Hans A. Vasquez-Gross

Decoding the massive genome of loblolly pine using haploid DNA and novel assembly strategies

BackgroundThe size and complexity of conifer genomes has, until now, prevented full genome sequencing and assembly. The large research community and economic importance of loblolly pine, Pinus taeda L., made it an early candidate for reference sequence determination.ResultsWe develop a novel strategy to sequence the genome of loblolly pine that combines unique aspects of pine reproductive biology and genome assembly methodology. We use a whole genome shotgun approach relying primarily on next generation sequence generated from a single haploid seed megagametophyte from a loblolly pine tree, 20-1010, that has been used in industrial forest tree breeding. The resulting sequence and assembly was used to generate a draft genome spanning 23.2 Gbp and containing 20.1 Gbp with an N50 scaffold size of 66.9 kbp, making it a significant improvement over available conifer genomes. The long scaffold lengths allow the annotation of 50,172 gene models with intron lengths averaging over 2.7 kbp and sometimes exceeding 100 kbp in length. Analysis of orthologous gene sets identifies gene families that may be unique to conifers. We further characterize and expand the existing repeat library based on the de novo analysis of the repetitive content, estimated to encompass 82% of the genome.ConclusionsIn addition to its value as a resource for researchers and breeders, the loblolly pine genome sequence and assembly reported here demonstrates a novel approach to sequencing the large and complex genomes of this important group of plants that can now be widely applied.

Unique Features of the Loblolly Pine (Pinus taeda L.) Megagenome Revealed Through Sequence Annotation

The largest genus in the conifer family Pinaceae is Pinus, with over 100 species. The size and complexity of their genomes (∼20–40 Gb, 2n = 24) have delayed the arrival of a well-annotated reference sequence. In this study, we present the annotation of the first whole-genome shotgun assembly of loblolly pine (Pinus taeda L.), which comprises 20.1 Gb of sequence. The MAKER-P annotation pipeline combined evidence-based alignments and ab initio predictions to generate 50,172 gene models, of which 15,653 are classified as high confidence. Clustering these gene models with 13 other plant species resulted in 20,646 gene families, of which 1554 are predicted to be unique to conifers. Among the conifer gene families, 159 are composed exclusively of loblolly pine members. The gene models for loblolly pine have the highest median and mean intron lengths of 24 fully sequenced plant genomes. Conifer genomes are full of repetitive DNA, with the most significant contributions from long-terminal-repeat retrotransposons. In depth analysis of the tandem and interspersed repetitive content yielded a combined estimate of 82%.

Efficient Genome-Wide Detection and Cataloging of EMS-Induced Mutations Using Exome Capture and Next-Generation Sequencing

The authors combined high-throughput global sequencing targeted to genes and custom-designed bioinformatics tools to catalog and characterize chemically induced mutations in rice and wheat. They demonstrate that this approach can be used to develop large-scale induced mutation resources with relatively small investments and is applicable to resource-limited and polyploid organisms. Chemical mutagenesis efficiently generates phenotypic variation in otherwise homogeneous genetic backgrounds, enabling functional analysis of genes. Advances in mutation detection have brought the utility of induced mutant populations on par with those produced by insertional mutagenesis, but systematic cataloguing of mutations would further increase their utility. We examined the suitability of multiplexed global exome capture and sequencing coupled with custom-developed bioinformatics tools to identify mutations in well-characterized mutant populations of rice (Oryza sativa) and wheat (Triticum aestivum). In rice, we identified ∼18,000 induced mutations from 72 independent M2 individuals. Functional evaluation indicated the recovery of potentially deleterious mutations for >2600 genes. We further observed that specific sequence and cytosine methylation patterns surrounding the targeted guanine residues strongly affect their probability to be alkylated by ethyl methanesulfonate. Application of these methods to six independent M2 lines of tetraploid wheat demonstrated that our bioinformatics pipeline is applicable to polyploids. In conclusion, we provide a method for developing large-scale induced mutation resources with relatively small investments that is applicable to resource-poor organisms. Furthermore, our results demonstrate that large libraries of sequenced mutations can be readily generated, providing enhanced opportunities to study gene function and assess the effect of sequence and chromatin context on mutations.

Uncovering hidden variation in polyploid wheat

Significance Pasta and bread wheat are polyploid species that carry multiple copies of each gene. Therefore, loss-of-function mutations in one gene copy are frequently masked by functional copies on other genomes. We sequenced the protein coding regions of 2,735 mutant lines and developed a public database including more than 10 million mutations. Researchers and breeders can search this database online, identify mutations in the different copies of their target gene, and request seeds to study gene function or improve wheat varieties. Mutations are being used to improve the nutritional value of wheat, increase the size of the wheat grains, and generate additional variability in flowering genes to improve wheat adaptation to new and changing environments. Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35–40 mutations per kb in each population. With these mutation densities, we identified an average of 23–24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.

Identification of the VERNALIZATION 4 gene reveals the origin of spring growth habit in ancient wheats from South Asia

Significance A precise regulation of flowering time is critical for plant reproductive success and for cereal crops to maximize grain production. In wheat, barley, and other temperate cereals, vernalization genes play an important role in the acceleration of reproductive development after long periods of low temperatures during the winter (vernalization). In this study, we identified VERNALIZATION 4 (VRN-D4), a vernalization gene that was critical for the development of spring growth habit in the ancient wheats from South Asia. We show that mutations in regulatory regions of VRN-D4 are shared with other VRN-A1 alleles and can be used to modulate the vernalization response. These previously unknown alleles provide breeders new tools to engineer wheat varieties better adapted to different or changing environments. Wheat varieties with a winter growth habit require long exposures to low temperatures (vernalization) to accelerate flowering. Natural variation in four vernalization genes regulating this requirement has favored wheat adaptation to different environments. The first three genes (VRN1–VRN3) have been cloned and characterized before. Here we show that the fourth gene, VRN-D4, originated by the insertion of a ∼290-kb region from chromosome arm 5AL into the proximal region of chromosome arm 5DS. The inserted 5AL region includes a copy of VRN-A1 that carries distinctive mutations in its coding and regulatory regions. Three lines of evidence confirmed that this gene is VRN-D4: it cosegregated with VRN-D4 in a high-density mapping population; it was expressed earlier than other VRN1 genes in the absence of vernalization; and induced mutations in this gene resulted in delayed flowering. VRN-D4 was found in most accessions of the ancient subspecies Triticum aestivum ssp. sphaerococcum from South Asia. This subspecies showed a significant reduction of genetic diversity and increased genetic differentiation in the centromeric region of chromosome 5D, suggesting that VRN-D4 likely contributed to local adaptation and was favored by positive selection. Three adjacent SNPs in a regulatory region of the VRN-D4 first intron disrupt the binding of GLYCINE-RICH RNA-BINDING PROTEIN 2 (TaGRP2), a known repressor of VRN1 expression. The same SNPs were identified in VRN-A1 alleles previously associated with reduced vernalization requirement. These alleles can be used to modulate vernalization requirements and to develop wheat varieties better adapted to different or changing environments.

Transcriptomic profile of leaf tissue from the leguminous tree, Millettia pinnata

Millettia pinnata (formerly Pongamia pinnata) is a fast-growing leguminous tree indigenous to the Indian subcontinent, Southeast Asia, and Australia. This species has been introduced to subtropical and arid regions of Africa, India, the Philippines, Malaysia, Australia, and the USA for commercial growth. Exhibiting saline and drought tolerance, as well as nitrogen-fixing properties, M. pinnata has been used extensively for traditional medicine and agriculture and, more recently, for the production of a biofuel feedstock. The large size, high oil content, and fatty acid profile of the seeds are well suited for biofuel production. In this study, we characterized the leaf transcriptome that was assembled de novo from 72 seedlings pooled into eight libraries. Deep paired-end short-read sequencing was performed on individual libraries using the Illumina HiSeq 2000 platform. The Trinity-assembled transcriptome of 25,146 unique genes was annotated with a combination of open-source tools. Functional annotation was facilitated through sequence homology searches, Gene Ontology term assignment, and protein domain identification. A total of 11,873 genes were classified as full-length, and 22,603 sequences were functionally annotated. Predominate Gene Ontology biological process categories included phosphorylation, metabolic processes, and oxidation-reduction processes. Orthologous gene family analysis identified 19,640 families among the 11 sequenced plant species compared. A total of 4280 were conserved across all species, and 103 were unique to the M. pinnata leaf transcriptome. The unique M. pinnata gene families included transcripts with an array of functions including ubiquitin-like modifier proteins and BED zinc finger proteins with membership in pathways related to salt tolerance and disease resistance.

CartograTree: connecting tree genomes, phenotypes and environment.

Today, researchers spend a tremendous amount of time gathering, formatting, filtering and visualizing data collected from disparate sources. Under the umbrella of forest tree biology, we seek to provide a platform and leverage modern technologies to connect biotic and abiotic data. Our goal is to provide an integrated web‐based workspace that connects environmental, genomic and phenotypic data via geo‐referenced coordinates. Here, we connect the genomic query web‐based workspace, DiversiTree and a novel geographical interface called CartograTree to data housed on the TreeGenes database. To accomplish this goal, we implemented Simple Semantic Web Architecture and Protocol to enable the primary genomics database, TreeGenes, to communicate with semantic web services regardless of platform or back‐end technologies. The novelty of CartograTree lies in the interactive workspace that allows for geographical visualization and engagement of high performance computing (HPC) resources. The application provides a unique tool set to facilitate research on the ecology, physiology and evolution of forest tree species. CartograTree can be accessed at: http://dendrome.ucdavis.edu/cartogratree.

Comparative transcriptomics among four white pine species

Conifers are the dominant plant species throughout the high latitude boreal forests as well as some lower latitude temperate forests of North America, Europe, and Asia. As such, they play an integral economic and ecological role across much of the world. This study focused on the characterization of needle transcriptomes from four ecologically important and understudied North American white pines within the Pinus subgenus Strobus. The populations of many Strobus species are challenged by native and introduced pathogens, native insects, and abiotic factors. RNA from the needles of western white pine (Pinus monticola), limber pine (Pinus flexilis), whitebark pine (Pinus albicaulis), and sugar pine (Pinus lambertiana) was sampled, Illumina short read sequenced, and de novo assembled. The assembled transcripts and their subsequent structural and functional annotations were processed through custom pipelines to contend with the challenges of non-model organism transcriptome validation. Orthologous gene family analysis of over 58,000 translated transcripts, implemented through Tribe-MCL, estimated the shared and unique gene space among the four species. This revealed 2025 conserved gene families, of which 408 were aligned to estimate levels of divergence and reveal patterns of selection. Specific candidate genes previously associated with drought tolerance and white pine blister rust resistance in conifers were investigated.