Project description:Single-cell human genome analysis using whole-genome amplified product is hampered by allele bias during amplification. Using an oligonucleotide SNP array, we examined the nature of the allele bias and its effect on the chromosomal copy number analysis. Keywords: single cell, copy number analysis, whole genome amplification, brain
Project description:Background: Insufficient quantities of human genomic DNA are a limiting factor for many clinical applications. Whole genome amplification (WGA) is an approach designed to overcome small amount of DNA for genome-wide genetic tests as it allows amplification of the entire genome from picogram or nanogram quantities of DNA. Various strategies of WGA have been developed; however, none of them can guarantee the absence of amplification bias. High-quality genome-representative amplified DNA is crucial for WGA use in basic research and clinical genetics. Thus, systematic evaluation of WGA effect on downstream methods is necessary. Results: In this paper, 4 multiple displacement amplification (MDA) -based and 2 PCR-based WGA kits were compared in their effect on segmental copy-number changes as well as copy-number neutral loss of heterozygosity detection by high-density oligonucleotide DNA arrays. We described outcomes and limits for each individual WGA; however, the main goal of this study was chiefly to show a general compatibility and features specific for particular WGA strategy. The main outcomes are as follows: 1) MDA-based WGAs showed higher tendency to generate false positive imbalances in contrast to PCR-based WGAs with higher risk of false negativity; 2) the specific risk of false positivity and/or negativity increased with decreasing copy-number segments size; 3) single-cell WGAs showed significantly worse effect on results in comparison to WGAs with nanogram level of DNA as input; 4) PCR-based WGAs were not compatible with copy-number neutral loss of heterozygosity analysis based on single nucleotide polymorphisms in restriction digestion sites and also showed higher risk of copy-number neutral loss of heterozygosity false negativity if combined with analysis based on simple hybridization. Conclusions: This study gives a comprehensive insight into the WGA effect on DNA array analysis. The results of this study help to choose WGA according to individual user requirements and options. Moreover, we show a strategy to verify and validate segmental copy-number changes detection by DNA array protocol including any WGA for any purpose to attain the highest efficiency without an unnecessary WGA bias.
Project description:Several recent studies have suggested that genes that are over 100 kb in length are particularly likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism, Fragile X syndrome, and Rett syndrome. These length-dependent transcriptional changes seem to be modest, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be reevaluated. Here we show that transcriptional changes reflected in microarray and RNA-Sequencing benchmark datasets from the SEQC Consortium show a bias toward genes of greater length, even in the comparison of technical replicates. We hypothesized that PCR amplification, which is used in both microarray and RNA-Seq technologies, could be introducing this bias. We found that, when the fold-change values are small, PCR amplification in microarray and RNA-Seq technologies does produce a bias toward longer genes; we found no similar bias with nCounter technology, which is not based on PCR amplification. We provide an approach to more rigorously assess length-dependent changes that begins with comparing randomized control samples to estimate baseline gene length dependency and evaluate the statistical significance of gene length regulation.
Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
Project description:This experiment highlights the extreme sequence bias generated by standard PCR amplication of sequencing libraries and decribes an adapted T7-polymerase based amplification method, which results in non-baised, representative libraries for Illumina sequencing
Project description:Zhao et al. Amplification Figure 1 This experiment was designed to evaluate the effect of in vitro transcription time on the fidelity, reproducibility, and yield of T7 based linear amplification. Duplicate reactions were performed at 37 degree for 2, 3, 4, 5, and 6 hours. Two additional 5-hour incubation reactions were stored at 4 degree overnight to determine the effect of low temperature incubation on amplification. BC2 total RNA was amplified using the Jeffrey lab protocol with the G50 column cleanup step. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set