ASV list for 16S, 18S rRNA and ITS sequences

Methods

Sample Collection and processing

"Samples were collected using a bucket to collect surface water and placed in polycarbonate 2-3L bottles (acid-washed and rinsed 2x with seawater). Bottles samples were immediately brought to the laboratory (SIO samples) or kept cool in an ice chest (SDB Samples) until brought to the laboratory for processing later the same day. Samples for DNA extraction were filtered in duplicate (0.5 L) using 0.2 mm pore size Supor membranes (47mm, Pall corporation, Port Washington, NY, USA). Membrane filters were stored at -80oC until use. DNA extractions were done using two methods. The first method used for samples from July 2015 to Oct 2021 was a phenol: chloroform extraction followed by further purification with the DNEasy Blood and tissue Kit (Qiagen, Valencia, CA, USA) (34 samples) as described in Nagarkar et al., 2021. Samples from November 2021 to September 2022 and April, July and August of 2023 (85 samples) were extracted using the following modified bead beating protocol. In the Bead Beating protocol, membranes were cut and split between 2 microcentrifuge tubes containing ~100 ml 212-300 µm acid washed glass beads (Sigma, St. Louis, MO, USA) and 400 ml ATL buffer (Qiagen). Tubes were frozen in a dry ice and ethanol slurry and then quickly thawed at 65oC, repeated three times. Samples were then homogenized 1 x 1 min in a mini bead beater (Biospec Products, Bartleville, OK, USA) before addition of 45 µl Proteinase K solution (20 mg/ml, Qiagen) and incubation at 55oC for 1.5 hours. 4 µl of RNase (10 mg/ml, Thermo Scientific) was added and the mixture was incubated at 65oC for 10 min with periodic mixing. Samples were then processed following the manufacturer’s instructions for the DNEasy Blood and tissue Kit (Qiagen). DNA concentration was measured by nanodrop and replicate extractions were pooled before DNA was stored at -80oC until sequencing. Sequencing at RTL – Extracted samples from July 2015 to Oct 2021 were sent for sequencing at Research and Testing Laboratory (RTL) Genomics (Lubbock, TX, USA). Primers for the Synechococcus -specific ITS region MSd_ITSafusF (GGATCACCTCCTAACAGGGAG) and MSd_SYnafusR R (AGGTTAGGAGACTCGAACTC) (Choi et al., 2014) were used for amplification. The 16S rRNA gene was amplified using primers 515yF (GTGYCAGCMGCCGCGGTAA) and 806R (GGACTACNVGGGTWTCTAAT) targeting the V4 region from Parada et al., (2016). The 18S rRNA gene was amplified using primers EUK1391F (GTACACACCGCCCGTC) and EUKBr (TGATCCTTCTGCAGGTTCACCTAC) targeting the V9 region (Amaral-Zettler et al., 2009; Stoeck et al., 2010). All regions were sequenced with paired-end 150 bp reads with an average of 10,000 sequencing reads using an Illumina MiSeq. Samples were processed according to the RTL company protocol. RTL genomics removed oligo-tags, demultiplexed and filtered the ITS sequences for length and quality. Sequencing at Novogene - Extracted samples from November 2021 to September 2022 were sent for sequencing at Novogene (Sacramento, CA, USA) using the ITS, 16S rRNA and 18S rRNA primers given above. Reads were paired end 250 bp reads with a sequencing depth of 30,000 reads using Illumina HiSeq. Adaptors and primers were removed from raw reads before reads were filtered at Novogene for length and quality."

Data processing

"For the ITS region, 16S rRNA and 18S rRNA sequencing primers were trimmed from complementary forward and reverse reads (RTL sequences) using CutAdapt (v3.4, (Martin, 2011). All sequences (RTL and Novogene) were further verified for quality using FastQC (v0.11.9, Babraham Bioinformatics) and filtered based on a minimum phred score of 33. Sequences from the two sequencing centers were denoised separately using dada2 pipeline in QIIME 2 (QIIMEiime2-2021.8, Bolyen E et al., 2019) where lengths were trimmed based on sequence quality of the sample. Representative amplicon sequence variants (ASV) were counted across all samples and rarefied in QIIME 2 to the samples with the lowest number of reads (ITS:3537, 16S:5481, 18S:2938) to reduce bias caused by the different sequencing depths. ASVs that occurred less than 10 times were removed from the dataset. ITS region representative sequences and count tables were merged after de-noising for further analysis at the ASV level. ITS ASVs were blasted (version; 2.12.0+, Altschul et al., 1990) against a Synechococcus ASV ITS database (Nagarkar et al., 2021) to determine clade association and ASV name. ASVs that were the exact match to ASVs found in the database were named accordingly, while ASVs that did not match exactly were named with numbers larger than 236. ASVs that were not represented in the database were blasted in Cyanorak (http://cyanorak.sb-roscoff.fr) to determine likely clade affiliation. Clade designations were further checked and adjusted based on phylogenetic trees constructed with reference ITS sequences from Synechococcus (Cyanorak)."

Instrumentation used

Instrumentation used for the project.