Biology subjects

Buell, C. R.

Publications and source records attributed to Buell, C. R..

36 records · Page 2Linked to original sources

bioRxiv2024

Cell-type aware regulatory landscapes governing monoterpene indole alkaloid biosynthesis in the medicinal plant Catharanthus roseus

In plants, the biosynthetic pathways of some specialized metabolites are partitioned into specialized or rare cell types, as exemplified by the monoterpenoid indole alkaloid (MIA) pathway of Catharanthus roseus (Madagascar Periwinkle), the source of the anti-cancer compounds vinblastine and vincristine. In the leaf, the C. roseus MIA biosynthetic pathway is partitioned into three cell types with the final known steps of the pathway expressed in the rare cell type termed idioblast. How cell-type specificity of MIA biosynthesis is achieved is poorly understood. Here, we generated single-cell multi-omics data from C. roseus leaves. Integrating gene expression and chromatin accessibility profiles across single cells, as well as transcription factor (TF) binding site profiles, we constructed a cell-type-aware gene regulatory network for MIA biosynthesis. We showcased cell-type-specific transcription factors as well as cell-type-specific cis-regulatory elements. Using motif enrichment analysis, co-expression across cell types, and functional validation approaches, we discovered a novel idioblast specific TF (Idioblast MYB1, CrIDM1) that activates expression of late stage vinca alkaloid biosynthetic genes in the idioblast. These analyses not only led to the discovery of the first documented cell-type-specific TF that regulates the expression of two idioblast specific biosynthetic genes within an idioblast metabolic regulon, but also provides insights into cell-type-specific metabolic regulation.

plant biology↗

bioRxiv2024

Quantitative single cell mass spectrometry reveals the dynamics of plant natural product biosynthesis

Plants produce an extraordinary array of complex natural products (specialized metabolites). Since the biosynthetic genes that are responsible for synthesis of these molecules are often localized to rare or distinct cell types, recently developed single cell RNA-sequencing (scRNA-seq) approaches have tremendous potential to resolve these complex pathways. In contrast, detection, identification, and quantification of metabolites in single cells has remained challenging. Here, we report a robust method for single cell mass spectrometry in which we rigorously characterize and quantify the concentrations of four classes of natural products in individual cells of leaf, root, and petal of the medicinal plant Catharanthus roseus. These single cell mass spectrometry datasets reveal information about the biosynthetic processes that cannot be determined from the corresponding scRNA-seq data alone, providing a highly resolved picture of natural product biosynthesis at cell-specific resolution.

biochemistry↗

bioRxiv2024

Targeted genotyping-by-sequencing of potato and software for imputation

Mid-density targeted genotyping-by-sequencing (GBS) combines trait-specific markers with thousands of genomic markers at an attractive price for linkage mapping and genomic selection. A 2.5K targeted GBS assay for potato was developed using the DArTagTM technology and later expanded to 4K targets. Genomic markers were selected from the potato InfiniumTM SNP array to maximize genome coverage and polymorphism rates. The DArTag and SNP array platforms produced equivalent dendrograms in a test set of 298 tetraploid samples, and 83% of the common markers showed good quantitative agreement, with RMSE (root-mean-squared-error) less than 0.5. DArTag is suited for genomic selection candidates in the clonal evaluation trial, coupled with imputation to a higher density platform for the training population. Using the software polyBreedR, an R package for the manipulation and analysis of polyploid marker data, the RMSE for imputation by linkage analysis was 0.15 in a small half-diallel population (N=85), which was significantly lower than the RMSE of 0.42 with the Random Forest method. Regarding high-value traits, the DArTag markers for resistance to potato virus Y, golden cyst nematode, and potato wart appeared to track their targets successfully, as did multi-allelic markers for maturity and tuber shape. In summary, the potato DArTag assay is a transformative and publicly available technology for potato breeding and genetics. Core IdeasO_LIA mid-density, targeted genotyping-by-sequencing (GBS) assay was developed for potato. C_LIO_LIThe GBS assay includes markers for resistance to potato virus Y, golden cyst nematode, and potato wart. C_LIO_LIThe GBS assay includes multi-allelic markers for potato maturity and tuber shape. C_LIO_LIThe polyBreedR software has functions for manipulating and imputing polyploid marker data in Variant Call Format. C_LIO_LILinkage Analysis was more accurate than the Random Forest method when imputing from 2K to 10K markers. C_LI

genomics↗

bioRxiv2023

Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis

Sweetpotato, Ipomoea batatas (L.), a key food security crop, is negatively impacted by heat, drought, and salinity stress. We exposed the orange-fleshed cultivar Beauregard to 24 and 48 hours of heat and salt stresses to identify differentially expressed genes (DEGs) in leaves. Analysis revealed both shared and unique sets of up-regulated (650 for heat; 287 for salt) and down-regulated (1,249 for heat; 793 for salt) DEGs suggesting common, yet stress-specific transcriptional responses to these two abiotic stressors. Gene Ontology analysis of downregulated DEGs common to both heat and salt stress revealed enrichment of terms associated with cell population proliferation suggestive of an impact on the cell cycle by the heat stress. To identify shared and unique gene coexpression networks under multiple abiotic stress conditions, weighted gene co-expression network analysis was performed using gene expression profiles from heat, salt, and drought stress treated Beauregard leaves yielding 18 coexpression modules. One module was enriched for response to water deprivation, response to abscisic acid, and nitrate transport indicating synergetic crosstalk between nitrogen, water and phytohormones with genes encoding osmotin, cell expansion, and cell wall modification proteins present as key hub genes in this drought-associated module. This research lays the background for future research in mediating abiotic stress tolerance in sweetpotato.

molecular biology↗

bioRxiv2022

'Simple Tidy GeneCoEx': a gene co-expression analysis workflow powered by tidyverse and graph-based clustering in R

Gene co-expression analysis is an effective method to detect groups (or modules) of co-expressed genes that display similar expression patterns, which may function in the same biological processes. Here, we present Simple Tidy GeneCoEx, a gene co-expression analysis workflow written in the R programming language. The workflow is highly customizable across multiple stages of the pipeline including gene selection, edge selection, clustering resolution, and data visualization. Powered by the tidyverse package ecosystem and network analysis functions provided by the igraph package, the workflow detects gene co-expression modules whose members are highly interconnected. Step-by-step instructions with two use case examples as well as source code are available at https://github.com/cxli233/SimpleTidy_GeneCoEx. Core IdeasO_LIAn R-based workflow that performs gene co-expression analysis was developed. C_LIO_LIThe workflow is based on tidyverse packages and graph theory. C_LIO_LIThe workflow is highly customizable, detects tight gene co-expression modules, and generates publication quality figures. C_LIO_LITwo plant gene expression datasets were used to benchmark the workflow. C_LI

plant biology↗

bioRxiv2022

Nuclei isolation protocol from diverse angiosperm species

The ability to generate intact nuclei is crucial to the success of a variety of genomics experiments, such as Assay for Transposase-Accessible Chromatin using sequencing (ATAC- seq), Cleavage Under Targets and Tagmentation (CUT&Tag), and nuclei-based single cell sequencing (e.g., single nuclei ATAC-seq and single nuclei RNA-seq). For plants, the presence of the cell wall presents significant challenges in the isolation of nuclei from tissues. Here, we report an optimized nuclei isolation protocol that can be adapted for diverse angiosperm species, including maize, soybean, tomato, potato, and wheat, starting from fresh or frozen tissues. Nuclei release is achieved through chopping tissue on ice, where a key parameter affecting nuclei integrity is the concentration of detergent TritonX-100 in the nuclei isolation buffer. The method is simple, quick, and largely centrifugation-free, in which debris is removed by serial filtration. Initial nuclei release and filtration can be performed within 20 min. Fluorescence activated nuclei sorting is then used for final nuclei purification to remove other organelles such as plastids. The protocol uses 500 mg or less plant tissue as input and typically yields at least 100,000 - 200,000 purified nuclei per sample, a common input amount for downstream experiments. Throughout the protocol, we provide guidelines for optimization if performing nuclei isolation from a given species and tissue for the first time.

plant biology↗

bioRxiv2022

Leveraging prior biological knowledge improves prediction of tocochromanols in maize grain

With an essential role in human health, tocochromanols are mostly obtained by consuming seed oils; however, the vitamin E content of the most abundant tocochromanols in maize grain is low. Several large-effect genes with cis-acting variants affecting mRNA expression are mostly responsible for tocochromanol variation in maize grain, with other relevant associated quantitative trait loci (QTL) yet to be fully resolved. Leveraging existing genomic and transcriptomic information for maize inbreds could improve prediction when selecting for higher vitamin E content. Here, we first evaluated a multikernel genomic best linear unbiased prediction (MK-GBLUP) approach for modeling known QTL in the prediction of nine tocochromanol grain phenotypes (12-21 QTL per trait) within and between two panels of 1,462 and 242 maize inbred lines. On average, MK-GBLUP models improved predictive abilities by 7.0 to 13.6% when compared to GBLUP. In a second approach with a subset of 545 lines from the larger panel, the highest average improvement in predictive ability relative to GBLUP was achieved with a multi-trait GBLUP model (15.4%) that had a tocochromanol phenotype and transcript abundances in developing grain for a few large-effect candidate causal genes (1-3 genes per trait) as multiple response variables. Taken together, our study illustrates the enhancement of prediction models when informed by existing biological knowledge pertaining to QTL and candidate causal genes. Core IdeasO_LIWith varying levels of vitamin E activity, tocochromanols found in maize grain are essential for human health C_LIO_LISelecting for higher vitamin E content in maize grain can be enhanced with genomic prediction C_LIO_LIPrediction models leveraging existing biological knowledge were evaluated in two panels of maize inbred lines C_LIO_LIMultikernel prediction models based on previously identified QTL improved predictive ability C_LIO_LIA multi-trait prediction model that had transcript abundances of a few large-effect causal genes performed the best C_LI

genetics↗

bioRxiv2022

Single-cell multi-omics enabled discovery of alkaloid biosynthetic pathway genes in the medical plant Catharanthus roseus

Advances in omics technologies now permit generation of highly contiguous genome assemblies, detection of transcripts and metabolites at the level of single cells, and high-resolution determination of gene regulatory features including 3-dimensional chromatin interactions. Using a complementary, multi-omics approach, we interrogated the monoterpene indole alkaloid (MIA) biosynthetic pathway in Catharanthus roseus, a source of leading anti-cancer drugs. We identified not only new clusters of genes involved in MIA biosynthesis on the eight C. roseus chromosomes but also rampant gene duplication including paralogs of MIA pathway genes. Clustering was not limited to the linear genome and through chromatin interaction data, MIA pathway genes were shown to be present within the same topologically associated domain, permitting identification of a secologanin transporter. Single cell RNA-sequencing revealed exquisite and sequential cell-type specific partitioning of the leaf MIA biosynthetic pathway that, when coupled with a newly developed single cell metabolomics approach, permitted identification of a reductase that yields the bis-indole alkaloid anhydrovinblastine. Last, we revealed cell-type specific expression in the root MIA pathway that is conferred in part by neo- and sub-functionalization of paralogous MIA pathway genes. This study highlights how a suite of omic approaches, including single cell gene expression and metabolomics, can efficiently link sequence with function in complex, specialized metabolic pathways of plants.

plant biology↗

bioRxiv2022

Combining GWAS and TWAS to identify candidate causal genes for tocochromanol levels in maize grain

Tocochromanols (tocopherols and tocotrienols, collectively vitamin E) are lipid-soluble antioxidants important for both plant fitness and human health. The main dietary sources of vitamin E are seed oils that often accumulate high levels of tocopherol isoforms with lower vitamin E activity. The tocochromanol biosynthetic pathway is conserved across plant species but an integrated view of the genes and mechanisms underlying natural variation of tocochromanol levels in seed of most cereal crops remains limited. To address this issue, we utilized the high mapping resolution of the maize Ames panel of [~]1,500 inbred lines scored with 12.2 million single-nucleotide polymorphisms to generate metabolomic (mature grain tocochromanols) and transcriptomic (developing grain) data sets for genetic mapping. By combining results from genome- and transcriptome-wide association studies, we identified a total of 13 candidate causal gene loci, including five that had not been previously associated with maize grain tocochromanols: four biosynthetic genes (arodeH2 paralog, dxs1, vte5, and vte7) and a plastid S-adenosyl methionine transporter (samt1). Expression quantitative trait locus (eQTL) mapping of these 13 gene loci revealed that they are predominantly regulated by cis-eQTL. Through a joint statistical analysis, we implicated cis-acting variants as responsible for co-localized eQTL and GWAS association signals. Our multi-omics approach provided increased statistical power and mapping resolution to enable a detailed characterization of the genetic and regulatory architecture underlying tocochromanol accumulation in maize grain and provided insights for ongoing biofortification efforts to breed and/or engineer vitamin E and antioxidant levels in maize and other cereals.

genetics↗

bioRxiv2022

Genetic mapping of flowering time and plant height in a maize Stiff Stalk MAGIC population

The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930s. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a six parent multiparent advanced generation intercross (MAGIC) population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in two field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to two testers, respectively, and evaluated as hybrids in two locations in 2018 and 2019 using an incomplete block design. Markers were derived from a Practical Haplotype Graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 636 of the DH lines and two sets of 571 and 472 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55 to 0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49 to 0.55). Overall, this finding is consistent with the overlapping and non-overlapping significant QTL found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available. Core IdeasA multi-parent advanced generation intercross (MAGIC) mapping population was developed from six founder Stiff Stalk maize inbreds with commercial relevance. Genetic mapping utilizing an update to R/qtl2 was demonstrated for flowering and plant height traits. Genetic mapping using maize inbred and hybrid information was compared and provided insight into trait expression in inbreds relative to heterotic testcross hybrids.

genomics↗

bioRxiv2021

Transcriptome-wide association and prediction for carotenoids and tocochromanols in fresh sweet corn kernels

Sweet corn is consistently one of the most highly consumed vegetables in the U.S., providing a valuable opportunity to increase nutrient intake through biofortification. Significant variation for carotenoid (provitamin A, lutein, zeaxanthin) and tocochromanol (vitamin E, antioxidants) levels is present in temperate sweet corn germplasm, yet previous genome-wide association studies (GWAS) of these traits have been limited by low statistical power and mapping resolution. Here, we employed a high-quality transcriptomic dataset collected from fresh sweet corn kernels to conduct transcriptome-wide association studies (TWAS) and transcriptome prediction studies for 39 carotenoid and tocochromanol traits. In agreement with previous GWAS findings, TWAS detected significant associations for four causal genes, {beta}-carotene hydroxylase (crtRB1), lycopene epsilon cyclase (lcyE),{gamma} -tocopherol methyltransferase (vte4), and homogentisate geranylgeranyltransferase (hggt1) on a transcriptome-wide level. Pathway-level analysis revealed additional associations for deoxy-xylulose synthase2 (dxs2), diphosphocytidyl methyl erythritol synthase2 (dmes2), cytidine methyl kinase1 (cmk1), and geranylgeranyl hydrogenase1 (ggh1), of which, dmes2, cmk1, and ggh1 have not previously been identified through maize association studies. Evaluation of prediction models incorporating genome-wide markers and transcriptome-wide abundances revealed a trait-dependent benefit to the inclusion of both genomic and transcriptomic data over solely genomic data, but both transcriptome- and genome-wide datasets outperformed a priori candidate gene-targeted prediction models for most traits. Altogether, this study represents an important step towards understanding the role of regulatory variation in the accumulation of vitamins in fresh sweet corn kernels. Core IdeasO_LITranscriptomic data aid the study of vitamin levels in fresh sweet corn kernels. C_LIO_LIcrtRB1, lcyE, dxs2, dmes2, and cmk1 were associated with carotenoid traits. C_LIO_LIvte4, hggt1, and ggh1 were associated with tocochromanol traits. C_LIO_LITranscriptomic data boosted predictive ability over genomic data alone for some traits. C_LIO_LIJoint transcriptome- and genome-wide models achieved the highest predictive abilities. C_LI

genomics↗

bioRxiv2021

Genome-wide association study reveals an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels

Despite being one of the most consumed vegetables in the United States, the elemental profile of sweet corn (Zea mays L.) is limited in its dietary contributions. To address this through genetic improvement, a genome-wide association study was conducted for the concentrations of 15 elements in fresh kernels of a sweet corn association panel. In concordance with mapping results from mature maize kernels, we detected a probable pleiotropic association of zinc and iron concentrations with nicotianamine synthase5 (nas5), which purportedly encodes an enzyme involved in synthesis of the metal chelator nicotianamine. Additionally, a pervasive association signal was identified for cadmium concentration within a recombination suppressed region on chromosome 2. The likely causal gene underlying this signal was heavy metal ATPase3 (hma3), whose counterpart in rice, OsHMA3, mediates vacuolar sequestration of cadmium and zinc in roots, whereby regulating zinc homeostasis and cadmium accumulation in grains. In our association panel, hma3 associated with cadmium but not zinc accumulation in fresh kernels. This finding implies that selection for low cadmium will not affect zinc levels in fresh kernels. Although less resolved association signals were detected for boron, nickel, and calcium, all 15 elements were shown to have moderate predictive abilities via whole-genome prediction. Collectively, these results help enhance our genomics-assisted breeding efforts centered on improving the elemental profile of fresh sweet corn kernels.

genetics↗

bioRxiv2020

Eleven biosynthetic genes explain the majority of natural variation for carotenoid levels in maize grain

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize is a food staple. Extensive natural variation exists for carotenoids in maize grain; to understand its genetic basis, we conducted a joint linkage and genome-wide association study in the U.S. maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percent phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide the most comprehensive genome-level understanding of the genetic and molecular control of carotenoids in any plant system, and a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.

genetics↗

bioRxiv2019

High molecular weight DNA isolation method from diverse plant species for use with Oxford Nanopore sequencing

The ability to generate long reads on the Oxford Nanopore Technologies sequencing platform is dependent on the isolation of high molecular weight DNA free of impurities. For some taxa, this is relatively straightforward; however, for plants, the presence of cell walls and a diverse set of specialized metabolites such as lignin, phenolics, alkaloids, terpenes, and flavonoids present significant challenges in the generation of DNA suitable for production of long reads. Success in generating long read lengths and genome assemblies of plants has been reported using diverse DNA isolation methods, some of which were tailored to the target species and/or required extensive labor. To avoid the need to optimize DNA isolation for each species, we developed a taxa-independent DNA isolation method that is relatively simple and efficient. This method expands on the Oxford Nanopore Technologies high molecular weight genomic DNA protocol from plant leaves and utilizes a conventional cetyl trimethylammonium bromide extraction followed by removal of impurities and short DNA fragments using commercially available kits that yielded robust N50 read lengths and yield on Oxford Nanopore Technologies flow cells.

plant biology↗

bioRxiv2019

Variation and inheritance of small RNAs in maize inbreds and F1 hybrids

Small RNAs (sRNAs) regulate gene expression, play important roles in epigenetic pathways, and have been hypothesised to contribute to hybrid vigor in plants. Prior investigations have provided valuable insights into associations between sRNAs and heterosis, often using a single hybrid genotype or tissue. However, our understanding of the role of sRNAs and their potential value to plant breeding are limited by an incomplete picture of sRNA variation between diverse genotypes and development stages. Here, we provide a deep exploration of sRNA variation and inheritance among a panel of 108 maize samples spanning five tissues from eight inbred parents and 12 hybrid genotypes, covering a spectrum of heterotic groups, genetic variation, and levels of heterosis for various traits. We document substantial developmental and genotypic influences on sRNA expression, with varying patterns for 21-nt, 22-nt and 24-nt sRNAs. We provide a detailed view of the distribution of sRNAs in the maize genome, revealing a complex make-up that also shows developmental plasticity, particularly for 22-nt sRNAs. sRNAs exhibited substantially more variation between inbreds as compared to observed variation for gene expression. In hybrids, we identify locus-specific examples of non-additive inheritance, mostly characterised as partial or complete dominance, but rarely outside the parental range. However, the global abundance of 21-nt, 22-nt and 24-nt sRNAs varies very little between inbreds and hybrids, suggesting that hybridization affects sRNA expression principally at specific loci rather than on a global scale. This study provides a valuable resource for understanding the potential role of sRNAs in hybrid vigor.\n\nOne-sentence summaryCharacterizing the roles of development and genotype in driving expression variation of different small RNA populations in maize inbreds and their F1 hybrids.

genomics↗

bioRxiv2019

Highly Genotype- and Tissue-specific Single-Parent Expression Drives Dynamic Gene Expression Complementation in Maize Hybrids

Maize exhibits tremendous gene expression variation between different lines. Complementation of diverse gene expression patterns in hybrids could play an important role in the manifestation of heterosis. In this study, we used transcriptome data of five different tissues from 33 maize inbreds and 89 hybrids (430 samples in total) to survey the global gene expression landscape of F1-hybrids relative to their inbred parents. Analysis of this data set revealed that single parent expression (SPE), which is defined as gene expression in only one of the two parents, while commonly observed, is highly genotype- and tissue-specific. Genes that have SPE in at least one pair of inbreds also tend to be tissue-specific. Genes with SPE caused by genomic presence/absence variation (PAV SPE) are much more frequently expressed in hybrids than genes that are present in the genome of both inbreds, but expressed in only a single-parent (non-PAV SPE) (74.7% vs. 59.7%). For non-PAV SPE genes, allele specific expression was used to investigate whether parental alleles not expressed in the inbred line (\"silent allele\") can be actively transcribed in the hybrid. We found that expression of the silent allele in the hybrid is relatively rare ([~]6.3% of non-PAV SPE genes), but is observed in almost all hybrids and tissues. Non-PAV SPE genes with expression of the silent allele in the hybrid are more likely to exhibit above high-parent expression level in the hybrid than those that do not express the silent allele. Finally, both PAV SPE and non-PAV SPE genes are highly enriched for being classified as non-syntenic, but depleted for curated genes with experimentally determined functions. This study provides a more comprehensive understanding of the potential role of non-PAV SPE and PAV SPE genes in heterosis.

genomics↗

bioRxiv2019

Multiple QTL mapping in autopolyploids: a random-effect model approach with application in a hexaploid sweetpotato full-sib population

In developing countries, the sweetpotato, Ipomoea batatas (L.) Lam. (2n = 6x = 90), is an important autopolyploid species, both socially and economically. However, quantitative trait loci (QTL) mapping has remained limited due to its genetic complexity. Current fixed-effect models can only fit a single QTL and are generally hard to interpret. Here we report the use of a random-effect model approach to map multiple QTL based on score statistics in a sweetpotato bi-parental population ( Beauregard x Tanzania) with 315 full-sibs. Phenotypic data were collected for eight yield component traits in six environments in Peru, and jointly predicted means were obtained using mixed-effect models. An integrated linkage map consisting of 30,684 markers distributed along 15 linkage groups (LGs) was used to obtain the genotype conditional probabilities of putative QTL at every cM position. Multiple interval mapping was performed using our R package QTLPOLY and detected a total of 41 QTL, ranging from one to ten QTL per trait. Some regions, such as those on LGs 3 and 15, were consistently detected among root number and yield traits and provided basis for candidate gene search. In addition, some QTL were found to affect commercial and noncommercial root traits distinctly. Further best linear unbiased predictions allowed us to characterize additive allele effects as well as to compute QTL-based breeding values for selection. Together with quantitative genotyping and its appropriate usage in linkage analyses, this QTL mapping methodology will facilitate the use of genomic tools in sweetpotato breeding as well as in other autopolyploids.

genetics↗

bioRxiv2017

Identification of Iridoid Synthases from Nepeta species: Iridoid cyclization does not determine nepetalactone stereochemistry

Graphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC=\"FIGDIR/small/179572_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (91K):\norg.highwire.dtl.DTLVardef@cc600dorg.highwire.dtl.DTLVardef@1b6240dorg.highwire.dtl.DTLVardef@f8e1beorg.highwire.dtl.DTLVardef@1acb9dd_HPS_FORMAT_FIGEXP M_FIG Iridoid synthase from Nepeta cateria (catnip) and Nepeta mussinii, have been cloned and characterized.\n\nC_FIG AbstractNepetalactones are iridoid monoterpenes with a broad range of biological activities produced by plants in the Nepeta genus. However, none of the genes for nepetalactone biosynthesis have been discovered. Here we report the transcriptomes of two Nepeta species, each with distinctive profiles of nepetalactone stereoisomers. As a starting point for investigation of nepetalactone biosynthesis in Nepeta, these transcriptomes were used to identify candidate genes for iridoid synthase homologs, an enzyme that has been shown to form the core iridoid skeleton in several iridoid producing plant species. Iridoid synthase homologs identified from the transcriptomes were cloned, heterologously expressed, and then assayed with the 8-oxogeranial substrate. These experiments revealed that catalytically active iridoid synthase enzymes are present in Nepeta, though there are unusual mutations in key active site residues. Nevertheless, these enzymes exhibit similar catalytic activity and product profile compared to previously reported iridoid synthases from other plants. Notably, four nepetalactone stereoisomers with differing stereochemistry at the 4 and 7 positions - which are generated during the iridoid synthase reaction - are observed at different ratios in various Nepeta species. This work strongly suggests that the variable stereochemistry at these 4 and 7 positions of nepetalactone diastereomers is established further downstream in the iridoid pathway in Nepeta. Overall, this work provides a gateway into the biosynthesis of nepetalactones in Nepeta.\n\nHighlightsO_LISpecies within the Nepeta genus (such as catnip) produce nepetalactone iridoids\nC_LIO_LIThe enzymes that produce the iridoid scaffold of nepetalactone were identified from two species of Nepeta\nC_LIO_LIThe iridoid synthase enzymes are not responsible for the stereochemical variation in these iridoids\nC_LI

biochemistry↗