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Asset Tag: diploid assembly

July 19, 2019  |  

De novo PacBio long-read and phased avian genome assemblies correct and add to reference genes generated with intermediate and short reads.

Reference-quality genomes are expected to provide a resource for studying gene structure, function, and evolution. However, often genes of interest are not completely or accurately assembled, leading to unknown errors in analyses or additional cloning efforts for the correct sequences. A promising solution is long-read sequencing. Here we tested PacBio-based long-read sequencing and diploid assembly for potential improvements to the Sanger-based intermediate-read zebra finch reference and Illumina-based short-read Anna’s hummingbird reference, 2 vocal learning avian species widely studied in neuroscience and genomics. With DNA of the same individuals used to generate the reference genomes, we generated diploid assemblies with the FALCON-Unzip assembler, resulting in contigs with no gaps in the megabase range, representing 150-fold and 200-fold improvements over the current zebra finch and hummingbird references, respectively. These long-read and phased assemblies corrected and resolved what we discovered to be numerous misassemblies in the references, including missing sequences in gaps, erroneous sequences flanking gaps, base call errors in difficult-to-sequence regions, complex repeat structure errors, and allelic differences between the 2 haplotypes. These improvements were validated by single long-genome and transcriptome reads and resulted for the first time in completely resolved protein-coding genes widely studied in neuroscience and specialized in vocal learning species. These findings demonstrate the impact of long reads, sequencing of previously difficult-to-sequence regions, and phasing of haplotypes on generating the high-quality assemblies necessary for understanding gene structure, function, and evolution.© The Authors 2017. Published by Oxford University Press.

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July 19, 2019  |  

How well can we create phased, diploid, human genomes?: An assessment of FALCON-Unzip phasing using a human trio

Long read sequencing technology has allowed researchers to create de novo assemblies with impressive continuity[1,2]. This advancement has dramatically increased the number of reference genomes available and hints at the possibility of a future where personal genomes are assembled rather than resequenced. In 2016 Pacific Biosciences released the FALCON-Unzip framework, which can provide long, phased haplotype contigs from de novo assemblies. This phased genome algorithm enhances the accuracy of highly heterozygous organisms and allows researchers to explore questions that require haplotype information such as allele-specific expression and regulation. However, validation of this technique has been limited to small genomes or inbred individuals[3]. As a roadmap to personal genome assembly and phasing, we assess the phasing accuracy of FALCON-Unzip in humans using publicly available data for the Ashkenazi trio from the Genome in a Bottle Consortium[4]. To assess the accuracy of the Unzip algorithm, we assembled the genome of the son using FALCON and FALCON Unzip, genotyped publicly available short read data for the mother and the father, and observed the inheritance pattern of the parental SNPs along the phased genome of the son. We found that 72.8% of haplotype contigs share SNPs with only one parent suggesting that these contigs are correctly phased. Most mis-phased SNPs are random but present in high frequency toward the end of haplotype contigs. Approximately 20.7% of mis-phased haplotype contigs contain clusters of mis-phased SNPs, suggesting that haplotypes were mis-joined by FALCON-Unzip. Mis-joined boundaries in those contigs are located in areas of low SNP density. This research demonstrates that the FALCON-Unzip algorithm can be used to create long and accurate haplotypes for humans and identifies problematic regions that could benefit in future improvement.

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July 7, 2019  |  

Completing the human genome: the progress and challenge of satellite DNA assembly.

Genomic studies rely on accurate chromosome assemblies to explore sequence-based models of cell biology, evolution and biomedical disease. However, even the extensively studied human genome has not yet reached a complete, ‘telomere-to-telomere’, chromosome assembly. The largest assembly gaps remain in centromeric regions and acrocentric short arms, sites known to contain megabase-sized arrays of tandem repeats, or satellite DNAs. This review aims to briefly address the progress and challenges of generating correct assemblies of satellite DNA arrays. Although the focus is placed on the human genome, many concepts presented here are applicable to other genomes.

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July 7, 2019  |  

De novo genome assembly of the economically important weed horseweed using integrated data from multiple sequencing platforms.

Horseweed (Conyza canadensis), a member of the Compositae (Asteraceae) family, was the first broadleaf weed to evolve resistance to glyphosate. Horseweed, one of the most problematic weeds in the world, is a true diploid (2n = 2x = 18), with the smallest genome of any known agricultural weed (335 Mb). Thus, it is an appropriate candidate to help us understand the genetic and genomic bases of weediness. We undertook a draft de novo genome assembly of horseweed by combining data from multiple sequencing platforms (454 GS-FLX, Illumina HiSeq 2000, and PacBio RS) using various libraries with different insertion sizes (approximately 350 bp, 600 bp, 3 kb, and 10 kb) of a Tennessee-accessed, glyphosate-resistant horseweed biotype. From 116.3 Gb (approximately 350× coverage) of data, the genome was assembled into 13,966 scaffolds with 50% of the assembly = 33,561 bp. The assembly covered 92.3% of the genome, including the complete chloroplast genome (approximately 153 kb) and a nearly complete mitochondrial genome (approximately 450 kb in 120 scaffolds). The nuclear genome is composed of 44,592 protein-coding genes. Genome resequencing of seven additional horseweed biotypes was performed. These sequence data were assembled and used to analyze genome variation. Simple sequence repeat and single-nucleotide polymorphisms were surveyed. Genomic patterns were detected that associated with glyphosate-resistant or -susceptible biotypes. The draft genome will be useful to better understand weediness and the evolution of herbicide resistance and to devise new management strategies. The genome will also be useful as another reference genome in the Compositae. To our knowledge, this article represents the first published draft genome of an agricultural weed.© 2014 American Society of Plant Biologists. All Rights Reserved.

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July 7, 2019  |  

Genomic innovation for crop improvement.

Crop production needs to increase to secure future food supplies, while reducing its impact on ecosystems. Detailed characterization of plant genomes and genetic diversity is crucial for meeting these challenges. Advances in genome sequencing and assembly are being used to access the large and complex genomes of crops and their wild relatives. These have helped to identify a wide spectrum of genetic variation and permitted the association of genetic diversity with diverse agronomic phenotypes. In combination with improved and automated phenotyping assays and functional genomic studies, genomics is providing new foundations for crop-breeding systems.

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July 7, 2019  |  

Genome graphs

There is increasing recognition that a single, monoploid reference genome is a poor universal reference structure for human genetics, because it represents only a tiny fraction of human variation. Adding this missing variation results in a structure that can be described as a mathematical graph: a genome graph. We demonstrate that, in comparison to the existing reference genome (GRCh38), genome graphs can substantially improve the fractions of reads that map uniquely and perfectly. Furthermore, we show that this fundamental simplification of read mapping transforms the variant calling problem from one in which many non-reference variants must be discovered de-novo to one in which the vast majority of variants are simply re-identified within the graph. Using standard benchmarks as well as a novel reference-free evaluation, we show that a simplistic variant calling procedure on a genome graph can already call variants at least as well as, and in many cases better than, a state-of-the-art method on the linear human reference genome. We anticipate that graph-based references will supplant linear references in humans and in other applications where cohorts of sequenced individuals are available.

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July 7, 2019  |  

Resolving multicopy duplications de novo using polyploid phasing

While the rise of single-molecule sequencing systems has enabled an unprecedented rise in the ability to assemble complex regions of the genome, long segmental duplications in the genome still remain a challenging frontier in assembly. Segmental duplications are at the same time both gene rich and prone to large structural rearrangements, making the resolution of their sequences important in medical and evolutionary studies. Duplicated sequences that are collapsed in mammalian de novo assemblies are rarely identical; after a sequence is duplicated, it begins to acquire paralog-specific variants. In this paper, we study the problem of resolving the variations in multicopy, long segmental duplications by developing and utilizing algorithms for polyploid phasing. We develop two algorithms: the first one is targeted at maximizing the likelihood of observing the reads given the underlying haplotypes using discrete matrix completion. The second algorithm is based on correlation clustering and exploits an assumption, which is often satisfied in these duplications, that each paralog has a sizable number of paralog-specific variants. We develop a detailed simulation methodology and demonstrate the superior performance of the proposed algorithms on an array of simulated datasets. We measure the likelihood score as well as reconstruction accuracy, i.e., what fraction of the reads are clustered correctly. In both the performance metrics, we find that our algorithms dominate existing algorithms on more than 93% of the datasets. While the discrete matrix completion performs better on likelihood score, the correlation-clustering algorithm performs better on reconstruction accuracy due to the stronger regularization inherent in the algorithm. We also show that our correlation-clustering algorithm can reconstruct on average 7.0 haplotypes in 10-copy duplication datasets whereas existing algorithms reconstruct less than one copy on average.

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July 7, 2019  |  

Building a locally diploid genome and transcriptome of the diatom Fragilariopsis cylindrus.

The genome of the cold-adapted diatom Fragilariopsis cylindrus is characterized by highly diverged haplotypes that intersperse its homozygous genome. Here, we describe how a combination of PacBio DNA and Illumina RNA sequencing can be used to resolve this complex genomic landscape locally into the highly diverged haplotypes, and how to map various environmentally controlled transcripts onto individual haplotypes. We assembled PacBio sequence data with the FALCON assembler and created a haplotype resolved annotation of the assembly using annotations of a Sanger sequenced F. cylindrus genome. RNA-seq datasets from six different growth conditions were used to resolve allele-specifc gene expression in F. cylindrus. This approach enables to study differential expression of alleles in a complex genomic landscape and provides a useful tool to study how diverged haplotypes in diploid organisms are used for adaptation and evolution to highly variable environments.

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July 7, 2019  |  

HapCol: accurate and memory-efficient haplotype assembly from long reads.

Haplotype assembly is the computational problem of reconstructing haplotypes in diploid organisms and is of fundamental importance for characterizing the effects of single-nucleotide polymorphisms on the expression of phenotypic traits. Haplotype assembly highly benefits from the advent of ‘future-generation’ sequencing technologies and their capability to produce long reads at increasing coverage. Existing methods are not able to deal with such data in a fully satisfactory way, either because accuracy or performances degrade as read length and sequencing coverage increase or because they are based on restrictive assumptions.By exploiting a feature of future-generation technologies-the uniform distribution of sequencing errors-we designed an exact algorithm, called HapCol, that is exponential in the maximum number of corrections for each single-nucleotide polymorphism position and that minimizes the overall error-correction score. We performed an experimental analysis, comparing HapCol with the current state-of-the-art combinatorial methods both on real and simulated data. On a standard benchmark of real data, we show that HapCol is competitive with state-of-the-art methods, improving the accuracy and the number of phased positions. Furthermore, experiments on realistically simulated datasets revealed that HapCol requires significantly less computing resources, especially memory. Thanks to its computational efficiency, HapCol can overcome the limits of previous approaches, allowing to phase datasets with higher coverage and without the traditional all-heterozygous assumption. Our source code is available under the terms of the GNU General Public License at http://hapcol.algolab.eu/.bonizzoni@disco.unimib.itSupplementary information: Supplementary data are available at Bioinformatics online.© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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