Documents & FAQ


Which steps to start a project?

  1. Enquire through our contact form
  2. Receive consultancy for available solutions along with quotes
  3. Fill the customer registration and samplesheet forms
  4. Submit an order along with the documents above
  5. Send the samples along with printed documents


What should I use to elute nucleic acids?

For most NGS library prep protocols, DNA must be resuspended in Tris-HCl (ph 8.0 - 8.5), which is the buffer used to elute DNA in most commercial kits (NO EDTA must be present in the solution except for specific handling previously agreed). UltraPure Water is a second-choice alternative. RNAse-free water is the mandatory elution for RNA.


How to submit samples?

We only accept samples in 1.5mL or 2.0mL tubes sealed with parafilm. Sample numbers of 24 or more are only accepted in skirted 96-wells plates, sealed with alluminium foil (heat-sealing is preferable). Tubes and plates (especially) must be wrapped in order to avoid shocks during the transportation that can cause unsealing/uncapping of plates/tubes.


Do reads contain adapters?

Unless differently agreed, reads are provided with masking of adapters read-through. When a minimum of 5bp read-through is found with respect to sample-specific (barcode included) adapters, bases are masked with N character. Thus, read length is maintained to its original size. No quality clipping is applied on raw reads delivery, while regularly used in our standard bioinformatic pipelines.


Which protocol should be used to extract RNA?

We strongly recommend commercial kits for totalRNA or miRNA extraction (e.g. Spectrum Plant Total RNA Kit, TRI-REAGENT, RNeasy, MirVANA or MirPremier).


What should I do before RNA sample shipment?

In order to obtain a high quality sequencing data, customers must provide a good quality RNA, in detail:
· the 260/280 ratio of your RNA sample should be >1.8;
· RNA samples should be resuspended in nuclease-free water;
· on a gel, high-quality RNA should have two prominent bands (e.g. ribosomal RNA) with the 28S one (at 4.5 kb) should be twice the intensity of 18S (at 1.9 kb);
· on an Agilent Bioanalyzer 2100, RNA should have an RNA Integrity Number
(RIN) > 8.

Customers need to provide the result analysis of Agilent 2100 Bioanalyzer or, at least, gel-electophoresis image that can show the RNA quality. Quantify your RNA samples by spectrophotometer (e.g. Nanodrop) or fluorimeter (e.g. QuBit).


Which instruments should be used to evaluate sample quality?

Customers need to provide the result analysis of Agilent 2100 Bioanalyzer or, at least, gel-electophoresis image that can show the RNA quality. Quantify your RNA samples by spectrophotometer (e.g. Nanodrop) or fluorimeter (e.g. QuBit).


Are there alternatives to dry ice in order to ship RNA?

If you’re not able to send RNA samples in dry-ice you can send them lyophilized with RNAstable (Biomatrica,


What is the sample volume and concentration required to perform mRNA-Seq?

The total amount requested is 2.5 µg in at least 100µl (minimum concentration of 40 ng/µl). Use of degraded RNA can result in low yield, over-representation of 3’ends of the RNA molecules or failure of the protocol. Please refer to "RNA-smallRNA_Sample_preparation_guidelines" document for more details.


What is the sample volume and concentration required to perform stranded Total RNA-Seq?

The total amount requested is 1 µg in at least 20 µl (minimum concentration of 50 ng/µl).
This protocol works also with degraded RNAs and FFPE RNAs even if the success rate is not guarantee.
DNase I step is mandatory after the RNA isolation. RNA that has DNA contamination will result in an underestimation of the amount of the RNA used and poor data quality. Look at species compatibility here. Please refer to "RNA-smallRNA_Sample_preparation_guidelines" document for more details.


What is the sample volume and concentration required to perform smallRNA-Seq?

The total amount requested is 2 µg (minimum concentration of 200 ng/µl) of total RNA or 100 ng of previously isolated microRNA (minimum concentration of 10 ng/µl) in 10 µl of nuclease-free water or 10 nM Tris-HCl, pH 8.5. Please refer to "RNA-smallRNA_Sample_preparation_guidelines" document for more details.


What is the depth of coverage that I need?

There is no official recommendation for sequencing coverage level. Coverage requirements depend on application and standards are set by the field you are in and scientific journals. One has to keep in mind that every base in the sample has to be sequenced several times to allow for the reliable base call and that, in addition, reads are not distributed evenly over an entire genome or target region (many bases will be covered by fewer reads than the average, while other bases will be covered by more reads than average). Increase of coverage enhances the detection of rare variants present in a highly heterogenous samples, such as cancer and permits detection of rarely expressed genes.


Why target enrichment doesn’t yield even coverage distribution?

PCR-based methods require highly multiplexed oligonucleotide pairs targeted to heterogeneous sequences with a range of melting temperatures and CG content to generate hundreds or thousands of amplicons in a single tube. This leads to differences in amplicon presentation and uneven sequence coverage. In hybridization-based methods efficiency of capture is not uniform. High GC content in regions such as the 5’UTR, promoter regions and the first exons of genes affect enrichment efficiency as well as repeat elements, tandem repeats and pseudogenes resulting in uneven distribution of coverage. Finally, but not less importantly, a lower quantity or lower quality of DNA is often found to introduce bias in the downstream analysis.


Should I treat my RNA samples with DNase?

SmallRNA-Seq and mRNA-Seq DOES NOT require DNase treatment. Instead DNase treatment is recommended for other protocols such as total RNA-Seq.


Should I remove duplicates in RNA-seq?

Duplicates in RNA-seq are not necessarily an artifact. In fact, observing high rates of read duplicates in RNA-seq libraries is common. It may not be an indication of poor library complexity caused by low sample input or over-amplification. In general, for paired-end reads, removal of duplicates could be a part of a standard procedure since alignments that start at the same locations at both read 1 and read 2 are very unlikely to occur by chance because of the variation in fragment size. However, for short RNA (i.e., small transcript, miRNA, etc) that is very highly expressed there might be many, many legitimate duplicate copies with exactly the same fragment size/position.


Which is the optimal sequencing depth in ChIP-seq experiments?

An important consideration in experimental design is the minimum number of sequenced reads required to obtain statistically significant results. The amount of produced reads, i.e. the required sequencing depth, depends on the nature of the mark and the state of the cell in each experiment. However you can find some good guidelines here. Jung et al. observed that sufficient depth is often reached at <20 million reads for fly, while for human they suggest 40-50 million reads as a practical minimum for most marks.


How to treat duplicated reads in ChIP-seq experiments?

The most “politically correct” solution is the MACS2 one. If the read length parameter is set to zero, MACS2 detects read length automatically and proceeds to filter out duplicate reads. By default it calculates the maximum number of duplicate reads in a single position warranted by the sequencing depth, and removes redundant reads in excess of this number. Alternatively, you can select to keep only one read, or all duplicates.


What is the best control for ChIP-Seq: Input, Igg or Untagged Strain?

Most labs use Input since IgG can be biased because: most IgG antibodies are not obtained from true preimmune serum from the same animal in which the specific antibody was raised; and IgG antibodies usually immunoprecipitate much less DNA than specific antibodies do, and thus limited genomic regions from the control may be over-amplified during the library construction step. You can find a good overview here.


What is the peak model building in ChIP-seq data?

MACS2 models the distance between the paired forward and reverse strand peaks from the data. It slides a window across the genome to find enriched regions, which have M-fold more reads than background. The size of the window is twice the bandwidth parameter. The expected background is the number of reads times their length divided by the mappable genome size. Note that the mappable genome size is always less than the real genome size because of repetitive sequence. The regions' fold enrichment must be higher than 10 and less than 30 (these values can be changed if not enough regions are found). However, a smaller value for the lower cutoff provides more regions for model building, but it can also include spurious data into the model and thereby adversely affect the peak finding results. MACS2 uses 1000 enriched regions to model the distance between the forward and reverse strand peaks, predicting the fragment size.


How does MACS2 detect peaks?

In the peak detection phase, MACS2 extends the reads in the 3' direction to the fragment length obtained from modeling. If the model building failed or if it was switched off, the reads are extended to the value of the extension size parameter. If a control sample is available, MACS2 scales the samples linearly to the same read number. It then selects candidate peaks by scanning the genome again, now using a window size which is twice the fragment length. MACS2 calculates a p-value for each peak using a dynamic Poisson distribution to capture local biases in read background levels. If a control sample is available, it is used to calculate the local background. Finally, q-values are calculated using the Benjamini-Hochberg correction.


Which is the effect of sequencing depth on new microRNA discovery?

Sequencing depth is one of the most crucial factors for both differential expression analysis and discovery of rare or novel microRNAs and can vary from tissue to tissue. Having said that, 10 million of reads are sufficient for thorough discovery and effective differential expression analysis. For more info, please, look here.


Does mRNA-seq detect long non-coding RNAs?

LncRNAs are 50/50 polyA+ and polyA-. If the RNA-seq library is polyA+ enriched there will be a bias in analysis for those lncRNAs that are polyA+.


Documents & Reports

Customer Registration Form 21032017.docx

Samples Spreadsheet 21032017.xlsx

BS Seq Sample preparation guidelines.pdf

Clinical Genotyping Sample preparation guidelines.pdf

ddRAD Sample requirements guidelines.pdf

Denovo Sample preparation guidelines.pdf

ChIP Seq Sample preparation guidelines.pdf

DNA Seq Sample preparation guidelines.pdf

Human microbiome Sample preparation guidelines.pdf

Exome Seq Sample preparation guidelines.pdf

Metabarcoding Sample preparation guidelines.pdf

Targeted Genotyping Sample preparation guidelines.pdf

Metagenomics Sample preparation guidelines.pdf

Terms and Conditions v2 28032017.pdf

RNA and smallRNA Sample preparation guidelines.pdf