Analysis of formaldehyde-inducedAdh mutations inDrosophila by RNA structure mapping and direct sequencing of PCR-amplified genomic DNA

1990 ◽  
Vol 28 (7-8) ◽  
pp. 367-387 ◽  
Author(s):  
Long Le ◽  
Stephen Ayer ◽  
Allen R. Place ◽  
Cheeptip Benyajati
Keyword(s):  
Rna Structure ◽  
Genomic Dna ◽  
Direct Sequencing ◽  
Structure Mapping ◽  
Rna Structure Mapping

scholarly journals Evaluation of the information content of RNA structure mapping data for secondary structure prediction

RNA ◽  
2010 ◽  
Vol 16 (6) ◽  
pp. 1108-1117 ◽  
Author(s):  
S. Quarrier ◽  
J. S. Martin ◽  
L. Davis-Neulander ◽  
A. Beauregard ◽  
A. Laederach
Keyword(s):  
Secondary Structure ◽  
Information Content ◽  
Rna Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Structure Mapping ◽  
Mapping Data ◽  
Rna Structure Mapping

scholarly journals An RNA Mapping DataBase for curating RNA structure mapping experiments

2012 ◽  
Vol 28 (22) ◽  
pp. 3006-3008 ◽  
Author(s):  
Pablo Cordero ◽  
Julius B. Lucks ◽  
Rhiju Das
Keyword(s):  
Rna Structure ◽  
Structure Mapping ◽  
Rna Mapping ◽  
Rna Structure Mapping

scholarly journals Rational experiment design for sequencing-based RNA structure mapping

RNA ◽  
2014 ◽  
Vol 20 (12) ◽  
pp. 1864-1877 ◽  
Author(s):  
Sharon Aviran ◽  
Lior Pachter
Keyword(s):  
Rna Structure ◽  
Experiment Design ◽  
Structure Mapping ◽  
Rna Structure Mapping

scholarly journals Keth-seq for transcriptome-wide RNA structure mapping

2020 ◽  
Vol 16 (5) ◽  
pp. 489-492 ◽  
Author(s):  
Xiaocheng Weng ◽  
Jing Gong ◽  
Yi Chen ◽  
Tong Wu ◽  
Fang Wang ◽  
...  
Keyword(s):  
Rna Structure ◽  
Structure Mapping ◽  
Rna Structure Mapping

scholarly journals Improved TGIRT-seq methods for comprehensive transcriptome profiling with decreased adapter dimer formation and bias correction

2018 ◽  
Author(s):  
Hengyi Xu ◽  
Jun Yao ◽  
Douglas C. Wu ◽  
Alan M. Lambowitz
Keyword(s):  
Rna Structure ◽  
Transcriptome Profiling ◽  
Rna Seq ◽  
Structure Mapping ◽  
Dimer Formation ◽  
Biochemical Basis ◽  
Reverse Transcriptases ◽  
Small Ncrnas ◽  
Rna Structure Mapping ◽  
Insight Into

ABSTRACTThermostable group II intron reverse transcriptases (TGIRTs) with high fidelity and processivity have been used for a variety of RNA sequencing (RNA-seq) applications, including comprehensive profiling of whole-cell, exosomal, and human plasma RNAs; quantitative tRNA-seq based on the ability of TGIRT enzymes to give full-length reads of tRNAs and other structured small ncRNAs; high-throughput mapping of post-transcriptional modifications; and RNA structure mapping. Here, we improved TGIRT-seq methods for comprehensive transcriptome profiling by (i) rationally designing RNA-seq adapters that minimize adapter dimer formation, and (ii) developing biochemical and computational methods that remediate 5’- and 3’-end biases. These improvements, some of which may be applicable to other RNA-seq methods, increase the efficiency of TGIRT-seq library construction and improve coverage of very small RNAs, such as miRNAs. Our findings provide insight into the biochemical basis of 5’- and 3’-end biases in RNA-seq and suggest general approaches for remediating biases and decreasing adapter dimer formation.

UGT1A1,A7 and A9 genotyping and pharmacokinetics of irinotecan-containing chemotherapy in patients with advanced cancer

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e14563-e14563
Author(s):  
B. Valenzuela ◽  
R. Nalda ◽  
M. Duart ◽  
V. Escudero ◽  
J. Perez-Ruixo ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Genomic Dna ◽  
Statistical Power ◽  
Direct Sequencing ◽  
Univariate Analysis ◽  
Statistical Correlation ◽  
Toxicity Data ◽  
Chi Square ◽  
Lung Cancer Patients ◽  
Grade Iii

e14563 Background: To the best of our knowledge only one previous report in asian lung cancer patients (pts) assesed UGT1A1, A7 and A9 genotypes along with irinotecan pharmacokinetics (Han et al. JCO 2006; 24: 2237–44). We set out to evaluate UGT1A1, A7 and A9 genotypes in caucasian cancer patients and their relationship with both irinotecan toxicity and irinotecan pharmacokinetics. Methods: UGT1A1, A7 and A9 genotypes were obtained from blood genomic DNA by direct sequencing. The area under the time-concentration curve (AUC) of SN-38 and SN-38G were calculated. The ratio between these AUCs (AUC SN-38G /AUC SN-38) was also calculated. Associations between pharmacokinetics parameters and the UGT1A genotypes were assessed by univariate analysis. Toxicity was collected using standard NCI grading criteria. Statistical correlation between presence of grade III and IV toxicity and UGT1A1,A7 and A9 genotypes was done by Pearson's Chi square. At least 80 patients (with both genotype and pharmacokinetics) are needed to achieve enough statistical power. Results: At the time of writing this abstract, complete genotyping and toxicity data from 59 patients were available. Sex (females 17, males 42). Median age 60 (range 25–88). Pathology (no. pts): lung (26), colon (17), others (16). 21 pts. (35.59%) had received previous chemotherapy. All but 5 pts received doses of irinotecan between 120 and 150 mg/m2. Median no. of cycles 6 (range 1–15). The frequencies of the different UGT1A1, A7 and A9 genotypes are similar to those previously reported. At least one episode of grade III or IV leukopenia was present in 19 pts. (32.2%), and grade III diarrea in 11 pts (18.6%). No statistically significant correlation was found between presence of leukopenia grades III and IV, and the genotypes UGT1A1,A7, and A9 (P=0.687, P=0.156 and P=0.476, respectively). Diarrea grade III was not statistically significantly associated with UGT1A1 (P=0.318), A7 (P=0.318) and A9 (P=0.158). 21 out of 59 pts. had pharmacokinetics (PK) data available. In genotype-PK association analysis, UGT1A1,A7 and A9 were not statistically associated with AUC SN-38G / AUC SN-38 ratios (P=0.844, P=0.911, P=0.431, respectively). Conclusions: Patients are still being accrued to achieve the targeted size. No significant financial relationships to disclose.

A Missense Mutation in the SH3BP2 Gene on Chromosome 4p16.3 Found in a Case of Nonfamilial Cherubism

2003 ◽  
Vol 40 (6) ◽  
pp. 632-638 ◽  
Author(s):  
Yoshimichi Imai ◽  
Kiyoshi Kanno ◽  
Takuya Moriya ◽  
Shuji Kayano ◽  
Hiroto Seino ◽  
...  
Keyword(s):  
Missense Mutation ◽  
Genomic Dna ◽  
Direct Sequencing ◽  
Point Mutations ◽  
Giant Cells ◽  
Japanese Woman ◽  
Tartrate Resistant Acid Phosphatase ◽  
Dna Diagnosis ◽  
Histochemical Analysis ◽  
Old Japanese

Objective Cherubism is a rare hereditary multilocular cystic disease of the jaws, characterized by its typical appearance. Although nonfamilial cases have been reported, it is difficult to distinguish nonfamilial cherubism from central giant cell granuloma. Recent studies have revealed the point mutations in the SH3BP2 gene on chromosome 4p16.3 in cherubism families. In this article, the SH3BP2 gene in nonfamilial cherubism was examined. Patient A 21-year-old Japanese woman with nonfamilial cherubism. Interventions Genomic DNA was purified from a blood sample obtained from the patient and used for direct sequencing. In addition, a sample of the lesion, resected during surgery, was used for histologic and immunohistochemical purposes. Results Genomic DNA sequencing found a Pro418Arg mutation in the SH3BP2 gene of the patient. In a histochemical analysis, the multinucleated giant cells proved to be strongly positive for PGM-1, KP-1, and tartrate-resistant acid phosphatase and faintly positive for osteopontin. Conclusions The missense mutation Pro418Arg was identified in the SH3BP2 gene from a nonfamilial case of cherubism. DNA diagnosis may play a significant role in the identification of cherubism.

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