scholarly journals Next Generation Sequencing to Discover Genetic Markers for Pacific White Shrimp

Author(s):  
Zhi-Qiang Du ◽  
Max F. Rothschild
2018 ◽  
Vol 115 (2) ◽  
pp. 202
Author(s):  
Rodriguez-Anaya Libia Zulema ◽  
Casillas-Hernandez Ramon ◽  
Lares-Jimenez Luis Fernando ◽  
Gonzalez-Galaviz Jose Reyes

2018 ◽  
Vol 20 (suppl_2) ◽  
pp. i182-i183
Author(s):  
Joanna Trubicka ◽  
Malgorzata Rydzanicz ◽  
Iwona Filipek ◽  
Piotr Iwanowski ◽  
Wieslawa Grajkowska ◽  
...  

JAMA Oncology ◽  
2019 ◽  
Vol 5 (7) ◽  
pp. 1076 ◽  
Author(s):  
Mark D. Ewalt ◽  
Howard West ◽  
Dara L. Aisner

2018 ◽  
Vol 146 (7-8) ◽  
pp. 407-411 ◽  
Author(s):  
Lidija Dokmanovic ◽  
Goran Milosevic ◽  
Jelena Peric ◽  
Natasa Tosic ◽  
Nada Krstovski ◽  
...  

Introduction/Objective. Next generation sequencing (NGS) technology has enabled genomic profiling of each patient. Growing knowledge in pharmacogenomics makes it possible to use NGS data for discovery of novel potential genetic markers for targeted therapy of many diseases, especially cancers. The aim of this study was to use targeted NGS to make a genetic profile of childhood acute lymphoblastic leukemia (cALL) in order to evaluate potential molecular targets for targeted therapy. Methods. We analyzed DNA samples from 17 cALL patients using NGS targeted sequencing. Advanced bioinformatic analysis was used to identify novel mutations in analyzed genes and to predict their effect and pharmacogenomic potential. Results. We identified nine variants that have not been previously reported in relevant databases, including two stop-gain variants, ABL1 p.Q252* and AKT1 p.W22*, one frameshift, STK11 p.G257fs*28, and six missense variants. We created three-dimensional models of four proteins harboring novel missense variants. We analyzed pharmacogenomic potential of each variant and found that two of them, STK11 c.1023G>T/ p.L341F and ERBB2 c.2341C>T/ p.R781W, are suitable candidates for targeted therapy. Conclusion. Most new variants detected in this study were found in the genes associated with Ras signaling pathway, which is frequently mutated in cALL patients. Pharmacogenomic profiling of each cALL will be indispensable for novel therapy approaches. Detection and initial analysis of novel variants, presented in this study, will become a standard procedure for the design and development of individualized therapies for children with ALL, leading to improved patient outcomes.


Author(s):  
Jürgen Claesen ◽  
Tomasz Burzykowski

AbstractThe analysis of polygenic, phenotypic characteristics such as quantitative traits or inheritable diseases requires reliable scoring of many genetic markers covering the entire genome. The advent of high-throughput sequencing technologies provides a new way to evaluate large numbers of single nucleotide polymorphisms as genetic markers. Combining the technologies with pooling of segregants, as performed in bulk segregant analysis, should, in principle, allow the simultaneous mapping of multiple genetic loci present throughout the genome. We propose a hidden Markov-model to analyze the marker data obtained by the bulk segregant next generation sequencing. The model includes several states, each associated with a different probability of observing the same/different nucleotide in an offspring as compared to the parent. The transitions between the molecular markers imply transitions between the states of the model. After estimating the transition probabilities and state-related probabilities of nucleotide (dis)similarity, the most probable state for each SNP is selected. The most probable states can then be used to indicate which genomic regions may be likely to contain trait-related genes. The application of the model is illustrated on the data from a study of ethanol tolerance in yeast. Software is written in R. R-functions, R-scripts and documentation are available on


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