Determination of Transgene Copy Numbers and Practical Biocalculation

2016 ◽  
pp. 551-560
Keyword(s):  
Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2385-2385
Author(s):  
Satsuki Muto ◽  
Go Yamamoto ◽  
Yasuhito Nannya ◽  
Masashi Sanada ◽  
Nazanin Dabaghmanesh ◽  
...  

Abstract Adult T cell leukemia/lymphoma (ATL) is a mature T-cell neoplasm in adult that is caused by human T-cell leukemia virus type 1 (HTLV-1) and highly intractable to conventional therapeutics. Since there are 1.2 million HTLV-1 carriers in Japan and more than 50,000 carriers are expected to develop ATL from now on, it is of particular importance to understand the pathogenesis of ATL. The malignant processes of T-cell transformation in ATL are initiated by HTLV-1 infection in early childhood, and the HTLV-1 infected and immortalized T-cells are thought to accumulate a series of genetic hits during the later life, ultimately giving rise to malignant ATL clones after decades of latency periods. However, little is known about the nature of these genetic hits that take place after the early immortalization processes of T-cells mediated by HTLV-1 Tax protein. So in order to clarify the genetic alterations involved in the later processes of T-cell transformation in ATL, we analyzed a total of 130 ATL samples using Affymetrix® GeneChip® 250K Nsp arrays. Combined with CNAG/AsCNAR software, these arrays allow for accurate determination of allele-specific copy numbers in extremely high-resolution (less than 12kb) to detect copy number alterations as well as allelic imbalances in ATL genomes without depending on the availability of constitutive DNA of tumor specimens (molecular allelo-karyotyping). ATL genomes show characteristic copy number profiles and unique patterns of allelic imbalances, which are distinct from acute lymphoblastic ALL and non-Hodgikin’s lymphomas and include gains of 1q arm, 2q33, 3p and 3q arms, 9p12, 17q12, and 19p13, and losses of 1p13.1, 2q end, 3q22, 4q31, 6p22, 7q31, 9p21, 10p14, 12q13, 14q24, and 19q13. Moreover, allele-specific determination of copy numbers disclosed a number of regions showing copy number neutral LOH. Numerous homozygous deletions and gene amplifications were also identified and commonly mapped to less than 500Kb regions, which facilitated identification of candidate gene targets. Interestingly, these genetic lesions involved many T-cell related genes, indicating that the de-regulation of normal T cell functions may contribute the pathogenesis of ATL. In conclusion, molecular allelo-karyotyping of ATL genomes using SNP arrays provides valuable information about the molecular targets in ATL pathogenesis.


2016 ◽  
Vol 20 (6) ◽  
pp. 756-761 ◽  
Author(s):  
R. B. Aitnazarov ◽  
N. S. Yudin ◽  
R. S. Kiril’chuk ◽  
N. N. Kochnev ◽  
S. P. Knyazev ◽  
...  

1995 ◽  
Vol 27 (3) ◽  
pp. 217-228 ◽  
Author(s):  
Christopher Hadfield ◽  
Jennifer A. Harikrishna ◽  
Jacqueline A. Wilson

2019 ◽  
Author(s):  
Huidong Chen ◽  
Caleb Lareau ◽  
Tommaso Andreani ◽  
Michael E. Vinyard ◽  
Sara P. Garcia ◽  
...  

AbstractBackgroundRecent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans) lead to inherent data sparsity (1-10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (20-50% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level.ResultsWe present a benchmarking framework that was applied to 10 computational methods for scATAC-seq on 13 synthetic and real datasets from different assays, profiling cell types from diverse tissues and organisms. Methods for processing and featurizing scATAC-seq data were evaluated by their ability to discriminate cell types when combined with common unsupervised clustering approaches. We rank evaluated methods and discuss computational challenges associated with scATAC-seq analysis including inherently sparse data, determination of features, peak calling, the effects of sequencing coverage and noise, and clustering performance. Running times and memory requirements are also discussed.ConclusionsThis reference summary of scATAC-seq methods offers recommendations for best practices with consideration for both the non-expert user and the methods developer. Despite variation across methods and datasets, SnapATAC, Cusanovich2018, and cisTopic outperform other methods in separating cell populations of different coverages and noise levels in both synthetic and real datasets. Notably, SnapATAC was the only method able to analyze a large dataset (> 80,000 cells).


1999 ◽  
Vol 339 (3) ◽  
pp. 737-742 ◽  
Author(s):  
Linda M. FIELD ◽  
Roger L. BLACKMAN ◽  
Chris TYLER-SMITH ◽  
Alan L. DEVONSHIRE

Overproduction of the insecticide-degrading esterases, E4 and FE4, in peach-potato aphids, Myzus persicae (Sulzer), depends on both gene amplification and transcriptional control, the latter being associated with changes in DNA methylation. The structure and function of the aphid esterase genes have been studied but the determination of their copy number has proved difficult, a common problem with gene amplification. We have now used a combination of pulsed-field gel electrophoresis and quantitative competitive PCR to determine relative esterase gene copy numbers in aphid clones with different levels of insecticide resistance (R1, R2 and R3). There are approx. 4-fold increases between susceptible, R1, R2 and R3 aphids, reaching a maximum of approx. 80 times more genes in R3; this gives proportionate increases in esterase protein relative to susceptible aphids. Thus there is no overexpression of the amplified genes, in contrast with what was thought previously. For E4 genes, the loss of 5-methylcytosine is correlated with a loss of expression, greatly decreasing the amount of enzyme relative to the copy number.


2011 ◽  
Vol 11 (3) ◽  
pp. O111.009613 ◽  
Author(s):  
Marlis Zeiler ◽  
Werner L. Straube ◽  
Emma Lundberg ◽  
Mathias Uhlen ◽  
Matthias Mann

2016 ◽  
Vol 7 ◽  
Author(s):  
Yuan-yuan Qi ◽  
Xu-jie Zhou ◽  
Ding-fang Bu ◽  
Ping Hou ◽  
Ji-cheng Lv ◽  
...  

2010 ◽  
Vol 5 (4) ◽  
pp. 413-420 ◽  
Author(s):  
Sandra Abad ◽  
Kerstin Kitz ◽  
Astrid Hörmann ◽  
Ulrike Schreiner ◽  
Franz S. Hartner ◽  
...  

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