CROPSR: an automated platform for complex genome-wide CRISPR gRNA design and validation.

BACKGROUND: CRISPR/Cas9 technology has become an important tool to generate targeted, highly specific genome mutations. The technology has great potential for crop improvement, as crop genomes are tailored to optimize specific traits over generations of breeding. Many crops have highly complex and polyploid genomes, particularly those used for bioenergy or bioproducts. The majority of tools currently available for designing and evaluating gRNAs for CRISPR experiments were developed based on mammalian genomes that do not share the characteristics or design criteria for crop genomes. RESULTS: We have developed an open source tool for genome-wide design and evaluation of gRNA sequences for CRISPR experiments, CROPSR. The genome-wide approach provides a significant decrease in the time required to design a CRISPR experiment, including validation through PCR, at the expense of an overhead compute time required once per genome, at the first run. To better cater to the needs of crop geneticists, restrictions imposed by other packages on design and evaluation of gRNA sequences were lifted. A new machine learning model was developed to provide scores while avoiding situations in which the currently available tools sometimes failed to provide guides for repetitive, A/T-rich genomic regions. We show that our gRNA scoring model provides a significant increase in prediction accuracy over existing tools, even in non-crop genomes. CONCLUSIONS: CROPSR provides the scientific community with new methods and a new workflow for performing CRISPR/Cas9 knockout experiments. CROPSR reduces the challenges of working in crops, and helps speed gRNA sequence design, evaluation and validation. We hope that the new software will accelerate discovery and reduce the number of failed experiments.

WI12Rhg1 interacts with DELLAs and mediates soybean cyst nematode resistance through hormone pathways.

The soybean cyst nematode (SCN) is one of the most important causes of soybean yield loss. The major source of genetic resistance to SCN is the Rhg1 repeat, a tandem copy number polymorphism of three genes. The roles of these genes are only partially understood. Moreover, nematode populations virulent on Rhg1-carrying soybeans are becoming more common, increasing the need to understand the most successful genetic resistance mechanism. Here, we show that a Rhg1-locus gene (Glyma.18G02270) encoding a wound-inducible protein (WI12Rhg1 ) is needed for SCN resistance. Furthermore, knockout of WI12Rhg1 reduces the expression of DELLA18, and the expression of WI12Rhg1 is itself induced by either JA, SA or GA. The content of the defence hormone SA is significantly lower whilst GA12 and GA53 are increased in WI12Rhg1 knockout roots compared with unedited hairy roots. We find that WI12Rhg1 directly interacts with DELLA18 (Glyma.18G040000) in yeast and plants and that double knockout of DELLA18 and its homeolog DELLA11 (Glyma.11G216500) significantly reduces SCN resistance and alters the root morphology. As DELLA proteins are implicated in hormone signalling, we explored the content of defence hormones (JA and SA) in DELLA knockout and unedited roots, finding reduced levels of JA and SA after the knockout of DELLA. Additionally, the treatment of DELLA-knockout roots with JA or SA rescues SCN resistance lost by the knockout. Meanwhile, the SCN resistance of unedited roots decreases after the treatment with GA, but increases with JA or SA. Our findings highlight the critical roles of WI12Rhg1 and DELLA proteins in SCN resistance through interconnection with hormone signalling.

Genome biology of the paleotetraploid perennial biomass crop Miscanthus.

Miscanthus is a perennial wild grass that is of global importance for paper production, roofing, horticultural plantings, and an emerging highly productive temperate biomass crop. We report a chromosome-scale assembly of the paleotetraploid M. sinensis genome, providing a resource for Miscanthus that links its chromosomes to the related diploid Sorghum and complex polyploid sugarcanes. The asymmetric distribution of transposons across the two homoeologous subgenomes proves Miscanthus paleo-allotetraploidy and identifies several balanced reciprocal homoeologous exchanges. Analysis of M. sinensis and M. sacchariflorus populations demonstrates extensive interspecific admixture and hybridization, and documents the origin of the highly productive triploid bioenergy crop M. × giganteus. Transcriptional profiling of leaves, stem, and rhizomes over growing seasons provides insight into rhizome development and nutrient recycling, processes critical for sustainable biomass accumulation in a perennial temperate grass. The Miscanthus genome expands the power of comparative genomics to understand traits of importance to Andropogoneae grasses.

t-SNAREs bind the Rhg1 α-SNAP and mediate soybean cyst nematode resistance.

Soybean cyst nematode (SCN; Heterodera glycines) is the largest pathogenic cause of soybean yield loss. The Rhg1 locus is the most used and best characterized SCN resistance locus, and contains three genes including one encoding an α-SNAP protein. Although the Rhg1 α-SNAP is known to play an important role in vesicle trafficking and SCN resistance, the protein's binding partners and the molecular mechanisms underpinning SCN resistance remain unclear. In this report, we show that the Rhg1 α-SNAP strongly interacts with two syntaxins of the t-SNARE family (Glyma.12G194800 and Glyma.16G154200) in yeast and plants; importantly, the genes encoding these syntaxins co-localize with SCN resistance quantitative trait loci. Fluorescent visualization revealed that the α-SNAP and the two interacting syntaxins localize to the plasma membrane and perinuclear space in both tobacco epidermal and soybean root cells. The two syntaxins and their two homeologs were mutated, individually and in combination, using the CRISPR-Cas9 system in the SCN-resistant Peking and SCN-susceptible Essex soybean lines. Peking roots with deletions introduced into syntaxin genes exhibited significantly reduced resistance to SCN, confirming that t-SNAREs are critical to resisting SCN infection. The results presented here uncover a key step in the molecular mechanism of SCN resistance, and will be invaluable to soybean breeders aiming to develop highly SCN-resistant soybean varieties.

Bacterial steroid-17,20-desmolase is a taxonomically rare enzymatic pathway that converts prednisone to 1,4-androstanediene-3,11,17-trione, a metabolite that causes proliferation of prostate cancer cells.

The adrenal gland has traditionally been viewed as a source of "weak androgens"; however, emerging evidence indicates 11-oxy-androgens of adrenal origin are metabolized in peripheral tissues to potent androgens. Also emerging is the role of gut bacteria in the conversion of C21 glucocorticoids to 11-oxygenated C19 androgens. Clostridium scindens ATCC 35,704 is a gut microbe capable of converting cortisol into 11-oxy-androgens by cleaving the side-chain. The desA and desB genes encode steroid-17,20-desmolase. Our prior study indicated that the urinary tract bacterium, Propionimicrobium lymphophilum ACS-093-V-SCH5 encodes desAB and converts cortisol to 11ß-hydroxyandrostenedione. We wanted to determine how widespread this function occurs in the human microbiome. Phylogenetic and sequence similarity network analyses indicated that the steroid-17,20-desmolase pathway is taxonomically rare and located in gut and urogenital microbiomes. Two microbes from each of these niches, C. scindens and Propionimicrobium lymphophilum, respectively, were screened for activity against endogenous (cortisol, cortisone, and allotetrahydrocortisol) and exogenous (prednisone, prednisolone, dexamethasone, and 9-fluorocortisol) glucocorticoids. LC/MS analysis showed that both microbes were able to side-chain cleave all glucocorticoids, forming 11-oxy-androgens. Pure recombinant DesAB from C. scindens showed the highest activity against prednisone, a commonly prescribed glucocorticoid. In addition, 0.1 nM 1,4-androstadiene-3,11,17-trione, bacterial side-chain cleavage product of prednisone, showed significant proliferation relative to vehicle in androgen-dependent growth LNCaP prostate cancer cells after 24 h (2.3 fold; P <  0.01) and 72 h (1.6 fold; P < 0.01). Taken together, DesAB-expressing microbes may be an overlooked source of androgens in the body, potentially contributing to various disease states, such as prostate cancer.

Genome Sequence of the Soybean Cyst Nematode (Heterodera glycines) Endosymbiont "Candidatus Cardinium hertigii" Strain cHgTN10.

In this study, we present the genome sequence of the "Candidatus Cardinium hertigii" strain cHgTN10, an endosymbiotic bacterium of the plant-parasitic nematode Heterodera glycines This is the first genome assembly reported for an endosymbiont directly sequenced from a tylenchid nematode.

Mapping of new quantitative trait loci for sudden death syndrome and soybean cyst nematode resistance in two soybean populations.

KEY MESSAGE: Novel QTL conferring resistance to both the SDS and SCN was detected in two RIL populations. Dual resistant RILs could be used in breeding programs for developing resistant soybean cultivars. Soybean cultivars, susceptible to the fungus Fusarium virguliforme, which causes sudden death syndrome (SDS), and to the soybean cyst nematode (SCN) (Heterodera glycines), suffer yield losses valued over a billion dollars annually. Both pathogens may occur in the same production fields. Planting of cultivars genetically resistant to both pathogens is considered one of the most effective means to control the two pathogens. The objective of the study was to map quantitative trait loci (QTL) underlying SDS and SCN resistances. Two recombinant inbred line (RIL) populations were developed by crossing 'A95-684043', a high-yielding maturity group (MG) II line resistant to SCN, with 'LS94-3207' and 'LS98-0582' of MG IV, resistant to both F. virguliforme and SCN. Two hundred F7 derived recombinant inbred lines from each population AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582) were screened for resistance to each pathogen under greenhouse conditions. Five hundred and eighty and 371 SNP markers were used for mapping resistance QTL in each population. In AX19286, one novel SCN resistance QTL was mapped to chromosome 8. In AX19287, one novel SDS resistance QTL was mapped to chromosome 17 and one novel SCN resistance QTL was mapped to chromosome 11. Previously identified additional SDS and SCN resistance QTL were also detected in the study. Lines possessing superior resistance to both pathogens were also identified and could be used as germplasm sources for breeding SDS- and SCN-resistant soybean cultivars.

A comparison of genotyping-by-sequencing analysis methods on low-coverage crop datasets shows advantages of a new workflow, GB-eaSy.

BACKGROUND: Genotyping-by-sequencing (GBS), a method to identify genetic variants and quickly genotype samples, reduces genome complexity by using restriction enzymes to divide the genome into fragments whose ends are sequenced on short-read sequencing platforms. While cost-effective, this method produces extensive missing data and requires complex bioinformatics analysis. GBS is most commonly used on crop plant genomes, and because crop plants have highly variable ploidy and repeat content, the performance of GBS analysis software can vary by target organism. Here we focus our analysis on soybean, a polyploid crop with a highly duplicated genome, relatively little public GBS data and few dedicated tools. RESULTS: We compared the performance of five GBS pipelines using low-coverage Illumina sequence data from three soybean populations. To address issues identified with existing methods, we developed GB-eaSy, a GBS bioinformatics workflow that incorporates widely used genomics tools, parallelization and automation to increase the accuracy and accessibility of GBS data analysis. Compared to other GBS pipelines, GB-eaSy rapidly and accurately identified the greatest number of SNPs, with SNP calls closely concordant with whole-genome sequencing of selected lines. Across all five GBS analysis platforms, SNP calls showed unexpectedly low convergence but generally high accuracy, indicating that the workflows arrived at largely complementary sets of valid SNP calls on the low-coverage data analyzed. CONCLUSIONS: We show that GB-eaSy is approximately as good as, or better than, other leading software solutions in the accuracy, yield and missing data fraction of variant calling, as tested on low-coverage genomic data from soybean. It also performs well relative to other solutions in terms of the run time and disk space required. In addition, GB-eaSy is built from existing open-source, modular software packages that are regularly updated and commonly used, making it straightforward to install and maintain. While GB-eaSy outperformed other individual methods on the datasets analyzed, our findings suggest that a comprehensive approach integrating the results from multiple GBS bioinformatics pipelines may be the optimal strategy to obtain the largest, most highly accurate SNP yield possible from low-coverage polyploid sequence data.

Simulating Next-Generation Sequencing Datasets from Empirical Mutation and Sequencing Models.

An obstacle to validating and benchmarking methods for genome analysis is that there are few reference datasets available for which the "ground truth" about the mutational landscape of the sample genome is known and fully validated. Additionally, the free and public availability of real human genome datasets is incompatible with the preservation of donor privacy. In order to better analyze and understand genomic data, we need test datasets that model all variants, reflecting known biology as well as sequencing artifacts. Read simulators can fulfill this requirement, but are often criticized for limited resemblance to true data and overall inflexibility. We present NEAT (NExt-generation sequencing Analysis Toolkit), a set of tools that not only includes an easy-to-use read simulator, but also scripts to facilitate variant comparison and tool evaluation. NEAT has a wide variety of tunable parameters which can be set manually on the default model or parameterized using real datasets. The software is freely available at github.com/zstephens/neat-genreads.

An efficient method for measuring copy number variation applied to improvement of nematode resistance in soybean.

Copy number variation (CNV) is implicated in important traits in multiple crop plants, but can be challenging to genotype using conventional methods. The Rhg1 locus of soybean, which confers resistance to soybean cyst nematode (SCN), is a CNV of multiple 31.2-kb genomic units each containing four genes. Reliable, high-throughput methods to quantify Rhg1 and other CNVs for selective breeding were developed. The CNV genotyping assay described here uses a homeologous gene copy within the paleopolyploid soybean genome to provide the internal control for a single-tube TaqMan copy number assay. Using this assay, CNV in breeding populations can be tracked with high precision. We also show that extensive CNV exists within Fayette, a released, inbred SCN-resistant soybean cultivar with a high copy number at Rhg1 derived from a single donor parent. Copy number at Rhg1 is therefore unstable within a released variety over a relatively small number of generations. Using this assay to select for individuals with altered copy number, plants were obtained with both increased copy number and increased SCN resistance relative to control plants. Thus, CNV genotyping technologies can be used as a new type of marker-assisted selection to select for desirable traits in breeding populations, and to control for undesirable variation within cultivars.

Evolution and selection of Rhg1, a copy-number variant nematode-resistance locus.

The soybean cyst nematode (SCN) resistance locus Rhg1 is a tandem repeat of a 31.2 kb unit of the soybean genome. Each 31.2-kb unit contains four genes. One allele of Rhg1, Rhg1-b, is responsible for protecting most US soybean production from SCN. Whole-genome sequencing was performed, and PCR assays were developed to investigate allelic variation in sequence and copy number of the Rhg1 locus across a population of soybean germplasm accessions. Four distinct sequences of the 31.2-kb repeat unit were identified, and some Rhg1 alleles carry up to three different types of repeat unit. The total number of copies of the repeat varies from 1 to 10 per haploid genome. Both copy number and sequence of the repeat correlate with the resistance phenotype, and the Rhg1 locus shows strong signatures of selection. Significant linkage disequilibrium in the genome outside the boundaries of the repeat allowed the Rhg1 genotype to be inferred using high-density single nucleotide polymorphism genotyping of 15 996 accessions. Over 860 germplasm accessions were found likely to possess Rhg1 alleles. The regions surrounding the repeat show indications of non-neutral evolution and high genetic variability in populations from different geographic locations, but without evidence of fixation of the resistant genotype. A compelling explanation of these results is that balancing selection is in operation at Rhg1.

Finding the missing honey bee genes: lessons learned from a genome upgrade.

BACKGROUND: The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. RESULTS: Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. CONCLUSIONS: Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.

Copy number variation of multiple genes at Rhg1 mediates nematode resistance in soybean.

The rhg1-b allele of soybean is widely used for resistance against soybean cyst nematode (SCN), the most economically damaging pathogen of soybeans in the United States. Gene silencing showed that genes in a 31-kilobase segment at rhg1-b, encoding an amino acid transporter, an α-SNAP protein, and a WI12 (wound-inducible domain) protein, each contribute to resistance. There is one copy of the 31-kilobase segment per haploid genome in susceptible varieties, but 10 tandem copies are present in an rhg1-b haplotype. Overexpression of the individual genes in roots was ineffective, but overexpression of the genes together conferred enhanced SCN resistance. Hence, SCN resistance mediated by the soybean quantitative trait locus Rhg1 is conferred by copy number variation that increases the expression of a set of dissimilar genes in a repeated multigene segment.

Microcollinearity between autopolyploid sugarcane and diploid sorghum genomes.

BACKGROUND: Sugarcane (Saccharum spp.) has become an increasingly important crop for its leading role in biofuel production. The high sugar content species S. officinarum is an octoploid without known diploid or tetraploid progenitors. Commercial sugarcane cultivars are hybrids between S. officinarum and wild species S. spontaneum with ploidy at approximately 12x. The complex autopolyploid sugarcane genome has not been characterized at the DNA sequence level. RESULTS: The microsynteny between sugarcane and sorghum was assessed by comparing 454 pyrosequences of 20 sugarcane bacterial artificial chromosomes (BACs) with sorghum sequences. These 20 BACs were selected by hybridization of 1961 single copy sorghum overgo probes to the sugarcane BAC library with one sugarcane BAC corresponding to each of the 20 sorghum chromosome arms. The genic regions of the sugarcane BACs shared an average of 95.2% sequence identity with sorghum, and the sorghum genome was used as a template to order sequence contigs covering 78.2% of the 20 BAC sequences. About 53.1% of the sugarcane BAC sequences are aligned with sorghum sequence. The unaligned regions contain non-coding and repetitive sequences. Within the aligned sequences, 209 genes were annotated in sugarcane and 202 in sorghum. Seventeen genes appeared to be sugarcane-specific and all validated by sugarcane ESTs, while 12 appeared sorghum-specific but only one validated by sorghum ESTs. Twelve of the 17 sugarcane-specific genes have no match in the non-redundant protein database in GenBank, perhaps encoding proteins for sugarcane-specific processes. The sorghum orthologous regions appeared to have expanded relative to sugarcane, mostly by the increase of retrotransposons. CONCLUSIONS: The sugarcane and sorghum genomes are mostly collinear in the genic regions, and the sorghum genome can be used as a template for assembling much of the genic DNA of the autopolyploid sugarcane genome. The comparable gene density between sugarcane BACs and corresponding sorghum sequences defied the notion that polyploidy species might have faster pace of gene loss due to the redundancy of multiple alleles at each locus.

Human cell toxicogenomic analysis of bromoacetic acid: a regulated drinking water disinfection by-product.

The disinfection of drinking water is a major achievement in protecting the public health. However, current disinfection methods also generate disinfection by-products (DBPs). Many DBPs are cytotoxic, genotoxic, teratogenic, and carcinogenic and represent an important class of environmentally hazardous chemicals that may carry long-term human health implications. The objective of this research was to integrate in vitro toxicology with focused toxicogenomic analysis of the regulated DBP, bromoacetic acid (BAA) and to evaluate modulation of gene expression involved in DNA damage/repair and toxic responses, with nontransformed human cells. We generated transcriptome profiles for 168 genes with 30 min and 4 hr exposure times that did not induce acute cytotoxicity. Using qRT-PCR gene arrays, the levels of 25 transcripts were modulated to a statistically significant degree in response to a 30 min treatment with BAA (16 transcripts upregulated and nine downregulated). The largest changes were observed for RAD9A and BRCA1. The majority of the altered transcript profiles are genes involved in DNA repair, especially the repair of double strand DNA breaks, and in cell cycle regulation. With 4 hr of treatment the expression of 28 genes was modulated (12 upregulated and 16 downregulated); the largest fold changes were in HMOX1 and FMO1. This work represents the first nontransformed human cell toxicogenomic study with a regulated drinking water disinfection by-product. These data implicate double strand DNA breaks as a feature of BAA exposure. Future toxicogenomic studies of DBPs will further strengthen our limited knowledge in this growing area of drinking water research.