Dataset Information

Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing.

ABSTRACT: Whole genome sequence construction is becoming increasingly feasible because of advances in next generation sequencing (NGS), including increasing throughput and read length. By simply overlapping paired-end reads, we can obtain longer reads with higher accuracy, which can facilitate the assembly process. However, the influences of different library sizes and assembly methods on paired-end sequencing-based de novo assembly remain poorly understood.We used 250 bp Illumina Miseq paired-end reads of different library sizes generated from genomic DNA from Escherichia coli DH1 and Streptococcus parasanguinis FW213 to compare the assembly results of different library sizes and assembly approaches. Our data indicate that overlapping paired-end reads can increase read accuracy but sometimes cause insertion or deletions. Regarding genome assembly, merged reads only outcompete original paired-end reads when coverage depth is low, and larger libraries tend to yield better assembly results. These results imply that distance information is the most critical factor during assembly. Our results also indicate that when depth is sufficiently high, assembly from subsets can sometimes produce better results.In summary, this study provides systematic evaluations of de novo assembly from paired end sequencing data. Among the assembly strategies, we find that overlapping paired-end reads is not always beneficial for bacteria genome assembly and should be avoided or used with caution especially for genomes containing high fraction of repetitive sequences. Because increasing numbers of projects aim at bacteria genome sequencing, our study provides valuable suggestions for the field of genomic sequence construction.

SUBMITTER: Chen TW

PROVIDER: S-EPMC4552406 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing.

Chen Ting-Wen TW Gan Ruei-Chi RC Chang Yi-Feng YF Liao Wei-Chao WC Wu Timothy H TH Lee Chi-Ching CC Huang Po-Jung PJ Lee Cheng-Yang CY Chen Yi-Ywan M YY Chiu Cheng-Hsun CH Tang Petrus P

BMC genomics 20150828

<h4>Background</h4>Whole genome sequence construction is becoming increasingly feasible because of advances in next generation sequencing (NGS), including increasing throughput and read length. By simply overlapping paired-end reads, we can obtain longer reads with higher accuracy, which can facilitate the assembly process. However, the influences of different library sizes and assembly methods on paired-end sequencing-based de novo assembly remain poorly understood.<h4>Results</h4>We used 250 b ...[more]

PMID: 26315384

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Project description:BACKGROUND: Reconstructability of population history, from genetic information of extant individuals, is studied under a simulation setting. We do not address the issue of accuracy of the reconstruction algorithms: we assume the availability of the theoretical best algorithm. On the other hand, we focus on the fraction (1 - f) of the common genetic history that is irreconstructible or impenetrable. Thus the fraction, f, gives an upper bound on the extent of estimability. In other words, there exists no method that can reconstruct a fraction larger than f of the entire common genetic history. For the realization of such a study, we first define a natural measure of the amount of genetic history. Next, we use a population simulator (from literature) that has at least two features. Firstly, it has the capability of providing samples from different demographies, to effectively reflect reality. Secondly, it also provides the underlying relevant genetic history, captured in its entirety, where such a measure is applicable. Finally, to compute f, we use an information content measure of the relevant genetic history. The simulator of choice provided the following demographies: Africans, Europeans, Asians and Afro-Americans. RESULTS: We observe that higher the rate of recombination, lower the value of f, while f is invariant over varying mutation rates, in each of the demographies. The value of f increases with the number of samples, reaching a plateau and suggesting that in all the demographies at least about one-third of the relevant genetic history is impenetrable. The most surprising observation is that the the sum of the reconstructible history of the subsegments is indeed larger than the reconstructible history of the whole segment. In particular, longer the chromosomal segment, smaller the value of f, in all the demographies. CONCLUSIONS: We present the very first framework for measuring the fraction of the relevant genetic history of a population that is mathematically elusive. Our observed results on the tested demographies suggest that it may be better to aggregate the analysis of smaller chunks of chromosomal segments than fewer large chunks. Also, no matter the richness of samples in a population, at least one-third of the population genetic history is impenetrable. The framework also opens up possible new lines of investigation along the following. Given the characteristics of a population, possibly derived from observed extant individuals, to estimate the (1) optimal sample size and (2) optimal sequence length for the most informative analysis.

Project description:BackgroundBiofuels extracted from the seeds of Camelina sativa have recently been used successfully as environmentally friendly jet-fuel to reduce greenhouse gas emissions. Camelina sativa is genetically very close to Arabidopsis thaliana, and both are members of the Brassicaceae. Although public databases are currently available for some members of the Brassicaceae, such as A. thaliana, A. lyrata, Brassica napus, B. juncea and B. rapa, there are no public Expressed Sequence Tags (EST) or genomic data for Camelina sativa. In this study, a high-throughput, large-scale RNA sequencing (RNA-seq) of the Camelina sativa transcriptome was carried out to generate a database that will be useful for further functional analyses.ResultsApproximately 27 million clean "reads" filtered from raw reads by removal of adaptors, ambiguous reads and low-quality reads (2.42 gigabase pairs) were generated by Illumina paired-end RNA-seq technology. All of these clean reads were assembled de novo into 83,493 unigenes and 103,196 transcripts using SOAPdenovo and Trinity, respectively. The average length of the transcripts generated by Trinity was 697 bp (N50 = 976), which was longer than the average length of unigenes (319 bp, N50 = 346 bp). Nonetheless, the assembly generated by SOAPdenovo produced similar number of non-redundant hits (22,435) with that of Trinity (22,433) in BLASTN searches of the Arabidopsis thaliana CDS sequence database (TAIR). Four public databases, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Swiss-prot, NCBI non-redundant protein (NR), and the Cluster of Orthologous Groups (COG), were used for unigene annotation; 67,791 of 83,493 unigenes (81.2%) were finally annotated with gene descriptions or conserved protein domains that were mapped to 25,329 non-redundant protein sequences. We mapped 27,042 of 83,493 unigenes (32.4%) to 119 KEGG metabolic pathways.ConclusionsThis is the first report of a transcriptome database for Camelina sativa, an environmentally important member of the Brassicaceae. We showed that C. savita is closely related to Arabidopsis spp. and more distantly related to Brassica spp. Although the majority of annotated genes had high sequence identity to those of A. thaliana, a substantial proportion of disease-resistance genes (NBS-encoding LRR genes) were instead more closely similar to the genes of other Brassicaceae; these genes included BrCN, BrCNL, BrNL, BrTN, BrTNL in B. rapa. As plant genomes are under long-term selection pressure from environmental stressors, conservation of these disease-resistance genes in C. sativa and B. rapa genomes implies that they are exposed to the threats from closely-related pathogens in their natural habitats.

Dataset Information

Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing.

Publications

Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing.

Similar Datasets

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