Leandro G. Neves

A high-density gene map of loblolly pine (Pinus taeda L.) based on exome sequence capture genotyping.

Loblolly pine (Pinus taeda L.) is an economically and ecologically important conifer for which a suite of genomic resources is being generated. Despite recent attempts to sequence the large genome of conifers, their assembly and the positioning of genes remains largely incomplete. The interspecific synteny in pines suggests that a gene-based map would be useful to support genome assemblies and analysis of conifers. To establish a reference gene-based genetic map, we performed exome sequencing of 14729 genes on a mapping population of 72 haploid samples, generating a resource of 7434 sequence variants segregating for 3787 genes. Most markers are single-nucleotide polymorphisms, although short insertions/deletions and multiple nucleotide polymorphisms also were used. Marker segregation in the population was used to generate a high-density, gene-based genetic map. A total of 2841 genes were mapped to pine’s 12 linkage groups with an average of one marker every 0.58 cM. Capture data were used to detect gene presence/absence variations and position 65 genes on the map. We compared the marker order of genes previously mapped in loblolly pine and found high agreement. We estimated that 4123 genes had enough sequencing depth for reliable detection of markers, suggesting a high marker conversation rate of 92% (3787/4123). This is possible because a significant portion of the gene is captured and sequenced, increasing the chances of identifying a polymorphic site for characterization and mapping. This sub-centiMorgan genetic map provides a valuable resource for gene positioning on chromosomes and guide for the assembly of a reference pine genome.

A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus.

BackgroundTechnological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of Eucalyptus using Single Feature Polymorphism (SFP) markers.ResultsSFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. In silico validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the Eucalyptus grandis genome.ConclusionsThe Eucalyptus 1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on Eucalyptus maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species.

Discovering candidate genes that regulate resin canal number in Pinus taeda stems by integrating genetic analysis across environments, ages, and populations.

Genetically improving constitutive resin canal development in Pinus stems may enhance the capacity to synthesize terpenes for bark beetle resistance, chemical feedstocks, and biofuels. To discover genes that potentially regulate axial resin canal number (RCN), single nucleotide polymorphisms (SNPs) in 4027 genes were tested for association with RCN in two growth rings and three environments in a complex pedigree of 520 Pinus taeda individuals (CCLONES). The map locations of associated genes were compared with RCN quantitative trait loci (QTLs) in a (P. taeda × Pinus elliottii) × P. elliottii pseudo-backcross of 345 full-sibs (BC1). Resin canal number was heritable (h(2) ˜ 0.12-0.21) and positively genetically correlated with xylem growth (rg ˜ 0.32-0.72) and oleoresin flow (rg ˜ 0.15-0.51). Sixteen well-supported candidate regulators of RCN were discovered in CCLONES, including genes associated across sites and ages, unidirectionally associated with oleoresin flow and xylem growth, and mapped to RCN QTLs in BC1. Breeding is predicted to increase RCN 11% in one generation and could be accelerated with genomic selection at accuracies of 0.45-0.52 across environments. There is significant genetic variation for RCN in loblolly pine, which can be exploited in breeding for elevated terpene content.

Ultraconserved Elements Sequencing as a Low-Cost Source of Complete Mitochondrial Genomes and Microsatellite Markers in Non-Model Amniotes.

Sequence capture of ultraconserved elements (UCEs) associated with massively parallel sequencing has become a common source of nuclear data for studies of animal systematics and phylogeography. However, mitochondrial and microsatellite variation are still commonly used in various kinds of molecular studies, and probably will complement genomic data in years to come. Here we show that besides providing abundant genomic data, UCE sequencing is an excellent source of both sequences for microsatellite loci design and complete mitochondrial genomes with high sequencing depth. Identification of dozens of microsatellite loci and assembly of complete mitogenomes is exemplified here using three species of Poospiza warbling finches from southern and southeastern Brazil. This strategy opens exciting opportunities to simultaneously analyze genome-wide nuclear datasets and traditionally used mtDNA and microsatellite markers in non-model amniotes at no additional cost.

Natural Allelic Variations in Highly Polyploidy Saccharum Complex

Sugarcane (Saccharum spp.) is an important sugar and biofuel crop with high polyploid and complex genomes. The Saccharum complex, comprised of Saccharum genus and a few related genera, are important genetic resources for sugarcane breeding. A large amount of natural variation exists within the Saccharum complex. Though understanding their allelic variation has been challenging, it is critical to dissect allelic structure and to identify the alleles controlling important traits in sugarcane. To characterize natural variations in Saccharum complex, a target enrichment sequencing approach was used to assay 12 representative germplasm accessions. In total, 55,946 highly efficient probes were designed based on the sorghum genome and sugarcane unigene set targeting a total of 6 Mb of the sugarcane genome. A pipeline specifically tailored for polyploid sequence variants and genotype calling was established. BWA-mem and sorghum genome approved to be an acceptable aligner and reference for sugarcane target enrichment sequence analysis, respectively. Genetic variations including 1,166,066 non-redundant SNPs, 150,421 InDels, 919 gene copy number variations, and 1,257 gene presence/absence variations were detected. SNPs from three different callers (Samtools, Freebayes, and GATK) were compared and the validation rates were nearly 90%. Based on the SNP loci of each accession and their ploidy levels, 999,258 single dosage SNPs were identified and most loci were estimated as largely homozygotes. An average of 34,397 haplotype blocks for each accession was inferred. The highest divergence time among the Saccharum spp. was estimated as 1.2 million years ago (MYA). Saccharum spp. diverged from Erianthus and Sorghum approximately 5 and 6 MYA, respectively. The target enrichment sequencing approach provided an effective way to discover and catalog natural allelic variation in highly polyploid or heterozygous genomes.

A Consensus Genetic Map for Pinus taeda and Pinus elliottii and Extent of Linkage Disequilibrium in Two Genotype-Phenotype Discovery Populations of Pinus taeda

A consensus genetic map for Pinus taeda (loblolly pine) and Pinus elliottii (slash pine) was constructed by merging three previously published P. taeda maps with a map from a pseudo-backcross between P. elliottii and P. taeda. The consensus map positioned 3856 markers via genotyping of 1251 individuals from four pedigrees. It is the densest linkage map for a conifer to date. Average marker spacing was 0.6 cM and total map length was 2305 cM. Functional predictions of mapped genes were improved by aligning expressed sequence tags used for marker discovery to full-length P. taeda transcripts. Alignments to the P. taeda genome mapped 3305 scaffold sequences onto 12 linkage groups. The consensus genetic map was used to compare the genome-wide linkage disequilibrium in a population of distantly related P. taeda individuals (ADEPT2) used for association genetic studies and a multiple-family pedigree used for genomic selection (CCLONES). The prevalence and extent of LD was greater in CCLONES as compared to ADEPT2; however, extended LD with LGs or between LGs was rare in both populations. The average squared correlations, r2, between SNP alleles less than 1 cM apart were less than 0.05 in both populations and r2 did not decay substantially with genetic distance. The consensus map and analysis of linkage disequilibrium establish a foundation for comparative association mapping and genomic selection in P. taeda and P. elliottii.

Capturing and genotyping the genome-wide genetic diversity of trees for association mapping and genomic selection

Background Growing demand for food and fiber, and a rapidly changing climate will require that plant breeders accelerate the improvement of germplasm adapted to new sources of biotic and abiotic stress. In trees, the threat from climate change is more evident and the solutions more challenging than in any other plant species, due to the complexity and cost of breeding programs, and the long breeding cycles. Therefore, the discovery of genetic polymorphism that can be exploited for early selection of better adapted and productive individuals is essential. Quantitative trait loci (QTL) analysis provided an initial glimpse at the architecture of complex traits, but limited transferability across populations and resolution hampered the adoption of markers in tree breeding programs. Recently, association studies have become the method of choice for detection of markers implicated in trait variation, because of higher resolution, population transferability and allelic diversity captured relative to the QTL approach. However, in tree species, association studies have been largely constrained to sampling the genetic diversity in a limited fraction of the genome, and in small populations. Evidence from genome-wide association studies (GWAS) in humans and advanced crops clearly show that larger populations, and the sampling of regulatory variants and rare alleles is critical to dissect the genetic control of complex traits for markerassisted breeding (MAB). As the limitations of QTL and GWAS approaches become evident, “hybrid” intermediate strategies that combine the advantages of both methods have emerged. Notably, genomic selection has become an alternative to MAB. Genomic selection (GS), which relies on developing genome-wide marker-based models that predict the genetic value of progeny, will be particularly valuable for early selection in tree breeding programs. However, the implications of GS may also be highly valuable to identify mating designs that generate progeny with optimal allelic combinations for superior growth and wood properties, and adaptive capabilities.

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

BackgroundThe 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.ResultsPredictive 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.ConclusionsThis 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.

Targeted sequencing in the loblolly pine (Pinus taeda) megagenome by exome capture

Background An essential use of genomics is in the discovery of genes controlling complex, quantitative traits. In forestry, attempts to identify genes that regulate quantitative variation are still limited to a few Association Studies (AS) focused largely on candidate genes [1]. In most studies, few markers have been identified in association with quantitative traits. Recent advances in DNA sequencing create the potential for high-throughput SNP genotyping at low cost, by re-sequencing genomes of interest [2]. For the particular case of conifers, two obstacles remain: (i) the lack of a reference genome to align the DNA sequences and identify SNPs, and (ii) the size and complexity of the genome that hinders the de novo assembly of reads. Whereas whole-genome sequencing of a large number of conifer genotypes is still unfeasible, concentrating the sequencing on gene-rich regions is an alternative to generate markers that are more likely to capture variation associated to complex traits. Here we report our approaches to develop methods of genotyping based on whole-exome capture using in-solution target enrichment (Agilent’s SureSelect) followed by high-throughput sequencing (Illumina’s GAIIx).

Population genomics of the eastern cottonwood (Populus deltoides)

Abstract Despite its economic importance as a bioenergy crop and key role in riparian ecosystems, little is known about genetic diversity and adaptation of the eastern cottonwood (Populus deltoides). Here, we report the first population genomics study for this species, conducted on a sample of 425 unrelated individuals collected in 13 states of the southeastern United States. The trees were genotyped by targeted resequencing of 18,153 genes and 23,835 intergenic regions, followed by the identification of single nucleotide polymorphisms (SNPs). This natural P. deltoides population showed low levels of subpopulation differentiation (F ST = 0.022–0.106), high genetic diversity (θW = 0.00100, π = 0.00170), a large effective population size (N e ≈ 32,900), and low to moderate levels of linkage disequilibrium. Additionally, genomewide scans for selection (Tajimas D), subpopulation differentiation (XTX), and environmental association analyses with eleven climate variables carried out with two different methods (LFMM and BAYENV2) identified genes putatively involved in local adaptation. Interestingly, many of these genes were also identified as adaptation candidates in another poplar species, Populus trichocarpa, indicating possible convergent evolution. This study constitutes the first assessment of genetic diversity and local adaptation in P. deltoides throughout the southern part of its range, information we expect to be of use to guide management and breeding strategies for this species in future, especially in the face of climate change.