High marker density GWAS provides novel insights into the genomic architecture of terpene oil yield in Eucalyptus

Exploration of advanced omics tools and resources for the improvement of industrial oil crops

The rapid advancement in the field of omics approaches plays a crucial role in the development of improved industrial oil crops. Industrial oil crops play a crucial role across sectors like food processing, biofuels, cosmetics, and pharmaceuticals, making them indispensable contributors to global economies and these crops serve as vital elements in a multitude of industrial processes. Significant improvements in genomics have revolutionized the agricultural sector, particularly in the realm of oil crops. Cutting-edge advancements have facilitated the efficient sequencing of genomes for key commercial oil crops. This breakthrough not only enhances our understanding of the genetic makeup of these crops but also empowers breeders with invaluable insights for targeted genetic manipulation and breeding programs. Moreover, integrating transcriptomics with genomic data has assisted in a new era of precision agriculture. This approach provides an in-depth understanding of molecular mechanisms involved in traits of interest, such as oil content, yield potential, and resistance to biotic and abiotic stresses. Proteomics methods are instrumental in deciphering the intricacies of protein structure, interactions, and function, while metabolomics and ionomics shed light on the intricate network of metabolites and ions within biological systems. Each omics discipline offers unique insights, and their integration holds the promise of enriching our understanding and furnishing invaluable insights for enhancing oil crops. This review delves into the efficacy and constraints of various omics approaches in the context of refining industrial oil crops. Moreover, it underscores the importance of multi-omics strategies and explores their convergence with genetic engineering techniques to cultivate superior oil crop varieties.

Enhancing prediction accuracy of foliar essential oil content, growth, and stem quality in Eucalyptus globulus using multi-trait deep learning models

Eucalyptus globulus Labill., is a recognized multipurpose tree, which stands out not only for the valuable qualities of its wood but also for the medicinal applications of the essential oil extracted from its leaves. In this study, we implemented an integrated strategy comprising genomic and phenomic approaches to predict foliar essential oil content, stem quality, and growth-related traits within a 9-year-old breeding population of E. globulus. The strategy involved evaluating Uni/Multi-trait deep learning (DL) models by incorporating genomic data related to single nucleotide polymorphisms (SNPs) and haplotypes, as well as the phenomic data from leaf near-infrared (NIR) spectroscopy. Our results showed that essential oil content (oil yield) ranged from 0.01 to 1.69% v/fw and had no significant correlation with any growth-related traits. This suggests that selection solely based on growth-related traits did n The emphases (colored text) from revisions were removed throughout the article. Confirm that this change is fine. ot influence the essential oil content. Genomic heritability estimates ranged from 0.25 (diameter at breast height (DBH) and oil yield) to 0.71 (DBH and stem straightness (ST)), while pedigree-based heritability exhibited a broader range, from 0.05 to 0.88. Notably, oil yield was found to be moderate to highly heritable, with genomic values ranging from 0.25 to 0.60, alongside a pedigree-based estimate of 0.48. The DL prediction models consistently achieved higher prediction accuracy (PA) values with a Multi-trait approach for most traits analyzed, including oil yield (0.699), tree height (0.772), DBH (0.745), slenderness coefficient (0.616), stem volume (0.757), and ST (0.764). The Uni-trait approach achieved superior PA values solely for branching quality (0.861). NIR spectral absorbance was the best omics data for CNN or MLP models with a Multi-trait approach. These results highlight considerable genetic variation within the Eucalyptus progeny trial, particularly regarding oil production. Our results contribute significantly to understanding omics-assisted deep learning models as a breeding strategy to improve growth-related traits and optimize essential oil production in this species.

Genomic analysis based on chromosome-level genome assembly reveals Myrtaceae evolution and terpene biosynthesis of rose myrtle

BACKGROUND

Rose myrtle (Rhodomyrtus tomentosa (Ait.) Hassk), is an evergreen shrub species belonging to the family Myrtaceae, which is enriched with bioactive volatiles (α-pinene and β-caryophyllene) with medicinal and industrial applications. However, the mechanism underlying the volatile accumulation in the rose myrtle is still unclear.

RESULTS

Here, we present a chromosome-level genomic assembly of rose myrtle (genome size = 466 Mb, scaffold N50 = 43.7 Mb) with 35,554 protein-coding genes predicted. Through comparative genomic analysis, we found that gene expansion and duplication had a potential contribution to the accumulation of volatile substances. We proposed that the action of positive selection was significantly involved in volatile accumulation. We identified 43 TPS genes in R. tomentosa. Further transcriptomic and TPS gene family analyses demonstrated that the distinct gene subgroups of TPS may contribute greatly to the biosynthesis and accumulation of different volatiles in the Myrtle family of shrubs and trees. The results suggested that the diversity of TPS-a subgroups led to the accumulation of special sesquiterpenes in different plants of the Myrtaceae family.

CONCLUSIONS

The high quality chromosome-level rose myrtle genome and the comparative analysis of TPS gene family open new avenues for obtaining a higher commercial value of essential oils in medical plants.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden)

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

A terpene synthase supergene locus determines chemotype in Melaleuca alternifolia (tea tree)

Leaf oil terpenes vary categorically in many plant populations, leading to discrete phenotypes of adaptive and economic significance, but for most species, a genetic explanation for the concerted fluctuation in terpene chemistry remains unresolved. To uncover the genetic architecture underlying multi-component terpene chemotypes in Melaleuca alternifolia (tea tree), a genome-wide association study was undertaken for 148 individuals representing all six recognised chemotypes. A number of single nucleotide polymorphisms in a genomic region of c. 400 kb explained large proportions of the variation in key monoterpenes of tea tree oil. The region contained a cluster of 10 monoterpene synthase genes, including four genes predicted to encode synthases for 1,8-cineole, terpinolene, and the terpinen-4-ol precursor, sabinene hydrate. Chemotype-dependent null alleles at some sites suggested structural variants within this gene cluster, providing a possible basis for linkage disequilibrium in this region. Genotyping in a separate domesticated population revealed that all alleles surrounding this gene cluster were fixed after artificial selection for a single chemotype. These observations indicate that a supergene accounts for chemotypes in M. alternifolia. A genetic model with three haplotypes, encompassing the four characterised monoterpene synthase genes, explained the six terpene chemotypes, and was consistent with available biparental cross-segregation data.

Economic potential of essential oil production from New Zealand-grown Eucalyptus bosistoana

Farm foresters and other growers are establishing a ground-durable hardwood resource, including the emerging plantation species Eucalyptus bosistoana in New Zealand. The foliage of this species contains essential oils in quantity and quality suitable for commercial extraction. Essential oil production could improve the economic viability of E. bosistoana plantations, diversifying the grower's income and providing an early revenue stream. This study assessed the economic potential for essential oil production from New Zealand grown E. bosistoana plantations. A sensitivity analysis indicated that uncertainty of leaf biomass availability, genetic as well as seasonal changes in oil content, and fluctuations in essential oil price are equally important on the viability of an essential oil operation. Small-scale essential oil production could be sustainably supplied with foliage from thinning and pruning operations sourced from the envisaged regional planting programmes and commence in 3-5 years. A large-scale operation could be supplied when trees will be harvested. Lastly, based on the operational costs of a domestic small-scale essential oil producer, oil value from E. bosistoana would exceed the cost of production.

Genome-wide identification, expression profile and evolutionary relationships of TPS genes in the neotropical fruit tree species Psidium cattleyanum

Terpenoids are essential for plant growth, development, defense, and adaptation mechanisms. Psidium cattleyanum (Myrtaceae) is a fleshy fruit tree species endemics from Atlantic Forest, known for its pleasant fragrance and sweet taste, attributed to terpenoids in its leaves and fruits. In this study, we conducted genome-wide identification, evolutionary and expression analyses of the terpene synthase gene (TPS) family in P. cattleyanum red guava (var. cattleyanum), and yellow guava (var. lucidum Hort.) morphotypes. We identified 32 full-length TPS in red guava (RedTPS) and 30 in yellow guava (YlwTPS). We showed different expression patterns of TPS paralogous in the two morphotypes, suggesting the existence of distinct gene regulation mechanisms and their influence on the final essential oil content in both morphotypes. Moreover, the oil profile of red guava was dominated by 1,8-cineole and linalool and yellow guava was enriched in α-pinene, coincident in proportion to TPS-b1 genes, which encode enzymes that produce cyclic monoterpenes, suggesting a lineage-specific subfamily expansion of this family. Finally, we identified amino acid residues near the catalytic center and functional areas under positive selection. Our findings provide valuable insights into the terpene biosynthesis in a Neotropical Myrtaceae species and their potential involvement in adaptation mechanisms.

Cost-effectively dissecting the genetic architecture of complex wool traits in rabbits by low-coverage sequencing

Background

Rabbit wool traits are important in fiber production and for model organism research on hair growth, but their genetic architecture remains obscure. In this study, we focused on wool characteristics in Angora rabbits, a breed well-known for the quality of its wool. Considering the cost to generate population-scale sequence data and the biased detection of variants using chip data, developing an effective genotyping strategy using low-coverage whole-genome sequencing (LCS) data is necessary to conduct genetic analyses.

Results

Different genotype imputation strategies (BaseVar + STITCH, Bcftools + Beagle4, and GATK + Beagle5), sequencing coverages (0.1X, 0.5X, 1.0X, 1.5X, and 2.0X), and sample sizes (100, 200, 300, 400, 500, and 600) were compared. Our results showed that using BaseVar + STITCH at a sequencing depth of 1.0X with a sample size larger than 300 resulted in the highest genotyping accuracy, with a genotype concordance higher than 98.8% and genotype accuracy higher than 0.97. We performed multivariate genome-wide association studies (GWAS), followed by conditional GWAS and estimation of the confidence intervals of quantitative trait loci (QTL) to investigate the genetic architecture of wool traits. Six QTL were detected, which explained 0.4 to 7.5% of the phenotypic variation. Gene-level mapping identified the fibroblast growth factor 10 (FGF10) gene as associated with fiber growth and diameter, which agrees with previous results from functional data analyses on the FGF gene family in other species, and is relevant for wool rabbit breeding.

Conclusions

We suggest that LCS followed by imputation can be a cost-effective alternative to array and high-depth sequencing for assessing common variants. GWAS combined with LCS can identify new QTL and candidate genes that are associated with quantitative traits. This study provides a cost-effective and powerful method for investigating the genetic architecture of complex traits, which will be useful for genomic breeding applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00766-y.

Variations of Nutrient and Antinutrient Components of Bambara Groundnut (Vigna subterranea (L.) Verdc.) Seeds

Bambara groundnut (BGN) fits the bill when it comes to an acceptable level of nutrient and mineral composition. BGN is a balanced food that can help eradicate food and nutritional insecurity if it is incorporated into the major food system. However, there is a large degree of variation in nutrient composition and antinutritional factors among BGN accessions. Here, we show the degree of variability of nutrient and antinutrient components such as percentage ash, moisture, protein, fat, tryptophan, tannin, and phytate contents in seeds of 95 accessions of BGN. Data were subjected to analysis of variance (ANOVA), followed by correlation and principal component analysis. Clustering was done to show the relatedness between the accessions in response to the various traits. A high level of heterogeneity was observed among the accessions for the various traits studied. PC1 and PC2 show 41.2% of the total observed variations. Cluster analysis grouped accessions into four main clusters. This study was able to confirm the high level of diversity in the components of nutrients and antinutrients previously reported in BGN. The results of this study are expected to aid in identifying parent lines for improved breeding programs.

Genome-wide association study identifies SNP markers and putative candidate genes for terpene traits important for Leptocybe invasa resistance in Eucalyptus grandis

Terpenes are an important group of plant specialized metabolites influencing, amongst other functions, defence mechanisms against pests. We used a genome-wide association study to identify single nucleotide polymorphism (SNP) markers and putative candidate genes for terpene traits. We tested 15,387 informative SNP markers derived from genotyping 416 Eucalyptus grandis individuals for association with 3 terpene traits, 1,8-cineole, γ-terpinene, and p-cymene. A multilocus mixed model analysis identified 21 SNP markers for 1,8-cineole on chromosomes 2, 4, 6, 7, 8, 9, 10, and 11, that individually explained 3.0%–8.4% and jointly 42.7% of the phenotypic variation. Association analysis of γ-terpinene found 32 significant SNP markers on chromosomes 1, 2, 4, 5, 6, 9, and 11, explaining 3.4–15.5% and jointly 54.5% of phenotypic variation. For p-cymene, 28 significant SNP markers were identified on chromosomes 1, 2, 3, 5, 6, 7, 10, and 11, explaining 3.4–16.1% of the phenotypic variation and jointly 46.9%. Our results show that variation underlying the 3 terpene traits is influenced by a few minor loci in combination with a few major effect loci, suggesting an oligogenic nature of the traits.

Increasing calling accuracy, coverage, and read-depth in sequence data by the use of haplotype blocks

High-throughput genotyping of large numbers of lines remains a key challenge in plant genetics, requiring geneticists and breeders to find a balance between data quality and the number of genotyped lines under a variety of different existing genotyping technologies when resources are limited. In this work, we are proposing a new imputation pipeline (“HBimpute”) that can be used to generate high-quality genomic data from low read-depth whole-genome-sequence data. The key idea of the pipeline is the use of haplotype blocks from the software HaploBlocker to identify locally similar lines and subsequently use the reads of all locally similar lines in the variant calling for a specific line. The effectiveness of the pipeline is showcased on a dataset of 321 doubled haploid lines of a European maize landrace, which were sequenced at 0.5X read-depth. The overall imputing error rates are cut in half compared to state-of-the-art software like BEAGLE and STITCH, while the average read-depth is increased to 83X, thus enabling the calling of copy number variation. The usefulness of the obtained imputed data panel is further evaluated by comparing the performance of sequence data in common breeding applications to that of genomic data generated with a genotyping array. For both genome-wide association studies and genomic prediction, results are on par or even slightly better than results obtained with high-density array data (600k). In particular for genomic prediction, we observe slightly higher data quality for the sequence data compared to the 600k array in the form of higher prediction accuracies. This occurred specifically when reducing the data panel to the set of overlapping markers between sequence and array, indicating that sequencing data can benefit from the same marker ascertainment as used in the array process to increase the quality and usability of genomic data.

High-throughput genotyping of large numbers of lines remains a key challenge in plant genetics and breeding. Cost, precision, and throughput must be balanced to achieve optimal efficiency given available technologies and finite resources. Although genotyping arrays are still considered the gold standard in high-throughput quantitative genetics, recent advances in sequencing provide new opportunities. Both the quality and cost of genomic data generated based on sequencing are highly dependent on the used read-depth. In this work, we propose a new imputation pipeline (“HBimpute”) that uses haplotype blocks to detect individuals of the same genetic origin and subsequently uses all reads of those individuals in the variant calling. Thus, the obtained virtual read-depth is artificially increased, leading to higher calling accuracy, coverage, and the ability to call copy number variation based on low read-depth sequencing data. To conclude, our approach makes sequencing a cost-competitive alternative to genotyping arrays with the added benefit of allowing the calling of structural variation.

Chromosome-specific polymorphic SSR markers in tropical eucalypt species using low coverage whole genome sequences: systematic characterization and validation

Eucalyptus is one of the major plantation species with wide variety of industrial uses. Polymorphic and informative simple sequence repeats (SSRs) have broad range of applications in genetic analysis. In this study, two individuals of Eucalyptus tereticornis (ET217 and ET86), one individual each from E. camaldulensis (EC17) and E. grandis (EG9) were subjected to whole genome resequencing. Low coverage (10×) genome sequencing was used to find polymorphic SSRs between the individuals. Average number of SSR loci identified was 95,513 and the density of SSRs per Mb was from 157.39 in EG9 to 155.08 in EC17. Among all the SSRs detected, the most abundant repeat motifs were di-nucleotide (59.6%–62.5%), followed by tri- (23.7%–27.2%), tetra- (5.2%–5.6%), penta- (5.0%–5.3%), and hexa-nucleotide (2.7%–2.9%). The predominant SSR motif units were AG/CT and AAG/TTC. Computational genome analysis predicted the SSR length variations between the individuals and identified the gene functions of SSR containing sequences. Selected subset of polymorphic markers was validated in a full-sib family of eucalypts. Additionally, genome-wide characterization of single nucleotide polymorphisms, InDels and transcriptional regulators were carried out. These variations will find their utility in genome-wide association studies as well as understanding of molecular mechanisms involved in key economic traits. The genomic resources generated in this study would provide an impetus to integrate genomics in marker-trait associations and breeding of tropical eucalypts.

Characterization of terpene biosynthesis in Melaleuca quinquenervia and ecological consequences of terpene accumulation during myrtle rust infection

Plants use a wide array of secondary metabolites including terpenes as defense against herbivore and pathogen attack, which can be constitutively expressed or induced. Here, we investigated aspects of the chemical and molecular basis of resistance against the exotic rust fungus Austropuccinia psidii in Melaleuca quinquenervia, with a focus on terpenes. Foliar terpenes of resistant and susceptible plants were quantified, and we assessed whether chemotypic variation contributed to resistance to infection by A. psidii. We found that chemotypes did not contribute to the resistance and susceptibility of M. quinquenervia. However, in one of the chemotypes (Chemotype 2), susceptible plants showed higher concentrations of several terpenes including α-pinene, limonene, 1,8-cineole, and viridiflorol compared with resistant plants. Transcriptome profiling of these plants showed that several TPS genes were strongly induced in response to infection by A. psidii. Functional characterization of these TPS showed them to be mono- and sesquiterpene synthases producing compounds including 1,8-cineole, β-caryophyllene, viridiflorol and nerolidol. The expression of these TPS genes correlated with metabolite data in a susceptible plant. These results suggest the complexity of resistance mechanism regulated by M. quinquenervia and that modulation of terpenes may be one of the components that contribute to resistance against A. psidii.

Plasticity engineering of plant monoterpene synthases and application for microbial production of monoterpenoids

Plant monoterpenoids with structural diversities have extensive applications in food, cosmetics, pharmaceuticals, and biofuels. Due to the strong dependence on the geographical locations and seasonal annual growth of plants, agricultural production for monoterpenoids is less effective. Chemical synthesis is also uneconomic because of its high cost and pollution. Recently, emerging synthetic biology enables engineered microbes to possess great potential for the production of plant monoterpenoids. Both acyclic and cyclic monoterpenoids have been synthesized from fermentative sugars through heterologously reconstructing monoterpenoid biosynthetic pathways in microbes. Acting as catalytic templates, plant monoterpene synthases (MTPSs) take elaborate control of the monoterpenoids production. Most plant MTPSs have broad substrate or product properties, and show functional plasticity. Thus, the substrate selectivity, product outcomes, or enzymatic activities can be achieved by the active site mutations and domain swapping of plant MTPSs. This makes plasticity engineering a promising way to engineer MTPSs for efficient production of natural and non-natural monoterpenoids in microbial cell factories. Here, this review summarizes the key advances in plasticity engineering of plant MTPSs, including the fundamental aspects of functional plasticity, the utilization of natural and non-natural substrates, and the outcomes from product isomers to complexity-divergent monoterpenoids. Furthermore, the applications of plasticity engineering for improving monoterpenoids production in microbes are addressed.

Monoterpene synthases responsible for the terpene profile of anther glands in Eucalyptus polybractea R.T. Baker (Myrtaceae)

Research on terpene biosynthesis in the genus Eucalyptus (Myrtaceae) is poorly developed, but recently large numbers of terpene synthase (TPS) genes have been identified. Few of these have been characterized or their expression localized to specific tissues. A prime candidate for detailed examination of TPS gene expression is the bisexual eucalypt flower-composed of male and female reproductive organs, and vegetative tissues that may express different TPS genes. We aimed to characterize and compare the terpene profile and TPS genes expressed in anthers and gynoecia in the high oil-yielding Eucalyptus polybractea R.T. Baker. We hypothesized that gynoecia will produce greater amounts of defensive terpenes, whereas anthers will have a terpene profile that is biased towards a role in pollination. Microscopy of isolated anthers showed them to possess a single, prominent oil gland. Chemical analysis of whole floral structures at different stages of development showed total oil per unit dry mass increased as flower buds expanded, with highest concentrations in mature flower buds just prior to flower opening. The oil profile of gynoecia was dominated by the monoterpene 1,8-cineole, whereas that of isolated anthers were enriched with the monoterpene α-pinene. Through transcriptomic analysis and recombinant protein expression, we were able to identify monoterpene synthases responsible for the different profiles. Synthases for α-pinene and 1,8-cineole were expressed in each tissue type, but the relative expression of the former was higher in anthers. Sequence comparison and site-directed mutagenesis of the α-pinene synthase allowed us to identify amino acids that influence the α-pinene to β-pinene ratio of the product profile. We suggest the terpene constituents of anthers may have multiple roles including attracting pollinators through emission of volatile α-pinene, deterrence of palynivores through emission of volatile 1,8-cineole and adhesion of pollen to pollinators via the release of sticky α-pinene onto the anther surface.

Strategies for the production of biochemicals in bioenergy crops

Industrial crops are grown to produce goods for manufacturing. Rather than food and feed, they supply raw materials for making biofuels, pharmaceuticals, and specialty chemicals, as well as feedstocks for fabricating fiber, biopolymer, and construction materials. Therefore, such crops offer the potential to reduce our dependency on petrochemicals that currently serve as building blocks for manufacturing the majority of our industrial and consumer products. In this review, we are providing examples of metabolites synthesized in plants that can be used as bio-based platform chemicals for partial replacement of their petroleum-derived counterparts. Plant metabolic engineering approaches aiming at increasing the content of these metabolites in biomass are presented. In particular, we emphasize on recent advances in the manipulation of the shikimate and isoprenoid biosynthetic pathways, both of which being the source of multiple valuable compounds. Implementing and optimizing engineered metabolic pathways for accumulation of coproducts in bioenergy crops may represent a valuable option for enhancing the commercial value of biomass and attaining sustainable lignocellulosic biorefineries.

A phylogenomic approach reveals a low somatic mutation rate in a long-lived plant

Somatic mutations can have important effects on the life history, ecology, and evolution of plants, but the rate at which they accumulate is poorly understood and difficult to measure directly. Here, we develop a method to measure somatic mutations in individual plants and use it to estimate the somatic mutation rate in a large, long-lived, phenotypically mosaic Eucalyptus melliodora tree. Despite being 100 times larger than Arabidopsis, this tree has a per-generation mutation rate only ten times greater, which suggests that this species may have evolved mechanisms to reduce the mutation rate per unit of growth. This adds to a growing body of evidence that illuminates the correlated evolutionary shifts in mutation rate and life history in plants.