Regional heritability mapping and genome-wide association identify loci for complex growth, wood and disease resistance traits in Eucalyptus

Identification of SNP Markers and Candidate Genes Associated with Major Agronomic Traits in Coffea arabica

Genome-wide association studies (GWASs) allow for inferences about the relationships between genomic variants and phenotypic traits in natural or breeding populations. However, few have used this methodology in Coffea arabica. We aimed to identify chromosomal regions with significant associations between SNP markers and agronomic traits in C. arabica. We used a coffee panel consisting of 195 plants derived from 13 families in F2 generations and backcrosses of crosses between leaf rust-susceptible and -resistant genotypes. The plants were phenotyped for 18 agronomic markers and genotyped for 21,211 SNP markers. A GWAS enabled the identification of 110 SNPs with significant associations (p < 0.05) for several agronomic traits in C. arabica: plant height, plagiotropic branch length, number of vegetative nodes, canopy diameter, fruit size, cercosporiosis incidence, and rust incidence. The effects of each SNP marker associated with the traits were analyzed, such that they can be used for molecular marker-assisted selection. For the first time, a GWAS was used for these important agronomic traits in C. arabica, enabling applications in accelerated coffee breeding through marker-assisted selection and ensuring greater efficiency and time reduction. Furthermore, our findings provide preliminary knowledge to further confirm the genomic loci and potential candidate genes contributing to various structural and disease-related traits of C. arabica.

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.

Population structure and genetic diversity in Eucalyptus pellita based on SNP markers

Eucalyptus pellita has the characteristics of rapid growth and high resistance. However, there is little research on molecular breeding of E. pellita, which is essential to shortening breeding life and selecting quality varieties. Therefore, a crucial step before selective breeding can be carried out to increase the wood quality of E. pellita is identifying genetic diversity and population structure using single nucleotide polymorphism (SNP) markers. In this study, the genetic diversity of 1st generation 196 E. pellita families from 23 geographically defined was assessed using 1,677,732 SNP markers identified by whole genome resequencing. SNP annotation showed that the ratio of non-synonymous to synonymous coding mutations was 0.83. Principal component analysis (PCA), phylogenetic tree, and population structure analysis permitted the families to be categorized into three groups, one of which (G2) contains most of the Indonesian (IDN) and Papua New Guinea (PNG) families. Genetic relationship analysis showed that IDN was closely related to PNG. Genetic diversity analysis showed that He, PIC, I, and H mean values were 0.2502, 0.2027, 0.3815, and 0.2680, respectively. PCA analysis classified various provenances in QLD into two categories (G1 and G3). The genetic diversity of G3 was higher than that of G2. The results of genetic differentiation (Fst) showed that PNG region was divided into two groups (PNG1 and PNG2), the Fst (0.172) between QLD and PNG2 region was higher than QLD and PNG1, and the Fst (0.024) between IDN and PNG1 is smaller than IDN and PNG2. A Mantel test revealed a positive correlation between the genetic and geographic distance of E. pellita. This study has a certain reference value for genetic identification, germplasm preservation, and breeding of E. pellita. Also, it provides a basis for subsequent association analysis to explore excellent alleles and introduction.

Identification of novel sources of partial and incomplete hypersensitive resistance to rust and associated genomic regions in common bean

Common bean (Phaseolus vulgaris) is one of the legume crops most consumed worldwide and bean rust is one of the most severe foliar biotrophic fungal diseases impacting its production. In this work, we searched for new sources of rust resistance (Uromyces appendiculatus) in a representative collection of the Portuguese germplasm, known to have accessions with an admixed genetic background between Mesoamerican and Andean gene pools. We identified six accessions with incomplete hypersensitive resistance and 20 partially resistant accessions of Andean, Mesoamerican, and admixed origin. We detected 11 disease severity-associated single-nucleotide polymorphisms (SNPs) using a genome-wide association approach. Six of the associations were related to partial (incomplete non-hypersensitive) resistance and five to incomplete hypersensitive resistance, and the proportion of variance explained by each association varied from 4.7 to 25.2%. Bean rust severity values ranged from 0.2 to 49.1% and all the infection types were identified, reflecting the diversity of resistance mechanisms deployed by the Portuguese germplasm.The associations with U. appendiculatus partial resistance were located in chromosome Pv08, and with incomplete hypersensitive resistance in chromosomes Pv06, Pv07, and Pv08, suggesting an oligogenic inheritance of both types of resistance. A resolution to the gene level was achieved for eight of the associations. The candidate genes proposed included several resistance-associated enzymes, namely β-amylase 7, acyl-CoA thioesterase, protein kinase, and aspartyl protease. Both SNPs and candidate genes here identified constitute promising genomics targets to develop functional molecular tools to support bean rust resistance precision breeding.

Natural variation in the prolyl 4-hydroxylase gene PtoP4H9 contributes to perennial stem growth in Populus

Perennial trees must maintain stem growth throughout their entire lifespan to progressively increase in size as they age. The overarching question of the molecular mechanisms that govern stem perennial growth in trees remains largely unanswered. Here we deciphered the genetic architecture that underlies perennial growth trajectories using genome-wide association studies (GWAS) for measures of growth traits across years in a natural population of Populus tomentosa. By analyzing the stem growth trajectory, we identified PtoP4H9, encoding prolyl 4-hydroxylase 9, which is responsible for the natural variation in the growth rate of diameter at breast height (DBH) across years. Quantifying the dynamic genetic contribution of PtoP4H9 loci to stem growth showed that PtoP4H9 played a pivotal role in stem growth regulation. Spatiotemporal expression analysis showed that PtoP4H9 was highly expressed in cambium tissues of poplars of various ages. Overexpression and knockdown of PtoP4H9 revealed that it altered cell expansion to regulate cell wall modification and mechanical characteristics, thereby promoting stem growth in Populus. We showed that natural variation in PtoP4H9 occurred in a BASIC PENTACYSTEINE transcription factor PtoBPC1-binding promoter element controlling PtoP4H9 expression. The geographic distribution of PtoP4H9 allelic variation was consistent with the modes of selection among populations. Altogether, our study provides important genetic insights into dynamic stem growth in Populus, and we confirmed PtoP4H9 as a potential useful marker for breeding or genetic engineering of poplars.

Oligogenic Control of Quantitative Resistance Against Powdery Mildew Revealed in Portuguese Common Bean Germplasm

Common bean (Phaseolus vulgaris L.) is one of the most important food legumes worldwide, and its production is severely affected by fungal diseases such as powdery mildew. Portugal has a diverse germplasm, with accessions of Andean, Mesoamerican, and admixed origin, making it a valuable resource for common bean genetic studies. In this work, we evaluated the response of a Portuguese collection of 146 common bean accessions to Erysiphe diffusa infection, observing a wide range of disease severity and different levels of compatible and incompatible reactions, revealing the presence of different resistance mechanisms. We identified 11 incompletely hypersensitive resistant and 80 partially resistant accessions. We performed a genome-wide association study to clarify its genetic control, resulting in the identification of eight disease severity-associated single-nucleotide polymorphisms, spread across chromosomes Pv03, Pv09, and Pv10. Two of the associations were unique to partial resistance and one to incomplete hypersensitive resistance. The proportion of variance explained by each association varied between 15 and 86%. The absence of a major locus, together with the relatively small number of loci controlling disease severity, suggested an oligogenic inheritance of both types of resistance. Seven candidate genes were proposed, including a disease resistance protein (toll interleukin 1 receptor-nucleotide binding site-leucine-rich repeat class), an NF-Y transcription factor complex component, and an ABC-2 type transporter family protein. This work contributes with new resistance sources and genomic targets valuable to develop selection molecular tools and support powdery mildew resistance precision breeding in common bean.

Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

Single-step genome-wide association study for susceptibility to Teratosphaeria nubilosa and precocity of vegetative phase change in Eucalyptus globulus

Introduction

Mycosphaerella leaf disease (MLD) is one of the most prevalent foliar diseases of Eucalyptus globulus plantations around the world. Since resistance management strategies have not been effective in commercial plantations, breeding to develop more resistant genotypes is the most promising strategy. Available genomic information can be used to detect genomic regions associated with resistance to MLD, which could significantly speed up the process of genetic improvement.

Methods

We investigated the genetic basis of MLD resistance in a breeding population of E. globulus which was genotyped with the EUChip60K SNP array. Resistance to MLD was evaluated through resistance of the juvenile foliage, as defoliation and leaf spot severity, and through precocity of change to resistant adult foliage. Genome-wide association studies (GWAS) were carried out applying four Single-SNP models, a Genomic Best Linear Unbiased Prediction (GBLUP-GWAS) approach, and a Single-step genome-wide association study (ssGWAS).

Results

The Single-SNP (model K) and GBLUP-GWAS models detected 13 and 16 SNP-trait associations in chromosomes 2, 3 y 11; whereas the ssGWAS detected 66 SNP-trait associations in the same chromosomes, and additional significant SNP-trait associations in chromosomes 5 to 9 for the precocity of phase change (proportion of adult foliage). For this trait, the two main regions in chromosomes 3 and 11 were identified for the three approaches. The SNPs identified in these regions were positioned near the key miRNA genes, miR156.5 and miR157.4, which have a main role in the regulation of the timing of vegetative change, and also in the response to environmental stresses in plants.

Discussion

Our results demonstrated that ssGWAS was more powerful in detecting regions that affect resistance than conventional GWAS approaches. Additionally, the results suggest a polygenic genetic architecture for the heteroblastic transition in E. globulus and identified useful SNP markers for the development of marker-assisted selection strategies for resistance to MLD.

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes

Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.

Haplotype mining panel for genetic dissection and breeding in Eucalyptus

To improve our understanding of genetic mechanisms underlying complex traits in plants, a comprehensive analysis of gene variants is required. Eucalyptus is an important forest plantation genus that is highly outbred. Trait dissection and molecular breeding in eucalypts currently relies on biallelic single-nucleotide polymorphism (SNP) markers. These markers fail to capture the large amount of haplotype diversity in these species, and thus multi-allelic markers are required. We aimed to develop a gene-based haplotype mining panel for Eucalyptus species. We generated 17 999 oligonucleotide probe sets for targeted sequencing of selected regions of 6293 genes implicated in growth and wood properties, pest and disease resistance, and abiotic stress responses. We identified and phased 195 834 SNPs using a read-based phasing approach to reveal SNP-based haplotypes. A total of 8915 target regions (at 4637 gene loci) passed tests for Mendelian inheritance. We evaluated the haplotype panel in four Eucalyptus species (E. grandis, E. urophylla, E. dunnii and E. nitens) to determine its ability to capture diversity across eucalypt species. This revealed an average of 3.13-4.52 haplotypes per target region in each species, and 33.36% of the identified haplotypes were shared by at least two species. This haplotype mining panel will enable the analysis of haplotype diversity within and between species, and provide multi-allelic markers that can be used for genome-wide association studies and gene-based breeding approaches.

Genetic associations with resistance to Meloidogyne enterolobii in guava (Psidium sp.) using cross-genera SNPs and comparative genomics to Eucalyptus highlight evolutionary conservation across the Myrtaceae

Tropical fruit tree species constitute a yet untapped supply of outstanding diversity of taste and nutritional value, barely developed from the genetics standpoint, with scarce or no genomic resources to tackle the challenges arising in modern breeding practice. We generated a de novo genome assembly of the Psidium guajava, the super fruit “apple of the tropics”, and successfully transferred 14,268 SNP probesets from Eucalyptus to Psidium at the nucleotide level, to detect genomic loci linked to resistance to the root knot nematode (RKN) Meloidogyne enterolobii derived from the wild relative P. guineense. Significantly associated loci with resistance across alternative analytical frameworks, were detected at two SNPs on chromosome 3 in a pseudo-assembly of Psidium guajava genome built using a syntenic path approach with the Eucalyptus grandis genome to determine the order and orientation of the contigs. The P. guineense-derived resistance response to RKN and disease onset is conceivably triggered by mineral nutrients and phytohormone homeostasis or signaling with the involvement of the miRNA pathway. Hotspots of mapped resistance quantitative trait loci and functional annotation in the same genomic region of Eucalyptus provide further indirect support to our results, highlighting the evolutionary conservation of genomes across genera of Myrtaceae in the adaptation to pathogens. Marker assisted introgression of the resistance loci mapped should accelerate the development of improved guava cultivars and hybrid rootstocks.

Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection

The ecological and economic importance of forest trees is evident and their survival is necessary to provide the raw materials needed for wood and paper industries, to preserve the diversity of associated animal and plant species, to protect water and soil, and to regulate climate. Forest trees are threatened by anthropogenic factors and biotic and abiotic stresses. Various diseases, including those caused by fungal pathogens, are one of the main threats to forest trees that lead to their dieback. Genomics and transcriptomics studies using next-generation sequencing (NGS) methods can help reveal the architecture of resistance to various diseases and exploit natural genetic diversity to select elite genotypes with high resistance to diseases. In the last two decades, QTL mapping studies led to the identification of QTLs related to disease resistance traits and gene families and transcription factors involved in them, including NB-LRR, WRKY, bZIP and MYB. On the other hand, due to the limitation of recombination events in traditional QTL mapping in families derived from bi-parental crosses, genome-wide association studies (GWAS) that are based on linkage disequilibrium (LD) in unstructured populations overcame these limitations and were able to narrow down QTLs to single genes through genotyping of many individuals using high-throughput markers. Association and QTL mapping studies, by identifying markers closely linked to the target trait, are the prerequisite for marker-assisted selection (MAS) and reduce the breeding period in perennial forest trees. The genomic selection (GS) method uses the information on all markers across the whole genome, regardless of their significance for development of a predictive model for the performance of individuals in relation to a specific trait. GS studies also increase gain per unit of time and dramatically increase the speed of breeding programs. This review article is focused on the progress achieved in the field of dissecting forest tree disease resistance architecture through GWAS and QTL mapping studies. Finally, the merit of methods such as GS in accelerating forest tree breeding programs is also discussed.

Genetic control of the operculum and capsule morphology of Eucalyptus globulus

BACKGROUND AND AIMS

The petaline operculum that covers the inner whorls until anthesis and the woody capsule that develops after fertilization are reproductive structures of eucalypts that protect the flower and seeds. Although they are distinct organs, they both develop from flower buds and this common ontogeny suggests shared genetic control. In Eucalyptus globulus their morphology is variable and we aimed to identify the quantitative trait loci (QTL) underlying this variation and determine whether there is common genetic control of these ecologically and taxonomically important reproductive structures.

METHODS

Samples of opercula and capsules were collected from 206 trees that belong to a large outcrossed F2E. globulus mapping population. The morphological variation in these structures was characterized by measuring six operculum and five capsule traits. QTL analysis was performed using these data and a linkage map consisting of 480 markers.

KEY RESULTS

A total of 27 QTL were detected for operculum traits and 28 for capsule traits, with the logarithm of odds ranging from 2.8 to 11.8. There were many co-located QTL associated with operculum or capsule traits, generally reflecting allometric relationships. A key finding was five genomic regions where co-located QTL affected both operculum and capsule morphology, and the overall trend for these QTL was to affect elongation of both organs. Some of these QTL appear to have a significant effect on the phenotype, with the strongest QTL explaining 26.4 % of the variation in operculum shape and 16.4 % in capsule shape. Flower bud measurements suggest the expression of these QTL starts during bud development. Several candidate genes were found associated with the QTL and their putative function is discussed.

CONCLUSIONS

Variation in both operculum and capsule traits in E. globulus is under strong genetic control. Our results suggest that these reproductive structures share a common genetic pathway during flower bud development.

Integrating genome-wide association mapping of additive and dominance genetic effects to improve genomic prediction accuracy in Eucalyptus

Genome-wide association studies (GWAS) is a powerful and widely used approach to decipher the genetic control of complex traits. Still, a significant challenge for dissecting quantitative traits in forest trees is statistical power. This study uses a population consisting of 1,123 samples derived from two successive generations of crosses between Eucalyptus grandis (W. Hill) and E. urophylla (S.T. Blake). All samples have been phenotyped for growth and wood property traits and genotyped using the EuChip60K chip, yielding 37,832 informative single nucleotide polymorphisms (SNPs). We use multi-locus GWAS models to assess additive and dominance effects to identify markers associated with growth and wood property traits in the eucalypt hybrids. Additive and dominance association models identified 78 and 82 significant SNPs across all traits, respectively, which captured between 39 and 86% of the genomic-based heritability. We also used SNPs identified from the GWAS and SNPs using less stringent significance thresholds to evaluate predictive abilities in a genomic selection framework. Genomic selection models based on the top 1% SNPs captured a substantially greater proportion of the genetic variance of traits compared with when we used all SNPs for model training. The prediction ability of estimated breeding values improved significantly for all traits when using either the top 1% SNPs or SNPs identified using a relaxed p value threshold (p < 10^-3 ). This study also highlights the added value of incorporating dominance effects for identifying genomic regions controlling growth traits in trees. Moreover, integrating GWAS results into genomic selection method provides enhanced power relative to discrete associations for identifying genomic variation potentially valuable for forest tree breeding.

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.

Genome Wide Association Study Identifies Candidate Genes Related to the Earlywood Tracheid Properties in Picea crassifolia Kom

Picea crassifolia Kom. is one of the timber and ecological conifers in China and its wood tracheid traits directly affect wood formation and adaptability under harsh environment. Molecular studies on P. crassifolia remain inadequate because relatively few genes have been associated with these traits. To identify markers and candidate genes that can potentially be used for genetic improvement of wood tracheid traits, we examined 106 clones of P. crassifolia, and investigated phenotypic data for 14 wood tracheid traits before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome wide association study (GWAS). Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the studied traits. We developed 4,058,883 SLAF-tags and 12,275,765 SNP loci, and our analyses identified a total of 96 SNP loci that showed significant correlations with three earlywood tracheid traits using a mixed linear model (MLM). Next, candidate genes were screened in the 100 kb zone (50 kb upstream, 50 kb downstream) of each of the SNP loci, whereby 67 candidate genes were obtained in earlywood tracheid traits, including 34 genes of known function and 33 genes of unknown function. We provide the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in wood traits improvement and candidate genes for the development of earlywood tracheid in P. crassifolia.

A transcriptome-based association study of growth, wood quality, and oleoresin traits in a slash pine breeding population

Slash pine (Pinus elliottii Engelm.) is an important timber and resin species in the United States, China, Brazil and other countries. Understanding the genetic basis of these traits will accelerate its breeding progress. We carried out a genome-wide association study (GWAS), transcriptome-wide association study (TWAS) and weighted gene co-expression network analysis (WGCNA) for growth, wood quality, and oleoresin traits using 240 unrelated individuals from a Chinese slash pine breeding population. We developed high quality 53,229 single nucleotide polymorphisms (SNPs). Our analysis reveals three main results: (1) the Chinese breeding population can be divided into three genetic groups with a mean inbreeding coefficient of 0.137; (2) 32 SNPs significantly were associated with growth and oleoresin traits, accounting for the phenotypic variance ranging from 12.3% to 21.8% and from 10.6% to 16.7%, respectively; and (3) six genes encoding PeTLP, PeAP2/ERF, PePUP9, PeSLP, PeHSP, and PeOCT1 proteins were identified and validated by quantitative real time polymerase chain reaction for their association with growth and oleoresin traits. These results could be useful for tree breeding and functional studies in advanced slash pine breeding program.

Slash pine is an important source of original timber and resin production on commercial forest plantations. It is necessary to implement precise breeding strategies to improve timber quality and resin yield. However, little is known about the species’ molecular genetic basis. Using a transcriptome dataset with sequencing from 240 individuals in the slash pine population, we combined multiple approaches (based on gene variation, expression variation and co-expression network) to dissect the genetic structure for slash pine major breeding traits. We found that the research population could be divided into three genetic groups with a mean heterozygosity of 0.2246. We also found that six genes with important functions in slash pine resin synthesis and timber formation through association studies. Four new SNPs associatation with the average ring width were also discovered. Our results provide new insights into the molecular genetic basis of important traits in slash pine and provide a comprehensive method for association analyses of conifer tree species with large genome.

Portuguese Common Bean Natural Variation Helps to Clarify the Genetic Architecture of the Legume's Nutritional Composition and Protein Quality

Common bean is a nutritious food legume widely appreciated by consumers worldwide. It is a staple food in Latin America, and a component of the Mediterranean diet, being an affordable source of protein with high potential as a gourmet food. Breeding for nutritional quality, including both macro and micronutrients, and meeting organoleptic consumers' preferences is a difficult task which is facilitated by uncovering the genetic basis of related traits. This study explored the diversity of 106 Portuguese common bean accessions, under two contrasting environments, to gain insight into the genetic basis of nutritional composition (ash, carbohydrates, fat, fiber, moisture, protein, and resistant starch contents) and protein quality (amino acid contents and trypsin inhibitor activity) traits through a genome-wide association study. Single-nucleotide polymorphism-trait associations were tested using linear mixed models accounting for the accessions' genetic relatedness. Mapping resolution to the gene level was achieved in 56% of the cases, with 102 candidate genes proposed for 136 genomic regions associated with trait variation. Only one marker-trait association was stable across environments, highlighting the associations' environment-specific nature and the importance of genotype × environment interaction for crops' local adaptation and quality. This study provides novel information to better understand the molecular mechanisms regulating the nutritional quality in common bean and promising molecular tools to aid future breeding efforts to answer consumers' concerns.

Genetic basis of growth, spring phenology, and susceptibility to biotic stressors in maritime pine

Forest ecosystems are increasingly challenged by extreme events, for example, drought, storms, pest attacks, and fungal pathogen outbreaks, causing severe ecological and economic losses. Understanding the genetic basis of adaptive traits in tree species is of key importance to preserve forest ecosystems, as genetic variation in a trait (i.e., heritability) determines its potential for human-mediated or evolutionary change. Maritime pine (Pinus pinaster Aiton), a conifer widely distributed in southwestern Europe and northwestern Africa, grows under contrasted environmental conditions promoting local adaptation. Genetic variation at adaptive phenotypes, including height, spring phenology, and susceptibility to two fungal pathogens (Diplodia sapinea and Armillaria ostoyae) and an insect pest (Thaumetopoea pityocampa), was assessed in a range-wide clonal common garden of maritime pine. Broad-sense heritability was significant for height (0.219), spring phenology (0.165-0.310), and pathogen susceptibility (necrosis length caused by D. sapinea, 0.152; and by A. ostoyae, 0.021, measured on inoculated, excised branches under controlled conditions), but not for pine processionary moth incidence in the common garden. The correlations of trait variation among populations revealed contrasting trends for pathogen susceptibility to D. sapinea and A. ostoyae with respect to height. Taller trees showed longer necrosis length caused by D. sapinea while shorter trees were more affected by A. ostoyae. Moreover, maritime pine populations from areas with high summer temperatures and frequent droughts were less susceptible to D. sapinea but more susceptible to A. ostoyae. Finally, an association study using 4227 genome-wide SNPs revealed several loci significantly associated with each trait (range of 3-26), including a possibly disease-induced translation initiation factor, eIF-5, associated with needle discoloration caused by D. sapinea. This study provides important insights to develop genetic conservation and breeding strategies integrating species responses to biotic stressors.

Targeted re-sequencing and genome-wide association analysis for wood property traits in breeding population of Eucalyptus tereticornis × E. grandis

Globally, Eucalyptus plantations occupy 22 million ha area and is one of the preferred hardwood species due to their short rotation, rapid growth, adaptability and wood properties. In this study, we present results of GWAS in parents and 100 hybrids of Eucalyptus tereticornis × E. grandis using 762 genes presumably involved in wood formation. Comparative analysis between parents predicted 32,202 polymorphic SNPs with high average read depth of 269-562× per individual per nucleotide. Seventeen wood related traits were phenotyped across three diverse environments and GWAS was conducted using 13,610 SNPs. A total of 45 SNP-trait associations were predicted across two locations. Seven large effect markers were identified which explained more than 80% of phenotypic variation for fibre area. This study has provided an array of candidate genes which may govern fibre morphology in this genus and has predicted potential SNPs which can guide future breeding programs in tropical Eucalyptus.

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

Integrative Pre-Breeding for Biotic Resistance in Forest Trees

Climate change is unleashing novel biotic antagonistic interactions for forest trees that may jeopardize populations' persistence. Therefore, this review article envisions highlighting major opportunities from ecological evolutionary genomics to assist the identification, conservation, and breeding of biotic resistance in forest tree species. Specifically, we first discuss how assessing the genomic architecture of biotic stress resistance enables us to recognize a more polygenic nature for a trait typically regarded Mendelian, an expectation from the Fisherian runaway pathogen-host concerted arms-race evolutionary model. Secondly, we outline innovative pipelines to capture and harness natural tree pre-adaptations to biotic stresses by merging tools from the ecology, phylo-geography, and omnigenetics fields within a predictive breeding platform. Promoting integrative ecological genomic studies promises a better understanding of antagonistic co-evolutionary interactions, as well as more efficient breeding utilization of resistant phenotypes.

Regional Heritability Mapping of Quantitative Trait Loci Controlling Traits Related to Growth and Productivity in Popcorn (Zea mays L.)

The method of regional heritability mapping (RHM) has become an important tool in the identification of quantitative trait loci (QTLs) controlling traits of interest in plants. Here, RHM was first applied in a breeding population of popcorn, to identify the QTLs and candidate genes involved in grain yield, plant height, kernel popping expansion, and first ear height, as well as determining the heritability of each significant genomic region. The study population consisted of 98 S1 families derived from the 9th recurrent selection cycle (C-9) of the open-pollinated variety UENF-14, which were genetically evaluated in two environments (ENV1 and ENV2). Seventeen and five genomic regions were mapped by the RHM method in ENV1 and ENV2, respectively. Subsequent genome-wide analysis based on the reference genome B73 revealed associations with forty-six candidate genes within these genomic regions, some of them are considered to be biologically important due to the proteins that they encode. The results obtained by the RHM method have the potential to contribute to knowledge on the genetic architecture of the growth and yield traits of popcorn, which might be used for marker-assisted selection in breeding programs.

Dissection of Allelic Variation Underlying Floral and Fruit Traits in Flare Tree Peony (Paeonia rockii) Using Association Mapping

Allelic variation in floral quantitative traits, including the elements of flowers and fruits, is caused by extremely complex regulatory processes. In the genetic improvement of flare tree peony (Paeonia rockii), a unique ornamental and edible oil woody species in the genus Paeonia, a better understanding of the genetic composition of these complex traits related to flowers and fruits is needed. Therefore, we investigated the genetic diversity and population structure of 160 P. rockii accessions and conducted single-marker association analysis for 19 quantitative flower and fruit traits using 81 EST-SSR markers. The results showed that the population had a high phenotypic diversity (coefficients of variation, 11.87-110.64%) and a high level of genetic diversity (mean number of alleles, N _A = 6.09). These accessions were divided into three subgroups by STRUCTURE analysis and a neighbor-joining tree. Furthermore, we also found a low level of linkage disequilibrium between these EST-SSRs and, by single-marker association analysis, identified 134 significant associations, including four flower traits with 11 EST-SSRs and 10 fruit traits with 32 EST-SSRs. Finally, based on the sequence alignment of the associated markers, P280, PS2, PS12, PS27, PS118, PS131, and PS145 may be considered potential loci to increase the yield of flare tree peony. These results laid the foundation for further analysis of the genetic structure of some key traits in P. rockii and had an obvious potential application value in marker-assisted selection breeding.

Rapid Identification of QTL for Mesocotyl Length in Rice Through Combining QTL-seq and Genome-Wide Association Analysis

Mesocotyl is a crucial organ for pushing buds out of soil, which plays a vital role in seedling emergence and establishment in direct-seeded rice. Thus, the identification of quantitative trait loci (QTL) associated with mesocotyl length (ML) could accelerate genetic improvement of rice for direct seeding cultivation. In this study, QTL sequencing (QTL-seq) applied to 12 F₂ populations identified 14 QTL for ML, which were distributed on chromosomes 1, 3, 4, 5, 6, 7, and 9 based on the Δ(SNP-index) or G-value statistics. Besides, a genome-wide association study (GWAS) using two diverse panels identified five unique QTL on chromosomes 1, 8, 9, and 12 (2), respectively, explaining 5.3–14.6% of the phenotypic variations. Among these QTL, seven were in the regions harboring known genes or QTLs, whereas the other 10 were potentially novel. Six of the QTL were stable across two or more populations. Eight high-confidence candidate genes related to ML were identified for the stable loci based on annotation and expression analyses. Association analysis revealed that two PCR gel-based markers for the loci co-located by QTL-seq and GWAS, Indel-Chr1:18932318 and Indel-Chr7:15404166 for loci qML1.3 and qML7.2 respectively, were significantly associated with ML in a collection of 140 accessions and could be used as breeder-friendly markers in further breeding.

Pests, diseases, and aridity have shaped the genome of Corymbia citriodora

Corymbia citriodora is a member of the predominantly Southern Hemisphere Myrtaceae family, which includes the eucalypts (Eucalyptus, Corymbia and Angophora; ~800 species). Corymbia is grown for timber, pulp and paper, and essential oils in Australia, South Africa, Asia, and Brazil, maintaining a high-growth rate under marginal conditions due to drought, poor-quality soil, and biotic stresses. To dissect the genetic basis of these desirable traits, we sequenced and assembled the 408 Mb genome of Corymbia citriodora, anchored into eleven chromosomes. Comparative analysis with Eucalyptus grandis reveals high synteny, although the two diverged approximately 60 million years ago and have different genome sizes (408 vs 641 Mb), with few large intra-chromosomal rearrangements. C. citriodora shares an ancient whole-genome duplication event with E. grandis but has undergone tandem gene family expansions related to terpene biosynthesis, innate pathogen resistance, and leaf wax formation, enabling their successful adaptation to biotic/abiotic stresses and arid conditions of the Australian continent.

Genetic Diversity and Association Analysis among Germplasms of Diospyros kaki in Zhejiang Province Based on SSR Markers

In subtropical to temperate regions, persimmon (Diospyros kaki Thunb.) is an economically important fruit crop cultivated for its edible fruits. Persimmons are distributed abundantly and widely in Zhejiang Province, representing a valuable resource for the breeding of new cultivars and studying the origin and evolution of persimmon. In this study, we elucidated the genetic structures and diversity patterns of 179 persimmon germplasms from 16 different ecologic populations in Zhejiang Province based on the analysis of 17 SSR markers. The results show that there was a medium degree of genetic diversity for persimmon found in Zhejiang Province. With the exception of the Tiantai Mountain and Xin’an River populations, we found extensive gene exchange had occurred among the other populations. The 179 D. kaki germplasms from the 16 populations could be separated into three distinct clusters (I, II, and III) with a higher mean pairwise genetic differentiation index (FST) (0.2714). Nearly all samples of Cluster-I were distributed inland. Cluster-II and Cluster-III contained samples that were widely distributed throughout Zhejiang Province including all samples from the coastal populations and the Northeast Plain populations. In addition, we performed association mapping with nine traits (fruit crude fiber content, fruit calcium content, fruit water content, fruit longitudinal diameter, fruit aspect ratio, seed width, seed length, leaf aspect ratio, and number of lateral veins) using these markers. This led to the identification of 13 significant marker–trait associations (MTAs; p < 0.00044, 0.1/228) using a general linear model, of which, six MTAs with a correlation coefficient (R2) >10% were consistently represented in the general linear model with p < 0.00044 in the two models. The genetic structures and diversity patterns of the persimmon germplasms revealed in this study will provide a reference for the efficient conservation and further utilization of persimmon germplasms. The MTAs identified in this study will be useful for future marker-assisted breeding of persimmon.

Evolution and Adaptation of Forest and Crop Pathogens in the Anthropocene

Anthropocene marks the era when human activity is making a significant impact on earth, its ecological and biogeographical systems. The domestication and intensification of agricultural and forest production systems have had a large impact on plant and tree health. Some pathogens benefitted from these human activities and have evolved and adapted in response to the expansion of crop and forest systems, resulting in global outbreaks. Global pathogen genomics data including population genomics and high-quality reference assemblies are crucial for understanding the evolution and adaptation of pathogens. Crops and forest trees have remarkably different characteristics, such as reproductive time and the level of domestication. They also have different production systems for disease management with more intensive management in crops than forest trees. By comparing and contrasting results from pathogen population genomic studies done on widely different agricultural and forest production systems, we can improve our understanding of pathogen evolution and adaptation to different selection pressures. We find that in spite of these differences, similar processes such as hybridization, host jumps, selection, specialization, and clonal expansion are shaping the pathogen populations in both crops and forest trees. We propose some solutions to reduce these impacts and lower the probability of global pathogen outbreaks so that we can envision better management strategies to sustain global food production as well as ecosystem services.

Bridging the genotype-phenotype gap for a Mediterranean pine by semi-automatic crown identification and multispectral imagery

Progress in high-throughput phenotyping and genomics provides the potential to understand the genetic basis of plant functional differentiation. We developed a semi-automatic methodology based on unmanned aerial vehicle (UAV) imagery for deriving tree-level phenotypes followed by genome-wide association study (GWAS). An RGB-based point cloud was used for tree crown identification in a common garden of Pinus halepensis in Spain. Crowns were combined with multispectral and thermal orthomosaics to retrieve growth traits, vegetation indices and canopy temperature. Thereafter, GWAS was performed to analyse the association between phenotypes and genomic variation at 235 single nucleotide polymorphisms (SNPs). Growth traits were associated with 12 SNPs involved in cellulose and carbohydrate metabolism. Indices related to transpiration and leaf water content were associated with six SNPs involved in stomata dynamics. Indices related to leaf pigments and leaf area were associated with 11 SNPs involved in signalling and peroxisome metabolism. About 16-20% of trait variance was explained by combinations of several SNPs, indicating polygenic control of morpho-physiological traits. Despite a limited availability of markers and individuals, this study is provides a successful proof-of-concept for the combination of high-throughput UAV-based phenotyping with cost-effective genotyping to disentangle the genetic architecture of phenotypic variation in a widespread conifer.

Genome-Wide Association Studies Detect Multiple QTLs for Productivity in Mesoamerican Diversity Panel of Common Bean Under Drought Stress

Drought stress is an important abiotic factor limiting common bean yield, with great impact on the production worldwide. Understanding the genetic basis regulating beans' yield and seed weight (SW) is a fundamental prerequisite for the development of superior cultivars. The main objectives of this work were to conduct genome-wide marker discovery by genotyping a Mesoamerican panel of common bean germplasm, containing cultivated and landrace accessions of broad origin, followed by the identification of genomic regions associated with productivity under two water regimes using different genome-wide association study (GWAS) approaches. A total of 11,870 markers were genotyped for the 339 genotypes, of which 3,213 were SilicoDArT and 8,657 SNPs derived from DArT and CaptureSeq. The estimated linkage disequilibrium extension, corrected for structure and relatedness (r ² _sv ), was 98.63 and 124.18 kb for landraces and breeding lines, respectively. Germplasm was structured into landraces and lines/cultivars. We carried out GWASs for 100-SW and yield in field environments with and without water stress for 3 consecutive years, using single-, segment-, and gene-based models. Higher number of associations at high stringency was identified for the SW trait under irrigation, totaling ∼185 QTLs for both single- and segment-based, whereas gene-based GWASs showed ∼220 genomic regions containing ∼650 genes. For SW under drought, 18 QTLs were identified for single- and segment-based and 35 genes by gene-based GWASs. For yield, under irrigation, 25 associations were identified, whereas under drought the total was 10 using both approaches. In addition to the consistent associations detected across experiments, these GWAS approaches provided important complementary QTL information (∼221 QTLs; 650 genes; r ² from 0.01% to 32%). Several QTLs were mined within or near candidate genes playing significant role in productivity, providing better understanding of the genetic mechanisms underlying these traits and making available molecular tools to be used in marker-assisted breeding. The findings also allowed the identification of genetic material (germplasm) with better yield performance under drought, promising to a common bean breeding program. Finally, the availability of this highly diverse Mesoamerican panel is of great scientific value for the analysis of any relevant traits in common bean.

A Genome-Wide Association Study for Resistance to the Insect Pest Leptocybe invasa in Eucalyptus grandis Reveals Genomic Regions and Positional Candidate Defense Genes

The galling insect, Leptocybe invasa, causes significant losses in plantations of various Eucalyptus species and hybrids, threatening its economic viability. We applied a genome-wide association study (GWAS) to identify single-nucleotide polymorphism (SNP) markers associated with resistance to L. invasa. A total of 563 insect-challenged Eucalyptus grandis trees, from 61 half-sib families, were genotyped using the EUChip60K SNP chip, and we identified 15,445 informative SNP markers in the test population. Multi-locus mixed-model (MLMM) analysis identified 35 SNP markers putatively associated with resistance to L. invasa based on four discreet classes of insect damage scores: (0) not infested, (1) infested showing evidence of oviposition but no gall development, (2) infested with galls on leaves, midribs or petioles and (3) stunting and lethal gall formation. MLMM analysis identified three associated genomic regions on chromosomes 3, 7 and 8 jointly explaining 17.6% of the total phenotypic variation. SNP analysis of a validation population of 494 E. grandis trees confirmed seven SNP markers that were also detected in the initial association analysis. Based on transcriptome profiles of resistant and susceptible genotypes from an independent experiment, we identified several putative candidate genes in associated genomic loci including Nucleotide-binding ARC- domain (NB-ARC) and toll-interleukin-1-receptor-Nucleotide binding signal- Leucine rich repeat (TIR-NBS-LRR) genes. Our results suggest that Leptocybe resistance in E. grandis may be influenced by a few large-effect loci in combination with minor effect loci segregating in our test and validation populations.

The genetics of exapted resistance to two exotic pathogens in pedunculate oak

Exotic pathogens cause severe damage in natural populations in the absence of coevolutionary dynamics with their hosts. However, some resistance to such pathogens may occur in naive populations. The objective of this study was to investigate the genetics of this so-called 'exapted' resistance to two pathogens of Asian origin (Erysiphe alphitoides and Phytophthora cinnamomi) in European oak. Host-pathogen compatibility was assessed by recording infection success and pathogen growth in a full-sib family of Quercus robur under controlled and natural conditions. Two high-resolution genetic maps anchored on the reference genome were used to study the genetic architecture of resistance and to identify positional candidate genes. Two genomic regions, each containing six strong and stable quantitative trait loci (QTLs) accounting for 12-19% of the phenotypic variation, were mainly associated with E. alphitoides infection. Candidate genes, especially genes encoding receptor-like-kinases and galactinol synthases, were identified in these regions. The three QTLs associated with P. cinnamomi infection did not colocate with QTLs found for E. alphitoides. These findings provide evidence that exapted resistance to E. alphitoides and P. cinnamomi is present in Q. robur and suggest that the underlying molecular mechanisms involve genes encoding proteins with extracellular signaling functions.

Natural Variation in Portuguese Common Bean Germplasm Reveals New Sources of Resistance Against Fusarium oxysporum f. sp. phaseoli and Resistance-Associated Candidate Genes

Common bean (Phaseolus vulgaris) is one of the most consumed legume crops in the world, and Fusarium wilt, caused by the fungus Fusarium oxysporum f. sp. phaseoli, is one of the major diseases affecting its production. Portugal holds a very promising common bean germplasm with an admixed genetic background that may reveal novel genetic resistance combinations between the original Andean and Mesoamerican gene pools. To identify new sources of Fusarium wilt resistance and detect resistance-associated single-nucleotide polymorphisms (SNPs), we explored, for the first time, a diverse collection of the underused Portuguese common bean germplasm by using genome-wide association analyses. The collection was evaluated for Fusarium wilt resistance under growth chamber conditions, with the highly virulent F. oxysporum f. sp. phaseoli strain FOP-SP1 race 6. Fourteen of the 162 Portuguese accessions evaluated were highly resistant and 71 intermediate. The same collection was genotyped with DNA sequencing arrays, and SNP-resistance associations were tested via a mixed linear model accounting for the genetic relatedness between accessions. The results from the association mapping revealed nine SNPs associated with resistance on chromosomes Pv04, Pv05, Pv07, and Pv08, indicating that Fusarium wilt resistance is under oligogenic control. Putative candidate genes related to phytoalexin biosynthesis, hypersensitive response, and plant primary metabolism were identified. The results reported here highlight the importance of exploring underused germplasm for new sources of resistance and provide new genomic targets for the development of functional markers to support selection in future disease resistance breeding programs.

Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados

Shorea platyclados (Dark Red Meranti) is a commercially important timber tree species in Southeast Asia. However, its stocks have dramatically declined due, inter alia, to excessive logging, insufficient natural regeneration and a slow recovery rate. Thus, there is a need to promote enrichment planting and develop effective technique to support its rehabilitation and improve timber production through implementation of Genome-Wide Association Studies (GWAS) and Genomic Selection (GS). To assist such efforts, plant materials were collected from a half-sib progeny population in Sari Bumi Kusuma forest concession, Kalimantan, Indonesia. Using 5900 markers in sequences obtained from 356 individuals, we detected high linkage disequilibrium (LD) extending up to >145 kb, suggesting that associations between phenotypic traits and markers in LD can be more easily and feasibly detected with GWAS than with analysis of quantitative trait loci (QTLs). However, the detection power of GWAS seems low, since few single nucleotide polymorphisms linked to any focal traits were detected with a stringent false discovery rate, indicating that the species’ phenotypic traits are mostly under polygenic quantitative control. Furthermore, Machine Learning provided higher prediction accuracies than Bayesian methods. We also found that stem diameter, branch diameter ratio and wood density were more predictable than height, clear bole, branch angle and wood stiffness traits. Our study suggests that GS has potential for improving the productivity and quality of S. platyclados, and our genomic heritability estimates may improve the selection of traits to target in future breeding of this species.

Genome-wide association study identified novel candidate loci affecting wood formation in Norway spruce

Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics underlying important wood quality traits in the species. We performed a functional genome-wide association study (GWAS) of 17 wood traits in Norway spruce using 178 101 single nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a Least Absolute Shrinkage and Selection Operator (LASSO-based) association mapping method using a functional multilocus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine a significant quantitative trait locus. The analysis provided 52 significant SNPs from 39 candidate genes, including genes previously implicated in wood formation and tree growth in spruce and other species. Our study represents a multilocus GWAS for complex wood traits in Norway spruce. The results advance our understanding of the genetics influencing wood traits and identifies candidate genes for future functional studies.

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

Terpenoid-based essential oils are economically important commodities, yet beyond their biosynthetic pathways, little is known about the genetic architecture of terpene oil yield from plants. Transport, storage, evaporative loss, transcriptional regulation and precursor competition may be important contributors to this complex trait. Here, we associate 2.39 million single nucleotide polymorphisms derived from shallow whole-genome sequencing of 468 Eucalyptus polybractea individuals with 12 traits related to the overall terpene yield, eight direct measures of terpene concentration and four biomass-related traits. Our results show that in addition to terpene biosynthesis, development of secretory cavities, where terpenes are both synthesized and stored, and transport of terpenes were important components of terpene yield. For sesquiterpene concentrations, the availability of precursors in the cytosol was important. Candidate terpene synthase genes for the production of 1,8-cineole and α-pinene, and β-pinene (which comprised > 80% of the total terpenes) were functionally characterized as a 1,8-cineole synthase and a β/α-pinene synthase. Our results provide novel insights into the genomic architecture of terpene yield and we provide candidate genes for breeding or engineering of crops for biofuels or the production of industrially valuable terpenes.

Improving genomic prediction of growth and wood traits in Eucalyptus using phenotypes from non-genotyped trees by single-step GBLUP

Genomic Best Linear Unbiased Prediction (GBLUP) in tree breeding typically only uses information from genotyped trees. However, information from phenotyped but non-genotyped trees can also be highly valuable. The single-step GBLUP approach (ssGBLUP) allows genomic prediction to take into account both genotyped and non-genotyped trees simultaneously in a single evaluation. In this study, we investigated the advantage, in terms of breeding value accuracy and bias, of including phenotypic observation from non-genotyped trees in a standard tree GBLUP evaluation. We compared the efficiency of the conventional pedigree-based (ABLUP), GBLUP and ssGBLUP approaches to evaluate eight growth and wood quality traits in a Eucalyptus hybrid population, genotyped with 33,398 single nucleotide polymorphisms (SNPs) using the EucHIP60k. Theoretical accuracies, predictive ability and bias were calculated by ten-fold cross validation on all traits. The use of additional phenotypic information from non-genotyped trees by means of ssGBLUP provided higher predictive ability (from 37% to 75%) and lower prediction bias (from 21% to 73%) for the genetic component of non-phenotyped but genotyped trees when compared to GBLUP. The increase (decrease) in the prediction accuracy (bias) became stronger as trait heritability decreased. We concluded that ssGBLUP is a promising breeding tool to improve accuracies and bias over classical GBLUP for genomic evaluation in Eucalyptus breeding practice.

Quantitative genetic parameters for growth and wood properties in Eucalyptus "urograndis" hybrid using near-infrared phenotyping and genome-wide SNP-based relationships

A thorough understanding of the heritability, genetic correlations and additive and non-additive variance components of tree growth and wood properties is a requisite for effective tree breeding. This knowledge is essential to maximize genetic gain, that is, the amount of increase in trait performance achieved annually through directional selection. Understanding the genetic attributes of traits targeted by breeding is also important to sustain decade-long genetic progress, that is, the progress made by increasing the average genetic value of the offspring as compared to that of the parental generation. In this study, we report quantitative genetic parameters for fifteen growth, wood chemical and physical traits for the world-famous Eucalyptus urograndis hybrid (E. grandis × E. urophylla). These traits directly impact the optimal use of wood for cellulose pulp, paper, and energy production. A population of 1,000 trees sampled in a progeny trial was phenotyped directly or following the development and use of near-infrared spectroscopy calibration models. Trees were genotyped with 33,398 SNPs and 24,001 DArT-seq genome-wide markers and genomic realized relationship matrices (GRM) were used for parameter estimation with an individual-tree additive-dominant mixed model. Wood chemical properties and wood density showed stronger genetic control than growth, cellulose and fiber traits. Additive effects are the main drivers of genetic variation for all traits, but dominance plays an equally or more important role for growth, singularly in this hybrid. GRM´s with >10,000 markers provided stable relationships estimates and more accurate parameters than pedigrees by capturing the full genetic relationships among individuals and disentangling the non-additive from the additive genetic component. Low correlations between growth and wood properties indicate that simultaneous selection for wood traits can be applied with minor effects on genetic gain for growth. Conversely, moderate to strong correlations between wood density and chemical traits exist, likely due to their interdependency on cell wall structure such that responses to selection will be connected for these traits. Our results illustrate the advantage of using genome-wide marker data to inform tree breeding in general and have important consequences for operational breeding of eucalypt urograndis hybrids.

The Road to Resistance in Forest Trees

In recent years, forests have been exposed to an unprecedented rise in pests and pathogens. This, coupled with the added challenge of climate change, renders forest plantation stock vulnerable to attack and severely limits productivity. Genotypes resistant to such biotic challenges are desired in plantation forestry to reduce losses. Conventional breeding has been a main avenue to obtain resistant genotypes. More recently, genetic engineering has become a viable approach to develop resistance against pests and pathogens in forest trees. Tree genomic resources have contributed to advancements in both these approaches. Genome-wide association studies and genomic selection in tree populations have accelerated breeding tools while integration of various levels of omics information facilitates the selection of candidate genes for genetic engineering. Furthermore, tree associations with non-pathogenic endophytic and subterranean microbes play a critical role in plant health and may be engineered in forest trees to improve resistance in the future. We look at recent studies in forest trees describing defense mechanisms using such approaches and propose the way forward to developing superior genotypes with enhanced resistance against biotic stress.

A Low Resolution Epistasis Mapping Approach To Identify Chromosome Arm Interactions in Allohexaploid Wheat

Epistasis is an important contributor to genetic variance. In inbred populations, pairwise epistasis is present as additive by additive interactions. Testing for epistasis presents a multiple testing problem as the pairwise search space for modest numbers of markers is large. Single markers do not necessarily track functional units of interacting chromatin as well as haplotype based methods do. To harness the power of multiple markers while minimizing the number of tests conducted, we present a low resolution test for epistatic interactions across whole chromosome arms. Epistasis covariance matrices were constructed from the additive covariances of individual chromosome arms. These covariances were subsequently used to estimate an epistatic variance parameter while correcting for background additive and epistatic effects. We find significant epistasis for 2% of the interactions tested for four agronomic traits in a winter wheat breeding population. Interactions across homeologous chromosome arms were identified, but were less abundant than other chromosome arm pair interactions. The homeologous chromosome arm pair 4BL/4DL showed a strong negative relationship between additive and interaction effects that may be indicative of functional redundancy. Several chromosome arms appeared to act as hubs in an interaction network, suggesting that they may contain important regulatory factors. The differential patterns of epistasis across different traits demonstrate that detection of epistatic interactions is robust when correcting for background additive and epistatic effects in the population. The low resolution epistasis mapping method presented here identifies important epistatic interactions with a limited number of statistical tests at the cost of low precision.

Independent and Joint-GWAS for growth traits in Eucalyptus by assembling genome-wide data for 3373 individuals across four breeding populations

Genome-wide association studies (GWAS) in plants typically suffer from limited statistical power. An alternative to the logistical and cost challenge of increasing sample sizes is to gain power by meta-analysis using information from independent studies. We carried out GWAS for growth traits with six single-marker models and regional heritability mapping (RHM) in four Eucalyptus breeding populations independently and by Joint-GWAS, using gene and segment-based models, with data for 3373 individuals genotyped with a communal EUChip60KSNP platform. While single-single nucleotide polymorphism (SNP) GWAS hardly detected significant associations at high-stringency in each population, gene-based Joint-GWAS revealed nine genes significantly associated with tree height. Associations detected using single-SNP GWAS, RHM and Joint-GWAS set-based models explained on average 3-20% of the phenotypic variance. Whole-genome regression, conversely, captured 64-89% of the pedigree-based heritability in all populations. Several associations independently detected for the same SNPs in different populations provided unprecedented GWAS validation results in forest trees. Rare and common associations were discovered in eight genes involved in cell wall biosynthesis and lignification. With the increasing adoption of genomic prediction of complex phenotypes using shared SNPs and much larger tree breeding populations, Joint-GWAS approaches should provide increasing power to pinpoint discrete associations potentially useful toward tree breeding and molecular applications.

Evolutionary and ecological functional genomics, from lab to the wild

Plant phenotypes are the result of both genetic and environmental forces that act to modulate trait expression. Over the last few years, numerous approaches in functional genomics and systems biology have led to a greater understanding of plant phenotypic variation and plant responses to the environment. These approaches, and the questions that they can address, have been loosely termed evolutionary and ecological functional genomics (EEFG), and have been providing key insights on how plants adapt and evolve. In particular, by bringing these studies from the laboratory to the field, EEFG studies allow us to gain greater knowledge of how plants function in their natural contexts.

Genome-Wide Association Studies to Improve Wood Properties: Challenges and Prospects

Wood formation is an excellent model system for quantitative trait analysis due to the strong associations between the transcriptional and metabolic traits that contribute to this complex process. Investigating the genetic architecture and regulatory mechanisms underlying wood formation will enhance our understanding of the quantitative genetics and genomics of complex phenotypic variation. Genome-wide association studies (GWASs) represent an ideal statistical strategy for dissecting the genetic basis of complex quantitative traits. However, elucidating the molecular mechanisms underlying many favorable loci that contribute to wood formation and optimizing GWAS design remain challenging in this omics era. In this review, we summarize the recent progress in GWAS-based functional genomics of wood property traits in major timber species such as Eucalyptus, Populus, and various coniferous species. We discuss several appropriate experimental designs for extensive GWAS in a given undomesticated tree population, such as omics-wide association studies and high-throughput phenotyping technologies. We also explain why more attention should be paid to rare allelic and major structural variation. Finally, we explore the potential use of GWAS for the molecular breeding of trees. Such studies will help provide an integrated understanding of complex quantitative traits and should enable the molecular design of new cultivars.

Hardwood Tree Genomics: Unlocking Woody Plant Biology

Woody perennial angiosperms (i.e., hardwood trees) are polyphyletic in origin and occur in most angiosperm orders. Despite their independent origins, hardwoods have shared physiological, anatomical, and life history traits distinct from their herbaceous relatives. New high-throughput DNA sequencing platforms have provided access to numerous woody plant genomes beyond the early reference genomes of Populus and Eucalyptus, references that now include willow and oak, with pecan and chestnut soon to follow. Genomic studies within these diverse and undomesticated species have successfully linked genes to ecological, physiological, and developmental traits directly. Moreover, comparative genomic approaches are providing insights into speciation events while large-scale DNA resequencing of native collections is identifying population-level genetic diversity responsible for variation in key woody plant biology across and within species. Current research is focused on developing genomic prediction models for breeding, defining speciation and local adaptation, detecting and characterizing somatic mutations, revealing the mechanisms of gender determination and flowering, and application of systems biology approaches to model complex regulatory networks underlying quantitative traits. Emerging technologies such as single-molecule, long-read sequencing is being employed as additional woody plant species, and genotypes within species, are sequenced, thus enabling a comparative ("evo-devo") approach to understanding the unique biology of large woody plants. Resource availability, current genomic and genetic applications, new discoveries and predicted future developments are illustrated and discussed for poplar, eucalyptus, willow, oak, chestnut, and pecan.

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

Forest tree breeding has been successful at delivering genetically improved material for multiple traits based on recurrent cycles of selection, mating, and testing. However, long breeding cycles, late flowering, variable juvenile-mature correlations, emerging pests and diseases, climate, and market changes, all pose formidable challenges. Genetic dissection approaches such as quantitative trait mapping and association genetics have been fruitless to effectively drive operational marker-assisted selection (MAS) in forest trees, largely because of the complex multifactorial inheritance of most, if not all traits of interest. The convergence of high-throughput genomics and quantitative genetics has established two new paradigms that are changing contemporary tree breeding dogmas. Genomic selection (GS) uses large number of genome-wide markers to predict complex phenotypes. It has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values. Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters' estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. In light of a recent flow of promising experimental results, here we briefly review the main concepts, analytical tools and remaining challenges that currently underlie the application of genomics data to tree breeding. With easy and cost-effective genotyping, we are now at the brink of extensive adoption of GS in tree breeding. Areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios. The buildup of phenotypic and genome-wide data across large-scale breeding populations and advances in computational prediction of discrete genomic features should also provide opportunities to enhance the application of genomics to tree breeding.

Genome-Wide Association and Regional Heritability Mapping of Plant Architecture, Lodging and Productivity in Phaseolus vulgaris

The availability of high-density molecular markers in common bean has allowed to explore the genetic basis of important complex agronomic traits with increased resolution. Genome-Wide Association Studies (GWAS) and Regional Heritability Mapping (RHM) are two analytical approaches for the detection of genetic variants. We carried out GWAS and RHM for plant architecture, lodging and productivity across two important growing environments in Brazil in a germplasm of 188 common bean varieties using DArTseq genotyping strategies. The coefficient of determination of G × E interaction (c2int ) was equal to 17, 21 and 41%, respectively for the traits architecture, lodging, and productivity. Trait heritabilities were estimated at 0.81 (architecture), 0.79 (lodging) and 0.43 (productivity), and total genomic heritability accounted for large proportions (72% to ≈100%) of trait heritability. At the same probability threshold, three marker-trait associations were detected using GWAS, while RHM detected eight QTL encompassing 145 markers along five chromosomes. The proportion of genomic heritability explained by RHM was considerably higher (35.48 to 58.02) than that explained by GWAS (28.39 to 30.37). In general, RHM accounted for larger fractions of the additive genetic variance being captured by markers effects inside the defined regions. Nevertheless, a considerable proportion of the heritability is still missing (∼42% to ∼64%), probably due to LD between markers and genes and/or rare allele variants not sampled. RHM in autogamous species had the potential to identify larger-effect QTL combining allelic variants that could be effectively incorporated into whole-genome prediction models and tracked through breeding generations using marker-assisted selection.

Regional Heritability Mapping Provides Insights into Dry Matter Content in African White and Yellow Cassava Populations

The HarvestPlus program for cassava ( Crantz) fortifies cassava with β-carotene by breeding for carotene-rich tubers (yellow cassava). However, a negative correlation between yellowness and dry matter (DM) content has been identified. We investigated the genetic control of DM in white and yellow cassava. We used regional heritability mapping (RHM) to associate DM with genomic segments in both subpopulations. Significant segments were subjected to candidate gene analysis and candidates were validated with prediction accuracies. The RHM procedure was validated via a simulation approach and revealed significant hits for white cassava on chromosomes 1, 4, 5, 10, 17, and 18, whereas hits for the yellow were on chromosome 1. Candidate gene analysis revealed genes in the carbohydrate biosynthesis pathway including plant serine-threonine protein kinases (SnRKs), UDP (uridine diphosphate)-glycosyltransferases, UDP-sugar transporters, invertases, pectinases, and regulons. Validation using 1252 unique identifiers from the SnRK gene family genome-wide recovered 50% of the predictive accuracy of whole-genome single nucleotide polymorphisms for DM, whereas validation using 53 likely genes (extracted from the literature) from significant segments recovered 32%. Genes including an acid invertase, a neutral or alkaline invertase, and a glucose-6-phosphate isomerase were validated on the basis of an a priori list for the cassava starch pathway, and also a fructose-biphosphate aldolase from the Calvin cycle pathway. The power of the RHM procedure was estimated as 47% when the causal quantitative trait loci generated 10% of the phenotypic variance (sample size = 451). Cassava DM genetics are complex and RHM may be useful for complex traits.

Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus

Background

The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses.

Results

Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000–10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study.

Conclusions

This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3920-2) contains supplementary material, which is available to authorized users.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F₂ hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.