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.

Soil microbial communities and degradation of pesticides in greenhouse effluent through a woodchip bioreactor.

Pesticides, including insecticides and fungicides, are major contaminants in the effluent from intensive agricultural systems, such as greenhouses. Because of their constant use and persistence, some pesticides can accumulate in soil and/or run off into adjacent waterways. Microbial communities in soil can degrade some pesticides, and bioreactors with enhanced microbial communities have the potential to facilitate decontamination before the effluent is released into the environment. In this study, we sampled the soil along a gradient from immediately below greenhouses, into, through and below a bioreactor. Multi-analyte pesticide screening was undertaken along with shotgun metagenomic sequencing, to assess microbial community taxonomic profiles and metabolic pathway responses for functional analysis. Two insecticides (imidacloprid and fipronil) and nine fungicides were identified in the soil samples, with a general decrease in most pesticides with increasing distance from the greenhouses. Diversity indexes of taxonomic profiles show changes in the microbial community along the gradient. In particular, microbial communities were significantly different in the bioreactor, with lower Shannon diversity compared to immediately below the greenhouses, in the channels leading into the bioreactor and further downstream. Metabolic pathway analysis revealed significant changes in a wide range of core housekeeping genes such as protein/amino acid synthesis and lipid/fatty acid biosynthesis among the sampling sites. The result demonstrates that the composition and potential functional pathways of the microbial community shifted towards an increased tendency for phytol and contaminant degradation in the bioreactor, facilitated by high organic matter content. This highlights the potential to use enhanced microbial communities within bioreactors to reduce contamination by some pesticides in sediment receiving run-off from greenhouses.

RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci.

BACKGROUND: As the number of genome-wide association study (GWAS) and quantitative trait locus (QTL) mappings in rice continues to grow, so does the already long list of genomic loci associated with important agronomic traits. Typically, loci implicated by GWAS/QTL analysis contain tens to hundreds to thousands of single-nucleotide polmorphisms (SNPs)/genes, not all of which are causal and many of which are in noncoding regions. Unraveling the biological mechanisms that tie the GWAS regions and QTLs to the trait of interest is challenging, especially since it requires collating functional genomics information about the loci from multiple, disparate data sources. RESULTS: We present RicePilaf, a web app for post-GWAS/QTL analysis, that performs a slew of novel bioinformatics analyses to cross-reference GWAS results and QTL mappings with a host of publicly available rice databases. In particular, it integrates (i) pangenomic information from high-quality genome builds of multiple rice varieties, (ii) coexpression information from genome-scale coexpression networks, (iii) ontology and pathway information, (iv) regulatory information from rice transcription factor databases, (v) epigenomic information from multiple high-throughput epigenetic experiments, and (vi) text-mining information extracted from scientific abstracts linking genes and traits. We demonstrate the utility of RicePilaf by applying it to analyze GWAS peaks of preharvest sprouting and genes underlying yield-under-drought QTLs. CONCLUSIONS: RicePilaf enables rice scientists and breeders to shed functional light on their GWAS regions and QTLs, and it provides them with a means to prioritize SNPs/genes for further experiments. The source code, a Docker image, and a demo version of RicePilaf are publicly available at https://github.com/bioinfodlsu/rice-pilaf.

A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable. RESULTS: Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a "subpopulation aware" 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq). CONCLUSIONS: This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

A terpene synthase supergene locus determines chemotype in Melaleuca alternifolia (tea tree).

Leaf oil terpenes vary categorically in many plant populations, leading to discrete phenotypes of adaptive and economic significance, but for most species, a genetic explanation for the concerted fluctuation in terpene chemistry remains unresolved. To uncover the genetic architecture underlying multi-component terpene chemotypes in Melaleuca alternifolia (tea tree), a genome-wide association study was undertaken for 148 individuals representing all six recognised chemotypes. A number of single nucleotide polymorphisms in a genomic region of c. 400 kb explained large proportions of the variation in key monoterpenes of tea tree oil. The region contained a cluster of 10 monoterpene synthase genes, including four genes predicted to encode synthases for 1,8-cineole, terpinolene, and the terpinen-4-ol precursor, sabinene hydrate. Chemotype-dependent null alleles at some sites suggested structural variants within this gene cluster, providing a possible basis for linkage disequilibrium in this region. Genotyping in a separate domesticated population revealed that all alleles surrounding this gene cluster were fixed after artificial selection for a single chemotype. These observations indicate that a supergene accounts for chemotypes in M. alternifolia. A genetic model with three haplotypes, encompassing the four characterised monoterpene synthase genes, explained the six terpene chemotypes, and was consistent with available biparental cross-segregation data.

Critical disease burdens of Australian adults with cystic fibrosis: Results from an online survey.

BACKGROUND: The objective of this study was to conduct a web-based questionnaire to investigate self-reported phenotypes and disease burdens of individuals living in Australia and diagnosed with cystic fibrosis (CF) using a case-control study design. METHODS: An online questionnaire was distributed to individuals with CF and healthy control subjects. Overall health rating, medications, family history, education, clinical indicators of disease, and symptoms, including their severity and frequency, were evaluated. RESULTS: There was a total of 119 respondents consisting of 59 people living with CF and 60 controls. The CF cohort had significantly lower tertiary educational levels compared to controls. The analysis specific to the CF cohort depicted a significant correlation between the frequency of hospitalizations and the level of education in the CF cohort. Of the 26 self-reported symptoms of CF that were analyzed, 14 were significantly higher in the people living with CF. The CF cohort reporting symptoms of chronic pain (25%) described an increase in the burden of disease, depicting a 30% longer mean hospitalization, increased consumption of medications and significant relationships with four other symptoms, including muscle aches, digestive issues, pancreatic insufficiency, and abdominal swelling. CONCLUSIONS: The nationwide survey identified a diverse range of clinical manifestations experienced by the Australian CF population. Chronic pain, linked to aging and the changing landscape of disease, was a significant indicator of the burden of disease. A comprehensive understanding of the phenotypic profiles and symptom variability will contribute to future research and provide insights into the impacts of disease and the burden of therapy, particularly in children, at the start of their health journey.

Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits.

Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn5.2, qFe7.1, qGY10.1, qDF7.1, qPH1.1, qNT4.1, qPT4.1, qPL1.2, qTGW5.1, qGL3.1 , and qGW6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R2. In all, 26 QTL clusters were identified on different chromosomes. qPH6.1 epistatically interacted with qZn5.1 and qGY6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.

Transcriptome analysis of the 2,4-dichlorophenoxyacetic acid (2,4-D)-tolerant cotton chromosome substitution line CS-B15sh and its susceptible parental lines G. hirsutum L. cv. Texas Marker-1 and G. barbadense L. cv. Pima 379.

The cotton chromosome substitution line, CS-B15sh, exhibits 41% lower injury from 2,4-D when applied at the field recommended rate of 1.12 kg ae ha-1 (1×) than does Texas Marker-1 (TM-1). CS-B15sh was developed in the genetic background of Gossypium hirsutum L. cv TM-1 and has chromosome introgression on the short arm of chromosome 15 from Gossypium barbadense L. cv. Pima 379. In a previous experiment, we observed reduced translocation of [14C]2,4-D outside the treated leaf tissue in CS-B15sh, which contrasted with an increased translocation of the herbicide in the tissues above and below the treated leaf in TM-1. Our results indicate a potential 2,4-D tolerance mechanism in CS-B15sh involving altered movement of 2,4-D. Here, we used RNA sequencing (RNA-seq) to determine the differential expression of genes between 2,4-D-challenged and control plants of the tolerant (CS-B15sh) and susceptible lines (TM-1 and Pima 379). Several components of the 2,4-D/auxin-response pathway-including ubiquitin E3 ligase, PB1|AUX/IAA, ARF transcription factors, and F-box proteins of the SCFTIR1/AFB complex-were upregulated with at least threefold higher expression in TM-1 compared with CS-B15sh, while both Pima 379 and TM-1 showed the same fold change expression for PB1|AUX/IAA mRNA. Some genes associated with herbicide metabolism, including flavin monooxygenase (Gohir.A01G174100) and FAD-linked oxidase (Gohir.D06G002600), exhibited at least a twofold increase in CS-B15sh than in TM-1 (the gene was not expressed in Pima 379), suggesting a potential relationship between the gene's expression and 2,4-D tolerance. It is interesting to note that glutathione S-transferase was differentially expressed in both CS-B15sh and Pima 379 but not in TM-1, while cytochrome P450 and other genes involved in the oxidation-reduction process were significantly expressed only in CS-B15sh in response to 2,4-D. Gene set enrichment analysis on the union DEGs of the three cotton genotypes revealed the depletion of transcripts involved in photosynthesis and enrichment of transcripts involved in ABA response and signaling.

Establishing a Common Nutritional Vocabulary - From Food Production to Diet.

Informed policy and decision-making for food systems, nutritional security, and global health would benefit from standardization and comparison of food composition data, spanning production to consumption. To address this challenge, we present a formal controlled vocabulary of terms, definitions, and relationships within the Compositional Dietary Nutrition Ontology (CDNO, www.cdno.info) that enables description of nutritional attributes for material entities contributing to the human diet. We demonstrate how ongoing community development of CDNO classes can harmonize trans-disciplinary approaches for describing nutritional components from food production to diet.