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Abstract
The widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived sequence data, I provide general recommendations regarding the optimal strength of trimming, specifically in mRNA-Seq studies. Although very aggressive quality trimming is common, this study suggests that a more gentle trimming, specifically of those nucleotides whose Phred score <2 or <5, is optimal for most studies across a wide variety of metrics.
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Affiliation(s)
- Matthew D Macmanes
- Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire Durham, NH, USA ; Hubbard Center for Genome Studies Durham, NH, USA
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Bradnam KR, Fass JN, Alexandrov A, Baranay P, Bechner M, Birol I, Boisvert S, Chapman JA, Chapuis G, Chikhi R, Chitsaz H, Chou WC, Corbeil J, Del Fabbro C, Docking TR, Durbin R, Earl D, Emrich S, Fedotov P, Fonseca NA, Ganapathy G, Gibbs RA, Gnerre S, Godzaridis E, Goldstein S, Haimel M, Hall G, Haussler D, Hiatt JB, Ho IY, Howard J, Hunt M, Jackman SD, Jaffe DB, Jarvis ED, Jiang H, Kazakov S, Kersey PJ, Kitzman JO, Knight JR, Koren S, Lam TW, Lavenier D, Laviolette F, Li Y, Li Z, Liu B, Liu Y, Luo R, Maccallum I, Macmanes MD, Maillet N, Melnikov S, Naquin D, Ning Z, Otto TD, Paten B, Paulo OS, Phillippy AM, Pina-Martins F, Place M, Przybylski D, Qin X, Qu C, Ribeiro FJ, Richards S, Rokhsar DS, Ruby JG, Scalabrin S, Schatz MC, Schwartz DC, Sergushichev A, Sharpe T, Shaw TI, Shendure J, Shi Y, Simpson JT, Song H, Tsarev F, Vezzi F, Vicedomini R, Vieira BM, Wang J, Worley KC, Yin S, Yiu SM, Yuan J, Zhang G, Zhang H, Zhou S, Korf IF. Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species. Gigascience 2013; 2:10. [PMID: 23870653 PMCID: PMC3844414 DOI: 10.1186/2047-217x-2-10] [Citation(s) in RCA: 415] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Accepted: 07/15/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. RESULTS In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. CONCLUSIONS Many current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.
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Rowe KC, Singhal S, Macmanes MD, Ayroles JF, Morelli TL, Rubidge EM, Bi K, Moritz CC. Museum genomics: low-cost and high-accuracy genetic data from historical specimens. Mol Ecol Resour 2011; 11:1082-92. [PMID: 21791033 DOI: 10.1111/j.1755-0998.2011.03052.x] [Citation(s) in RCA: 90] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Natural history collections are unparalleled repositories of geographical and temporal variation in faunal conditions. Molecular studies offer an opportunity to uncover much of this variation; however, genetic studies of historical museum specimens typically rely on extracting highly degraded and chemically modified DNA samples from skins, skulls or other dried samples. Despite this limitation, obtaining short fragments of DNA sequences using traditional PCR amplification of DNA has been the primary method for genetic study of historical specimens. Few laboratories have succeeded in obtaining genome-scale sequences from historical specimens and then only with considerable effort and cost. Here, we describe a low-cost approach using high-throughput next-generation sequencing to obtain reliable genome-scale sequence data from a traditionally preserved mammal skin and skull using a simple extraction protocol. We show that single-nucleotide polymorphisms (SNPs) from the genome sequences obtained independently from the skin and from the skull are highly repeatable compared to a reference genome.
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Affiliation(s)
- Kevin C Rowe
- Sciences Department, Museum Victoria, GPO Box 666, Melbourne, Vic. 3001, Australia.
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