Amplification Refractory Mutation System (ARMS)-PCR for Waxy Sorghum Authentication with Single-Nucleotide Resolution

Waxy sorghum has greater economic value than wild sorghum in relation to their use in food processing and the brewing industry. Thus, the authentication of the waxy sorghum species is an important issue. Herein, a rapid and sensitive Authentication Amplification Refractory Mutation System-PCR (aARMS-PCR) method was employed to identify sorghum species via its ability to resolve single-nucleotide in genes. As a proof of concept, we chose a species of waxy sorghum containing the wxc mutation which is abundantly used in liquor brewing. The aARMS-PCR can distinguish non-wxc sorghum from wxc sorghum to guarantee identification of specific waxy sorghum species. It allowed to detect as low as 1% non-wxc sorghum in sorghum mixtures, which ar one of the most sensitive tools for food authentication. Due to its ability for resolving genes with single-nucleotide resolution and high sensitivity, aARMS-PCR may have wider applicability in monitoring food adulteration, offering a rapid food authenticity verification in the control of adulteration.

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NmSEER V2.0: a prediction tool for 2′-O-methylation sites based on random forest and multi-encoding combination

BMC Bioinformatics ◽

10.1186/s12859-019-3265-8 ◽

2019 ◽

Vol 20 (S25) ◽

Cited By ~ 2

Author(s):

Yiran Zhou ◽

Qinghua Cui ◽

Yuan Zhou

Keyword(s):

Random Forest ◽

Prediction Model ◽

Learning Algorithm ◽

High Sensitivity ◽

Sequence Information ◽

Sequence Profile ◽

Single Nucleotide ◽

Nucleotide Resolution ◽

Validation Tests ◽

Single Nucleotide Resolution

Abstract Background 2′-O-methylation (2′-O-me or Nm) is a post-transcriptional RNA methylation modified at 2′-hydroxy, which is common in mRNAs and various non-coding RNAs. Previous studies revealed the significance of Nm in multiple biological processes. With Nm getting more and more attention, a revolutionary technique termed Nm-seq, was developed to profile Nm sites mainly in mRNA with single nucleotide resolution and high sensitivity. In a recent work, supported by the Nm-seq data, we have reported a method in silico for predicting Nm sites, which relies on nucleotide sequence information, and established an online server named NmSEER. More recently, a more confident dataset produced by refined Nm-seq was available. Therefore, in this work, we redesigned the prediction model to achieve a more robust performance on the new data. Results We redesigned the prediction model from two perspectives, including machine learning algorithm and multi-encoding scheme combination. With optimization by 5-fold cross-validation tests and evaluation by independent test respectively, random forest was selected as the most robust algorithm. Meanwhile, one-hot encoding, together with position-specific dinucleotide sequence profile and K-nucleotide frequency encoding were collectively applied to build the final predictor. Conclusions The predictor of updated version, named NmSEER V2.0, achieves an accurate prediction performance (AUROC = 0.862) and has been settled into a brand-new server, which is available at http://www.rnanut.net/nmseer-v2/ for free.

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Genetic Variation in Intergenic and Exonic miRNA Sequence and Risk of Multiple Sclerosis in the Isfahan Patients

Iranian Journal of Allergy Asthma and Immunology ◽

10.18502/ijaai.v17i5.305 ◽

2018 ◽

pp. 477-484 ◽

Cited By ~ 1

Author(s):

Golshani Golshani ◽

Zohreh Hojati ◽

Ali Sharifzadeh ◽

Vahid Shaygannejad ◽

Mojtaba Jafarinia

Keyword(s):

Multiple Sclerosis ◽

Autoimmune Disease ◽

Mirna Sequence ◽

Amplification Refractory Mutation System ◽

Single Nucleotide ◽

Increased Risk ◽

Significant Difference ◽

Mutation System ◽

Pcr Method ◽

The Relationship

MicroRNAs (miRNAs), have been documented to perform a key role in the pathogenesis of multiple sclerosis (MS), a chronic inflammatory and autoimmune disease. Recent studies have shown that single nucleotide polymorphism in the sequence of the miRNA may change their production and expression which can lead to miRNA dysfunction and pathogenicity. Some studies have reported the relationship between miRNA polymorphism and the increased risk of autoimmune disease. This study was conducted to investigate the association between mir155 rs767649, mir196a2 rs11614913 and mir23a rs3745453 polymorphism and the risk of multiple sclerosis in the Iranian MS patients in Isfahan. A population of 80 patients and the same number control were selected. After DNA extraction, genotyping was performed through tetra amplification refractory mutation system-PCR method (T ARMS PCR). The frequencies of TT, TC and CC genotypes of mir23a were 46, 35 and 20% in MS patients and 42, 14 and 24 in healthy subjects respectively. These results showed that individuals carrying the genotypes of rs3745453 TC had a 2.3-fold increased risk of MS (OR=2.3, p=0.048). There was no significant difference between genotypes and allele frequency of mir155 and mir196a2 in patients and healthy controls (p>0.05). Our findings specified that CT heterozygosity in mir23a gene significantly related with risk of MS. Unlike mir155 and mir196a2, mir23a rs3745453 may have contributed to the etiology of MS in Isfahan patients. However, extensive studies are required to gain more reliable and authentic results.

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BreakID: genomics breakpoints identification to detect gene fusion events using discordant pairs and split reads

Bioinformatics ◽

10.1093/bioinformatics/bty1070 ◽

2019 ◽

Vol 35 (16) ◽

pp. 2859-2861

Author(s):

Linfang Jin ◽

Jinhuo Lai ◽

Yang Zhang ◽

Ying Fu ◽

Shuhang Wang ◽

...

Keyword(s):

Gene Fusion ◽

Source Code ◽

High Sensitivity ◽

Supplementary Information ◽

Sequencing Data ◽

Single Nucleotide ◽

Nucleotide Resolution ◽

Single Nucleotide Resolution ◽

Fusion Detection ◽

Better Than

AbstractSummaryHere we developed a tool called Breakpoint Identification (BreakID) to identity fusion events from targeted sequencing data. Taking discordant read pairs and split reads as supporting evidences, BreakID can identify gene fusion breakpoints at single nucleotide resolution. After validation with confirmed fusion events in cancer cell lines, we have proved that BreakID can achieve high sensitivity of 90.63% along with PPV of 100% at sequencing depth of 500× and perform better than other available fusion detection tools. We anticipate that BreakID will have an extensive popularity in the detection and analysis of fusions involved in clinical and research sequencing scenarios.Availability and implementationSource code is freely available at https://github.com/SinOncology/BreakID.Supplementary informationSupplementary data are available at Bioinformatics online.

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