A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A

嶺南通訊 Lingnan Newsletter (第63期)

https://commons.ln.edu.hk/lingnan_newsletter/1062/thumbnail.jp

Use of “default” parameter settings when analyzing single cell RNA sequencing data using Seurat: a biologist’s perspective

Aim: Analysis of large datasets has become integral to biological studies due to the advent of high throughput technologies such as next generation sequencing. Techniques for analyzing these large datasets are normally developed by bioinformaticists and statisticians, with input from biologists. Frequently, the end-user does not have the training or knowledge to make informed decisions on input parameter settings required to implement the analyses pipelines. Instead, the end-user relies on “default” settings present within the software packages, consultations with in-house bioinformaticists, or on methods described in previous publications. The aim of this study was to explore the effects of altering default parameters on the cell clustering solutions generated by a common pipeline implemented in the Seurat R package that is used to cluster cells based on single cell RNA sequencing (scRNAseq) data.Methods: We systematically assessed the effect of altering input parameters by performing iterative analyses on a single scRNAseq dataset. We compared the clustering solutions using the different input parameters to determine which parameters have a large effect on cell clustering solutions.Results: We used a range of input parameters for many, but not all, of the input parameters required by the Seurat R pipeline. We found that some input parameters had a very small effect on the clustering solution, while other parameters had a much larger effect.Conclusion: We conclude that, when implementing the Seurat R package, the “default” parameters should be used with caution. We identified specific parameters that have a significant effect on clustering solutions

Data from: Genome-guided investigation of plant natural product biosynthesis

The medicinal plant Madagascar periwinkle, Catharanthus roseus (L.) G. Don, produces hundreds of biologically active monoterpene-derived indole alkaloid (MIA) metabolites and is the sole source of the potent, expensive anti-cancer compounds vinblastine and vincristine. Access to a genome sequence would enable insights into the biochemistry, control, and evolution of genes responsible for MIA biosynthesis. However, generation of a near-complete, scaffolded genome is prohibitive to small research communities due to the expense, time, and expertise required. In this study, we generated a genome assembly for C. roseus which provides a near comprehensive representation of the genic space that revealed the genomic context of key points within the MIA biosynthetic pathway including physically clustered genes, tandem gene duplication, expression subfunctionalization, and putative neofunctionalization. The genome sequence also facilitated high resolution coexpression analyses that revealed three distinct clusters of co-expression within the components of the MIA pathway. Coordinated biosynthesis of precursors and intermediates throughout the pathway appear to be a feature of vinblastine/vincristine biosynthesis. The C. roseus genome also revealed localization of enzyme-rich genic regions and transporters near known biosynthetic enzymes, highlighting how even a draft genome sequence can empower the study of high-value specialized metabolites

A Foundation for Provitamin A Biofortification of Maize: Genome-Wide Association and Genomic Prediction Models of Carotenoid Levels

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A

A foundation for provitamin A biofortification of maize: genome-wide association and genomic prediction models of carotenoid levels.

Efforts are underway for development of crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency. As a global staple crop with considerable variation in kernel carotenoid composition, maize (Zea mays L.) could have a widespread impact. We performed a genome-wide association study (GWAS) of quantified seed carotenoids across a panel of maize inbreds ranging from light yellow to dark orange in grain color to identify some of the key genes controlling maize grain carotenoid composition. Significant associations at the genome-wide level were detected within the coding regions of zep1 and lut1, carotenoid biosynthetic genes not previously shown to impact grain carotenoid composition in association studies, as well as within previously associated lcyE and crtRB1 genes. We leveraged existing biochemical and genomic information to identify 58 a priori candidate genes relevant to the biosynthesis and retention of carotenoids in maize to test in a pathway-level analysis. This revealed dxs2 and lut5, genes not previously associated with kernel carotenoids. In genomic prediction models, use of markers that targeted a small set of quantitative trait loci associated with carotenoid levels in prior linkage studies were as effective as genome-wide markers for predicting carotenoid traits. Based on GWAS, pathway-level analysis, and genomic prediction studies, we outline a flexible strategy involving use of a small number of genes that can be selected for rapid conversion of elite white grain germplasm, with minimal amounts of carotenoids, to orange grain versions containing high levels of provitamin A

Data from: Novel loci underlie natural variation in vitamin E levels in maize grain

Tocopherols, tocotrienols and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot Arabidopsis thaliana, which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are non-photosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5,000-line U.S. maize (Zea mays) nested association-mapping panel. Fifty-two quantitative trait loci (QTL) for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted, given that, like most major cereal crops, maize grain is non-photosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops