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ConPADE: genome assembly ploidy estimation from next-generation sequencing data.

Margarido GR, Heckerman D - PLoS Comput. Biol. (2015)

Bottom Line: As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace.Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions.We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

View Article: PubMed Central - PubMed

Affiliation: Microsoft Research, Los Angeles, California, United States of America; Departamento de Genética, Escola Superior de Agricultura ''Luiz de Queiroz", Universidade de São Paulo, Piracicaba, Brazil.

ABSTRACT
As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace. With well-established methodologies, larger and more complex genomes are being tackled, including polyploid plant genomes. Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions. Unfortunately, such collapse is often not ideal, as keeping contigs separate can lead both to improved assembly and also insights about how haplotypes influence phenotype. Here, we describe a first step in avoiding inappropriate collapse during assembly. In particular, we describe ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, we report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. We also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low. We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

No MeSH data available.


Related in: MedlinePlus

Sequencing error probabilities.Observed sequencing error probability as a function of the Phred quality score (dots connected by the dotted line) and the expected error probability according to the expression 10(−QS /10), where QS represents the quality score (solid line). There is overall agreement between empirical observations and theoretical expectation, expect for the quality score of 2.
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pcbi.1004229.g001: Sequencing error probabilities.Observed sequencing error probability as a function of the Phred quality score (dots connected by the dotted line) and the expected error probability according to the expression 10(−QS /10), where QS represents the quality score (solid line). There is overall agreement between empirical observations and theoretical expectation, expect for the quality score of 2.

Mentions: Examination of the quality score distribution showed an apparent excess of bases with quality 2 (S1 Fig), the lowest possible value, indicating that the base calling algorithm could not reliably call a nucleotide for over 12% of the cases. Furthermore, assessment of realized error probabilities showed a strong deviation from the expected value particularly for a quality score of 2 (Fig 1). These observations indicate that many sequenced nucleotides were inappropriately assigned a poor quality score. One approach for dealing with low scores would be to trim reads or remove entire reads. In Section Simulations, however, we show that such reads can be incorporated into the analysis of ploidy, provided an appropriate error model is used.


ConPADE: genome assembly ploidy estimation from next-generation sequencing data.

Margarido GR, Heckerman D - PLoS Comput. Biol. (2015)

Sequencing error probabilities.Observed sequencing error probability as a function of the Phred quality score (dots connected by the dotted line) and the expected error probability according to the expression 10(−QS /10), where QS represents the quality score (solid line). There is overall agreement between empirical observations and theoretical expectation, expect for the quality score of 2.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4400156&req=5

pcbi.1004229.g001: Sequencing error probabilities.Observed sequencing error probability as a function of the Phred quality score (dots connected by the dotted line) and the expected error probability according to the expression 10(−QS /10), where QS represents the quality score (solid line). There is overall agreement between empirical observations and theoretical expectation, expect for the quality score of 2.
Mentions: Examination of the quality score distribution showed an apparent excess of bases with quality 2 (S1 Fig), the lowest possible value, indicating that the base calling algorithm could not reliably call a nucleotide for over 12% of the cases. Furthermore, assessment of realized error probabilities showed a strong deviation from the expected value particularly for a quality score of 2 (Fig 1). These observations indicate that many sequenced nucleotides were inappropriately assigned a poor quality score. One approach for dealing with low scores would be to trim reads or remove entire reads. In Section Simulations, however, we show that such reads can be incorporated into the analysis of ploidy, provided an appropriate error model is used.

Bottom Line: As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace.Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions.We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

View Article: PubMed Central - PubMed

Affiliation: Microsoft Research, Los Angeles, California, United States of America; Departamento de Genética, Escola Superior de Agricultura ''Luiz de Queiroz", Universidade de São Paulo, Piracicaba, Brazil.

ABSTRACT
As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace. With well-established methodologies, larger and more complex genomes are being tackled, including polyploid plant genomes. Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions. Unfortunately, such collapse is often not ideal, as keeping contigs separate can lead both to improved assembly and also insights about how haplotypes influence phenotype. Here, we describe a first step in avoiding inappropriate collapse during assembly. In particular, we describe ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, we report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. We also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low. We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

No MeSH data available.


Related in: MedlinePlus