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Acgt101 mir v3

Manufactured by LC Sciences
Sourced in United States

The ACGT101-miR v3.5 is a lab equipment product designed for microRNA (miRNA) analysis. It provides a platform for the detection and quantification of miRNA expression levels. The core function of this product is to enable researchers to study the role of miRNA in biological processes and disease mechanisms.

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2 protocols using acgt101 mir v3

1

Small RNA Sequencing Data Analysis

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The raw data were processed with data cleaning analysis using ACGT101-miR v3.5 (LC Sciences, Huston, TX). In brief, the quality of raw data was measured by Illumina Fast QC to obtain Q30 data. Clean full-length reads were collected after removing all low-quality reads, adapter contaminants, and reads smaller than 18 nt and junk sequences (≥2 N, ≥7A, ≥8C, ≥6G, ≥7 T, ≥10 Dimer, ≥6 Trimer or ≥ 5 Tetramer). In addition, the clean data were filtered using various RNA databases, such as mRNA, RFam (release 9.1) and Repbase (version 15.07) databases, and rRNA, scRNA, snoRNA, snRNA, tRNA, etc. were found and removed as much as possible. The remaining unique sequences were mapped to the precursors in miRBase 21.0. by the fast gapped-read alignment software Bowtie 2 [88 (link)]. The unique sequences mapping to specific species mature miRNAs in hairpin arms were identified as known miRNAs. The unannotated sRNAs were expanded to about 250 nt and their structures were predicted using Mfold software (http://unafold.rna.albany.edu/?q=mfold). Novel miRNAs were obtained according to Meyers and Li prediction criteria [39 (link), 89 (link)].
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2

Identification of miRNAs in Rice Cultivars

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MiRNAs were identified in “Xushu 22” cultivar similarly as in “Xushu 32” (Yang et al., 2020 (link)). In brief, original data was first processed and analyzed by ACGT101-miR v3.5 software (LC Sciences, Huston, TX, United States). Small RNAs were compared with known non-redundant plant mature miRNAs in miRBase 21.0 (one mismatch is allowed in the alignment) using Bowtie software, and the unique sequences mapped to specific species mature miRNAs were considered miRNAs. The matching sequences are considered to be known miRNAs, and did not match sequences using Mfold software1 predicted its structure and then obtained novel miRNA according to previous criteria (Meyers et al., 2008 (link); Li et al., 2013 (link)). The criteria for secondary structure prediction were: (a) number of nucleotides in one bulge in stem ≤ 12, (b) number of base pairs in the stem region of the predicted hairpin ≥ 16, (c) cutoff of free energy kCal/mol ≤ 15, (d) length of hairpin (up and down stems + terminal loop ≥ 50), (e) length of hairpin loop ≤ 200, (f) number of nucleotides in one bulge in mature region ≤ 4, (g) number of biased errors in one bulge in mature region ≤ 2, (h) number of biased bulges in mature region ≤ 2, (i) number of errors in mature region ≤ 4, (j) number of base pairs in the mature region of the predicted hairpin ≥ 12, (k) percent of mature in stem ≥ 80.
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