Methodologies for probing the metatranscriptome of grassland soil

Metatranscriptomics provides an opportunity to identify active microbes and expressed genes in complex soil communities in response to particular conditions. Currently, there are a limited number of soil metatranscriptome studies to provide guidance for using this approach in this challenging matrix. Hence, we evaluated the technical challenges of applying soil metatranscriptomics to a highly diverse, low activity natural system. We used a non-targeted rRNA removal approach, duplex nuclease specific (DSN) normalization, to generate a metatranscriptomic library from field collected soil supporting a perennial grass, Miscanthus x giganteus (a biofuel crop), and evaluated its ability to provide insight into its active community members and their expressed protein-coding genes. We also evaluated various bioinformatics approaches for analyzing our soil metatranscriptome, including annotation of unassembled transcripts, de novo assembly, and aligning reads to known genomes. Further, we evaluated various databases for their ability to provide annotations for our metatranscriptome. Overall, our results emphasize that low activity, highly genetically diverse and relatively stable microbiomes, like soil, requires very deep sequencing to sample the transcriptome beyond the common core functions. We identified several key areas that metatranscriptomic analyses will benefit from including increased rRNA removal, assembly of short read transcripts, and more relevant reference bases while providing a priority set of expressed genes for functional assessment

RefSoil: A reference database of soil microbial genomes

A database of curated genomes is needed to better assess soil microbial communities and their processes associated with differing land management and environmental impacts. Interpreting soil metagenomic datasets with existing sequence databases is challenging because these datasets are biased towards medical and biotechnology research and can result in misleading annotations. We have curated a database of 922 genomes of soil-associated organisms (888 bacteria and 34 archaea). Using this database, we evaluated phyla and functions that are enriched in soils as well as those that may be underrepresented in RefSoil. Our comparison of RefSoil to soil amplicon datasets allowed us to identify targets that if cultured or sequenced would significantly increase the biodiversity represented within RefSoil. To demonstrate the opportunities to access these underrepresented targets, we employed single cell genomics in a pilot experiment to sequence 14 genomes. This effort demonstrates the value of RefSoil in the guidance of future research efforts and the capability of single cell genomics as a practical means to fill the existing genomic data gaps

Strategies to improve reference databases for soil microbiomes

Microbial populations in the soil are critical in our lives. The soil microbiome helps to grow our food, nourishing and protecting plants, while also providing important ecological services such as erosion protection, water filtration and climate regulation. We are increasingly aware of the tremendous microbial diversity that has a role in soil heath; yet, despite significant efforts to isolate microbes from the soil, we have accessed only a small fraction of its biodiversity. Even with novel cell isolation techniques

Methodologies for probing the metatranscriptome of grassland soil

Metatranscriptomics provides an opportunity to identify active microbes and expressed genes in complex soil communities in response to particular conditions. Currently, there are a limited number of soil metatranscriptome studies to provide guidance for using this approach in this challenging matrix. Hence, we evaluated the technical challenges of applying soil metatranscriptomics to a highly diverse, low activity natural system. We used a non-targeted rRNA removal approach, duplex nuclease specific (DSN) normalization, to generate a metatranscriptomic library from field collected soil supporting a perennial grass, Miscanthus x giganteus (a biofuel crop), and evaluated its ability to provide insight into its active community members and their expressed protein-coding genes. We also evaluated various bioinformatics approaches for analyzing our soil metatranscriptome, including annotation of unassembled transcripts, de novo assembly, and aligning reads to known genomes. Further, we evaluated various databases for their ability to provide annotations for our metatranscriptome. Overall, our results emphasize that low activity, highly genetically diverse and relatively stable microbiomes, like soil, requires very deep sequencing to sample the transcriptome beyond the common core functions. We identified several key areas that metatranscriptomic analyses will benefit from including increased rRNA removal, assembly of short read transcripts, and more relevant reference bases while providing a priority set of expressed genes for functional assessment.This is the accepted manuscript of an article published in Journal of Microbiological Methods, 131 (December 2016): 122-129, http://dx.doi.org/10.1016/j.mimet.2016.10.018. </p

RefSoil: A reference database of soil microbial genomes

A database of curated genomes is needed to better assess soil microbial communities and their processes associated with differing land management and environmental impacts. Interpreting soil metagenomic datasets with existing sequence databases is challenging because these datasets are biased towards medical and biotechnology research and can result in misleading annotations. We have curated a database of 922 genomes of soil-associated organisms (888 bacteria and 34 archaea). Using this database, we evaluated phyla and functions that are enriched in soils as well as those that may be underrepresented in RefSoil. Our comparison of RefSoil to soil amplicon datasets allowed us to identify targets that if cultured or sequenced would significantly increase the biodiversity represented within RefSoil. To demonstrate the opportunities to access these underrepresented targets, we employed single cell genomics in a pilot experiment to sequence 14 genomes. This effort demonstrates the value of RefSoil in the guidance of future research efforts and the capability of single cell genomics as a practical means to fill the existing genomic data gaps.This preprint is from bioRxiv 053397; doi: https://doi.org/10.1101/053397. Posted with permission.</p

Rapid establishment of a flowering cline in Medicago polymorpha after invasion of North America

To establish and spread in a new location, an invasive species must be able to carry out its life cycle in novel environmental conditions. A key trait underlying fitness is the shift from vegetative to reproductive growth through floral development. In this study, we used a common garden experiment and genotyping-by-sequencing to test whether the latitudinal flowering cline of the North American invasive plant Medicago polymorpha was translocated from its European native range through multiple introductions, or whether the cline rapidly established due to evolution following a genetic bottleneck. Analysis of flowering time in 736 common garden plants showed a latitudinal flowering time cline in both the native and invaded ranges where genotypes from lower latitudes flowered earlier. Genotyping-by-sequencing of 9,658 SNPs in 446 individuals revealed two major subpopulations of M. polymorpha in the native range, only one of which is present in the invaded range. Additionally, native range populations have higher genetic diversity than invaded range populations, suggesting that a genetic bottleneck occurred during invasion. All invaded range individuals are closely related to plants collected from native range populations in Portugal and southern Spain, and population assignment tests assigned invaded range individuals to this same narrow source region. Taken together, our results suggest that latitudinal clinal variation in flowering time has rapidly evolved across the invaded range despite a genetic bottleneck following introduction

Strategies to improve reference databases for soil microbiomes

Microbial populations in the soil are critical in our lives. The soil microbiome helps to grow our food, nourishing and protecting plants, while also providing important ecological services such as erosion protection, water filtration and climate regulation. We are increasingly aware of the tremendous microbial diversity that has a role in soil heath; yet, despite significant efforts to isolate microbes from the soil, we have accessed only a small fraction of its biodiversity. Even with novel cell isolation techniques,This article is available as an advance online publication at 10.1038/ismej.2016.168,</p

Data from: Associative nitrogen fixation (ANF) in switchgrass (Panicum virgatum) across a nitrogen input gradient

Associative N fixation (ANF), the process by which dinitrogen gas is converted to ammonia by bacteria in casual association with plants, has not been well-studied in temperate ecosystems. We examined the ANF potential of switchgrass (Panicum virgatum L.), a North American prairie grass whose productivity is often unresponsive to N fertilizer addition, via separate short-term 15N2 incubations of rhizosphere soils and excised roots four times during the growing season. Measurements occurred along N fertilization gradients at two sites with contrasting soil fertility (Wisconsin, USA Mollisols and Michigan, USA Alfisols). In general, we found that ANF potentials declined with long-term N addition, corresponding with increased soil N availability. Although we hypothesized that ANF potential would track plant N demand through the growing season, the highest root fixation rates occurred after plants senesced, suggesting that root diazotrophs exploit carbon (C) released during senescence, as C is translocated from aboveground tissues to roots for wintertime storage. Measured ANF potentials, coupled with mass balance calculations, suggest that ANF appears to be an important source of N to unfertilized switchgrass, and, by extension, to temperate grasslands in general

Roley_etal_2018_Nfix_SG_roots

During 2015, net nitrogen mineralization, net nitrification, soil nitrogen fixation, and root nitrogen fixation was measured in the Switchgrass Nitrogen Rate Experiment, at both Kellogg Biological Station (MI, USA) and Arlington Agricultural Research Station (WI, USA). All replicates of 3 fertilizer treatments (0 kg N/ha/yr, 56 kg N/ha/yr, and 196 kg N/ha/yr) were measured 4 times: pre-fertilizer (May), post-fertilizer (June), at peak biomass (late July) and post-senescence (October). This data file contains the data on root N fixation, measured with 7-day lab incubations with 15N2 and glucose

Roley_etal_2018_Nfix_minnit_SG

During 2015, net nitrogen mineralization, net nitrification, soil nitrogen fixation, and root nitrogen fixation was measured in the Switchgrass Nitrogen Rate Experiment at both Kellogg Biological Station (MI, USA) and Arlington Agricultural Research Station (WI, USA). All replicates of fertilizer treatments SWF1 (0 kg N/ha/yr), SWF3 (56 kg N/ha/yr), and SWF8 (196 kg N/ha/yr) were measured 4 times: pre-fertilizer (May), post-fertilizer (June), at peak biomass (late July) and post-senescence (October). This data file contains the data on net mineralization and net nitrification, measured with 28-day lab incubations at constant moisture and temperature, and soil N fixation, measured with 7-day lab incubations with 15N2 and glucose