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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

Error probability surface depicting predictive influence of the average neighboring quality score.Note that Phred quality score 2 was not included.
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pcbi.1004229.g002: Error probability surface depicting predictive influence of the average neighboring quality score.Note that Phred quality score 2 was not included.

Mentions: Sequencing quality of the neighboring region gives further indication of whether a given nucleotide can be relied upon. In particular, it is known that nucleotides with high quality scores can nonetheless be of lower actual quality when surrounded by a region of low quality [30]. Our observed error probability surface over the nucleotide quality score and the average neighboring quality score does indeed show a slight bump in the plot for high quality nucleotides in a poor quality region (bottom part of Fig 2). More interestingly, however, we have also observed that the error probability is significantly increased when an intermediate quality nucleotide is surrounded by a high quality neighborhood.


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

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

Error probability surface depicting predictive influence of the average neighboring quality score.Note that Phred quality score 2 was not included.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi.1004229.g002: Error probability surface depicting predictive influence of the average neighboring quality score.Note that Phred quality score 2 was not included.
Mentions: Sequencing quality of the neighboring region gives further indication of whether a given nucleotide can be relied upon. In particular, it is known that nucleotides with high quality scores can nonetheless be of lower actual quality when surrounded by a region of low quality [30]. Our observed error probability surface over the nucleotide quality score and the average neighboring quality score does indeed show a slight bump in the plot for high quality nucleotides in a poor quality region (bottom part of Fig 2). More interestingly, however, we have also observed that the error probability is significantly increased when an intermediate quality nucleotide is surrounded by a high quality neighborhood.

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