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April 21, 2020  |  

Genome-Scale Sequence Disruption Following Biolistic Transformation in Rice and Maize.

Biolistic transformation delivers nucleic acids into plant cells by bombarding the cells with microprojectiles, which are micron-scale, typically gold particles. Despite the wide use of this technique, little is known about its effect on the cell’s genome. We biolistically transformed linear 48-kb phage lambda and two different circular plasmids into rice (Oryza sativa) and maize (Zea mays) and analyzed the results by whole genome sequencing and optical mapping. Although some transgenic events showed simple insertions, others showed extreme genome damage in the form of chromosome truncations, large deletions, partial trisomy, and evidence of chromothripsis and breakage-fusion bridge cycling. Several transgenic events contained megabase-scale arrays of introduced DNA mixed with genomic fragments assembled by nonhomologous or microhomology-mediated joining. Damaged regions of the genome, assayed by the presence of small fragments displaced elsewhere, were often repaired without a trace, presumably by homology-dependent repair (HDR). The results suggest a model whereby successful biolistic transformation relies on a combination of end joining to insert foreign DNA and HDR to repair collateral damage caused by the microprojectiles. The differing levels of genome damage observed among transgenic events may reflect the stage of the cell cycle and the availability of templates for HDR. © 2019 American Society of Plant Biologists. All rights reserved.


April 21, 2020  |  

RADAR-seq: A RAre DAmage and Repair sequencing method for detecting DNA damage on a genome-wide scale.

RAre DAmage and Repair sequencing (RADAR-seq) is a highly adaptable sequencing method that enables the identification and detection of rare DNA damage events for a wide variety of DNA lesions at single-molecule resolution on a genome-wide scale. In RADAR-seq, DNA lesions are replaced with a patch of modified bases that can be directly detected by Pacific Biosciences Single Molecule Real-Time (SMRT) sequencing. RADAR-seq enables dynamic detection over a wide range of DNA damage frequencies, including low physiological levels. Furthermore, without the need for DNA amplification and enrichment steps, RADAR-seq provides sequencing coverage of damaged and undamaged DNA across an entire genome. Here, we use RADAR-seq to measure the frequency and map the location of ribonucleotides in wild-type and RNaseH2-deficient E. coli and Thermococcus kodakarensis strains. Additionally, by tracking ribonucleotides incorporated during in vivo lagging strand DNA synthesis, we determined the replication initiation point in E. coli, and its relation to the origin of replication (oriC). RADAR-seq was also used to map cyclobutane pyrimidine dimers (CPDs) in Escherichia coli (E. coli) genomic DNA exposed to UV-radiation. On a broader scale, RADAR-seq can be applied to understand formation and repair of DNA damage, the correlation between DNA damage and disease initiation and progression, and complex biological pathways, including DNA replication.Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.


April 21, 2020  |  

Fast and accurate genomic analyses using genome graphs.

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Here we present a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million insertions and deletions (indels). The pipeline processes one whole-genome sequencing sample in 6.5?h using a system with 36?CPU cores. We show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, with unaffected specificity. Structural variations incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is an important advance toward fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.


April 21, 2020  |  

MSC: a metagenomic sequence classification algorithm.

Metagenomics is the study of genetic materials directly sampled from natural habitats. It has the potential to reveal previously hidden diversity of microscopic life largely due to the existence of highly parallel and low-cost next-generation sequencing technology. Conventional approaches align metagenomic reads onto known reference genomes to identify microbes in the sample. Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory which is not often available to researchers. Alternative approaches follow an alignment-free methodology where the presence of a microbe is predicted using the information about the unique k-mers present in the microbial genomes. However, such approaches suffer from high false positives due to trading off the value of k with the computational resources. In this article, we propose a highly efficient metagenomic sequence classification (MSC) algorithm that is a hybrid of both approaches. Instead of aligning reads to the full genomes, MSC aligns reads onto a set of carefully chosen, shorter and highly discriminating model sequences built from the unique k-mers of each of the reference sequences.Microbiome researchers are generally interested in two objectives of a taxonomic classifier: (i) to detect prevalence, i.e. the taxa present in a sample, and (ii) to estimate their relative abundances. MSC is primarily designed to detect prevalence and experimental results show that MSC is indeed a more effective and efficient algorithm compared to the other state-of-the-art algorithms in terms of accuracy, memory and runtime. Moreover, MSC outputs an approximate estimate of the abundances.The implementations are freely available for non-commercial purposes. They can be downloaded from https://drive.google.com/open?id=1XirkAamkQ3ltWvI1W1igYQFusp9DHtVl. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.


April 21, 2020  |  

Retrospective whole-genome sequencing analysis distinguished PFGE and drug-resistance-matched retail meat and clinical Salmonella isolates.

Non-typhoidal Salmonella is a leading cause of outbreak and sporadic-associated foodborne illnesses in the United States. These infections have been associated with a range of foods, including retail meats. Traditionally, pulsed-field gel electrophoresis (PFGE) and antibiotic susceptibility testing (AST) have been used to facilitate public health investigations of Salmonella infections. However, whole-genome sequencing (WGS) has emerged as an alternative tool that can be routinely implemented. To assess its potential in enhancing integrated surveillance in Pennsylvania, USA, WGS was used to directly compare the genetic characteristics of 7 retail meat and 43 clinical historic Salmonella isolates, subdivided into 3 subsets based on PFGE and AST results, to retrospectively resolve their genetic relatedness and identify antimicrobial resistance (AMR) determinants. Single nucleotide polymorphism (SNP) analyses revealed that the retail meat isolates within S. Heidelberg, S. Typhimurium var. O5- subset 1 and S. Typhimurium var. O5- subset 2 were separated from each primary PFGE pattern-matched clinical isolate by 6-12, 41-96 and 21-81 SNPs, respectively. Fifteen resistance genes were identified across all isolates, including fosA7, a gene only recently found in a limited number of Salmonella and a =95?%?phenotype to genotype correlation was observed for all tested antimicrobials. Moreover, AMR was primarily plasmid-mediated in S. Heidelberg and S. Typhimurium var. O5- subset 2, whereas AMR was chromosomally carried in S. Typhimurium var. O5- subset 1. Similar plasmids were identified in both the retail meat and clinical isolates. Collectively, these data highlight the utility of WGS in retrospective analyses and enhancing integrated surveillance for Salmonella from multiple sources.


April 21, 2020  |  

Confident phylogenetic identification of uncultured prokaryotes through long read amplicon sequencing of the 16S-ITS-23S rRNA operon.

Amplicon sequencing of the 16S rRNA gene is the predominant method to quantify microbial compositions and to discover novel lineages. However, traditional short amplicons often do not contain enough information to confidently resolve their phylogeny. Here we present a cost-effective protocol that amplifies a large part of the rRNA operon and sequences the amplicons with PacBio technology. We tested our method on a mock community and developed a read-curation pipeline that reduces the overall read error rate to 0.18%. Applying our method on four environmental samples, we captured near full-length rRNA operon amplicons from a large diversity of prokaryotes. The method operated at moderately high-throughput (22286-37,850 raw ccs reads) and generated a large amount of putative novel archaeal 23S rRNA gene sequences compared to the archaeal SILVA database. These long amplicons allowed for higher resolution during taxonomic classification by means of long (~1000 bp) 16S rRNA gene fragments and for substantially more confident phylogenies by means of combined near full-length 16S and 23S rRNA gene sequences, compared to shorter traditional amplicons (250 bp of the 16S rRNA gene). We recommend our method to those who wish to cost-effectively and confidently estimate the phylogenetic diversity of prokaryotes in environmental samples at high throughput. © 2019 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.


April 21, 2020  |  

Long-read sequence capture of the haemoglobin gene clusters across codfish species.

Combining high-throughput sequencing with targeted sequence capture has become an attractive tool to study specific genomic regions of interest. Most studies have so far focused on the exome using short-read technology. These approaches are not designed to capture intergenic regions needed to reconstruct genomic organization, including regulatory regions and gene synteny. Here, we demonstrate the power of combining targeted sequence capture with long-read sequencing technology for comparative genomic analyses of the haemoglobin (Hb) gene clusters across eight species separated by up to 70 million years. Guided by the reference genome assembly of the Atlantic cod (Gadus morhua) together with genome information from draft assemblies of selected codfishes, we designed probes covering the two Hb gene clusters. Use of custom-made barcodes combined with PacBio RSII sequencing led to highly continuous assemblies of the LA (~100 kb) and MN (~200 kb) clusters, which include syntenic regions of coding and intergenic sequences. Our results revealed an overall conserved genomic organization of the Hb genes within this lineage, yet with several, lineage-specific gene duplications. Moreover, for some of the species examined, we identified amino acid substitutions at two sites in the Hbb1 gene as well as length polymorphisms in its regulatory region, which has previously been linked to temperature adaptation in Atlantic cod populations. This study highlights the use of targeted long-read capture as a versatile approach for comparative genomic studies by generation of a cross-species genomic resource elucidating the evolutionary history of the Hb gene family across the highly divergent group of codfishes. © 2018 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.


April 21, 2020  |  

Reference genome sequences of two cultivated allotetraploid cottons, Gossypium hirsutum and Gossypium barbadense.

Allotetraploid cotton species (Gossypium hirsutum and Gossypium barbadense) have long been cultivated worldwide for natural renewable textile fibers. The draft genome sequences of both species are available but they are highly fragmented and incomplete1-4. Here we report reference-grade genome assemblies and annotations for G. hirsutum accession Texas Marker-1 (TM-1) and G. barbadense accession 3-79 by integrating single-molecule real-time sequencing, BioNano optical mapping and high-throughput chromosome conformation capture techniques. Compared with previous assembled draft genomes1,3, these genome sequences show considerable improvements in contiguity and completeness for regions with high content of repeats such as centromeres. Comparative genomics analyses identify extensive structural variations that probably occurred after polyploidization, highlighted by large paracentric/pericentric inversions in 14 chromosomes. We constructed an introgression line population to introduce favorable chromosome segments from G. barbadense to G. hirsutum, allowing us to identify 13 quantitative trait loci associated with superior fiber quality. These resources will accelerate evolutionary and functional genomic studies in cotton and inform future breeding programs for fiber improvement.


April 21, 2020  |  

Computational aspects underlying genome to phenome analysis in plants.

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features. © 2018 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.


April 21, 2020  |  

The Genome of C57BL/6J “Eve”, the Mother of the Laboratory Mouse Genome Reference Strain.

Isogenic laboratory mouse strains enhance reproducibility because individual animals are genetically identical. For the most widely used isogenic strain, C57BL/6, there exists a wealth of genetic, phenotypic, and genomic data, including a high-quality reference genome (GRCm38.p6). Now 20 years after the first release of the mouse reference genome, C57BL/6J mice are at least 26 inbreeding generations removed from GRCm38 and the strain is now maintained with periodic reintroduction of cryorecovered mice derived from a single breeder pair, aptly named Adam and Eve. To provide an update to the mouse reference genome that more accurately represents the genome of today’s C57BL/6J mice, we took advantage of long read, short read, and optical mapping technologies to generate a de novo assembly of the C57BL/6J Eve genome (B6Eve). Using these data, we have addressed recurring variants observed in previous mouse genomic studies. We have also identified structural variations, closed gaps in the mouse reference assembly, and revealed previously unannotated coding sequences. This B6Eve assembly explains discrepant observations that have been associated with GRCm38-based analyses, and will inform a reference genome that is more representative of the C57BL/6J mice that are in use today.Copyright © 2019 Sarsani et al.


April 21, 2020  |  

WGS of 1058 Enterococcus faecium from Copenhagen, Denmark, reveals rapid clonal expansion of vancomycin-resistant clone ST80 combined with widespread dissemination of a vanA-containing plasmid and acquisition of a heterogeneous accessory genome.

From 2012 to 2015, a sudden significant increase in vancomycin-resistant (vanA) Enterococcus faecium (VREfm) was observed in the Capital Region of Denmark. Clonal relatedness of VREfm and vancomycin-susceptible E. faecium (VSEfm) was investigated, transmission events between hospitals were identified and the pan-genome and plasmids from the largest VREfm clonal group were characterized.WGS of 1058 E. faecium isolates was carried out on the Illumina platform to perform SNP analysis and to identify the pan-genome. One isolate was also sequenced on the PacBio platform to close the genome. Epidemiological data were collected from laboratory information systems.Phylogeny of 892 VREfm and 166 VSEfm revealed a polyclonal structure, with a single clonal group (ST80) accounting for 40% of the VREfm isolates. VREfm and VSEfm co-occurred within many clonal groups; however, no VSEfm were related to the dominant VREfm group. A similar vanA plasmid was identified in =99% of isolates belonging to the dominant group and 69% of the remaining VREfm. Ten plasmids were identified in the completed genome, and ~29% of this genome consisted of dispensable accessory genes. The size of the pan-genome among isolates in the dominant group was 5905 genes.Most probably, VREfm emerged owing to importation of a successful VREfm clone which rapidly transmitted to the majority of hospitals in the region whilst simultaneously disseminating a vanA plasmid to pre-existing VSEfm. Acquisition of a heterogeneous accessory genome may account for the success of this clone by facilitating adaptation to new environmental challenges. © The Author(s) 2019. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.


April 21, 2020  |  

The role of genomic structural variation in the genetic improvement of polyploid crops

Many of our major crop species are polyploids, containing more than one genome or set of chromosomes. Polyploid crops present unique challenges, including difficulties in genome assembly, in discriminating between multiple gene and sequence copies, and in genetic mapping, hindering use of genomic data for genetics and breeding. Polyploid genomes may also be more prone to containing structural variation, such as loss of gene copies or sequences (presence–absence variation) and the presence of genes or sequences in multiple copies (copy-number variation). Although the two main types of genomic structural variation commonly identified are presence–absence variation and copy-number variation, we propose that homeologous exchanges constitute a third major form of genomic structural variation in polyploids. Homeologous exchanges involve the replacement of one genomic segment by a similar copy from another genome or ancestrally duplicated region, and are known to be extremely common in polyploids. Detecting all kinds of genomic structural variation is challenging, but recent advances such as optical mapping and long-read sequencing offer potential strategies to help identify structural variants even in complex polyploid genomes. All three major types of genomic structural variation (presence–absence, copy-number, and homeologous exchange) are now known to influence phenotypes in crop plants, with examples of flowering time, frost tolerance, and adaptive and agronomic traits. In this review, we summarize the challenges of genome analysis in polyploid crops, describe the various types of genomic structural variation and the genomics technologies and data that can be used to detect them, and collate information produced to date related to the impact of genomic structural variation on crop phenotypes. We highlight the importance of genomic structural variation for the future genetic improvement of polyploid crops.


April 21, 2020  |  

A Species-Wide Inventory of NLR Genes and Alleles in Arabidopsis thaliana.

Infectious disease is both a major force of selection in nature and a prime cause of yield loss in agriculture. In plants, disease resistance is often conferred by nucleotide-binding leucine-rich repeat (NLR) proteins, intracellular immune receptors that recognize pathogen proteins and their effects on the host. Consistent with extensive balancing and positive selection, NLRs are encoded by one of the most variable gene families in plants, but the true extent of intraspecific NLR diversity has been unclear. Here, we define a nearly complete species-wide pan-NLRome in Arabidopsis thaliana based on sequence enrichment and long-read sequencing. The pan-NLRome largely saturates with approximately 40 well-chosen wild strains, with half of the pan-NLRome being present in most accessions. We chart NLR architectural diversity, identify new architectures, and quantify selective forces that act on specific NLRs and NLR domains. Our study provides a blueprint for defining pan-NLRomes.Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.


April 21, 2020  |  

Informatics for PacBio Long Reads.

In this article, we review the development of a wide variety of bioinformatics software implementing state-of-the-art algorithms since the introduction of SMRT sequencing technology into the field. We focus on the three major categories of development: read mapping (aligning to reference genomes), de novo assembly, and detection of structural variants. The long SMRT reads benefit all the applications, but they are achievable only through considering the nature of the long reads technology properly.


April 21, 2020  |  

Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.

The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5?kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15?megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.


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