We have checked for the presence of PCR duplicates for both the sequencing experiments. It is important to notice that the sequencing of S2 of Exp2 yielded a very low amount of reads because of the paucity of the available DNA, then introducing a bias from the beginning of the analysis. The choice of reporting results also for this sample is deliberate. The aim is to make the difference between biased and not biased results clear.
As for Supplementary Figures S2 and S3 , the four samples are heterogeneous in terms of QVs distribution and of the number of reads produced by both experiments.
The number of reads range from 70 to million, apart from S2 of Exp2, whose reads set size is about 10 million. The rapid decline of the color calling accuracy occurs for both forward and reverse fragments. Regarding Exp2, proportions of reads with high-quality initial sites are dramatically reduced for S1 and S3.
By the QV run assessment tool we have also verified that, as expected, the reverse reads of each pair have systematically lower QVs.
This is probably due to the SOLiD 4 chemistry, which is characterized by five cyclic subsequent ligations of primers. Given the impact of the pre-processing step on the mapped reads, we have further investigated the degree of coverage of the target regions and reported in Table 2. Coverage analysis of the target regions.
Column 9 holds the proportion of uncovered regions i. Consistently, results showed that the less stringent the applied filters, the more covered each site, for each sample and experiment. Coverage was also calculated on the full length of the target regions. Thus, we checked the bases composition of our targets by comparing the GC content of the skipped exons with that of the Good quality variants were selected from the consensus lists of the variants outputted by the three callers, when run on the four samples filtered and unfiltered of both experiments.
Additionally, we filled Table 3 with the numbers of the detected non-synonymous, stop-gain, stop-loss, splice-site mutations and Indels that have been predicted to be homozygous because of the recessive mode of inheritance presumed for the studied diseases.
General statistics of the variants. Columns 12 holds the ratio between non-synonymous nsyn and synonymous SNPs. Non-synonyomus, stop codon gain sg , stop codon loss sl for homozygous SNPs are presented in columns 13— Indels called in target exonic regions and novel homozygous Indels are shown in columns 16 and We found less than The number of exonic SNPs detected in the Exp2 was close to that expected in the human nuclear genome [ 23 , 24 ].
The proportion of novel exonic variants varied with the reads sets: generally, filtered reads sets had less unpublished SNPs than the raw reads sets. Their numbers were closer to the expectations.
However, several inconsistencies emerged. Generally, the less stringent the filter, the more variants were detected. Table 3 shows that a very few number of Indels were novel and homozygous and that the reads set of S2 of Exp2 contains the smallest pool of Indels. Filtered sets exhibited higher and more real ratios. In particular, if considering all variants, we measured an average ratio of 2.
Equally when considering novel or exonic variants only, ratios were under the expectations. Again, more stringent filtering criteria F1, F3 and F4 generally determined higher ratios. Instead, a discrete excess of putative non-synonymous mutations was present in the unfiltered reads sets. We also tried to review the disease-related exonic mutations: given the recessive nature of the considered diseases, we searched for homozygous mutations causing amino-acid changes nsyn , stop codon gain sg , stop codon loss sl and splice site disruption.
We detected no mutations having the homozygous genotype on splicing sites. We finally estimated the number of SNPs in common among the reads sets, performing both a pairwise and a global comparison among the variants sets Table 4. Similar figures were obtained for Indels data not shown. Common variants between pairs of variants sets. For all samples sequenced in both experiments, all possible comparisons among the six filtered F1—F6 and two raw reads sets Raw Exp1, Raw Exp2 are calculated.
Variants detection is notably a crucial topic in genetic field. A plethora of NGS technologies, software, statistical and computational methods witness the current growing interest of scientists in this topic [ 21 , 23 , 24 , 25 ]. This work focuses on the impact of the sequences quality on the process of determining the candidate variants within the human exome. In particular, it assesses how poor quality short-reads can affect their mapping against the reference human genome and, consequently, the identification of the variants.
To do that, it makes use of some existing as well as custom tools, of which one delineates the range of applicability, functionality, parameters and format of the output.
The test cases are four samples, taken from three patients affected by three diverse severe neurogenetic diseases and one control patient, which have been sequenced twice by two different NGS facilities SOLiD 4. Data revealed that the accuracy of the color calling systematically decreased right from the first 20—25 positions of the reads and, then, that their general quality was rather low for both experiments, so that to confer a worst-case nature to our study.
We then evaluated the opportunity of filtering the reads and observed how that impacted on the overall variants discovery process. Filters have been chosen in a way to guarantee different average levels of quality and coverage. This value allows to reliably call variants and genotypes. Obviously, filtering impacted on the overall number of determined variants for each dataset, which was lower than the canonical 15— Exons resulted to have a significantly elevate GC content with respect to the contiguous noncoding regions [ 27 ].
Studies based on large samplings e. Our filters matched these figures as well. Statistics about Indels enjoyed a poor consensus within the literature, probably because of the general difficulty of distinguishing real variants from artifacts. For this reason, figures cannot be rigorously confirmed here. Estimates from Table 3 and pairwise comparisons presented in Table 4 demonstrated how read quality influences the mapping and, consequently, the variants discovery processes.
Generally, we have obtained a lower than expected number of SNPs and Indels, given that low-quality reads were discarded, thereby decreasing the libraries sizes. Furthermore, considering the unfiltered reads sets from both experiments, we verified that the proportion of common SNPs within same samples is quite low. Contrarily, any paired filtered set showed a higher number of common variants, meaning that the filtering process improved both the reads mapping and the variants call processes.
Raw data are often affected by systematic errors due to the particular sequencing chemistry. Any downstream analysis performed on raw data exhibits false positive results. Pre-processing the raw data may help to improve the quality of any downstream analysis result. Some of the required pre-processing steps can be successfully performed by the existing tools, while others require custom implementations.
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Volume Article Contents Abstract. Stefano Castellana , Stefano Castellana. Oxford Academic. Marta Romani. Enza Maria Valente. Tommaso Mazza. Select Format Select format. Permissions Icon Permissions. Abstract Next generation sequencers have greatly improved our ability to mine polymorphisms and mutations out of entire or portions of genomes.
Figure Open in new tab Download slide. Thus, we have tested the QV run assessment tool on our reads sets. By applying six default combinations of values of independent and polyclonality errors, the tool gave us a preliminary insight into the quality of data.
Results are summarized in Supplementary Figures S1 and S2. Table 1: Results of the filters. Total reads. Mapped reads. On-target reads. Open in new tab.
Table 2: Coverage analysis of the target regions. Mean SC. Median SC. Poorly cov. S1 F1 Table 3: General statistics of the variants.
Reads sets. Exonic SNPs. Novel SNPs. Exonic novel. Homozygous mutations. Exonic Indels. A semiconductor chip detects the hydrogen ions produced during DNA polymerization Figure 5. The dNTP is then incorporated into the new strand if complementary to the nucleotide on the target strand. Each time a nucleotide is successfully added, a hydrogen ion is released, and it detected by the sequencer's pH sensor.
Ion torrent sequencing is the first commercial technique not to use fluorescence and camera scanning; it is therefore faster and cheaper than many of the other methods. Unfortunately, it can be difficult to enumerate the number of identical bases added consecutively.
For example, it may be difficult to differentiate the pH change for a homorepeat of length 9 to one of length 10, making it difficult to decode repetitive sequences. These beads are then deposited onto a glass surface - a high density of beads can be achieved which which in turn, increases the throughput of the technique.
Once bead deposition has occurred, a primer of length N is hybridized to the adapter, then the beads are exposed to a library of 8-mer probes which have different fluorescent dye at the 5' end and a hydroxyl group at the 3' end. Bases 1 and 2 are complementary to the nucleotides to be sequenced whilst bases are degenerate and bases are inosine bases.
Only a complementary probe will hybridize to the target sequence, adjacent to the primer. DNA ligase is then uses to join the 8-mer probe to the primer. A phosphorothioate linkage between bases 5 and 6 allows the fluorescent dye to be cleaved from the fragment using silver ions.
Many rounds of sequencing using shorter primers each time i. Due to the two-base sequencing method since each base is effectively sequenced twice , the SOLiD technique is highly accurate at It can complete a single run in 7 days and in that time can produce 30 Gb of data.
Unfortunately, its main disadvantage is that read lengths are short, making it unsuitable for many applications. Reversible terminator sequencing differs from the traditional Sanger method in that, instead of terminating the primer extension irreversibly using dideoxynucleotide, modified nucleotides are used in reversible termination.
Whilst many other techniques use emulsion PCR to amplify the DNA library fragments, reversible termination uses bridge PCR, improving the efficiency of this stage of the process. Reversible terminators can be grouped into two categories: 3'-O-blocked reversible terminators and 3'-unblocked reversible terminators. The mechanism uses a sequencing by synthesis approach, elongating the primer in a stepwise manner.
Firstly, the sequencing primers and templates are fixed to a solid support. Only the correct base anneals to the target and is subsequently ligated to the primer. The solid support is then imaged and nucleotides that have not been incorporated are washed away and the fluorescent branch is cleaved using TCEP tris 2-carboxyethyl phosphine. The reversible termination group of 3'-unblocked reversible terminators is linked to both the base and the fluorescence group, which now acts as part of the termination group as well as a reporter.
The main disadvantage of these techniques lies with their poor read length, which can be caused by one of two phenomena. In order to prevent incorporation of two nucleotides in a single step, a block is put in place, however in the event of no block addition due to a poor synthesis, strands can become out of phase creating noise which limits read length.
Noise can also be created if the fluorophore is unsuccessfully attached or removed. These problems are prevalent in other sequencing methods and are the main limiting factors to read length. It also has a high data output of Gb per run which takes around 8 days to complete. A new cohort of techniques has since been developed using single molecule sequencing and single real time sequencing, removing the need for clonal amplification.
This reduces errors caused by PCR, simplifies library preparation and, most importantly, gives a much higher read length using higher throughput platforms.
Examples include Pacific Biosciences' platform which uses SMRT single molecule real time sequencing to give read lengths of around one thousand bases and Helicos Biosciences which utilises single molecule sequencing and therefore does not require amplification prior to sequencing. Oxford Nanopore Technologies are currently developing silicon-based nanopores which are subjected to a current that changes as DNA passes through the pore.
This is anticipated to be a high-throughput rapid method of DNA sequencing, although problems such as slowing transportation through the pore must first be addressed. Just as Next generation sequencing enabled genomic sequencing on a massive scale, it has become clear recently that the genetic code does not contain all the information needed by organisms. Epigenetic modifications to DNA bases, in particular 5-methylcytosine, also convey important information.
All of the second generation sequencing platforms depend, like Sanger sequencing, on PCR and therefore cannot sequence modified DNA bases. In fact, both 5-methylcytosine and 5-hydroxymethylcytosine are treated as cytosine by the enzymes involved in PCR; therefore, epigenetic information is lost during sequencing. Bisulfite sequencing exploits the difference in reactivity of cytosine and 5-methylcytosine with respect to bisulfite: cytosine is deaminated by bisulfite to form uracil which reads as T when sequenced , whereas 5-methylcytosine is unreactive i.
If two sequencing runs are done in parallel, one with bisulfite treatment and one without, the differences between the outputs of the two runs indicate methylated cytosines in the original sequence. This technique can also be used for dsDNA, since after treatment with bisulfite, the strands are no longer complementary and can be treated as ssDNA. This complicates matters somewhat, and means that bisulfite sequencing cannot be used as a true indicator of methylation in itself.
Oxidative bisulfite sequencing adds a chemical oxidation step, which converts 5-hydroxymethylcytosine to 5-formylcytosine using potassium perruthenate, KRuO4, before bisulfite treatment. Now, three separate sequencing runs are necessary to distinguish cytosine, 5-methylcytosine and 5-hydroxymethylcytosine see Figure 9. Next generation sequencing has enabled researchers to collect vast quantities of genomic sequencing data. A large focus area in gene therapy is cancer treatment — one potential method would be to introduce an antisense RNA which specifically prevents the synthesis of a targeted protein to the oncogene, which is triggered to form tumorous cells.
Many genetic codes for toxic proteins and enzymes are known, and introduction of these genes into tumor cells would result in cell death. The difficulty in this method is to ensure a very precise delivery system to prevent killing healthy cells. As the cost of DNA sequencing goes down, it will become more widespread, which brings a number of issues.
Sequencing produces huge volumes of data, and there are many computational challenges associated with processing and storing the data. DNA sequencing data must be stored securely, since there are concerns that insurance groups, mortgage brokers and employers may use this data to modify insurance quotes or distinguish between candidates.
Sequencing may also help to find out whether an individual has an increased risk to a particular disease, but whether the patient is informed or if there is a cure for the disease is another issue altogether.
Ahmadian, A. Sequencing Platforms using Lab on a Chip Technologies. Lab Chip, 11, - Balasubramanian, S. Chem Int. Chen, F. Mardis, E. Genomics Hum. Show all chapters. Introduction The sequencing of the human genome was completed in , after 13 years of international collaboration and investment of USD 3 billion. Sanger sequencing and Next-generation sequencing The principle behind Next Generation Sequencing NGS is similar to that of Sanger sequencing , which relies on capillary electrophoresis.
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