coverage (genetics)

Even though the sequencing accuracy for each individual nucleotide is very high, the very large number of nucleotides in the genome means that if an individual genome is only sequenced once, there will be a significant number of sequencing errors. Furthermore, many positions in a genome contain rare single-nucleotide polymorphisms (SNPs). Hence to distinguish between sequencing errors and true SNPs, it is necessary to increase the sequencing accuracy even further by sequencing individual genomes a large number of times.

The term "ultra-deep" can sometimes also refer to higher coverage (>100-fold), which allows for detection of sequence variants in mixed populations.{{cite journal|date=September 2011|title=Accurate and comprehensive sequencing of personal genomes|journal=Genome Res.|volume=21|issue=9|pages=1498–505|doi=10.1101/gr.123638.111|pmc=3166834|pmid=21771779|vauthors=Ajay SS, Parker SC, Abaan HO, Fajardo KV, Margulies EH}}{{Cite journal|last1=Mirebrahim|first1=Hamid|last2=Close|first2=Timothy J.|last3=Lonardi|first3=Stefano|date=2015-06-15|title=De novo meta-assembly of ultra-deep sequencing data|journal=Bioinformatics|volume=31|issue=12|pages=i9–i16|doi=10.1093/bioinformatics/btv226|issn=1367-4803|pmid=26072514|pmc=4765875}}{{Cite journal|last1=Beerenwinkel|first1=Niko|last2=Zagordi|first2=Osvaldo|date=2011-11-01|title=Ultra-deep sequencing for the analysis of viral populations|journal=Current Opinion in Virology|volume=1|issue=5|pages=413–418|doi=10.1016/j.coviro.2011.07.008|pmid=22440844|author1-link=Niko Beerenwinkel}} In the extreme, error-corrected sequencing approaches such as Maximum-Depth Sequencing can make it so that coverage of a given region approaches the throughput of a sequencing machine, allowing coverages of >10^8.{{cite journal|journal=Nature|volume=534|issue=7609|doi=10.1038/nature18313|pmid=27338792|title=Rates and mechanisms of bacterial mutagenesis from maximum-depth sequencing|pages=693–696|pmc=4940094|year=2016|last1=Jee|first1=J.|last2=Rasouly|first2=A.|last3=Shamovsky|first3=I.|last4=Akivis|first4=Y.|last5=Steinman|first5=S.|last6=Mishra|first6=B.|last7=Nudler|first7=E.|bibcode=2016Natur.534..693J}}

Deep sequencing of transcriptomes, also known as RNA-Seq, provides both the sequence and frequency of RNA molecules that are present at any particular time in a specific cell type, tissue or organ.{{Cite journal|last1=Malone|first1=John H.|last2=Oliver|first2=Brian|date=2011-01-01|title=Microarrays, deep sequencing and the true measure of the transcriptome|journal=BMC Biology|volume=9|pages=34|doi=10.1186/1741-7007-9-34|pmid=21627854|pmc=3104486|issn=1741-7007 |doi-access=free }} Counting the number of mRNAs that are encoded by individual genes provides an indicator of protein-coding potential, a major contributor to phenotype.{{cite journal|year=2011|title=Deep sequencing the transcriptome reveals seasonal adaptive mechanisms in a hibernating mammal|journal=PLOS ONE|volume=6|issue=10|pages=e27021|doi=10.1371/journal.pone.0027021|pmc=3203946|pmid=22046435|vauthors=Hampton M, Melvin RG, Kendall AH, Kirkpatrick BR, Peterson N, Andrews MT|bibcode=2011PLoSO...627021H|doi-access=free}} Improving methods for RNA sequencing is an active area of research both in terms of experimental and computational methods.{{cite journal|year=2015|title=An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments.|journal=Nucleic Acids Res.|volume=43|issue=1|pages=e2|doi=10.1093/nar/gku1235|pmid=25505164|vauthors=Heyer EE, Ozadam H, Ricci EP, Cenik C, Moore MJ|pmc=4288154}}

The average coverage for a whole genome can be calculated from the length of the original genome (G), the number of reads (N), and the average read length (L) as $N\backslash times\; L/G$. For example, a hypothetical genome with 2,000 base pairs reconstructed from 8 reads with an average length of 500 nucleotides will have 2× redundancy. This parameter also enables one to estimate other quantities, such as the percentage of the genome covered by reads (sometimes also called breadth of coverage). A high coverage in shotgun sequencing is desired because it can overcome errors in base calling and assembly. The subject of DNA sequencing theory addresses the relationships of such quantities.

Sometimes a distinction is made between sequence coverage and physical coverage. Where sequence coverage is the average number of times a base is read, physical coverage is the average number of times a base is read or spanned by mate paired reads.{{Cite journal | last1 = Meyerson | first1 = M. | last2 = Gabriel | first2 = S. | last3 = Getz | first3 = G. | doi = 10.1038/nrg2841 | title = Advances in understanding cancer genomes through second-generation sequencing | journal = Nature Reviews Genetics | volume = 11 | issue = 10 | pages = 685–696 | year = 2010 | pmid = 20847746| s2cid = 2544266 }}{{cite journal |last1=Ekblom |first1=Robert |last2=Wolf |first2=Jochen B. W. |title=A field guide to whole-genome sequencing, assembly and annotation |journal=Evolutionary Applications |date=2014 |volume=7 |issue=9 |pages=1026–42 |doi=10.1111/eva.12178 |pmid=25553065 |pmc=4231593 |bibcode=2014EvApp...7.1026E }}

In terms of genomic coverage and accuracy, whole genome sequencing can broadly be classified into either of the following:{{cite web|url=https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost|title=The Cost of Sequencing a Human Genome|website=National Human Genome Research Institute|author=Kris A. Wetterstrand, M.S.}} Last updated: November 1, 2021

• A draft sequence, covering approximately 90% of the genome at approximately 99.9% accuracy
• A finished sequence, covering more than 95% of the genome at approximately 99.99% accuracy

Producing a truly high-quality finished sequence by this definition is very expensive. Thus, most human "whole genome sequencing" results are draft sequences (sometimes above and sometimes below the accuracy defined above).

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Category:Molecular biology

Category:DNA sequencing