GLBRC Data Sets

This Data Catalog is a collection of data from GLBRC's Sustainability research carried out in Michigan and Wisconsin. The Data Catalog summarizes each data table in order to allow the GLBRC community to better understand the data that have been collected and encourage collaboration.

This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass-based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation.

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems.

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. It has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces.

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will be maintained only if the benefit outweighs the cost, which remains incompletely understood.

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question.

Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming.

The formation of complex traits is the consequence of genotype and activities at multiple molecular levels. However, connecting genotypes and these activities to complex traits remains challenging. Here, we investigate whether integrating genomic, transcriptomic, and methylomic data can improve prediction for six Arabidopsis traits.

Mitigating the effects of climate stress on crops is important for global food security. The microbiome associated with plant roots, the rhizobiome, can harbor beneficial microbes that alleviate stress, but the factors influencing their recruitment are unclear.

Aromatic compounds are an important source of commodity chemicals traditionally produced from fossil fuels. Aromatics derived from plant lignin can potentially be converted into commodity chemicals through depolymerization followed by microbial funneling of monomers and low molecular weight oligomers.

Maximum likelihood (ML) phylogenetic inference is widely used in phylogenomics. As heuristic searches most likely find suboptimal trees, it is recommended to conduct multiple (e.g., ten) tree searches in phylogenetic analyses. However, beyond its positive role, how and to what extent multiple tree searches aid ML phylogenetic inference remains poorly explored.

Scientific advances due to conceptual or technological innovations can be revealed by examining how research topics have evolved. But such topical evolution is difficult to uncover and quantify because of the large body of literature and the need for expert knowledge in a wide range of areas in a field.

Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors.

Knowing where and when croplands have been abandoned or otherwise removed from cultivation is fundamental to evaluating future uses of these areas, e.g. as sites for ecological restoration, recultivation, bioenergy production, or other uses.

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Two general paradigms have been proposed to explain this variation: (i) trade-offs between performance efficiency and breadth and (ii) the joint influence of extrinsic (environmental) and intrinsic (genomic) factors.

How genomic differences contribute to phenotypic differences is a major question in biology. The recently characterized genomes, isolation environments, and qualitative patterns of growth on 122 sources and conditions of 1,154 strains from 1,049 fungal species (nearly all known) in the yeast subphylum Saccharomycotina provide a powerful, yet complex, dataset for addressing this question.

The Saccharomycotina yeasts ("yeasts" hereafter) are a fungal clade of scientific, economic, and medical significance. Yeasts are highly ecologically diverse, found across a broad range of environments in every biome and continent on earth; however, little is known about what rules govern the macroecology of yeast species and their range limits in the wild.

When Saccharomyces cerevisiae grows on mixtures of glucose and galactose, galactose utilization is repressed by glucose, and induction of the GAL gene network only occurs when glucose is exhausted.

BACKGROUND: Cost-effective production of biofuels from lignocellulose requires the fermentation of D-xylose. Many yeast species within and closely related to the genera Spathaspora and Scheffersomyces (both of the order Serinales) natively assimilate and ferment xylose. Other species consume xylose inefficiently, leading to extracellular accumulation of xylitol.

Delineation of microbial habitats within the soil matrix and characterization of their environments and metabolic processes are crucial to understand soil functioning, yet their experimental identification remains persistently limited.