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

Xylem Transcriptome Analysis in Contrasting Wood Phenotypes of Eucalyptus urophylla × tereticornis Hybrids

An investigation of the effects of two important post-transcriptional regulatory mechanisms, gene transcription and alternative splicing (AS), on the wood formation of Eucalyptusurophylla × tereticornis, an economic tree species widely planted in southern China, was carried out. We performed RNA-seq on E. urophylla × tereticornis hybrids with highly contrasting wood basic density (BD), cellulose content (CC), hemicellulose content (HC), and lignin content (LC). Signals of strong differentially expressed genes (DEGs) and differentially spliced genes (DSGs) were detected in all four groups of wood properties, suggesting that gene transcription and selective splicing may have important regulatory roles in wood properties. We found that there was little overlap between DEGs and DSGs in groups of the same trait. Furthermore, the key DEGs and DSGs that were detected simultaneously in the four groups tended to be enriched in different Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathways, and transcription factors. These results implied that regulation of gene transcription and AS is controlled by independent regulatory systems in wood formation. Lastly, we detected transcript levels of known wood biosynthetic genes and found that 79 genes encoding mainly enzymes or proteins such as UGT, LAC, CAD, and CESA may be involved in the positive or negative regulation of wood properties. This study reveals potential molecular mechanisms that may regulate wood formation and will contribute to the genetic improvement of Eucalyptus.

Genomic studies with preselected markers reveal dominance effects influencing growth traits in Eucalyptus nitens

Genomic selection (GS) is being increasingly adopted by the tree breeding community. Most of the GS studies in trees are focused on estimating additive genetic effects. Exploiting the dominance effects offers additional opportunities to improve genetic gain. To detect dominance effects, trait-relevant markers may be important compared to nonselected markers. Here, we used preselected markers to study the dominance effects in a Eucalyptus nitens (E. nitens) breeding population consisting of open-pollinated (OP) and controlled-pollinated (CP) families. We used 8221 trees from six progeny trials in this study. Of these, 868 progeny and 255 parents were genotyped with the E. nitens marker panel. Three traits; diameter at breast height (DBH), wood basic density (DEN), and kraft pulp yield (KPY) were analyzed. Two types of genomic relationship matrices based on identity-by-state (IBS) and identity-by-descent (IBD) were tested. Performance of the genomic best linear unbiased prediction (GBLUP) models with IBS and IBD matrices were compared with pedigree-based additive best linear unbiased prediction (ABLUP) models with and without the pedigree reconstruction. Similarly, the performance of the single-step GBLUP (ssGBLUP) with IBS and IBD matrices were compared with ABLUP models using all 8221 trees. Significant dominance effects were observed with the GBLUP-AD model for DBH. The predictive ability of DBH is higher with the GBLUP-AD model compared to other models. Similarly, the prediction accuracy of genotypic values is higher with GBLUP-AD compared to the GBLUP-A model. Among the two GBLUP models (IBS and IBD), no differences were observed in predictive abilities and prediction accuracies. While the estimates of predictive ability with additive effects were similar among all four models, prediction accuracies of ABLUP were lower than the GBLUP models. The prediction accuracy of ssGBLUP-IBD is higher than the other three models while the theoretical accuracy of ssGBLUP-IBS is consistently higher than the other three models across all three groups tested (parents, genotyped, and nongenotyped). Significant inbreeding depression was observed for DBH and KPY. While there is a linear relationship between inbreeding and DBH, the relationship between inbreeding and KPY is nonlinear and quadratic. These results indicate that the inbreeding depression of DBH is mainly due to directional dominance while in KPY it may be due to epistasis. Inbreeding depression may be the main source of the observed dominance effects in DBH. The significant dominance effect observed for DBH may be used to select complementary parents to improve the genetic merit of the progeny in E. nitens.

Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus

Bellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

Miniature inverted repeat transposable elements cis-regulate circular RNA expression and promote ethylene biosynthesis, reducing heat tolerance in Populus tomentosa

Transposable elements (TEs) and their reverse complementary sequence pairs (RCPs) are enriched around loci that produce circular RNAs (circRNAs) in plants. However, the function of these TE-RCP pairs in modulating circRNA expression remains elusive. Here, we identified 4609 circRNAs in poplar (Populus tomentosa) and showed that miniature inverted repeat transposable elements (MITEs)-RCPs were enriched in circRNA flanking regions. Moreover, we used expression quantitative trait nucleotide (eQTN) mapping to decipher the cis-regulatory role of MITEs. eQTN results showed that 14 single-nucleotide polymorphisms (SNPs) were significantly associated with Circ_0000408 and Circ_0003418 levels and the lead associated SNPs were located in MITE-RCP regions, indicating that MITE-RCP sequence variations affect exon circularization. Overexpression and knockdown analysis showed that Circ_0003418 positively modulated its parental gene, which encodes the RING-type E3 ligase XBAT32, and specifically increased the expression of the PtoXBAT32.5 transcript variant, which lacks the E3 ubiquitin ligase domain. Under heat stress, PtoXBAT32.5 expression was induced with up-regulation of Circ_0003418, resulting in increased production of ethylene and peroxidation of membrane lipids. Our findings thus reveal the cis-regulatory mechanism by which a MITE-RCP pair affects circRNA abundance in poplar and indicate that Circ_0003418 is a negative regulator of poplar heat tolerance via the ubiquitin-mediated protein modification pathway.

Genomic Studies Reveal Substantial Dominant Effects and Improved Genomic Predictions in an Open-Pollinated Breeding Population of Eucalyptus pellita

Most of the genomic studies in plants and animals have used additive models for studying genetic parameters and prediction accuracies. In this study, we used genomic models with additive and nonadditive effects to analyze the genetic architecture of growth and wood traits in an open-pollinated (OP) population of Eucalyptus pellita. We used two progeny trials consisting of 5742 trees from 244 OP families to estimate genetic parameters and to test genomic prediction accuracies of three growth traits (diameter at breast height - DBH, total height - Ht and tree volume - Vol) and kraft pulp yield (KPY). From 5742 trees, 468 trees from 28 families were genotyped with 2023 pre-selected markers from candidate genes. We used the pedigree-based additive best linear unbiased prediction (ABLUP) model and two marker-based models (single-step genomic BLUP – ssGBLUP and genomic BLUP – GBLUP) to estimate the genetic parameters and compare the prediction accuracies. Analyses with the two genomic models revealed large dominant effects influencing the growth traits but not KPY. Theoretical breeding value accuracies were higher with the dominance effect in ssGBLUP model for the three growth traits. Accuracies of cross-validation with random folding in the genotyped trees have ranged from 0.60 to 0.82 in different models. Accuracies of ABLUP were lower than the genomic models. Accuracies ranging from 0.50 to 0.76 were observed for within family cross-validation predictions with low relationships between training and validation populations indicating part of the functional variation is captured by the markers through short-range linkage disequilibrium (LD). Within-family phenotype predictive abilities and prediction accuracies of genetic values with dominance effects are higher than the additive models for growth traits indicating the importance of dominance effects in predicting phenotypes and genetic values. This study demonstrates the importance of genomic approaches in OP families to study nonadditive effects. To capture the LD between markers and the quantitative trait loci (QTL) it may be important to use informative markers from candidate genes.

Identification of transcriptome-wide, nut weight-associated SNPs in Castanea crenata

Nut weight is one of the most important traits that can affect a chestnut grower's returns. Due to the long juvenile phase of chestnut trees, the selection of desired characteristics at early developmental stages represents a major challenge for chestnut breeding. In this study, we identified single nucleotide polymorphisms (SNPs) in transcriptomic regions, which were significantly associated with nut weight in chestnuts (Castanea crenata), using a genome-wide association study (GWAS). RNA-sequencing (RNA-seq) data were generated from large and small nut-bearing trees, using an Illumina HiSeq. 2000 system, and 3,271,142 SNPs were identified. A total of 21 putative SNPs were significantly associated with chestnut weight (false discovery rate [FDR] < 10-5), based on further analyses. We also applied five machine learning (ML) algorithms, support vector machine (SVM), C5.0, k-nearest neighbour (k-NN), partial least squares (PLS), and random forest (RF), using the 21 SNPs to predict the nut weights of a second population. The average accuracy of the ML algorithms for the prediction of chestnut weights was greater than 68%. Taken together, we suggest that these SNPs have the potential to be used during marker-assisted selection to facilitate the breeding of large chestnut-bearing varieties.

Co-expression network of transcription factors reveal ethylene-responsive element-binding factor as key regulator of wood phenotype in Eucalyptus tereticornis

Suitability of wood biomass for pulp production is dependent on the cellular architecture and composition of secondary cell wall. Presently, systems genetics approach is being employed to understand the molecular basis of trait variation and co-expression network analysis has enabled holistic understanding of complex trait such as secondary development. Transcription factors (TFs) are reported as key regulators of meristematic growth and wood formation. The hierarchical TF network is a multi-layered system which interacts with downstream structural genes involved in biosynthesis of cellulose, hemicelluloses and lignin. Several TFs have been associated with wood formation in tree species such as Populus, Eucalyptus, Picea and Pinus. However, TF-specific co-expression networks to understand the interaction between these regulators are not reported. In the present study, co-expression network was developed for TFs expressed during wood formation in Eucalyptus tereticornis and ethylene-responsive element-binding factor, EtERF2, was identified as the major hub transcript which co-expressed with other secondary cell wall biogenesis-specific TFs such as EtSND2, EtVND1, EtVND4, EtVND6, EtMYB70, EtGRAS and EtSCL8. This study reveals a probable role of ethylene in determining natural variation in wood properties in Eucalyptus species. Understanding this transcriptional regulation underpinning the complex bio-processing trait of wood biomass will complement the Eucalyptus breeding program through selection of industrially suitable phenotypes by marker-assisted selection.

De Novo Transcriptome Characterization of a Sterilizing Trematode Parasite (Microphallus sp.) from Two Species of New Zealand Snails

Snail-borne trematodes represent a large, diverse, and evolutionarily, ecologically, and medically important group of parasites, often imposing strong selection on their hosts and causing host morbidity and mortality. Even so, there are very few genomic and transcriptomic resources available for this important animal group. We help to fill this gap by providing transcriptome resources from trematode metacercariae infecting two congeneric snail species, Potamopyrgus antipodarum and P. estuarinus. This genus of New Zealand snails has gained prominence in large part through the development of P. antipodarum and its sterilizing trematode parasite Microphallus livelyi into a textbook model for host–parasite coevolutionary interactions in nature. By contrast, the interactions between Microphallus trematodes and P. estuarinus, an estuary-inhabiting species closely related to the freshwater P. antipodarum, are relatively unstudied. Here, we provide the first annotated transcriptome assemblies from Microphallus isolated from P. antipodarum and P. estuarinus. We also use these transcriptomes to produce genomic resources that will be broadly useful to those interested in host–parasite coevolution, local adaption, and molecular evolution and phylogenetics of this and other snail–trematode systems. Analyses of the two Microphallus transcriptomes revealed that the two trematode types are more genetically differentiated from one another than are the M. livelyi infecting different populations of P. antipodarum, suggesting that the Microphallus infecting P. estuarinus represent a distinct lineage. We also provide a promising set of candidate genes likely involved in parasitic infection and response to salinity stress.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

Application of Genomic Technologies to the Breeding of Trees

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.