Abstract
For lignocellulosic bioenergy to become a viable alternative to traditional energy production methods, rapid increases in conversion efficiency and biomass yield must be achieved. Increased productivity in bioenergy production can be achieved through concomitant gains in processing efficiency as well as genetic improvement of feedstock that have the potential for bioenergy production at an industrial scale. The purpose of this review is to explore the genetic and genomic resource landscape for the improvement of a specific bioenergy feedstock group, the C4 bioenergy grasses. First, bioenergy grass feedstock traits relevant to biochemical conversion are examined. Then we outline genetic resources available bioenergy grasses for mapping bioenergy traits to DNA markers and genes. This is followed by a discussion of genomic tools and how they can be applied to understanding bioenergy grass feedstock trait genetic mechanisms leading to further improvement opportunities.
Highlights
Paleobioenergy obtained from coal, natural gas and oil deposits has allowed mankind to implement unprecedented technological advances in the last 250 years
We believe that gene interaction networks will significantly reduce the candidate gene list underlying a bioenergy trait if the requirement is made that interacting genetic signal genomic positions must overlap with tightly interacting genes from the network (e.g. [323])
We conclude that a deeper understanding of feedstock traits affecting bioconversion such as enzyme inhibition, cellulose accessibility, and enzyme adsorption will ameliorate hurdles to bioenergy production so that it is competitive with current fossil fuel based transportation fuels
Summary
Paleobioenergy obtained from coal, natural gas and oil deposits has allowed mankind to implement unprecedented technological advances in the last 250 years. There was a noticeable difference in enzyme recovery between dilute-acid and alkali pretreated samples, where alkali pretreated samples were able to desorb a larger amount of cellulase While this discussion is focused on the putative industrial processes, it may be that specific feedstock varieties naturally exhibit lower adsorption rates that would further enhance the engineering endeavors. Adsorption has been shown to be correlated with the initial rate of hydrolysis, while enzyme desorption is essential for enzyme recycling and reducing the cost of enzymes in bioenergy production While these process components are being examined at the engineering level, a simple screen of existing bioenergy grass varieties could identify genotypes with a favorable trait baseline making the process engineering task less difficult. It is at the intersection of genetics and genomics that complex bioenergy traits, which by definition are polygenic, can be tested as a genetic sub-system as opposed to breaking the system into individual genetic components such as a single largeeffect QTL
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