Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes

Genetics and “omics” studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.&nbsp

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices

Tree Peony Species Are a Novel Resource for Production of α-Linolenic Acid

Tree peony is known worldwide for its excellent ornamental and medical values, but recent reports that their seeds contain over 40% α-linolenic acid (ALA), an essential fatty acid for humans drew additional interest of biochemists. To understand the key factors that contribute to this rich accumulation of ALA, we carried out a comprehensive study of oil accumulation in developing seeds of nine wild tree peony species. The fatty acid content and composition was highly variable among the nine species; however, we selected a high- (P. rockii) and low-oil (P. lutea) accumulating species for a comparative transcriptome analysis. Similar to other oilseed transcriptomic studies, upregulation of select genes involved in plastidial fatty acid synthesis, and acyl editing, desaturation and triacylglycerol assembly in the endoplasmic reticulum was noted in seeds of P. rockii relative to P. lutea. Also, in association with the ALA content, transcript levels for fatty acid desaturases (SAD, FAD2 and FAD3), which encode for enzymes necessary for polyunsaturated fatty acid synthesis were higher in P. rockii compared to P. lutea. We further showed that the overexpression of PrFAD2 and PrFAD3 in Arabidopsis increased linoleic and α-linolenic acid content, respectively and modulated their final ratio in the seed oil. In conclusion, we identified the key steps that contribute to efficient ALA synthesis and validated the necessary desaturases in P. rockii that are responsible for not only increasing oil content but also modulating 18:2/18:3 ratio in seeds. Together, these results will aid to improve essential fatty acid content in seeds of tree peonies and other crops of agronomic interest

Ontologies as Integrative Tools for Plant Science

Premise of the study: Bio-ontologies are essential tools for accessing and analyzing the rapidly growing pool of plant genomic and phenomic data. Ontologies provide structured vocabularies to support consistent aggregation of data and a semantic framework for automated analyses and reasoning. They are a key component of the semantic web. Methods: This paper provides background on what bio-ontologies are, why they are relevant to botany, and the principles of ontology development. It includes an overview of ontologies and related resources that are relevant to plant science, with a detailed description of the Plant Ontology (PO). We discuss the challenges of building an ontology that covers all green plants (Viridiplantae). Key results: Ontologies can advance plant science in four keys areas: (1) comparative genetics, genomics, phenomics, and development; (2) taxonomy and systematics; (3) semantic applications; and (4) education. Conclusions: Bio-ontologies offer a flexible framework for comparative plant biology, based on common botanical understanding. As genomic and phenomic data become available for more species, we anticipate that the annotation of data with ontology terms will become less centralized, while at the same time, the need for cross-species queries will become more common, causing more researchers in plant science to turn to ontologies.Keywords: Bio-ontologies, Plant Ontology, Plant genomics, OBO Foundry, Plant systematics, Plant anatomy, Genome annotation, Semantic web, PhenomicsKeywords: Bio-ontologies, Plant Ontology, Plant genomics, OBO Foundry, Plant systematics, Plant anatomy, Genome annotation, Semantic web, Phenomic

Uncovering the genetic basis of seed amino acid composition in arabidopsis using a multi-omics integrative approach

Seeds are a vital source of protein in the diet of humans and livestock. However, protein composition in the seed is low, comprising about 10 percent of the total composition in the seed. Additionally, protein quality in the seed is poor due to low concentrations of certain essential amino acids (EAA). Since the body is unable to produce EAA, they must be consumed in the diet and failure to do so has detrimental, potentially irreversible, health implications that can result in death. In developing counties where meat and dairy are lacking, protein-energy malnutrition frequently occurs. In contrast, in developing countries large portions of seeds are used in the diet of livestock which must be supplemented with costly synthetic amino acids. Collectively seed amino acid composition of major crops are not sufficient to meet dietary requirements. Protein in the seed is comprised of free amino acids (FAA) and protein bound amino acids (PBAA) which have both been the targets of manipulation in order to create a seed with a more balanced amino acid profile. However, upon perturbations to the proteome, mutant seeds have demonstrated a rebalancing phenomenon where even large alterations to the amino acid composition activate a compensation mechanism that returns amino acid levels to a comparable composition to the wild-type. Although a lot is known about amino acid metabolic pathways, what regulates such rebalancing mechanisms is still unknown. However, despite the tight regulation, natural variation does exist in seed FAA and PBAA across Arabidopsis ecotypes with a unique composition specific to each ecotype; this suggests rebalancing has a genetic basis. Thus, the first step in seed biofortification efforts must be to first increase the fundamental understanding of the genetic basis of both FAA and PBAA composition in the seed. Chapter One of this dissertation gives a more in-depth introduction that elaborates on amino acid composition in the seed, the challenges identified in previous experimentation, and how the content of Chapter Two through Chapter Four builds upon and adds value to the area of seed amino acid research as a whole. Chapter Two focuses on uncovering the genes and biological processes that underly the regulation of free Glutamine which belongs to the Glutamate Family (Arginine, Proline, Glutamine, and Glutamate). Although Glutamine is not an EAA, it is a major nitrogencontaining amino acid that is transported to the seed; thus it's regulatory control is of particular interest. I harness the natural variation of Glutamine in a 360 Arabidopsis diversity panel to uncover key regulatory genes. Later, I validate observations from GWAS using both a quantitative trait locus (QTL) analysis and reverse genetic approaches to identify a unique, seed-specific Glutamine-glucosinolate relationship that alters nitrogen and sulfur homeostasis in the seed in the Arabidopsis 360 population. Such finds were substantial as they link primary and secondary metabolism in the seed. Chapter Three focuses on uncovering the genetic basis underlying PBAA composition in dry Arabidopsis seeds while expanding upon the work completed in Chapter Two. 576 high confidence candidate genes (HCCGs) are found through integration of GWAS using PBAA traits and transcriptomic analysis across seed development of two mutants showing active rebalancing. To reveal the underlying biological process, I further subject the HCCGs to a protein-protein interaction (PPI) network that strongly suggests that ribosomal genes and potentially other translational machinery may be in the heart of PBAA composition homeostasis and the proteomic rebalancing response. Chapter Four addresses the need of a comprehensive tool to efficiently and automatically analyze many biochemical derived-traits in GWAS, while also completing pre and post-GWAS analysis. Here, I present the R tool HAPPI GWAS, describing each step in the pipeline, and giving an example of its implementation. Lastly, Chapter Five reiterates the contributions of this dissertation to the field of seed amino acid research and provides insight into future direction and research projects. The results from this work are vital steps in understanding the complex regulatory mechanisms underlying amino acid composition in the seed which can be used in manipulating the amino acid pools in future translational crop research