AL
encodes a functional gene; if from a gene, on the other hand, it is more likely to have important biological implications.
With short-read sequencing, it is nearly impossible to fi nd mutations confi - dently in these areas of the genome. What is particularly interesting about these regions is that frequently there has been a selective pressure in the regions where a duplication has occurred. Repeat-rich parts of the genome are therefore enriched for biologically and clinically important genes. For example, many of the most important pharmacogenomics genes, which regulate how drugs are metabolized, overlap repeated parts of the genome.
Long-range sequencing allows researchers to align many more of these ambiguous regions because it provides information across a broader win- dow. If two regions are 99.9% identical, approximately every thousandth base will be diff erent. Therefore, by gathering information across tens of thousands of bases or more, there is a clear indication as to where to place those reads. Short-read sequencing is limited to a couple of hundred bases at a time, so the placement of reads and any variants implied by these reads remains ambiguous.
De novo assembly Two major paradigms are used in genome sequencing: 1) an alignment or
reference-based methodology, which involves aligning data to a reference genome and fi nding mutations with respect to that reference, and 2) de novo assembly, in which the genome is inferred entirely from the data itself. Most human genetic sequencing is done using the alignment methodol- ogy. For humans, the Human Genome Project was undertaken to create this reference, which is a compilation of a number of diff erent human sequences but is a reasonable representation of an “average” human genome. When scientists run an experiment for an individual, they fi rst align the reads to this reference, and then call changes in the sample relative to the reference, which are then identifi ed as mutations.
The problem with this method is that, for many parts of the genome, the reference is not a good model for the underlying variation present in the population. For example, the genes associated with human leukocyte an- tigen (HLA) have so much variation that the underlying assumption that people are roughly similar is false. The HLA genes carry a high mutation and variation rate because those genes modify the immune system to protect an individual from pathogens.
In these cases, it is not suffi cient to work from a reference and is prefer- able to start with the data and reconstruct the sequence, i.e., perform a de novo assembly. This is vital for reconstructing complex regions like HLA in human germline samples, and for understanding the full set of variations in cancer, where rearrangements can be so dramatic that the reference no longer serves as a good model for the underlying genome. For species outside of human, there is frequently no reference at all.(this is true for the vast majority of species on earth), and de novo assembly is the only way to analyze the sequencing data.
Additionally, shotgun metagenomics, which involves collecting and sequencing the DNA from all the bacteria from an environmental or anatomical sample, is emerging as an important application for de novo assembly. Scientists have traditionally studied bacteria by isolating and growing individual strains in the laboratory. This method falls short be- cause many species cannot be isolated and cultured in the laboratory. Shotgun metagenomics provides a more unbiased measurement of the species and genes present in environmental samples. These samples often contain a complex mix of species of microbes that are highly similar in
AMERICAN LABORATORY 45
multiple regions. De novo assembly with long-range sequencing eff ectively separates and reconstructs the genomes of the constituent microbes in environmental samples.
De novo assembly from short-read data yields incomplete results. Assemblies work on relatively short, unique stretches of the genome, but frequently encounter repeat regions that may come from multiple genomic locations. It is not possible to fully assemble anywhere near a complete genome using short-read sequencing, whereas with long-range sequencing, researchers can stitch those pieces together correctly into chromosome-scale stretches.
The new defi nition of sequencing The GemCode platform provides long-range information from sequencing
data and partitions large DNA molecules (on average 100 kilobases or more) into droplets, and then tags these fragments with a specifi c oligo that is sequenced along with the DNA. The oligo tags allow analysis software to reconstruct accurate, long-range genomic information. GemCode comple- ments, but does not replace, existing technology, providing the additional benefi ts of high throughput and a low error rate. With this molecular bar- coding and analysis platform, scientists can access complete and actionable data from which they can learn more about the genome than ever before.
Michael Schnall-Levin, Ph.D., is vice president, Computation Biology and Applications, 10X Genomics, 7068 Koll Center Pkwy., Ste. 401, Pleasanton, Calif. 94566, U.S.A.; tel.: 925-401-7300; e-mail:
mike@10xgenomics.com;
www.10xgenomics.com
The road to contamination-free PCR reactions
OPTIMIZER PCR Workstation • 4)101/+% &'5+)0 (14 %1/(146#$.' 215674' •
.+)*6 5#('6; +06'4.1%-
• .#%- (14/+%# 14 56#+0.'55 56''. 914- 574(#%' • 8#+.#$.' +0 G 5+<'5 • %%'55 2#0'. %.15'5 &74+0) ':2'4+/'06#. 241%'&74'5
+44#&+#6+10X 6*'0 5.+&'5 +061 $#5' &74+0)
For more information WJTJU XXX DCTTDJFOUJƋD DPN FNBJM TBMFT!DCTTDJ DPN DBMM
MARCH 2016
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60