotted against phenotypic CMD score (fig.5).

Fig.5. An X-Y Scatter plot of Ct values against CMD2 scores in some 1M genotypes.

On farm participative of improved varieties of cassava (Manihot esculenta Crantz) in the Center of Côte d'Ivoire

1 2N'zue Boni , Zohouri Goli Pierre , Sangare 3Abdourahamane ,

4 5Gnaore-Yapi Valentine and Kouadio Krah1 2 3Cassava Breeder, Phytopathologist, Molecular

4 5biologist, Scientific Coordinator, Research Assistant Centre National de Recherche Agronomique (CNRA) 01 BP 1740 Abidjan Côte d'IvoirePhone : (225) 23 47 24 24, Fax : (225) 23 47 24 11 Site : www.cnra.ci

Summary In Côte d'Ivoire, cassava is cultivated on all the territory and occupies the second place of food crops after yam. It constitutes at the same time a food and revenue crop for the producers. However, its production remains of traditional type with a low level of intensification, of which the use of traditional cultivars often less productive and sensitive to pests and diseases. To mitigate this insufficiency, the continuous provision of the farmers of improved varieties proves to be necessary. Thus within the framework of project WASDU, varietal tests of cassava were conducted from 2001 to 2002 in 4 localities (Kouakro, Niambrun, Tiengala and Ouokoukro) in central Regions of Côte d'Ivoire. In each locality, a community field of 4000 m² was used. Measurements and observations related, inter alia, to the pests and diseases, yield and on the reaction of farmers with respect to the agronomic and sensory characteristics were also observed. The harvest of the tuberous roots having intervened 12 months after plantation. The cultivars used as control obtained an average yield (6 t/ha to 18 t/ha) comparable with that of the variety IM93, but lower than those of the other improved varieties; except for the locality of Ouokoukro. The analysis of the data including localities and varieties, indicated that the average yield varied from 9 t/ha (IM93) to 19 t/ha (IM84). The locality of Niambrun recorded the best yield with 26 t/ha whereas that of Kouakro recorded lowest yield with 8 t/ha. As a whole, the farmers, while referring to a certain number of criteria (yield, size of the tuberous roots, cooking and taste, painfulness of harvest and vegetation covering), selected improved varieties IM84, TMS4(2)1425 and Im89.

Correlated resistance to cassava mosaic and bacterial blight diseases. Euphytica 29:305-311.

IITA (1990). Cassava in tropical Africa. A reference manual. Chayce Publications, 196.

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