HASCH - A high-throughput amplicon-based SNP-platform for medicinal cannabis and industrial hemp genotyping applications.

BACKGROUND: Cannabis sativa is seeing a global resurgence as a food, fiber and medicinal crop for industrial hemp and medicinal Cannabis industries respectively. However, a widespread moratorium on the use and research of C. sativa throughout most of the 20th century has seen the development of improved cultivars for specific end uses lag behind that of conventional crops. While C. sativa research and development has seen significant investments in the recent past, resulting in a suite of publicly available genomic resources and tools, a versatile and cost-effective mid-density genotyping platform for applied purposes in breeding and pre-breeding is lacking. Here we report on a first mid-density fixed-target SNP platform for C. sativa. RESULTS: The High-throughput Amplicon-based SNP-platform for medicinal Cannabis and industrial Hemp (HASCH) was designed using a combination of filtering and Integer Linear Programming on publicly available whole-genome sequencing and RNA sequencing data, supplemented with in-house generated genotyping-by-sequencing (GBS) data. HASCH contains 1,504 genome-wide targets of high call rate (97% mean) and even distribution across the genome, designed to be highly informative (> 0.3 minor allele frequency) across both medicinal cannabis and industrial hemp gene pools. Average numbers of mismatch SNP between any two accessions were 251 for medicinal cannabis (N = 116) and 272 for industrial hemp (N = 87). Comparing HASCH data with corresponding GBS data on a collection of diverse C. sativa accessions demonstrated high concordance and resulted in comparable phylogenies and genetic distance matrices. Using HASCH on a segregating F2 population derived from a cross between a tetrahydrocannabinol (THC)-dominant and a cannabidiol (CBD)-dominant accession resulted in a genetic map consisting of 310 markers, comprising 10 linkage groups and a total size of 582.7 cM. Quantitative Trait Locus (QTL) mapping identified a major QTL for CBD content on chromosome 7, consistent with previous findings. CONCLUSION: HASCH constitutes a versatile, easy to use and cost-effective genotyping solution for the rapidly growing Cannabis research community. It provides consistent genetic fingerprints of 1504 SNPs with wide applicability genetic resource management, quantitative genetics and breeding.

Genomic variation in 3,010 diverse accessions of Asian cultivated rice.

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.

Progress in single-access information systems for wheat and rice crop improvement.

Improving productivity of the staple crops wheat and rice is essential to feed the growing global population, particularly in the context of a changing climate. However, current rates of yield gain are insufficient to support the predicted population growth. New approaches are required to accelerate the breeding process, and many of these are driven by the application of large-scale crop data. To leverage the substantial volumes and types of data that can be applied for precision breeding, the wheat and rice research communities are working towards the development of integrated systems to access and standardize the dispersed, heterogeneous available data. Here, we outline the initiatives of the International Wheat Information System (WheatIS) and the International Rice Informatics Consortium (IRIC) to establish Web-based single-access systems and data mining tools to make the available resources more accessible, drive discovery and accelerate the production of new crop varieties. We discuss the progress of WheatIS and IRIC towards unifying specialized wheat and rice databases and building custom software platforms to manage and interrogate these data. Single-access crop information systems will strengthen scientific collaboration, optimize the use of public research funds and help achieve the required yield gains in the two most important global food crops.

Rice SNP-seek database update: new SNPs, indels, and queries.

We describe updates to the Rice SNP-Seek Database since its first release. We ran a new SNP-calling pipeline followed by filtering that resulted in complete, base, filtered and core SNP datasets. Besides the Nipponbare reference genome, the pipeline was run on genome assemblies of IR 64, 93-11, DJ 123 and Kasalath. New genotype query and display features are added for reference assemblies, SNP datasets and indels. JBrowse now displays BAM, VCF and other annotation tracks, the additional genome assemblies and an embedded VISTA genome comparison viewer. Middleware is redesigned for improved performance by using a hybrid of HDF5 and RDMS for genotype storage. Query modules for genotypes, varieties and genes are improved to handle various constraints. An integrated list manager allows the user to pass query parameters for further analysis. The SNP Annotator adds traits, ontology terms, effects and interactions to markers in a list. Web-service calls were implemented to access most data. These features enable seamless querying of SNP-Seek across various biological entities, a step toward semi-automated gene-trait association discovery. URL: http://snp-seek.irri.org.

SNP-Seek database of SNPs derived from 3000 rice genomes.

We have identified about 20 million rice SNPs by aligning reads from the 3000 rice genomes project with the Nipponbare genome. The SNPs and allele information are organized into a SNP-Seek system (http://www.oryzasnp.org/iric-portal/), which consists of Oracle database having a total number of rows with SNP genotypes close to 60 billion (20 M SNPs × 3 K rice lines) and web interface for convenient querying. The database allows quick retrieving of SNP alleles for all varieties in a given genome region, finding different alleles from predefined varieties and querying basic passport and morphological phenotypic information about sequenced rice lines. SNPs can be visualized together with the gene structures in JBrowse genome browser. Evolutionary relationships between rice varieties can be explored using phylogenetic trees or multidimensional scaling plots.

CannSeek? Yes we Can! An open-source single nucleotide polymorphism database and analysis portal for Cannabis sativa.

A growing interest in Cannabis sativa uses for food, fiber, and medicine, and recent changes in regulations have spurred numerous genomic studies of this once-prohibited plant. Cannabis research uses Next Generation Sequencing technologies for genomics and transcriptomics. While other crops have genome portals enabling access and analysis of numerous genotyping data from diverse accessions, leading to the discovery of alleles for important traits, this is absent for cannabis. The CannSeek web portal aims to address this gap. Single nucleotide polymorphism datasets were generated by identifying genome variants from public resequencing data and genome assemblies. Results and accompanying trait data are hosted in the CannSeek web application, built using the Rice SNP-Seek infrastructure with improvements to allow multiple reference genomes and provide a web-service Application Programming Interface. The tools built into the portal allow phylogenetic analyses, varietal grouping and identifications, and favorable haplotype discovery for cannabis accessions using public sequencing data. Availability and implementation: The CannSeek portal is available at https://icgrc.info/cannseek, https://icgrc.info/genotype_viewer.

Characterization of growth and metabolism of the haloalkaliphile Natronomonas pharaonis.

Natronomonas pharaonis is an archaeon adapted to two extreme conditions: high salt concentration and alkaline pH. It has become one of the model organisms for the study of extremophilic life. Here, we present a genome-scale, manually curated metabolic reconstruction for the microorganism. The reconstruction itself represents a knowledge base of the haloalkaliphile's metabolism and, as such, would greatly assist further investigations on archaeal pathways. In addition, we experimentally determined several parameters relevant to growth, including a characterization of the biomass composition and a quantification of carbon and oxygen consumption. Using the metabolic reconstruction and the experimental data, we formulated a constraints-based model which we used to analyze the behavior of the archaeon when grown on a single carbon source. Results of the analysis include the finding that Natronomonas pharaonis, when grown aerobically on acetate, uses a carbon to oxygen consumption ratio that is theoretically near-optimal with respect to growth and energy production. This supports the hypothesis that, under simple conditions, the microorganism optimizes its metabolism with respect to the two objectives. We also found that the archaeon has a very low carbon efficiency of only about 35%. This inefficiency is probably due to a very low P/O ratio as well as to the other difficulties posed by its extreme environment.

Rice Galaxy: an open resource for plant science.

BACKGROUND: Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high-density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers. FINDINGS: The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. The Rice Galaxy web server and deployment installer includes tools for designing single-nucleotide polymorphism assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented. CONCLUSIONS: Rice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.

Identification of candidate genes for drought stress tolerance in rice by the integration of a genetic (QTL) map with the rice genome physical map.

Genetic improvement for drought stress tolerance in rice involves the quantitative nature of the trait, which reflects the additive effects of several genetic loci throughout the genome. Yield components and related traits under stressed and well-water conditions were assayed in mapping populations derived from crosses of AzucenaxIR64 and AzucenaxBala. To find the candidate rice genes underlying Quantitative Trait Loci (QTL) in these populations, we conducted in silico analysis of a candidate region flanked by the genetic markers RM212 and RM319 on chromosome 1, proximal to the semi-dwarf (sd1) locus. A total of 175 annotated genes were identified from this region. These included 48 genes annotated by functional homology to known genes, 23 pseudogenes, 24 ab initio predicted genes supported by an alignment match to an EST (Expressed sequence tag) of unknown function, and 80 hypothetical genes predicted solely by ab initio means. Among these, 16 candidate genes could potentially be involved in drought stress response.