Bala R. Thumma

Polymorphisms in Cinnamoyl CoA Reductase ( CCR ) Are Associated With Variation in Microfibril Angle in Eucalyptus spp.

Linkage disequilibrium (LD) mapping using natural populations results in higher resolution of marker-trait associations compared to family-based quantitative trait locus (QTL) studies. Depending on the extent of LD, it is possible to identify alleles within candidate genes associated with a trait. Analysis of a natural mutant in Arabidopsis has shown that mutations in cinnamoyl CoA reductase (CCR), a key lignin gene, affect physical properties of the secondary cell wall such as stiffness and strength. Using this gene, we tested whether LD mapping could identify alleles associated with microfibril angle (MFA), a wood quality trait affecting stiffness and strength of wood. We identified 25 common single-nucleotide polymorphism (SNP) markers in the CCR gene in Eucalyptus nitens. Using single-marker and haplotype analyses in 290 trees from a E. nitens natural population, two haplotypes significantly associated with MFA were found. These results were confirmed in two full-sib families of E. nitens and Eucalyptus globulus. In an effort to understand the functional significance of the SNP markers, we sequenced the cDNA clones and identified an alternatively spliced variant from the significant haplotype region. This study demonstrates that LD mapping can be used to identify alleles associated with wood quality traits in natural populations of trees.

Progress in Myrtaceae genetics and genomics: Eucalyptus as the pivotal genus

The status of genomics and genetics research in the Myrtaceae, a large family of dicotyledonous woody plants, is reviewed with Eucalyptus as the focal genus. The family contains over 5,650 species in 130 to 150 genera, predominantly of neo-tropical and Southern Hemisphere distribution. Several genera are well known for their economic importance worldwide. Myrtaceae are typically diploids with small to intermediate genome size. Microsatellites have been developed for several genera while higher throughput marker systems such as diversity arrays technology and single nucleotide polymorphism are available for Eucalyptus. Molecular data have been fundamental to current perspectives on the phylogeny, phylogeography and taxonomy of the Myrtaceae, while numerous studies of genetic diversity have been carried out particularly as it relates to endangered, rare, fragmented, overharvested or economically important species. Large expressed sequence tag collections for species of Eucalyptus have recently become public to support the annotation of the Eucalyptus grandis genome. Transcriptomics in Eucalyptus has advanced by microarrays and next-generation sequencing focusing on wood development. Linkage maps for Eucalyptus display high synteny across species and have been extensively used to map quantitative trait loci for a number of traits including growth, wood quality, disease and insect resistance. Candidate gene-based association genetics have successfully found marker–trait associations for wood and fiber traits. Genomic selection experiments have demonstrated clear potential to improve the efficiency of breeding programs while freeze-tolerant transgenic Eucalyptus trials have recently been initiated. The recently released E. grandis genome, sequenced to an average coverage of 8×, will open up exceptional opportunities to advance Myrtaceae genetics and genomics research.

Identification of a Cis-Acting Regulatory Polymorphism in a Eucalypt COBRA-Like Gene Affecting Cellulose Content

Populations with low linkage disequilibrium (LD) offer unique opportunities to study functional variants influencing quantitative traits. We exploited the low LD in forest trees to identify functional polymorphisms in a Eucalyptus nitens COBRA-like gene (EniCOBL4A), whose Arabidopsis homolog has been implicated in cellulose deposition. Linkage analysis in a full-sib family revealed that EniCOBL4A is the most strongly associated marker in a quantitative trait locus (QTL) region for cellulose content. Analysis of LD by genotyping 11 common single-nucleotide polymorphisms (SNPs) and a simple sequence repeat (SSR) in an association population revealed that LD declines within the length of the gene. Using association studies we fine mapped the effect of the gene to SNP7, a synonymous SNP in exon 5, which occurs between two small haplotype blocks. We observed patterns of allelic expression imbalance (AEI) and differential binding of nuclear proteins to the SNP7 region that indicate that SNP7 is a cis-acting regulatory polymorphism affecting allelic expression. We also observed AEI in SNP7 heterozygotes in a full-sib family that is linked to heritable allele-specific methylation near SNP7. This study demonstrates the potential to reveal functional polymorphisms underlying quantitative traits in low LD populations.

Quantitative trait locus (QTL) analysis of wood quality traits in Eucalyptus nitens

To identify the chromosomal regions affecting wood quality traits, we conducted a genome-wide quantitative trait locus (QTL) analysis of wood quality traits in Eucalyptus nitens. This information is important to exploit the full potential of the impending Eucalyptus genome sequence. A three generational mapping population consisting of 296 progeny trees was used to identify QTL associated with several wood quality traits in E. nitens. Thirty-six QTL positions for cellulose content, pulp yield, lignin content, density, and microfibril angle (MFA) were identified across different linkage groups. On linkage groups (LG)2 and 8, cellulose QTL cluster with pulp yield and extractives QTL while on LG4 and 10 cellulose and pulp yield QTLs cluster together. Similarly, on LG4, 5, and 6 QTL for lignin traits were clustered together. At two positions, QTL for MFA, a physical trait related to wood stiffness, were clustered with QTL for lignin traits. Several cell wall candidate genes were co-located to QTL positions affecting different traits. Comparative QTL analysis with Eucalyptus globulus revealed two common QTL regions for cellulose and pulp yield. The QTL positions identified in this study provide a resource for identifying wood quality genes using the impending Eucalyptus genome sequence. Candidate genes identified in this study through co-location to QTL regions may be useful in association studies.

Quantitative trait locus (QTL) analysis of growth and vegetative propagation traits in Eucalyptus nitens full-sib families

Tree growth and vegetative propagation are complex but important traits under selection in many tree improvement programmes. To understand the genetic control of these traits, we conducted a quantitative trait locus (QTL) study in three full-sib families of Eucalyptus nitens growing at two different sites. One family growing at Ridgley, Tasmania had 300 progeny and two clonally replicated families growing at Mt. Gambier, South Australia had 327 and 210 progeny. Tree growth was measured over several years at both sites and percentages of roots produced by either stem cuttings or tissue culture were assessed in the two Mt. Gambier families. Linkage analysis of growth traits revealed several QTLs for later year traits but few for early year traits, reflecting temporal differences in the heritabilities of these traits. Two growth QTL positions, one on LG8 and another on LG11 were common between the Ridgley and Mt. Gambier families. Four QTLs were observed for each of the two vegetative propagation methods. Two QTLs for vegetative propagation on LG7 and LG11 were validated in the second family at Mt. Gambier. These results suggest that growth and vegetative propagation traits are controlled by several small effect loci. The QTLs identified in this study are useful starting points for identifying candidate genes using the Eucalyptus grandis genome sequence.

Dissection of complex traits in forest trees — opportunities for marker-assisted selection

Due to their long reproductive cycles and the time to expression of mature traits, marker-assisted selection is particularly attractive for tree breeding. In this review, we discuss different approaches used for developing markers and propose a method for application of markers in low linkage disequilibrium (LD) populations. Identification of useful markers for application in tree breeding is mainly based on two approaches, quantitative trait locus (QTL) mapping and association genetic studies. While several studies have identified significant markers, effect of the individual markers is low making it difficult to utilize them in breeding programs. Recently, genomic selection (GS) was proposed for overcoming some of these difficulties. In GS, high density markers are used for predicting phenotypes from genotypes. Currently small effective populations with high LD are being tested for GS in tree breeding. For wider application, GS needs to be applied in low LD populations which are found in many tree breeding programs. Here we propose an approach in which the significant markers from association studies may be used for developing prediction models in low LD populations using the same methods as in GS. Preliminary analyses indicate that a modest numbers of markers may be sufficient for developing prediction models in low LD populations. GS based on large numbers of random markers or small numbers of associated markers is poised to make marker-assisted selection a reality in forest tree breeding.

Comparison of Genomic Selection Models to Predict Flowering Time and Spike Grain Number in Two Hexaploid Wheat Doubled Haploid Populations

Genomic selection (GS) is becoming an important selection tool in crop breeding. In this study, we compared the ability of different GS models to predict time to young microspore (TYM), a flowering time-related trait, spike grain number under control conditions (SGNC) and spike grain number under osmotic stress conditions (SGNO) in two wheat biparental doubled haploid populations with unrelated parents. Prediction accuracies were compared using BayesB, Bayesian least absolute shrinkage and selection operator (Bayesian LASSO / BL), ridge regression best linear unbiased prediction (RR-BLUP), partial least square regression (PLS), and sparse partial least square regression (SPLS) models. Prediction accuracy was tested with 10-fold cross-validation within a population and with independent validation in which marker effects from one population were used to predict traits in the other population. High prediction accuracies were obtained for TYM (0.51–0.84), whereas moderate to low accuracies were observed for SGNC (0.10–0.42) and SGNO (0.27–0.46) using cross-validation. Prediction accuracies based on independent validation are generally lower than those based on cross-validation. BayesB and SPLS outperformed all other models in predicting TYM with both cross-validation and independent validation. Although the accuracies of all models are similar in predicting SGNC and SGNO with cross-validation, BayesB and SPLS had the highest accuracy in predicting SGNC with independent validation. In independent validation, accuracies of all the models increased by using only the QTL-linked markers. Results from this study indicate that BayesB and SPLS capture the linkage disequilibrium between markers and traits effectively leading to higher accuracies. Excluding markers from QTL studies reduces prediction accuracies.

RNA-Seq using two populations reveals genes and alleles controlling wood traits and growth in Eucalyptus nitens.

Eucalyptus nitens is a perennial forest tree species grown mainly for kraft pulp production in many parts of the world. Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. KPY is positively correlated with growth measured as diameter at breast height (DBH) in both trials. In total, six RNA bulks from two treatments were sequenced on an Illumina HiSeq platform. At 5% false discovery rate level, 3953 transcripts showed differential expression in the same direction in both trials; 2551 (65%) were down-regulated and 1402 (35%) were up-regulated in low KPY samples. The genes up-regulated in low KPY trees were largely involved in biotic and abiotic stress response reflecting the low growth among low KPY trees. Genes down-regulated in low KPY trees mainly belonged to gene categories involved in wood formation and growth. Differential allelic expression was observed in 2103 SNPs (in 1068 genes) and of these 640 SNPs (30%) occurred in 313 unique genes that were also differentially expressed. These SNPs may represent the cis-acting regulatory variants that influence total gene expression. In addition we also identified 196 genes which had Ka/Ks ratios greater than 1.5, suggesting that these genes are under positive selection. Candidate genes and alleles identified in this study will provide a valuable resource for future association studies aimed at identifying molecular markers for KPY and growth.

Transcriptome sequencing of Eucalyptus camaldulensis seedlings subjected to water stress

Water stress limits plant survival and production in many parts of the world. Identification of genes responding to water stress conditions will underpin efforts to breed plants better adapted to drought. We studied the effect of water stress on Eucalyptus camaldulensis seedlings derived from three natural populations. Physiological and growth traits were measured and gene and allelic expression in leaves was examined by RNA sequencing (RNA-seq). Water stress had a significant impact on all the physiological and growth traits, while differences between the populations were not significant. Genes differentially expressed in leaves were identified by de novo assembly and by ab initio transcriptome mapping using the Eucalyptus grandis reference genome sequence. Gene ontology (GO) enrichment tests with 2,500 significantly differentiated genes revealed 128 stress-related gene categories were up-regulated while 28 gene categories belonging to photosynthesis and other metabolic processes were down-regulated under stress treatment. More than 190,000 single nucleotide polymorphisms (SNPs) and small indels were detected and 4,053 of these revealed differential allelic expression between control and drought stressed seedlings. Allelic expression of 70% of these variants was correlated with total gene expression. These variants may be cis-acting variants or in high linkage disequilibrium with such variants. The SNPs and indels identified in this study form a useful resource for further testing in association studies.

Identification of genes and alleles influencing wood development in Eucalyptus

The goal of many forest tree breeding programs is to increase the quantity and quality of wood products from plantations. Due to their outcrossing breeding systems, long generation times and relatively short history of domestication, breeding populations of most forest trees closely resemble the wild state. Consequently, vast stores of genetic variation are available for selection. Because wood traits are under polygenetic control (quantitative), genetic improvement will rely on selection of multiple alleles, each of relatively small individual effect. Marker-assisted selection may enhance tree breeding programs by enabling informed selection of parents for crossing; fixing desirable alleles in the homozygous state; increasing selection intensity through screening large numbers of individuals; enabling early selection in seedlings and by reducing phenotyping costs. The low linkage disequilibrium found in most forest trees makes them ideally suited to candidate gene-based association mapping approaches for marker discovery. This approach seeks to find alleles which affect phenotype and that remain linked to the trait across populations and over many generations. This methodology is well suited to tree breeding programs which aim to maintain a broad genetic base i.e. programs with a large number of families. We are using association studies to identify genes and allelic variation that influences wood fibre properties in Eucalyptus nitens. Candidate genes are being selected on the basis of their known involvement in cell wall synthesis pathways expected to impact wood traits. Single nucleotide polymorphisms (SNPs) are identified in candidate genes by sequencing in a number of unrelated individuals. Selected SNPs are being genotyped across large unrelated E. nitens populations that have been extensively phenotyped for wood properties including cellulose and lignin content, pulp yield, MFA, and density. Several SNPs significantly associated with wood properties have been identified and subsequently validated in other provenance or mapping populations growing in different environments. Selected SNPs are being investigated further to determine whether or not the SNP is the causative polymorphism and how the polymorphism influences the trait. DNA markers identified in this research may be used to complement existing index selection strategies in E. nitens breeding programs. Strategies for exploiting SNPs for marker-assisted selection in seedling-based breeding programs will be discussed.