For continuous regions, our design strategy for primers is tiling and the amplicons are overlapping on each other to avoid the gap regions between amplicons. In this case, in order to avoid generating unwanted amplicons, primers of adjacent amplicons will be put into different pools. And for special hard-to-amplify regions like high GC content regions, an extra pool might be needed to ensure the performance.
There are some regions in the genome that we classify as hard-to-capture regions, including high GC content sequences, repetitive sequences and homologous sequences. Based on the evaluation result, some of these target regions might be dropped as they might affect the overall performance or introduce errors.
The lengths of the amplicons are affected by the sequencing read length, integrity of gDNA and application scenarios. Normally, the lengths of amplicons in MultipSeq® panels are 160 to 260 bp for PE150 sequencing, while they are shorter for PPFE or cfDNA panels but longer for STRs.
Of course. We offer customization and semi-customization options to our customers to build their own BisCap® methylation panels.
No. Although the sequences of the adapters are the same, the cytosines in the adapter used in methylation library construction are methylated. They are different products with different names and catalog numbers. Please use the correct version of adapters in methylation library construction.
We use a dual-strand dual-methylation status probe design strategy to design the BisCap® methylation panels. Dual-strand strategy: the methylation statuses of positive and negative strands are normally different, and the dual-strand strategy ensures the capture of both strands. Dual-methylation status strategy: data has shown that, normally, the methylation status of a DNA sequence with continuous cytosines is full-methylation or non-methylation. Therefore, the probes are designed for both these statuses and it is has been proven that this dual-methylation status design strategy is capable of capture most of the targets while reducing the cost hugely compared to the exhaustive strategy.
There are several reasons that might cause low conversion rate of methylated cytosine: 1) The converted library is contaminated by the unconverted library. 2) The bisulfite conversion kit has a short shelf life and the use of an expired kit will significantly affect the result. 3) The input amount is too high.
Pre-BS and post-BS are strategies of adding adaptors before or after BS conversion. BS conversion causes damage to the DNA sequences and some of the DNA will become ssDNA, which leads to a low utilization rate of raw molecules and a much higher input amount requirement.
For qualified samples, most of the human DNA TargetSeq® panels can be evaluated by using the criteria of Coverage rate (%) > 99%, Target reads capture rate (%) > 50%, T 20% X coverage rate (%) > 97%. For TargetSeq® panels of other species, the performance might vary due to the differences of reference genome, target regions and strains.
We provide different design strategy to detect CNV according to its different sizes. For CNVs over 10 kb, a strategy called CNV backbone can be used by including high MAF SNPs at the intervals based on the target CNV sizes. For exon level CNVs (100 to 1000 bp), panels can be designed by covering all the related exon regions. The AIExome® Human Exome Panel V3 – Inherit includes the specially designed CNV backbone, which can be used for CNVs over 500 kb at whole genome level and CNVs over 50 kb at curated regions.
There are some regions in the genome that we classify as hard-to-capture regions, including high GC content sequences, repetitive sequences and homologous sequences. Based on the evaluation result, some of these target regions might be dropped as they might affect the overall performance or introduce errors. The probe coverage of most designs will be over 99% and the missed regions will be specified in probeMissed.bed.
No. DNA panels are designed based on the reference genome, while the RNA panels are designed based on the transcripts. RNA panels normally include additional probes at the edge of exons in order to increase the detection rate of fusions.
In our design report, we provide different versions of bed files for different analysis. Loci.bed and ProbeCov.bed are the bed files for target regions and the regions covered by actual probes, respectively. Please select the appropriate bed file according to your requirements. Please be noted that if the target is a point mutation or the panels includes the genome fixed/novel patches, the performance evaluated by using Loci.bed and ProbeCov.bed will be significantly different.
For human panels, TargetSeq® panel uses the 3X tiling design strategy based on thermodynamic stability, and a specifically optimized multi-factor strategy for hard-to-capture regions and different variation types to improve the overall performance and the detection rate of key markers. For other species, based on the self-developed algorithm, we will perform the evaluation of the genome first and design the panels using different tiling strategy to ensure the balance of the performance and the cost.
The capture rate is affected by multiple factors of the target region including the region size, high GC content sequences, repetitive sequences, homologous sequences and conservative sequences. All factors need to be considered to design well-performing panels. We use a multi-factor algorithm to design and evaluate the panels with specific strategy for hard-to-capture regions to ensure the best coverage and capture rates of the panels.
We will provide a form to collect the info we need to design the panel. Firstly, you need to specify the species name and reference genome info. Secondly, you need to provide the detailed info about the target regions, e.g., gene names, functional types (full length or exon), reference SNP cluster ID (rsID) number and type of variants. Thirdly, you also need to provide the sequencing read lengths of the panel. Lastly, you need to specify if you have any further requirement of the panel.
Customized TargetSeq® panels can be designed for any species with reference genomes, which means customized TargetSeq® panels can be designed not only for human, but also for other species with reference genome, e.g., animals, plants and microbes (single or multiple species).
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