Biology subjects

Kremling, K.

Publications and source records attributed to Kremling, K..

3 recordsLinked to original sources

bioRxiv2018

Metabolome-scale genome-wide association studies reveal chemical diversity and genetic control of maize specialized metabolites

One Sentence SummaryHPLC-MS metabolite profiling of maize seedlings, in combination with genome-wide association studies, identifies numerous quantitative trait loci that influence the accumulation of foliar metabolites.\n\nAbstractCultivated maize (Zea mays) retains much of the genetic and metabolic diversity of its wild ancestors. Non-targeted HPLC-MS metabolomics using a diverse panel of 264 maize inbred lines identified a bimodal distribution in the prevalence of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated primarily by flavonoid abundance, maize varieties (stiff-stalk, non-stiff-stalk, tropical, sweet corn, and popcorn) were differentiated predominantly by benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often metabolically related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS dataset constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.

genetics↗

bioRxiv2018

Transcriptome-wide association supplements genome-wide association in Zea mays

Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The potential of using endophenotypes for dissecting traits of interest remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299 genotype and 7 tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation for agronomic and seed quality (carotenoid, tocochromanol) traits is regulatory. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits, beating the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This improves not only the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants.\n\nAuthor summaryWe examined the ability to associate variability in gene expression directly with terminal phenotypes of interest, as a supplement linking genotype to phenotype. We found that transcriptome-wide association studies (TWAS) are a useful accessory to genome-wide association studies (GWAS). In a combined test with GWAS results, TWAS improves the capacity to re-detect genes known to underlie quantitative trait loci for kernel and agronomic phenotypes. This improves not only the capacity to link genes to phenotypes, but also illustrates the widespread importance of regulation for phenotype.

genetics↗

bioRxiv2018

Tripsacum de novo transcriptome assemblies reveal parallel gene evolution with maize after ancient polyploidy

Plant genomes reduce in size following a whole genome duplication event, and one gene in a duplicate gene pair can lose function in absence of selective pressure to maintain duplicate gene copies. Maize and its sister genus, Tripsacum, share a genome duplication event that occurred 5 to 26 million years ago. Because few genomic resources for Tripsacum exist, it is unknown whether Tripsacum grasses and maize have maintained a similar set of genes under purifying selection. Here we present high quality de novo transcriptome assemblies for two species: Tripsacum dactyloides and Tripsacum floridanum. Genes with experimental protein evidence in maize were good candidates for genes under purifying selection in both genera because pseudogenes by definition do not produce protein. We tested whether 15,160 maize genes with protein evidence are resisting gene loss and whether their Tripsacum homologs are also resisting gene loss. Protein-encoding maize transcripts and their Tripsacum homologs have higher GC content, higher gene expression levels, and more conserved expression levels than putatively untranslated maize transcripts and their Tripsacum homologs. These results indicate that gene loss is occurring in a similar fashion in both genera after a shared ancient polyploidy event. The Tripsacum transcriptome assemblies provide a high quality genomic resource that can provide insight into the evolution of maize, an highly valuable crop worldwide.\n\nCore ideasO_LIMaize genes with protein evidence have higher expression and GC content\nC_LIO_LITripsacum homologs of maize genes exhibit the same trends as in maize\nC_LIO_LIMaize proteome genes have more highly correlated gene expression with Tripsacum\nC_LIO_LIExpression dominance for homeologs occurs similarly between maize and Tripsacum\nC_LIO_LIA similar set of genes may be decaying into pseudogenes in maize and Tripsacum\nC_LI

genomics↗