RNA-Seq Blog Transcriptome Research & Industry News
RNA-Seq was used to examine the microbial, eukaryotic, and viral communities in water catchments (‘tanks’) formed by tropical bromeliads from Costa Rica. In total, transcripts with taxonomic affiliation to a wide array of bacteria, archaea, and eukaryotes, were observed, as well as RNA-viruses that appeared related to the specific presence of eukaryotes. Bacteria from 25 phyla appeared to comprise the majority of transcripts in one tank (Wg24), compared to only 14 phyla in the other (Wg25). Conversely, eukaryotes from only 16 classes comprised the majority of transcripts in Wg24, compared to 24 classes in the Wg25, revealing a greater eukaryote diversity in the latter.
Given that these bromeliads had tanks of similar size (i.e. vertical oxygen gradient), and were neighboring with presumed similar light regime and acquisition of leaf litter through-fall, it is possible that pH was the factor governing these differences in bacterial and eukaryotic communities (Wg24 had a tank pH of 3.6 and Wg25 had a tank pH of 6.2). Archaeal diversity was similar in both tanks, represented by 7 orders, with the exception of Methanocellales transcripts uniquely recovered from Wg25. Based on measures of FPKG (fragments mapped per kilobase of gene length), genes involved in methanogenesis, in addition to a spirochaete flagellin gene, were among those most highly expressed in Wg25. Conversely, aldehyde dehydrogenase and monosaccharide-binding protein were among genes most highly expressed in Wg24.
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Top 10 most highly expressed bacterial and archaeal functional transcripts based on fragments mapped per kilobase of gene length (FPKG), as annotated by IMG, and not including hypothetical genes.
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Functional gene Organism FPKG FPKG normala Wg24 Aldehyde dehydrogenase (NAD) Acidobacterium capsulatum 25,799 1902 Coenzyme-B sulfoethylthiotransferase (i.e. methyl-coenzyme M reductase) Methanoregula boonei 18,004 1327 Monosaccharide-binding protein Spirochaeta aurantia 10,866 801 Copper amine oxidase-like protein Clostridium thermocellum 10,117 746 5,10-Methylenetetrahydromethanopterin reductase Methanoregula formicicum 9453 697 Chaperonin GroL Thermaerobacter subterraneus 8523 628 Cytoplasmic filament protein A Spirochaeta smaragdinae 7818 576 Periplasmic sugar-binding protein Spirochaeta caldaria 7211 532 Flagellin domain protein Spirochaeta smaragdinae 4296 317 Coenzyme F420 hydrogenase Methanoregula boonei 3864 285 Wg25 Periplasmic flagellin Leptospira interrogans 2,541,718 236,194 Methyl-coenzyme M reductase operon D Methanoregula formicicum 8868 824 Methyl-coenzyme M reductase operon C Methanoregula formicicum 7705 716 Methyl-coenzyme M reductase, g subunit Methanoregula boonei 6525 606 Elongation factor Ts Flavobacteria sp. BAL38 6373 592 Methyl-coenzyme M reductase, b subunit Methanoregula formicicum 5432 505 Glyceraldehyde-3-phosphate dehydrogenase Enterobacter cancerogenus 5355 498 Methyl-coenzyme M reductase, a subunit Methanolinea tarda 4799 446 Cytochrome c oxidase, subunit III Rhodopseudomonas palustris 3869 360 Coenzyme F420 hydrogenase Methanoregula boonei 3780 351 -
- a FPKG values were normalized within each library (raw FPKG/rRNA subtracted reads ∗ 1,000,000) in order to compare between libraries.
The ability to observe specific presence of insect, plant, and fungi-associated RNA-viruses was unexpected. As with other techniques, there are inherent biases in the use of RNA-Seq, however, these data suggest the possibility of understanding the entire community, including ecological interactions, via simultaneous analysis of microbial, eukaryotic, and viral transcripts.
