About this Research Topic
Native and amenity grasses are a critical part of the landscape and provide a large number of ecosystem services. Many of these species are polyploid, with small chromosomes and complex inheritance patterns. Although several of these grasses have been improved through conventional breeding, detailed genomic information is absent for a majority of these species. This lack of data has often proved to be a significant roadblock for the continued improvement and enhanced use of these grasses. More recently, the selection of native grasses specifically for biofuel end-uses has resulted in large-scale genomic data for several C-4 grasses. Additionally other research groups have utilized a variety of genomic and functional genomic techniques to augment genetic, germplasm and related resources for other understudied grasses.
Combined, these data indicate that many of the experiments once confined to model plants, such as rice and Arabidopsis can be reasonably pursued in just about any species. However, the details accruing from studies using model dicots and monocots have proved to be essential in creating molecular frameworks in these understudied species. Although a 1:1 functional relationship of homologous genes has generally been assumed, they may not occur for every gene across species. This is particularly true for transcription factors. However, unbiased, large scale investigations at the transcriptome, proteome and metabolome can be used to develop networks in understudied species, and correlative predictions can be derived from such analyses.
In this Research Topic, our intent is to highlight the state-of-the-art research in these understudied but important grasses.
Combined, these data indicate that many of the experiments once confined to model plants, such as rice and Arabidopsis can be reasonably pursued in just about any species. However, the details accruing from studies using model dicots and monocots have proved to be essential in creating molecular frameworks in these understudied species. Although a 1:1 functional relationship of homologous genes has generally been assumed, they may not occur for every gene across species. This is particularly true for transcription factors. However, unbiased, large scale investigations at the transcriptome, proteome and metabolome can be used to develop networks in understudied species, and correlative predictions can be derived from such analyses.
In this Research Topic, our intent is to highlight the state-of-the-art research in these understudied but important grasses.
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