Association mapping study for wood quality traits in Eucalyptus grandis

PAMELA V. VILLALBA; JANET HIGGINS; NATALIA C. AGUIRRE; CINTIA ACUÑA; MARTÍN N. GARCIA; CAPPA EDUARDO PABLO; JAVIER OBERSCHELP; LEONEL HARRAND; JUAN LOPEZ; MARTÍN MARCÓ; HORACIO ESTEBAN HOPP; NORMA PANIEGO; SUSANA N. MARCUCCI POLTRI

Talca

Conferencia; Phenotyping and Phenomics for Plant Breeding; 2015

There has always been a great interest in finding connections between genotype and phenotype, which is the fundamental objective of genetics studies. In particular, to understand the molecular basis that explains the phenotypic variation and to recognize how this knowledge can be applied directly to the improvement programs. That is why the search for markers linked to genomic regions involved in the control of characteristics of interest is of utmost importance in forest breeding programs. In this context, Association Mapping (AM) is one of the strategies most commonly used for this purpose mainly due to the development in recent years of several high-throughput technologies.In this study we used one population of Eucalyptus grandis (E.grandis) because the genus is the forest gender of hard wood's largest plantation in the world and the continuum incremented in world demand is a key objective in the improvement of the quality of the wood to make industrial processes more efficient. A total of 188 individual from an open-pollinated (OP) progeny trial in Argentina (hereafter EgrAR), was assessed for different characteristics related to growth and quality of wood such as DBH (diameter at breast height), FORM (righteousness of the shaft), TH (total height), PILO (wood density), LIG TOTAL and KLASON (tenor and type of lignin), SG (ratio Syringil:Guayacil of lignin), ET EXT and EXT TOTAL (ethanolic and total extractives) and DB (basic density).The population was genotyped with a high throughput array-based genotyping system of 7,680 DArT developed by Sansaloni et al. (2010), and a panel of 384 single nucleotide polymorphism markers (SNP) developed by Grattapaglia et al. (2011) using the Illumina GoldenGate Genotyping assay. As a result, subsets of 3,004 high quality DArT molecular markers and 160 SNP markers were obtained to use in the association study. Using 400 random selected DArT markers we examined the population structure of the populations, identifying three subpopulations (K=3) that represents the broad geographical origin in Australia. To minimize the detection of false-positive marker-trait associations we also calculated relationship matrices based on pairwise relatedness estimates between individuals to be included in the mixed linear model analysis (Mixed Linear Model, MLM). We obtained 79 DArT marker?trait associations (MTAs) but only four SNP MTAs even after using a more flexible correction such as Benjamini and Hochberg (1995) adjustment, all the MTAs were for four growth-related traits. Eighteen DArT and one SNP MTAs for DBH, 14 DArT and two SNP MTAs for FORM, 33 DArT and two SNP MTAs for TH and, 13 DArT and two SNP MTAs for VOL. Sequences of the markers associated significantly were mapping and annotated on the genome of E.grandis (version 1.1, http://phytozome.jgi.doe.gov); the allocation was performed using the component of BWA-SW (version 0.6.2) of the alignment tool Burrows-Wheeler using the default configuration with a perl script to annotate sequences with genes within a window of 600 kb approximately corresponding to a distance of recombination of 1.2 cM. In silico we found 1,930 genes located in the reference genome, additionally, 53 of them correspond to important genes connected with the synthesis of cellulose and lignin (e.g. CesA, Susy, CCR and COMT genes), with the synthesis of peroxidase and laccase genes, with MYB transcription factors, with MADS and SDRLK genes (S-domain-Receptor-Like Kinase). These results show that association studies are useful methods to identify genes involved in complex characters to be used as tools for forest breeding programs, as well as contribute to understand the genetics behind the phenotypic variation.