What can you do with 0.1x genome coverage? A case study based on a genome survey of the scuttle fly Megaselia scalaris (Phoridae).
BACKGROUND
The declining cost of DNA sequencing is making genome sequencing a feasible option for more organisms, including many of interest to ecologists and evolutionary biologists. While obtaining high-depth, completely assembled genome sequences for most non-model organisms remains challenging, low-coverage genome survey sequences (GSS) can provide a wealth of biologically useful information at low cost. Here, using a random pyrosequencing approach, we sequence the genome of the scuttle fly Megaselia scalaris and evaluate the utility of our low-coverage GSS approach.


RESULTS
Random pyrosequencing of the M. scalaris genome provided a depth of coverage (0.05x0.1x) much lower than typical GSS studies. We demonstrate that, even with extremely low-coverage sequencing, bioinformatics approaches can yield extensive information about functional and repetitive elements. We also use our GSS data to develop genomic resources such as a nearly complete mitochondrial genome sequence and microsatellite markers for M. scalaris.


CONCLUSIONS
We conclude that low-coverage genome surveys are effective at generating useful information about organisms currently lacking genomic sequence data.
Rasmussen
David A
DA
Department of Biology, Duke University, Durham, NC 27708, USA. dar24@duke.edu
Noor
Mohamed A F
MA
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D004175:Diptera / Q000235:genetics*; D004330:Drosophila / Q000235:genetics; D005260:Female; D049750:Genome, Insect; D054629:Genome, Mitochondrial; D023281:Genomics / Q000379:methods; D020071:Interspersed Repetitive Sequences; D008297:Male; D018895:Microsatellite Repeats; D017422:Sequence Analysis, DNA / Q000379:methods*
Biotechniques. 2009 Mar;46(3):195-200
19317662
Science. 2007 Jun 22;316(5832):1718-23
17510324
Nucleic Acids Res. 2009 Jan;37(Database issue):D583-7
19028744
Cytogenet Genome Res. 2005;110(1-4):462-7
16093699
Cytogenet Genome Res. 2005;110(1-4):25-34
16093655
Nucleic Acids Res. 1999 Apr 15;27(8):1767-80
10101183
BMC Genomics. 2008 Oct 31;9:518
18976483
Nucleic Acids Res. 1997 Sep 1;25(17):3389-402
9254694
Am J Trop Med Hyg. 2004 Apr;70(4):386-9
15100451
PLoS Comput Biol. 2005 Sep;1(4):e43
16184192
Annu Rev Entomol. 2008;53:39-60
17622197
Science. 2002 Oct 4;298(5591):129-49
12364791
BMC Bioinformatics. 2008 Sep 09;9:366
18782453
Bioinformatics. 2007 Jul 1;23(13):1683-5
17463017
PLoS One. 2009;4(3):e4688
19259274
Mol Ecol Resour. 2008 Jan;8(1):3-17
21585713
Nature. 2007 Nov 8;450(7167):203-18
17994087
Nucleic Acids Res. 2009 Jan;37(Database issue):D555-9
18948289
PLoS One. 2007 May 09;2(5):e438
17487284
Biotechniques. 2009 Mar;46(3):185-92
19317661
Genome Res. 2005 Jan;15(1):1-18
15632085
BMC Genomics. 2007 Nov 21;8:427
18031571
Evolution. 2001 Jan;55(1):1-24
11263730
BMC Genomics. 2007 May 24;8:132
17524145
Genome Res. 2007 Nov;17(11):1547-9
17975171
J Egypt Soc Parasitol. 2005 Apr;35(1):331-40
15881016
BMC Genomics. 2005 May 10;6:70
15885146
Genome Res. 1998 Oct;8(10):1074-84
9799794
Science. 2003 Sep 26;301(5641):1898-903
14512627
Korean J Parasitol. 2008 Mar;46(1):33-6
18344675
Genetics. 2007 Nov;177(3):1277-90
18039867