question: What is the difference between Next-Generation DNA Sequencing and regular DNA Sequencing (is there even a difference)? What does it mean to "complete the whole genome" and how does it relate to DNA sequencing?
comment: Imagine finding all the unnumbered pages of a very long book scattered, and your job was to put it back together in the proper order. With sanger sequencing (or first gen) basically you'd pick a section you know or have seen before, and then work your way backwards (and forwards) from that middle point, figuring out which pages fit right before or after, basically one page at a time. In Next-gen sequencing, you would make multiple copies of all the pages, and with the help of a computer, use multiple starting points to come up with millions of small sections, or groups of pages (called "reads") that can then be pieced together. In this way, you'll have multiple sections that overlap; some reads might have pages 3-14, while others might have pgs 10-14, or 3-8 or 5-7. And hopefully you'll have some that not only have some overlap, but give you a new "end" to work with. In the example above, a section like pgs 9-17 would be awesome: I have enough overlap from page 9 to page 14 that I can trust pages 15, 16 and 17 being correct. And now I can look at sections that include 17. This does a couple things: it gives you a level of confidence, because if you keep getting the same order of pages over and over again, you know that those pages probably go together. But it also makes it so much faster, because you're able to do multiple sections at a time. Just like a 10 piece puzzle is much easier than a 1000 piece puzzle of the same image. All that said, however, even after next gen sequencing, first-gen is still often used to verify the results and cross check for accuracy. As far as "completing the whole genome": basically the goal is to figure out the entire genetic sequence of organisms, in order, to serve as a map. Where certain genes are on the genome can help with many things, for example, we can come up with more targeted gene therapies. Also, if we know where genes are *supposed* to be, we can compare completely different organisms and deduce evolutionary pathways (which is what I used to do in my research.)
passages: It seems likely that in the future, MinION raw data will be used to detect many different epigenetic marks in DNA.
   Section::::Challenges.
   Third-generation sequencing
  
  Third-generation sequencing (also known as long-read sequencing) is a class of DNA sequencing methods currently under active development. Third generation sequencing works by reading the nucleotide sequences at the single molecule level, in contrast to existing methods that require breaking long strands of DNA into small segments then inferring nucleotide sequences by amplification and synthesis. Critical challenges exist in the engineering of the necessary molecular instruments for whole genome sequencing to make the technology commercially available.
   Section::::Current technologies.
  
  Sequencing technologies with a different approach than second-generation platforms were first described as "third-generation" in 2008-2009.
  
  There are several companies currently at the heart of third generation sequencing technology development, namely, Pacific Biosciences, Oxford Nanopore Technology, Quantapore (CA-USA), and Stratos (WA-USA). These companies are taking fundamentally different approaches to sequencing single DNA molecules.
  
  PacBio developed the sequencing platform of single molecule real time sequencing (SMRT), based on the properties of zero-mode waveguides. Signals are in the form of fluorescent light emission from each nucleotide incorporated by a DNA polymerase bound to the bottom of the zL well.
   Section::::Genome assembly.:Hybrid assembly.
  
  Long read lengths offered by third generation sequencing may alleviate many of the challenges currently faced by de novo genome assemblies. For example, if an entire repetitive region can be sequenced unambiguously in a single read, no computation inference would be required. Computational methods have been proposed to alleviate the issue of high error rates. For example, in one study, it was demonstrated that de novo assembly of a microbial genome using PacBio sequencing alone performed superior to that of second generation sequencing.
   Section::::Metagenomics.
  
  Metagenomics is the analysis of genetic material recovered directly from environmental samples.
  
  Section::::Metagenomics.:Advantages.
  
  The main advantage for third-generation sequencing technologies in metagenomics is their speed of sequencing in comparison to second generation techniques. Speed of sequencing is important for example in the clinical setting (i.e. pathogen identification), to allow for efficient diagnosis and timely clinical actions.
   A common phylogenetic marker for microbial community diversity studies is the 16S ribosomal RNA gene. Both MinION and PacBio's SMRT platform have been used to sequence this gene. In this context the PacBio error rate was comparable to that of shorter reads from 454 and Illumina's MiSeq sequencing platforms.
  
  Section::::Metagenomics.:Drawbacks.
   Section::::Transcriptomics.:Transcript reconstruction.
   Massive parallel sequencing
  
  Massive parallel sequencing or massively parallel sequencing is any of several high-throughput approaches to DNA sequencing using the concept of massively parallel processing; it is also called next-generation sequencing (NGS) or second-generation sequencing. Some of these technologies emerged in 1994-1998 and have been commercially available since 2005. These technologies use miniaturized and parallelized platforms for sequencing of 1 million to 43 billion short reads (50-400 bases each) per instrument run.
   Second-generation sequencing, often referred to as Next-generation sequencing (NGS), has dominated the DNA sequencing space since its development. It has dramatically reduced the cost of DNA sequencing by enabling a massively-paralleled approach capable of producing large numbers of reads at exceptionally high coverages throughout the genome.
   It is well known that eukaryotic genomes including primates and humans are complex and have large numbers of long repeated regions. Short reads from second generation sequencing must resort to approximative strategies in order to infer sequences over long ranges for assembly and genetic variant calling. Pair end reads have been leveraged by second generation sequencing to combat these limitations. However, exact fragment lengths of pair ends are often unknown and must also be approximated as well. By making long reads lengths possible, third generation sequencing technologies have clear advantages.
  
  Section::::Advantages.:Epigenetics.
   The current most common methods for examining methylation state require an assay that fragments DNA before standard second generation sequencing on the Illumina platform. As a result of short read length, information regarding the longer patterns of methylation are lost. Third generation sequencing technologies offer the capability for single molecule real-time sequencing of longer reads, and detection of DNA modification without the aforementioned assay.
   In comparison to the current generation of sequencing technologies, third generation sequencing has the obvious advantage of producing much longer reads. It is expected that these longer read lengths will alleviate numerous computational challenges surrounding genome assembly, transcript reconstruction, and metagenomics among other important areas of modern biology and medicine.
   Section::::Post Human Genome Project advancements.:Metagenomic sequencing.
   To identify the causal DNA-binding motif for CUT&RUN-seq peak calls one can apply the MEME motif-finding program to the CUT&RUN sequences. This involves using a position-specific scoring matrix (PSSM) along with the Motif Alignment and Search Tool (MAST) to identify motifs in a reference genome that match the acquired sequence reads. This process allows the identification of the transcription-factor binding motif, or if the binding motif was previously known, this process can act to confirm the success of the experiment
  
  Section::::Limitations.
   Other important advantages of third generation sequencing technologies include portability and sequencing speed. Since minimal sample preprocessing is required in comparison to second generation sequencing, smaller equipments could be designed. Oxford Nanopore Technology has recently commercialized the MinION sequencer. This sequencing machine is roughly the size of a regular USB flash drive and can be used readily by connecting to a laptop. In addition, since the sequencing process is not parallelized across regions of the genome, data could be collected and analyzed in real time. These advantages of third generation sequencing may be well-suited in hospital settings where quick and on-site data collection and analysis is demanded.
   Section::::Research tools available.
  
  BULLET::::- DNA sequencing
  
  BULLET::::- Massively Parallel Sequencing "next-gen sequencing"
  
  BULLET::::- Full genome sequencing
  
  BULLET::::- Gene mapping
  
  BULLET::::- SNP analysis
  
  BULLET::::- Genotyping
  
  BULLET::::- Linkage analysis
  
  BULLET::::- Genomic sequencing
  
  BULLET::::- ChIP-Seq
  
  BULLET::::- RNA-Seq
  
  BULLET::::- GRO-Seq
  
  BULLET::::- Digital gene expression
  
  BULLET::::- Genome resequencing
  
  BULLET::::- High level indexing for directed resequencing
  
  BULLET::::- Protein Sequencing (suspended)
  
  BULLET::::- N-terminal sequencing (suspended)
  
  BULLET::::- Radioactive tracer detection (suspended)
  
  BULLET::::- Mass spectrometry
  
  BULLET::::- MALDI-TOF
  
  BULLET::::- Ion trap
  
  BULLET::::- Nanospray
  
  BULLET::::- DNA synthesis (suspended)
  
  BULLET::::- Peptide synthesis (suspended)
  
  BULLET::::- Amino acid analysis
  
  BULLET::::- Biacore
  
  BULLET::::- HPLC (for MBCF Q/C only)
  
  BULLET::::- Bioinformatics
  
  BULLET::::- Sequence analysis
   Section::::Advanced methods and "de novo" sequencing.:Shotgun sequencing.
  
  Shotgun sequencing is a sequencing method designed for analysis of DNA sequences longer than 1000 base pairs, up to and including entire chromosomes. This method requires the target DNA to be broken into random fragments. After sequencing individual fragments, the sequences can be reassembled on the basis of their overlapping regions.
  
  Section::::Advanced methods and "de novo" sequencing.:Bridge PCR.
   Section::::Current method.
  
  Second-generation or "Next-Gen" (NGS) techniques have evolved radically: the sequencing capacity has increased more than ten thousandfold and the cost has dropped by over one million fold since 2007(National Human Genome Research Institute). NGS has revolutionized the Genetic field in many ways.
  
  Section::::Current method.:Library construction.
  
  A library is often prepared by random fragmentation of DNA and ligation of common adaptor sequences. 
   In 1995, Roach "et al." proposed and demonstrated through simulations a generalization of a set of strategies explored earlier by Edwards and Caskey. This whole-genome sequencing method became immensely popular as it was championed by Celera and used to sequence several model organisms before Celera applied it to the human genome. Today, most sequencing projects employ this strategy, often called paired end sequencing.
  
  Section::::Post Human Genome Project advancements.
   BULLET::::- Capture Uniformity: analogous to recall – the fraction of genomic targets that are captured with confidence. Specifically, the relative abundance of sequence reads that are mapped to each genomic target.
  
  BULLET::::- Capture Specificity: analogous to precision – the fraction of sequence reads that actually map to the genomic targets of interest.
  
  These two metrics are directly affected by the quality of the batch of probes.
  
  To improve the results for low quality probes, higher levels of sequencing depths can be performed. The amount of sequencing scales needed nearly exponentially with decreases in uniformity and specificity.
   The term ""de novo" sequencing" specifically refers to methods used to determine the sequence of DNA with no previously known sequence. "De novo" translates from Latin as "from the beginning". Gaps in the assembled sequence may be filled by primer walking. The different strategies have different tradeoffs in speed and accuracy; shotgun methods are often used for sequencing large genomes, but its assembly is complex and difficult, particularly with sequence repeats often causing gaps in genome assembly.
   One strategy that incorporates HT-NGS is hybrid sequencing, wherein several sequencing technologies are used at different levels of coverage, so that they can complement each other with their respective strengths. The release of the SMRT platform, from Pacific Biosciences, marked the beginning of single molecule sequencing and long read tech. It has been shown that 80-100X coverage with SMRT technology, which generates average read with lengths of 5456bp, is usually sufficient to create a finished de novo assembly for prokaryotic organisms. When the funds for that level of coverage are not available to a researcher, they might decide to use a hybrid approach.
   Other methods address different types of DNA modifications using the MinION platform. Stoiber et al. examined 4-methylcytosine (4mC) and 6-methyladenine (6mA), along with 5mC, and also created a software to directly visualize the raw MinION data in human-friendly way. Here they found that in "E. coli", which has a known methylome, event windows of 5 base pairs long can be used to divide and statistically analyze the raw MinION electrical signals. A straightforward Mann-Whitney U test can detect modified portions of the "E. coli" sequence, as well as further split the modifications into 4mC, 6mA or 5mC regions.
   There are two principal methods for this fragmentation and sequencing process. Primer walking (or "chromosome walking") progresses through the entire strand piece by piece, whereas shotgun sequencing is a faster but more complex process that uses random fragments.
  
  In shotgun sequencing, DNA is broken up randomly into numerous small segments, which are sequenced using the chain termination method to obtain "reads". Multiple overlapping reads for the target DNA are obtained by performing several rounds of this fragmentation and sequencing. Computer programs then use the overlapping ends of different reads to assemble them into a continuous sequence.
  