PREDICTING COMPLEX PHENOTYPE-GENOTYPE RELATIONSHIPS IN GRASSES: A SYSTEMS GENETICS APPROACH

It is becoming increasingly urgent to identify and understand the mechanisms underlying complex traits. Expected increases in the human population coupled with climate change make this especially urgent for grasses in the Poaceae family because these serve as major staples of the human and livestock diets worldwide. In particular, Oryza sativa (rice), Triticum spp. (wheat), Zea mays (maize), and Saccharum spp. (sugarcane) are among the top agricultural commodities. Molecular marker tools such as linkage-based Quantitative Trait Loci (QTL) mapping, Genome-Wide Association Studies (GWAS), Multiple Marker Assisted Selection (MMAS), and Genome Selection (GS) techniques offer promise for understanding the mechanisms behind complex traits and to improve breeding programs. These methods have shown some success. Often, however, they cannot identify the causal genes underlying traits nor the biological context in which those genes function. To improve our understanding of complex traits as well improve breeding techniques, additional tools are needed to augment existing methods. This work proposes a knowledge-independent systems-genetic paradigm that integrates results from genetic studies such as QTL mapping, GWAS and mutational insertion lines such as Tos17 with gene co-expression networks for grasses--in particular for rice. The techniques described herein attempt to overcome the bias of limited human knowledge by relying solely on the underlying signals within the data to capture a holistic representation of gene interactions for a species. Through integration of gene co-expression networks with genetic signal, modules of genes can be identified with potential effect for a given trait, and the biological function of those interacting genes can be determined

High-density multi-population consensus genetic linkage map for peach

Highly saturated genetic linkage maps are extremely helpful to breeders and are an essential prerequisite for many biological applications such as the identification of marker-trait associations, mapping quantitative trait loci (QTL), candidate gene identification, development of molecular markers for marker-assisted selection (MAS) and comparative genetic studies. Several high-density genetic maps, constructed using the 9K SNP peach array, are available for peach. However, each of these maps is based on a single mapping population and has limited use for QTL discovery and comparative studies. A consensus genetic linkage map developed from multiple populations provides not only a higher marker density and a greater genome coverage when compared to the individual maps, but also serves as a valuable tool for estimating genetic positions of unmapped markers. In this study, a previously developed linkage map from the cross between two peach cultivars ‘Zin Dai’ and ‘Crimson Lady’ (ZC2) was improved by genotyping additional progenies. In addition, a peach consensus map was developed based on the combination of the improved ZC2 genetic linkage map with three existing high-density genetic maps of peach and a reference map of Prunus. A total of 1,476 SNPs representing 351 unique marker positions were mapped across eight linkage groups on the ZC2 genetic map. The ZC2 linkage map spans 483.3 cM with an average distance between markers of 1.38 cM/marker. The MergeMap and LPmerge tools were used for the construction of a consensus map based on markers shared across five genetic linkage maps. The consensus linkage map contains a total of 3,092 molecular markers, consisting of 2,975 SNPs, 116 SSRs and 1 morphological marker associated with slow ripening in peach (SR). The consensus map provides valuable information on marker order and genetic position for QTL identification in peach and other genetic studies within Prunus and Rosaceae.info:eu-repo/semantics/publishedVersio

Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium

Over the last several decades, there has been rapid growth in the number and scope of agricultural genetics, genomics and breeding (GGB) databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, conducted a survey to assess the status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data sharing practices by AgBioData databases are in a healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that ontology use has not substantially changed since a similar survey was conducted in 2017. We recommend 1) providing training for database personnel in specific data sharing techniques, as well as in ontology use; 2) further study on what metadata is shared, and how well it is shared among databases; 3) promoting an understanding of data sharing and ontologies in the stakeholder community; 4) improving data sharing and ontologies for specific phenotypic data types and formats; and 5) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.Comment: 17 pages, 8 figure

The Future of Indiana’s Water Resources: A Report from the Indiana Climate Change Impacts Assessment

This report from the Indiana Climate Change Impacts Assessment (IN CCIA) applies climate change projections for the state to explore how continued changes in Indiana’s climate are going to affect all aspects of water resources, including soil water, evaporation, runoff, snow cover, streamflow, drought, and flooding. As local temperatures continue to rise and rainfall patterns shift, managing the multiple water needs of communities, natural systems, recreation, industry, and agriculture will become increasingly difficult. Ensuring that enough water is available in the right places and at the right times will require awareness of Indiana’s changing water resources and planning at regional and state levels

Tripal, a community update after 10 years of supporting open source, standards-based genetic, genomic and breeding databases

Online, open access databases for biological knowledge serve as central repositories for research communities to store, find and analyze integrated, multi-disciplinary datasets. With increasing volumes, complexity and the need to integrate genomic, transcriptomic, metabolomic, proteomic, phenomic and environmental data, community databases face tremendous challenges in ongoing maintenance, expansion and upgrades. A common infrastructure framework using community standards shared by many databases can reduce development burden, provide interoperability, ensure use of common standards and support long-term sustainability. Tripal is a mature, open source platform built to meet this need. With ongoing improvement since its first release in 2009, Tripal provides full functionality for searching, browsing, loading and curating numerous types of data and is a primary technology powering at least 31 publicly available databases spanning plants, animals and human data, primarily storing genomics, genetics and breeding data. Tripal software development is managed by a shared, inclusive governance structure including both project management and advisory teams. Here, we report on the most important and innovative aspects of Tripal after 11 years development, including integration of diverse types of biological data, successful collaborative projects across member databases, and support for implementing FAIR principles

A genetically anchored physical framework for Theobroma cacao cv. Matina 1-6

<p>Abstract</p> <p>Background</p> <p>The fermented dried seeds of <it>Theobroma cacao </it>(cacao tree) are the main ingredient in chocolate. World cocoa production was estimated to be 3 million tons in 2010 with an annual estimated average growth rate of 2.2%. The cacao bean production industry is currently under threat from a rise in fungal diseases including black pod, frosty pod, and witches' broom. In order to address these issues, genome-sequencing efforts have been initiated recently to facilitate identification of genetic markers and genes that could be utilized to accelerate the release of robust <it>T. cacao </it>cultivars. However, problems inherent with assembly and resolution of distal regions of complex eukaryotic genomes, such as gaps, chimeric joins, and unresolvable repeat-induced compressions, have been unavoidably encountered with the sequencing strategies selected.</p> <p>Results</p> <p>Here, we describe the construction of a BAC-based integrated genetic-physical map of the <it>T. cacao </it>cultivar Matina 1-6 which is designed to augment and enhance these sequencing efforts. Three BAC libraries, each comprised of 10× coverage, were constructed and fingerprinted. 230 genetic markers from a high-resolution genetic recombination map and 96 Arabidopsis-derived conserved ortholog set (COS) II markers were anchored using pooled overgo hybridization. A dense tile path consisting of 29,383 BACs was selected and end-sequenced. The physical map consists of 154 contigs and 4,268 singletons. Forty-nine contigs are genetically anchored and ordered to chromosomes for a total span of 307.2 Mbp. The unanchored contigs (105) span 67.4 Mbp and therefore the estimated genome size of <it>T. cacao </it>is 374.6 Mbp. A comparative analysis with <it>A. thaliana, V. vinifera</it>, and <it>P. trichocarpa </it>suggests that comparisons of the genome assemblies of these distantly related species could provide insights into genome structure, evolutionary history, conservation of functional sites, and improvements in physical map assembly. A comparison between the two <it>T. cacao </it>cultivars Matina 1-6 and Criollo indicates a high degree of collinearity in their genomes, yet rearrangements were also observed.</p> <p>Conclusions</p> <p>The results presented in this study are a stand-alone resource for functional exploitation and enhancement of <it>Theobroma cacao </it>but are also expected to complement and augment ongoing genome-sequencing efforts. This resource will serve as a template for refinement of the <it>T. cacao </it>genome through gap-filling, targeted re-sequencing, and resolution of repetitive DNA arrays.</p

Modes of Gene Duplication Contribute Differently to Genetic Novelty and Redundancy, but Show Parallels across Divergent Angiosperms

BACKGROUND: Both single gene and whole genome duplications (WGD) have recurred in angiosperm evolution. However, the evolutionary effects of different modes of gene duplication, especially regarding their contributions to genetic novelty or redundancy, have been inadequately explored. RESULTS: In Arabidopsis thaliana and Oryza sativa (rice), species that deeply sample botanical diversity and for which expression data are available from a wide range of tissues and physiological conditions, we have compared expression divergence between genes duplicated by six different mechanisms (WGD, tandem, proximal, DNA based transposed, retrotransposed and dispersed), and between positional orthologs. Both neo-functionalization and genetic redundancy appear to contribute to retention of duplicate genes. Genes resulting from WGD and tandem duplications diverge slowest in both coding sequences and gene expression, and contribute most to genetic redundancy, while other duplication modes contribute more to evolutionary novelty. WGD duplicates may more frequently be retained due to dosage amplification, while inferred transposon mediated gene duplications tend to reduce gene expression levels. The extent of expression divergence between duplicates is discernibly related to duplication modes, different WGD events, amino acid divergence, and putatively neutral divergence (time), but the contribution of each factor is heterogeneous among duplication modes. Gene loss may retard inter-species expression divergence. Members of different gene families may have non-random patterns of origin that are similar in Arabidopsis and rice, suggesting the action of pan-taxon principles of molecular evolution. CONCLUSION: Gene duplication modes differ in contribution to genetic novelty and redundancy, but show some parallels in taxa separated by hundreds of millions of years of evolution