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Supplemental Methods: RNA-SIP metatranscriptomic library preparation: At each temperature, four metatranscriptomic libraries were constructed, two from the 12C-control, named 12C-light and 12C-heavy and two from the 13C-experiment, named 13C-light and 13C-heavy (Figure 1). The two density fractions with the highest RNA concentration in the 12C-control incubation were combined to construct the 12Clight library, which represents the natural community. Similarly, two density fractions with the highest RNA concentration in the 13C-experiment incubation were combined to construct the 13C-heavy library, which represents the labeled autotrophic community. The other two libraries from each temperature, 12C-heavy and 13C-light were constructed to act as additional controls. To construct the 12C-heavy library, density fractions were chosen that corresponded to the same density fractions used to construct the 13C-heavy library. The 12C-heavy library represent the heavier density unlabeled community and acts as a key comparison to the 13C-heavy labeled community to confirm that the populations in the 13C-heavy have taken up the labeled isotope and are not naturally found at heavier nucleic acid densities. To construct the 13C-light library, density fractions were chosen that corresponded to the same density fractions used to construct the 12C-light library. The 13C-light library represents the lighter density community in the 13 C-experiment, which includes both labeled and unlabeled populations that are found at lighter densities. For each library, double stranded cDNA was constructed using SuperScript III First-strand synthesis system (Invitrogen, Grand Island, NY, USA) and mRNA second strand synthesis module (NEB, Ipswich, MA, USA). Double stranded cDNA was sheared to a fragment size of 175bp using a Covaris S-series sonicator (Woburn, MA, USA). SIP metatranscriptomic library construction was completed using the Ovation Ultralow Library DR multiplex system (Nugen, San Carlos, CA, USA) following manufacturer instructions. Ribosomal RNA was not removed before construction of libraries. Sequencing was performed on an Illumina HiSeq 1000 at the W.M. Keck sequencing facility at the Marine Biological Laboratory. All libraries were paired-end, with a 30 bp overlap, resulting in an average merged read length of 160 bp. Metagenomic and metatranscriptomic library preparation: The 47mm flat filters were first cut in half with a sterile razor, with half used for DNA and half used for RNA extraction. RNA was extracted using the mirVana miRNA isolation kit (Ambion, Grand Island, NY, USA) with an added bead-beating step using RNA PowerSoil beads (MoBio, Carlsbad, CA, USA). A total volume of 100 µl was extracted and was then DNase treated using the Turbo-DNase kit (Ambion), purified, and concentrated using the RNAeasy MinElute kit (Qiagen, Hilden, Germany). Ribosomal RNA removal, cDNA synthesis, and metatranscriptomic library preparation was carried out using the Ovation Complete Prokaryotic RNA-Seq DR multiplex system (Nugen) following manufacturer instructions. Prior to library construction, cDNA was sheared to a fragment size of 175 bp using a Covaris S-series sonicator. For DNA extraction, the DNA filter was first rinsed with sterile PBS to remove RNAlater and then was extracted using a phenol-chloroform method adapted from Crump et al. (2003) and Zhou et al. (1996). DNA was then sheared to a fragment size of 175 bp using a Covaris S-series sonicator. Metagenomic library construction was completed using the Ovation Ultralow Library DR multiplex system (Nugen) following manufacturer instructions. Metagenomic and metatranscriptomic sequencing was preformed on an Illumina HiSeq 1000 at the W.M. Keck sequencing facility at the Marine Biological Laboratory. All libraries were pairedend, with a 30 bp overlap, resulting in an average merged read length of 160 bp. Library analyses: For all metagenomic, metatranscriptomic, and RNA-SIP metatranscriptomic libraries, paired-end partially overlapping reads were merged and quality filtered using custom Illumina utility scripts (https://github.com/meren/illumina-utils). Merged reads were dereplicated then assembled using CLC Genomics Workbench (v 7.0) using default settings and a minimum contig length of 200 bp. Dereplicated libraries were only used for easing assembly, mapping was completed using all reads. Assembled contigs from each library were submitted to the DOE Joint Genome Institute’s Integrated Microbial Genome Metagenomic Expert Review (IMG/ER) annotation pipeline for Open Reading Frame (ORF) identification and functional and taxonomic annotation (Markowitz et al., 2012). To determine the number of reads per annotated ORF, reads from each library were mapped to ORFs using CLC Genomics Workbench (v 7.0), using default settings (50% percent identity and 80% minimum length fraction). To identify rRNA reads in the metatranscriptomes, reads were mapped to SILVA SSU and LSU databases (release 111, Pruesse et al., 2007) using Bowtie2 (v. 2.0.0-beta5, Langmead and Salzberg, 2012) with a local alignment and default settings. Identified rRNA reads were separated from each metatranscriptome using custom Perl scripts. Ribosomal RNA from metagenomes was also identified using this method but reads were not separated. For the Marker 113 metagenome and the RNA-SIP metatranscriptomes, 16S rRNA reads were specifically identified from the rRNA by mapping all rRNA reads to the Greengenes 16S rRNA unclustered taxonomic database (May 2013 release, McDonald et al., 2012) using Bowtie2. 16S rRNA reads were taxonomically identified with MOTHUR (v. 1.33, Schloss et al., 2009) using an updated Greengenes taxonomic database clustered at 99% similarity (August 2013 release, McDonald et al., 2012). ORFs from each library were annotated against the KEGG ontology (KO) database. Only annotations with minimum requirements of an e-score of 1e-10, 30% amino acid identity, and alignment length of 40 amino acids were included in functional analyses. KO abundances for the Marker 113 metagenome were normalized by dividing each KO annotation by the number of hits to DNA-directed RNA polymerase, beta subunit gene (rpoB). The Marker 113 metatranscriptome was normalized using the following ratio: ((number of hits to each KO/total annotated transcripts)/(average number of hits to rpoB in the metagenome/total annotated metagenomic reads)). For the SIP metatranscriptomes, relative abundance was calculated for each KO annotation and used for downstream analysis, including hierarchal clustering. To determine the correlation between the sequenced density fractions within each SIP experiment, pairwise Pearson correlations (r) were calculated and were used for hierarchical clustering (average-linkage method) seen in Figure 2. Clustering was done using the statistical program R (v. 3.1.1, R-Development-Core-Team, 2011) with the package pvclust. References: Crump BC, Kling GW, Bahr M, Hobbie JE (2003). Bacterioplankton community shifts in an arctic lake correlate with seasonal changes in organic matter source. Appl Environ Microbiol 69: 2253-2268. Langmead B, Salzberg SL (2012). Fast gapped-read alignment with Bowtie 2. Nat Meth 9: 357-359. Markowitz VM, Chen IMA, Chu K, Szeto E, Palaniappan K, Grechkin Y et al (2012). IMG/M: the integrated metagenome data management and comparative analysis system. Nucleic Acids Res 40: D123-D129. McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A et al (2012). An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J 6: 610-618. Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig WG, Peplies J et al (2007). SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35: 7188-7196. R-Development-Core-Team (2011). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB et al (2009). Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities. Appl Environ Microbiol 75: 7537-7541. Zhou JZ, Bruns MA, Tiedje JM (1996). DNA recovery from soils of diverse composition. Appl Environ Microbiol 62: 316-322.