Cotton Genomics and Genetics 2016, Vol.7, No.2, 1-23
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Small RNA library construction and sequencing were done at Shrimpex Biotech Services Private Limited,
Chennai, India. Briefly, the miRNA was isolated according to the manufacturer’s protocol and concentration was
measured using Nanodrop Spectrophotometer. To avoid DNA contamination, the miRNA was treated with DNase
@ 0.5 unit per μg of miRNA (the reaction mixture contains, 0.5 unit of DNase, 10X DNase buffer and the miRNA
template to a final volume of 30 μL) and incubated at 37°C for 30 minutes. The reaction was stopped by
incubating at 65°C for 10 minutes with 1 μL of 50 mM EDTA. The miRNA was purified from DNase using
Shrimpex spin column concentration module according to the manufacturer’s protocol. The quality of the
obtained miRNA before and after DNase treatment was analyzed using Agilent 2100 small RNA kit.
The miRNA library was prepared using Ion Total-RNA Seq kit v2 and the miRNAs were enriched using magnetic
bead clean up module for small RNA enrichment. In the next step, Ion RNA-Seq adapter was ligated to the
enriched miRNA to facilitate reverse transcription of first strand cDNA synthesis and further purification using
magnetic bead clean up module. The purified cDNA were amplified using a barcoded forward primer and a
common reverse primer and quantified using Agilent Bioanalyzer 2100 DNA 1000 kit. Smear analysis was
performed to determine the size distribution range of the four samples to confirm that the size of the four libraries
was in the range of 94~114 bp.
The molar concentration of each library was determined and diluted to the same molar concentration. Equal
volumes of each barcoded library of the replicated samples were mixed to prepare a pool of barcoded libraries and
were amplified using emulsion PCR (ePCR). In ePCR, the clonal bead populations are generated in water-in-oil
microreactors. After ePCR, the templates were denatured and bead enrichment step was performed to separate the
beads with templates from non-template beads. The enriched beads were then loaded onto the Ion P1 Chip and
sequenced.
3.4 Sequence analysis for miRNA identification
Sequences were trimmed to eliminate low-quality reads and other contaminants from the adaptor tags. All low
quality reads were removed such as reads with 3’ and 5’ adapter contaminants, those without insert tags, and those
with poly-A sequences. The remaining high-quality sequences were trimmed of their adapter sequences. All high-
quality sequences were considered significant and number of reads in each nucleotide class was classified. Each
read were annotated through BLAST searching for identification of rRNA, scRNA, snoRNA, snRNA and tRNA
using ‘Rfam’ (ftp://ftp.sanger.ac.uk/pub/databases/Rfam/) and those matched reads were avoided for further
analysis.
Initially, a simple blast search of resulted small RNA sequences identified in both the replications (in the size
range of 20 - 33 nt) with miRBase was done to categorize their family classification based on conservation
(version 19
(August, 2012),
). Sequences that were identical or related to known
miRNA sequences (with maximum of single nucleotide
substitution) were considered as known or conserved
miRNAs and others were considered as putative novel miRNAs.
3.5 Identification of novel miRNAs
Considering the complicated structure of miRNA gene and its biogenesis, a series of strict filters were used during
the new miRNA identification process to enhance reliability of the result presented here. Currently, no
allopolyploid cotton genome sequence was available; therefore ESTs from NCBI and the genome sequence of
G.
raimondii
(Wang et al., 2012), the closest living relative of the progenitor D-genome donor of allotetropolyploid
cottons (
G. hirsutum
and
G. barbadense)
were used as reference sequences to predict the miRNA precursors. The
20-33 nt reads that were assumed as putative novel miRNA were mapped to cotton nucleotide sequences available
at NCBI and D genome sequence (
). Approximately 100
nucleotides flanking both side of the query sequence were obtained and the characteristic secondary hairpin
structure of each miRNA precursors was predicted using the miRNA prediction software, mFold 3.2 (Zuker,
2003). During this process the following characteristics were considered to affirm novel cotton miRNAs: i)
formation of flawless secondary structure (including formation of a perfect stem-loop structure, the read sequence
