Benchmark study comparing liftover tools for genome conversion of epigenome sequencing data

Abstract As reference genome assemblies are updated there is a need to convert epigenome sequence data from older genome assemblies to newer versions, to facilitate data integration and visualization on the same coordinate system. Conversion can be done by re-alignment of the original sequence data to the new assembly or by converting the coordinates of the data between assemblies using a mapping file, an approach referred to as ‘liftover’. Compared to re-alignment approaches, liftover is a more rapid and cost-effective solution. Here, we benchmark six liftover tools commonly used for conversion between genome assemblies by coordinates, including UCSC liftOver, rtracklayer::liftOver, CrossMap, NCBI Remap, flo and segment_liftover to determine how they performed for whole genome bisulphite sequencing (WGBS) and ChIP-seq data. Our results show high correlation between the six tools for conversion of 43 WGBS paired samples. For the chromatin sequencing data we found from interval conversion of 366 ChIP-Seq datasets, segment_liftover generates more reliable results than USCS liftOver. However, we found some regions do not always remain the same after liftover. To further increase the accuracy of liftover and avoid misleading results, we developed a three-step guideline that removes aberrant regions to ensure more robust genome conversion between reference assemblies.

Download Full-text

Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies

PeerJ ◽

10.7717/peerj.1839 ◽

2016 ◽

Vol 4 ◽

pp. e1839 ◽

Cited By ~ 57

Author(s):

Tom O. Delmont ◽

A. Murat Eren

Keyword(s):

High Throughput Sequencing ◽

Draft Genome ◽

Cost Effective ◽

Single Copy ◽

Eukaryotic Genome ◽

Sequencing Data ◽

Bacterial Genomes ◽

Long Read ◽

Domains Of Life ◽

Genome Assemblies

High-throughput sequencing provides a fast and cost-effective mean to recover genomes of organisms from all domains of life. However, adequate curation of the assembly results against potential contamination of non-target organisms requires advanced bioinformatics approaches and practices. Here, we re-analyzed the sequencing data generated for the tardigradeHypsibius dujardini,and created a holistic display of the eukaryotic genome assembly using DNA data originating from two groups and eleven sequencing libraries. By using bacterial single-copy genes, k-mer frequencies, and coverage values of scaffolds we could identify and characterize multiple near-complete bacterial genomes from the raw assembly, and curate a 182 Mbp draft genome forH. dujardinisupported by RNA-Seq data. Our results indicate that most contaminant scaffolds were assembled from Moleculo long-read libraries, and most of these contaminants have differed between library preparations. Our re-analysis shows that visualization and curation of eukaryotic genome assemblies can benefit from tools designed to address the needs of today’s microbiologists, who are constantly challenged by the difficulties associated with the identification of distinct microbial genomes in complex environmental metagenomes.

Download Full-text

The Dark Matter of Large Cereal Genomes: Long Tandem Repeats

International Journal of Molecular Sciences ◽

10.3390/ijms20102483 ◽

2019 ◽

Vol 20 (10) ◽

pp. 2483 ◽

Cited By ~ 5

Author(s):

Veronika Kapustová ◽

Zuzana Tulpová ◽

Helena Toegelová ◽

Petr Novák ◽

Jiří Macas ◽

...

Keyword(s):

Bread Wheat ◽

Tandem Repeats ◽

Reference Genome ◽

Sequence Data ◽

Repetitive Sequences ◽

Short Read Sequence ◽

Cereal Genomes ◽

Genome Assemblies ◽

Reference Genomes ◽

Size Estimates

Reference genomes of important cereals, including barley, emmer wheat and bread wheat, were released recently. Their comparison with genome size estimates obtained by flow cytometry indicated that the assemblies represent not more than 88–98% of the complete genome. This work is aimed at identifying the missing parts in two cereal genomes and proposing techniques to make the assemblies more complete. We focused on tandemly organised repetitive sequences, known to be underrepresented in genome assemblies generated from short-read sequence data. Our study found arrays of three tandem repeats with unit sizes of 1242 to 2726 bp present in the bread wheat reference genome generated from short reads. However, this and another wheat genome assembly employing long PacBio reads failed in integrating correctly the 2726-bp repeat in the pseudomolecule context. This suggests that tandem repeats of this size, frequently incorporated in unassigned scaffolds, may contribute to shrinking of pseudomolecules without reducing size of the entire assembly. We demonstrate how this missing information may be added to the pseudomolecules with the aid of nanopore sequencing of individual BAC clones and optical mapping. Using the latter technique, we identified and localised a 470-kb long array of 45S ribosomal DNA absent from the reference genome of barley.

Download Full-text

Comparison of MiSeq, MinION, and hybrid genome sequencing for analysis of Campylobacter jejuni

Scientific Reports ◽

10.1038/s41598-021-84956-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jason M. Neal-McKinney ◽

Kun C. Liu ◽

Christopher M. Lock ◽

Wen-Hsin Wu ◽

Jinxin Hu

Keyword(s):

Genome Sequencing ◽

Sequence Data ◽

Bacterial Genome ◽

Illumina Miseq ◽

Trna Genes ◽

Sequencing Data ◽

Data Types ◽

Field Isolates ◽

Hybrid Genome ◽

Genome Assemblies

AbstractThe sequencing, assembly, and analysis of bacterial genomes is central to tracking and characterizing foodborne pathogens. The bulk of bacterial genome sequencing at the US Food and Drug Administration is performed using short-read Illumina MiSeq technology, resulting in highly accurate but fragmented genomic sequences. The MinION sequencer from Oxford Nanopore is an evolving technology that produces long-read sequencing data with low equipment cost. The goal of this study was to compare Campylobacter genome assemblies generated from MiSeq and MinION data independently, as well as hybrid genome assemblies combining both data types. Two reference strains and two field isolates of C. jejuni were sequenced using MiSeq and MinION, and the sequence data were assembled using the software programs SPAdes and Canu, respectively. Hybrid genome assembly was performed using the program Unicycler. Comparison of the C. jejuni 81-176 and RM1221 genome assemblies to the PacBio reference genomes revealed that the SPAdes assemblies had the most accurate nucleotide identity, while the hybrid assemblies were the most contiguous. Assemblies generated only from MinION data using Canu were the least accurate, containing many indels and substitutions that affected downstream analyses. The hybrid sequencing approach was the most useful for detecting plasmids, large genome rearrangements, and repetitive elements such as rRNA and tRNA genes. The full genomes of both C. jejuni field isolates were completed and circularized using hybrid sequencing, and a plasmid was detected in one isolate. Continued development of nanopore sequencing technologies will likely enhance the accuracy of hybrid genome assemblies and enable public health laboratories to routinely generate complete circularized bacterial genome sequences.

Download Full-text

Sequencing smart: De novo sequencing and assembly approaches for a non-model mammal

GigaScience ◽

10.1093/gigascience/giaa045 ◽

2020 ◽

Vol 9 (5) ◽

Cited By ~ 2

Author(s):

Graham J Etherington ◽

Darren Heavens ◽

David Baker ◽

Ashleigh Lister ◽

Rose McNelly ◽

...

Keyword(s):

De Novo ◽

Cost Effective ◽

Genome Project ◽

Model Organisms ◽

Sequencing Data ◽

Data Types ◽

High Molecular Weight Dna ◽

Assembly Method ◽

A Genome ◽

Genome Assemblies

Abstract Background Whilst much sequencing effort has focused on key mammalian model organisms such as mouse and human, little is known about the relationship between genome sequencing techniques for non-model mammals and genome assembly quality. This is especially relevant to non-model mammals, where the samples to be sequenced are often degraded and of low quality. A key aspect when planning a genome project is the choice of sequencing data to generate. This decision is driven by several factors, including the biological questions being asked, the quality of DNA available, and the availability of funds. Cutting-edge sequencing technologies now make it possible to achieve highly contiguous, chromosome-level genome assemblies, but rely on high-quality high molecular weight DNA. However, funding is often insufficient for many independent research groups to use these techniques. Here we use a range of different genomic technologies generated from a roadkill European polecat (Mustela putorius) to assess various assembly techniques on this low-quality sample. We evaluated different approaches for de novo assemblies and discuss their value in relation to biological analyses. Results Generally, assemblies containing more data types achieved better scores in our ranking system. However, when accounting for misassemblies, this was not always the case for Bionano and low-coverage 10x Genomics (for scaffolding only). We also find that the extra cost associated with combining multiple data types is not necessarily associated with better genome assemblies. Conclusions The high degree of variability between each de novo assembly method (assessed from the 7 key metrics) highlights the importance of carefully devising the sequencing strategy to be able to carry out the desired analysis. Adding more data to genome assemblies does not always result in better assemblies, so it is important to understand the nuances of genomic data integration explained here, in order to obtain cost-effective value for money when sequencing genomes.

Download Full-text

BioKIT: a versatile toolkit for processing and analyzing diverse types of sequence data

10.1101/2021.10.02.462868 ◽

2021 ◽

Author(s):

Jacob L. Steenwyk ◽

Thomas J. Buida ◽

Carla Goncalves ◽

Dayna C. Goltz ◽

Grace H Morales ◽

...

Keyword(s):

Codon Usage ◽

Sequence Data ◽

Synonymous Codon ◽

Synonymous Codon Usage ◽

Relative Synonymous Codon Usage ◽

Summary Statistics ◽

Sequencing Data ◽

Sequence Alignments ◽

Multiple Sequence ◽

Genome Assemblies

Bioinformatic analysis - such as genome assembly quality assessment, alignment summary statistics, relative synonymous codon usage, paired-end aware quality trimming and filtering of sequencing reads, file format conversion, and processing and analysis - is integrated into diverse disciplines in the biological sciences. Several command-line pieces of software have been developed to conduct some of these individual analyses; however, the lack of a unified toolkit that conducts all these analyses can be a barrier in workflows. To address this obstacle, we introduce BioKIT, a versatile toolkit for the UNIX shell environment with 40 functions, several of which were community-sourced, that conduct routine and novel processing and analysis of genome assemblies, multiple sequence alignments, coding sequences, sequencing data, and more. To demonstrate the utility of BioKIT, we assessed the quality and characteristics of 901 eukaryotic genome assemblies, calculated alignment summary statistics for 10 phylogenomic data matrices, determined relative synonymous codon usage across 171 fungal genomes including those that use alternative genetic codes, and demonstrate that a novel metric, gene-wise relative synonymous codon usage, can accurately estimate gene-wise codon optimization. BioKIT will be helpful in facilitating and streamlining sequence analysis workflows. BioKIT is freely available under the MIT license from GitHub (https://github.com/JLSteenwyk/BioKIT), PyPi (https://pypi.org/project/biokit), and the Anaconda Cloud (https://anaconda.org/JLSteenwyk/biokit). Documentation, user tutorials, and instructions for requesting new features are available online (https://jlsteenwyk.com/BioKIT).

Download Full-text

Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies

10.7287/peerj.preprints.1695 ◽

2016 ◽

Author(s):

Tom O Delmont ◽

A. Murat Eren

Keyword(s):

High Throughput Sequencing ◽

Draft Genome ◽

Cost Effective ◽

Single Copy ◽

Eukaryotic Genome ◽

Metagenomic Data ◽

Sequencing Data ◽

Long Read ◽

Domains Of Life ◽

Genome Assemblies

High-throughput sequencing provides a fast and cost effective mean to recover genomes of organisms from all domains of life. However, adequate curation of the assembly results against potential contamination of non-target organisms requires advanced bioinformatics approaches and practices. Here, we re-analyzed the sequencing data generated for the tardigrade Hypsibius dujardini using approaches routinely employed by microbial ecologists who reconstruct bacterial and archaeal genomes from metagenomic data. We created a holistic display of the eukaryotic genome assembly using DNA data originating from two groups and eleven sequencing libraries. By using bacterial single-copy genes, k-mer frequencies, and coverage values of scaffolds we could identify and characterize multiple near-complete bacterial genomes, and curate a 182 Mbp draft genome for H. dujardini supported by RNA-Seq data. Our results indicate that most contaminant scaffolds were assembled from Moleculo long-read libraries, and most of these contaminants have differed between library preparations. Our re-analysis shows that visualization and curation of eukaryotic genome assemblies can benefit from tools designed to address the needs of today’s microbiologists, who are constantly challenged by the difficulties associated with the identification of distinct microbial genomes in complex environmental metagenomes.

Download Full-text

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

10.1101/460345 ◽

2018 ◽

Cited By ~ 1

Author(s):

Danang Crysnanto ◽

Christine Wurmser ◽

Hubert Pausch

Keyword(s):

Dna Sequences ◽

Reference Genome ◽

Sequence Data ◽

Sequence Variant ◽

Sequence Variants ◽

Sequencing Data ◽

Reference Allele ◽

Reference Genomes ◽

Genome Graph ◽

Genotype Concordance

Background: The genotyping of sequence variants typically involves as a first step the alignment of sequencing reads to a linear reference genome. Because a linear reference genome represents only a small fraction of sequence variation within a species, reference allele bias may occur at highly polymorphic or diverged regions of the genome. Graph-based methods facilitate to compare sequencing reads to a variation-aware genome graph that incorporates non-redundant DNA sequences that segregate within a species. We compared accuracy and sensitivity of graph-based sequence variant genotyping using the Graphtyper software to two widely used methods, i.e., GATK and SAMtools, that rely on linear reference genomes using whole-genomes sequencing data of 49 Original Braunvieh cattle. Results: We discovered 21,140,196, 20,262,913 and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant and microarray-derived genotypes showed that Graphtyper outperformed both GATK and SAMtools in terms of genotype concordance, non-reference sensitivity, and non-reference discrepancy. The sequence variant genotypes that were obtained using Graphtyper had the lowest number of mendelian inconsistencies for both SNPs and indels in nine sire-son pairs with sequence data. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all tools evaluated particularly for animals that have been sequenced at low coverage. Following imputation, the concordance between sequence- and microarray-derived genotypes was almost identical for the three methods evaluated, i.e., 99.32, 99.46, and 99.24 % for GATK, Graphtyper, and SAMtools, respectively. Variant filtration based on commonly used criteria improved the genotype concordance slightly but it also decreased sensitivity. Graphtyper required considerably more computing resources than SAMtools but it required less than GATK. Conclusions: Sequence variant genotyping using Graphtyper is accurate, sensitive and computationally feasible in cattle. Graph-based methods enable sequence variant genotyping from variation-aware reference genomes that may incorporate cohort-specific sequence variants which is not possible with the current implementations of state-of-the-art methods that rely on linear reference genomes.

Download Full-text

New gains with a slimmer genome – An automated approach to improve reference genome assemblies

10.1101/2020.08.18.255596 ◽

2020 ◽

Author(s):

Mikko Kivikoski ◽

Pasi Rastas ◽

Ari Löytynoja ◽

Juha Merilä

Keyword(s):

Gasterosteus Aculeatus ◽

Reference Genome ◽

De Novo ◽

Biological Research ◽

Integrative Approach ◽

Sequencing Data ◽

Pungitius Pungitius ◽

Model Study ◽

Long Reads ◽

Genome Assemblies

AbstractThe utility of genome-wide sequencing data in biological research depends heavily on the quality of the reference genome. Although the reference genomes have improved, it is evident that the assemblies could still be refined, especially in non-model study organisms. Here, we describe an integrative approach to improve contiguity and haploidy of a reference genome assembly. With two novel features of Lep-Anchor software and a combination of dense linkage maps, overlap detection and bridging long reads we generated an improved assembly of the nine-spined stickleback (Pungitius pungitius) reference genome. We were able to remove a significant number of haplotypic contigs, detect more genetic variation and improve the contiguity of the genome, especially that of X chromosome. However, improved scaffolding cannot correct for mosaicism of erroneously assembled contigs, demonstrated by a de novo assembly of a 1.7 Mbp inversion. Qualitatively similar gains were obtained with the genome of three-spined stickleback (Gasterosteus aculeatus).

Download Full-text

Pangenome-based genome inference

10.1101/2020.11.11.378133 ◽

2020 ◽

Author(s):

Jana Ebler ◽

Wayne E. Clarke ◽

Tobias Rausch ◽

Peter A. Audano ◽

Torsten Houwaart ◽

...

Keyword(s):

Reference Genome ◽

Wide Spectrum ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Linkage Information ◽

Almost All ◽

Genome Assemblies ◽

The Given ◽

Genotype A

AbstractTypical analysis workflows map reads to a reference genome in order to detect genetic variants. Generating such alignments introduces references biases, in particular against insertion alleles absent in the reference and comes with substantial computational burden. In contrast, recent k-mer-based genotyping methods are fast, but struggle in repetitive or duplicated regions of the genome. We propose a novel algorithm, called PanGenie, that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation. The given haplotypes enable our method to take advantage of linkage information to aid genotyping in regions poorly covered by unique k-mers and provides access to regions otherwise inaccessible by short reads. Compared to classic mapping-based approaches, our approach is more than 4× faster at 30× coverage and at the same time, reached significantly better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (> 50bp), where we are able to genotype > 99.9% of all tested variants with over 90% accuracy at 30× short-read coverage, where the best competing tools either typed less than 60% of variants or reached accuracies below 70%. PanGenie now enables the inclusion of this commonly neglected variant type in downstream analyses.

Download Full-text

Application of genotyping-by-sequencing data on inferring the phylogeny of Curcuma (Zingiberaceae) from China

10.21203/rs.2.15210/v1 ◽

2019 ◽

Author(s):

Heng Liang ◽

Yan Zhang ◽

Jiabing Deng ◽

Gang Gao ◽

Chunbang Ding ◽

...

Keyword(s):

Phylogenetic Relationships ◽

Phylogenetic Trees ◽

Large Scale ◽

Reference Genome ◽

Genomic Sequence ◽

Sequence Data ◽

Morphological Differentiation ◽

Genotyping By Sequencing ◽

Tibet Plateau ◽

Sequencing Data

Abstract Background: Genotyping-by-sequencing (GBS), as one of the next generation sequences, has been applied to large scale genotyping in plants, which is poor in morphological differentiation and low in genetic divergence among different species. Curcuma is a significantly medicinal and edible genus. Improvement efforts of phylogenetic relationships and disentangling species are still a challenge due to poor morphology and lack in a reference genome. Result: A high-throughput genomic sequence data which was obtained through GBS protocols was used to investigate the relationships among 8 species with 60 total samples of Curcuma. Through the use of the ipyrad software, 437,061 loci and 997,988 filtered SNPs without reliance upon a reference genome were produced. After quality control (QC) of the filtered SNPs, 1,295 high-quality SNPs were used to clarify the phylogenetic relationships among Curcuma species. Based on these data, a supermatrix approach was used to speculate the phylogeny, and the phylogenetic trees and the relationships were inferred . Conclusions: Varying degrees of support can be explained, as well as the diversification events for Chinese Curcuma. The diversification events showed that the third intense uplift of Qinghai–Tibet Plateau (QTP) and formation of the Hengduan Mountains may speed up Curcuma interspecific divergence in China. The PCA suggested the same topology of the phylogenetic tree. The genetic structure analysis revealed that extensive hybridization may exist in Chinese Curcuma. Additionally, the GBS will be a promising approach for the phylogenetic and systematic study in the future.

Download Full-text