Genetics of Growth in Teak Clonal Seed Orchard Families and Provenances in Contrasted Tropical Sites

Roberto Bacilieri1, Doreen K S Goh2, Gilles Chaix3, Olivier Monteuuis3

(ref. Goh et al. 2013. Tree Genetics & Genomes 2013, 9:1329-1341)

Abstract : Teak is diploid (2n=36), has a small genome (480Mpb), and displays a high level of heterozygosity (more than 70% in the genetically richest forests), all favorable traits for improvement through selection and breeding. In spite of the interest of teak for the world market, R&D efforts in teak genetic improvement are still rare. As a result, forest companies still have little choice for their investment in genetically superior materials. As a first step towards a better exploitation of teak genetic potential, we compared 16 teak families derived from an open-pollinated improved clonal seed orchard (CSO) with 10 non-improved commercial or natural teak provenances (Prov). Plants were grown in two different tropical sites, so to : a) compare, in a statistically sound experiment, the provenances among them and with the CSO families, b) estimate the heritability of growth traits and c) estimate the genetic gains that can be expected via improvement and breeding. Both experimental sites are located in Sabah, East Malaysia.

For the analysis of the variance we used a state-of-the-art mixed statistical model accounting for spatial variation. Nine years after planting, the two genetic entries, CSO and Prov, showed highly significant differences for height, DBH and volume in both sites. The superiority of the improved CSO families compared with the non-improved Prov class was large for volume production, resulting in an advantage of +67.9% and +40.3% in Luasong and Taliwas respectively. Narrow-sense heritabilities for the 16 CSO families were large for height (0.38) and volume (0.23). These promising results for bole growth will translate in even better outcomes in the field, once geneticists will be able to concomitantly deal with the improvement of stem form, wood quality and tolerance to biotic and abiotic stresses. The exploration of these favourable traits using a combination of sound field experiments and deployment of modern DNA technologies, should make teak genetic improvement through selection and breeding attainable and effective in short time and with a moderate R&D investment.

1. INRA, UMR 1334 AGAP Genetic Improvement and Adaptation of Tropical Plants, Montpellier, France • Corresponding author: bacilieri@supagro.inra.fr

2. YSG Biotech Sdn Bhd, Yayasan Sabah Group, Kota Kinabalu, Sabah, Malaysia 3. CIRAD, UMR 1334 AGAP Genetic Improvement and Adaptation of Tropical Plants, Montpellier, France

The Experiment : Trees were planted in 1998 and were measured 9 years after planting. In total 2.046 trees from 26 genetic entries were measured for growth in DBH, height and volume (Table 1).

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Statistics : A mixed model analysis of variance accounting simultaneously for genetic and spatial variation of growth. Neighbour trees may have similar performances because of a shared micro-environment. Accounting for spatial auto-correlation (Fig. 1) improves the estimation of the genetic parameters, in particular for irregular terrains (Fig. 2).

Figure 1 : Variograms of the spatial autocorrelation according to tree distances.

Mixed-model analysis of variance (SAS 9.2)

Figure 2 : Plots of the spatial variation residuals, accounting for the genetic effect, across the irregular hilly site in Luasong and the more regular flat area in Taliwas (right).

Results : Adopting a spatial model for the analysis of variance resulted in a noticeable reduction of the block effects and of the residual variance, particularly in the hilly site of Luasong, improving the estimation of the genetic effects and of their interaction with the site environment. The superiority of the CSO Families compared to the Prov. (Fig. 3) was more obvious in the hilly site of Luasong than in Taliwas, with an average gain of +67.9% and 40.3% respectively. In addition to growing faster, the CSO Families also showed less within-class variation. It is well known than more homogeneous genetic material is easier to grow. GxE effects were found for both genetic classes (Site X Prov and Site X CSO Family respectively, Fig. 4). Some families performed well in both sites, but the best families in one site were often not the best ones in the other site. According to the plantation charateristics, choices are thus possible between well performing and stable, or superior but specialised, genetic materials. Narrow sense-heritabilities estimated for the 16 CSO families across the two sites were ℎ� i

2 = 0.23 for volume and hi2 = 0.38 for height, which is

promising for recurrent breeding. Due to missing data, we were not able to introduce in this elaborated statistical model two other traits of interest, the fork height and the bole straightness. However the available data suggests that an improvement of the order of 15% to 22% were obtained for these traits too in our experiment.

0.06

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Luasong (hilly,irregular)

Taliwas (flat,lowland)

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8367 8668

8823 8824

8831 8832

8833 8844

9999 8839

9411 9412

9418 9426

9430 9435

9437 9440

9443 9446

9450 9452

9454 9457

9459 9463

Figure 4 : BLUP ranking of the genetic entries in the two sites. Some superior CSO Families (ex. 9430) are quite stable across sites, while others (ex. 9450) display a GxE inter-action, being more « specialised » to one environment.

CSO Families are in brown-bold, Prov. are in grey

Literature : Funda T et al. 2007. J. For. Sci., 53,: 47–56. - Callister AN, Collins SL. 2008. Tree Genetics and Genomes 4: 237-245. - Indira EP et al. 2008. ITTO Japan, pp. 205-213. - Chaix G. et al. 2011: Annals of Forest Science, 68: 1015–1026. - Monteuuis O et al. 2011. Tree Genetics and Genomes, 7: 1263-1275. - Goh DKS et al. 2007. Bois et Forêts des Tropiques 293: 65-77. Harfouche et al. 2012, Trends in Plant Science 12:1360-1385. - SAS Institute Inc. 2008. SAS/STAT® 9.2 User’s Guide. Cary, NC: SAS Institute Inc. Photos : 1: 0livier Monteuuis - 2:YSG Biotech Sdn Bhd – 3: Prota4U.org – 4: CIRAD.

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Luasong (hilly) Taliwas (flat) Both sites

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Figure 3 : Compared growth of improved CSO faimlies as compared to commercial provenances

Fig 6. GWAS : Genome wide association study, localising genes along chromosomes (example)

Fig 7. DL in natural populations allows finer gene mapping as compared to

biparetal crosses

Fig 5. Genomic selection, exploting DNA information from young plants to predict traits at mature stage, allows shotening of the breeding cycles, as compared to conven-tional breeding.

Discussion : This study confirms, under wet tropical conditions, the superiority of CSO families compared to non-selected provenances, for producing in a short time high yields of teak timber (Chaix et al. 2011; Monteuuis et al. 2011). It shows that growth performances are, however, liable to vary markedly among different genetic sources, even closely related ones, according to soil characteristics. This offers new prospects for selecting teak material that could perform well in a broader range of soils. The project also reveals and makes available valuable genetic resources for future recurrent crossing and breeding schemes. Such investigations deserve to be extended to quality-related traits such as wood properties (Goh et al. 2007), stem form, and pest and disease resistance. In this respect, there may be a real advantage in deploying populations of selected clones, while maintaining the diversity of multiple genetic origins. Future : In the last decade, DNA technology has made impressive steps forward, making the study of variation in genes and genomes accessible at very low cost. Integrating modern genetics and genomics tools with conventional breeding allows today to significantly accelerate domestication, improvement and adaptation of long-lived forest trees (Fig. 5, Harfouche et al. 2012). This objective can be achieved with Teak, through a strong collaboration between forest landowners, tree breders and biotechnologists, focusing on a cost-effective, accessible and publicly accepted R&D strategy. The different steps to implement for the realisation of these objectives are :

1- Characterization of the genetic diversity (targeted DNA sequencing, SNP molecular markers) for understanding the genomic and geographic structure of the species richness and allow clonal and provenance identification. 2- Constitution of core-collections of the most diverse genetic resources for gene discovery via genetic association (3) and as a training population for genomic selection (4). This « discovery » panel will be phenotyped for the most important traits both in-situ (growth, resistance to diseases) and ex-situ (wood properties), then thinned according to tree quality, and conducted as a clonal seed orchard. (CSO). 3 – Identification of functional or candidate genes variation using, according to the target trait, a specifically designed gene-by-gene, or a genome-wide, association genetics approach, exploiting linkage desequilibrium between molecular markers and traits of interest (Fig. 6, 7). 4 – Development of predictive models for genomic selection, exploiting DNA SNP variation in young seedlings to predict mature tree quality. 5 – Using these predictions for early selection and release of superior and diverse genetic materials .

Spatial model: Yikln = µ + Si + Ok + El(k) + SOik + SEil(k) + + ηn(i) + εikln