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 usefulness of endophenotypes for delineating the regulatory landscape of the genome and genetic dissection of complex trait variation remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299-genotype and seven-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 acts through altered transcript abundance for maize kernel traits, including 30 grain carotenoid abundance traits, 20 grain tocochromanol abundance traits, and 22 field-measured agronomic traits. 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 largely 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 than the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This not only improves the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants

Analysis of the mtDNA insertion site on chromosome 9L in maize inbreds using fluorescence in situ hybridization

Abstract only availableAlmost all eukaryotic nuclear genomes show evidence of organellar DNA insertions originating from mitochondrial DNA (mtDNA) and chloroplast DNA (cpDNA). While the precise mechanisms of incorporation remain unknown, the phenomenon is frequent and ongoing in many species. In Zea mays, mtDNA insertions differ among inbred lines. A very large mtDNA insertion is found near the centromere of the long arm of chromosome 9 in the B73 inbred. This insertion contains the majority of the mitochondrial genome, while a similarly positioned insertion in the Mo17 inbred line is much smaller. We used recombinant inbred lines from the intermated B73 x Mo17 (IBM) population to determine if the insertions are indeed at the same position. We selected lines with recombination in this region of chromosome 9L. Using two mtDNA probes present in the insertions in both B73 and Mo17, we applied a chromosome painting technique called fluorescence in situ hybridization (FISH) to root-tip metaphase chromosomes and looked for the presence of the mtDNA site on chromosome 9L in the selected IBM lines. If the mtDNA insertion sites in B73 and Mo17 are at different locations, then at least one of the recombinant IBM lines should not display a mtDNA insertion at the chromosome 9 location. However, all of the recombinant IBM lines examined displayed the mtDNA insertion site on chromosome 9L. This indicates that the Mo17 and B73 insertions likely occupy the same region on the chromosome. Furthermore, this suggests that the large mtDNA insertion occurred recently in B73 at a pre-existing site present in both B73 and Mo17.NSF-REU Program in Biological Sciences & Biochemistr

Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence

Deep learning methodologies have revolutionized prediction in many fields and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological systems and can result in false positives and spurious conclusions. We developed two approaches that account for evolutionary relatedness in machine learning models: (i) gene-family–guided splitting and (ii) ortholog contrasts. The first approach accounts for evolution by constraining model training and testing sets to include different gene families. The second approach uses evolutionarily informed comparisons between orthologous genes to both control for and leverage evolutionary divergence during the training process. The two approaches were explored and validated within the context of mRNA expression level prediction and have the area under the ROC curve (auROC) values ranging from 0.75 to 0.94. Model weight inspections showed biologically interpretable patterns, resulting in the hypothesis that the 3′ UTR is more important for fine-tuning mRNA abundance levels while the 5′ UTR is more important for large-scale changes

Unexpected changes in the oxic/anoxic interface in the Black Sea

THE Black Sea is the largest anoxic marine basin in the world today1. Below the layer of oxygenated surface water, hydrogen sulphide builds up to concentrations as high as 425 μM in the deep water down to a maximum depth of 2,200 m (ref. 2). The hydrographic regime is characterized by low-salinity surface water of river origin overlying high-salinity deep water of Mediterranean origin1,3. A steep pycnocline, centred at about 50 m is the primary physical barrier to mixing and is the origin of the stability of the anoxic (oxygen/hydrogen sulphide) interface. Here we report new observations, however, that indicate dramatic changes in the oceanographic characteristics of the anoxic interface of the Black Sea over decadal or shorter timescales. The anoxic, sulphide-containing interface has moved up in the water column since the last US cruises in 1969 and 1975. In addition, a suboxic zone overlays the sulphide-containing deep water. The expected overlap of oxygen and sulphide was not present. We believe that these observations result from horizontal mixing or flushing events that inject denser, saltier water into the relevant part of the water column. It is possible that man-made reduction in freshwater inflow into the Black Sea could cause these changes, although natural variability cannot be discounted. © 1989 Nature Publishing Group

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 ( L.) and its sister genus, , share a genome duplication event that occurred 5 to 26 million years ago. Because few genomic resources for exist, it is unknown whether grasses and maize have maintained a similar set of genes that have resisted decay into pseudogenes. Here we present high-quality de novo transcriptome assemblies for two species: (L.) L. and Porter ex Vasey. Genes with experimental protein evidence in maize were good candidates for genes resistant to pseudogenization 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 homologs are also resisting gene loss. Protein-encoding maize transcripts and their homologs have higher guanine–cytosine (GC) content, higher gene expression levels, and more conserved expression levels than putatively untranslated maize transcripts and their homologs. These results suggest that similar genes may be decaying into pseudogenes in both genera after a shared ancient polyploidy event. The transcriptome assemblies provide a high-quality genomic resource that can provide insight into the evolution of maize, a highly valuable crop worldwide

Quantitative Genetics of the Maize Leaf Microbiome

The degree to which the genotype of an organism can affect the composition of its associated microbial communities ("microbiome") varies by organism and habitat, and in many cases is unknown. We analyzed the metabolically active bacteria of maize leaves across 300 diverse maize lines growing in a common environment. We performed comprehensive heritability analysis for 49 community diversity metrics, 380 bacterial clades, and 9,042 predicted metagenomic functions. We find that only a few bacterial clades (5) and diversity metrics (2) are significantly heritable, while a much larger number of metabolic functions (200) are. Many of these associations appear to be driven by the Methylobacteria in each sample. Among these heritable metabolic traits, Fisher's exact test identifies significant overrepresentation of traits relating to short-chain carbon metabolism, secretion, and nitrotoluene degradation. Genome-wide association analysis identified a small number of associated loci for these heritable traits, including two that affect multiple traits. Our results indicate that while most of the maize leaf microbiome composition is driven by environmental factors and/or stochastic founder events, a subset of bacterial taxa and metabolic functions is nonetheless significantly impacted by host genetics. Additional work will be needed to identify the exact nature of these interactions and what effects they may have on their host

Identification of miRNA-eQTLs in maize mature leaf by GWAS

Background: MiRNAs play essential roles in plant development and response to biotic and abiotic stresses through interaction with their target genes. The expression level of miRNAs shows great variations among different plant accessions, developmental stages, and tissues. Little is known about the content within the plant genome contributing to the variations in plants. This study aims to identify miRNA expression-related quantitative trait loci(miR-QTLs) in the maize genome. Results: The miRNA expression level from next generation sequencing (NGS) small RNA libraries derived from mature leaf samples of the maize panel (200 maize lines) was estimated as phenotypes, and maize Hapmap v3.2.1 was chosen as the genotype for the genome-wide association study (GWAS). A total of four significant miR-eQTLs were identified contributing to miR156k-5p, miR159a-3p, miR390a-5p and miR396e-5p, and all of them are transeQTLs. In addition, a strong positive coexpression of miRNA was found among five miRNA families. Investigation of the effects of these miRNAs on the expression levels and target genes provided evidence that miRNAs control the expression of their targets by suppression and enhancement. Conclusions: These identified significant miR-eQTLs contribute to the diversity of miRNA expression in the maize penal at the developmental stages of mature leaves in maize, and the positive and negative regulation between miRNA and its target genes has also been uncovered