@article {153, title = {Optimized sample selection for cost-efficient long-read population sequencing.}, journal = {Genome Res}, volume = {31}, year = {2021}, month = {2021 May}, pages = {910-918}, abstract = {

An increasingly important scenario in population genetics is when a large cohort has been genotyped using a low-resolution approach (e.g., microarrays, exome capture, short-read WGS), from which a few individuals are resequenced using a more comprehensive approach, especially long-read sequencing. The subset of individuals selected should ensure that the captured genetic diversity is fully representative and includes variants across all subpopulations. For example, human variation has historically focused on individuals with European ancestry, but this represents a small fraction of the overall diversity. Addressing this, SVCollector identifies the optimal subset of individuals for resequencing by analyzing population-level VCF files from low-resolution genotyping studies. It then computes a ranked list of samples that maximizes the total number of variants present within a subset of a given size. To solve this optimization problem, SVCollector implements a fast, greedy heuristic and an exact algorithm using integer linear programming. We apply SVCollector on simulated data, 2504 human genomes from the 1000 Genomes Project, and 3024 genomes from the 3000 Rice Genomes Project and show the rankings it computes are more representative than alternative naive strategies. When selecting an optimal subset of 100 samples in these cohorts, SVCollector identifies individuals from every subpopulation, whereas naive methods yield an unbalanced selection. Finally, we show the number of variants present in cohorts selected using this approach follows a power-law distribution that is naturally related to the population genetic concept of the allele frequency spectrum, allowing us to estimate the diversity present with increasing numbers of samples.

}, issn = {1549-5469}, doi = {10.1101/gr.264879.120}, author = {Ranallo-Benavidez, T Rhyker and Lemmon, Zachary and Soyk, Sebastian and Aganezov, Sergey and Salerno, William J and McCoy, Rajiv C and Lippman, Zachary B and Schatz, Michael C and Sedlazeck, Fritz J} } @article {112, title = {Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato.}, journal = {Cell}, volume = {182}, year = {2020}, month = {2020 07 09}, pages = {145-161.e23}, abstract = {

Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.

}, keywords = {Alleles, Crops, Agricultural, Cytochrome P-450 Enzyme System, Ecotype, Epistasis, Genetic, Fruit, Gene Duplication, Gene Expression Regulation, Plant, Genome, Plant, Genomic Structural Variation, Genotype, Inbreeding, Lycopersicon esculentum, Molecular Sequence Annotation, Phenotype, Plant Breeding, Quantitative Trait Loci}, issn = {1097-4172}, doi = {10.1016/j.cell.2020.05.021}, author = {Alonge, Michael and Wang, Xingang and Benoit, Matthias and Soyk, Sebastian and Pereira, Lara and Zhang, Lei and Suresh, Hamsini and Ramakrishnan, Srividya and Maumus, Florian and Ciren, Danielle and Levy, Yuval and Harel, Tom Hai and Shalev-Schlosser, Gili and Amsellem, Ziva and Razifard, Hamid and Caicedo, Ana L and Tieman, Denise M and Klee, Harry and Kirsche, Melanie and Aganezov, Sergey and Ranallo-Benavidez, T Rhyker and Lemmon, Zachary H and Kim, Jennifer and Robitaille, Gina and Kramer, Melissa and Goodwin, Sara and McCombie, W Richard and Hutton, Samuel and Van Eck, Joyce and Gillis, Jesse and Eshed, Yuval and Sedlazeck, Fritz J and van der Knaap, Esther and Schatz, Michael C and Lippman, Zachary B} } @article {135, title = {Parliament2: Accurate structural variant calling at scale.}, journal = {Gigascience}, volume = {9}, year = {2020}, month = {2020 12 21}, abstract = {

BACKGROUND: Structural variants (SVs) are critical contributors to genetic diversity and genomic disease. To predict the phenotypic impact of SVs, there is a need for better estimates of both the occurrence and frequency of SVs, preferably from large, ethnically diverse cohorts. Thus, the current standard approach requires the use of short paired-end reads, which remain challenging to detect, especially at the scale of hundreds to thousands of samples.

FINDINGS: We present Parliament2, a consensus SV framework that leverages multiple best-in-class methods to identify high-quality SVs from short-read DNA sequence data at scale. Parliament2 incorporates pre-installed SV callers that are optimized for efficient execution in parallel to reduce the overall runtime and costs. We demonstrate the accuracy of Parliament2 when applied to data from NovaSeq and HiSeq X platforms with the Genome in a Bottle (GIAB) SV call set across all size classes. The reported quality score per SV is calibrated across different SV types and size classes. Parliament2 has the highest F1 score (74.27\%) measured across the independent gold standard from GIAB. We illustrate the compute performance by processing all 1000 Genomes samples (2,691 samples) in <1 day on GRCH38. Parliament2 improves the runtime performance of individual methods and is open source (https://github.com/slzarate/parliament2), and a Docker image, as well as a WDL implementation, is available.

CONCLUSION: Parliament2 provides both a highly accurate single-sample SV call set from short-read DNA sequence data and enables cost-efficient application over cloud or cluster environments, processing thousands of samples.

}, issn = {2047-217X}, doi = {10.1093/gigascience/giaa145}, author = {Zarate, Samantha and Carroll, Andrew and Mahmoud, Medhat and Krasheninina, Olga and Jun, Goo and Salerno, William J and Schatz, Michael C and Boerwinkle, Eric and Gibbs, Richard A and Sedlazeck, Fritz J} } @article {78, title = {Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.}, journal = {Nat Biotechnol}, volume = {37}, year = {2019}, month = {2019 Oct}, pages = {1155-1162}, abstract = {

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 {\textquoteright}genome in a bottle{\textquoteright} (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.

}, issn = {1546-1696}, doi = {10.1038/s41587-019-0217-9}, author = {Wenger, Aaron M and Peluso, Paul and Rowell, William J and Chang, Pi-Chuan and Hall, Richard J and Concepcion, Gregory T and Ebler, Jana and Fungtammasan, Arkarachai and Kolesnikov, Alexey and Olson, Nathan D and T{\"o}pfer, Armin and Alonge, Michael and Mahmoud, Medhat and Qian, Yufeng and Chin, Chen-Shan and Phillippy, Adam M and Schatz, Michael C and Myers, Gene and DePristo, Mark A and Ruan, Jue and Marschall, Tobias and Sedlazeck, Fritz J and Zook, Justin M and Li, Heng and Koren, Sergey and Carroll, Andrew and Rank, David R and Hunkapiller, Michael W} } @article {51, title = {Genome-wide patterns of transposon proliferation in an evolutionary young hybrid fish.}, journal = {Mol Ecol}, volume = {28}, year = {2019}, month = {2019 Mar}, pages = {1491-1505}, abstract = {

Hybridization can induce transposons to jump into new genomic positions, which may result in their accumulation across the genome. Alternatively, transposon copy numbers may increase through nonallelic (ectopic) homologous recombination in highly repetitive regions of the genome. The relative contribution of transposition bursts versus recombination-based mechanisms to evolutionary processes remains unclear because studies on transposon dynamics in natural systems are rare. We assessed the genomewide distribution of transposon insertions in a young hybrid lineage ("invasive Cottus", n~=~11) and its parental species Cottus rhenanus (n~=~17) and Cottus perifretum(n~=~9) using a reference genome assembled from long single molecule pacbio reads. An inventory of transposable elements was reconstructed from the same data and annotated. Transposon copy numbers in the hybrid lineage increased in 120 (15.9\%) out of 757 transposons studied here. The copy number increased on average by 69\% (range: 10\%-197\%). Given the age of the hybrid lineage, this suggests that they have proliferated within a few hundred generations since admixture began. However, frequency spectra of transposon insertions revealed no increase in novel and rare insertions across assembled parts of the genome. This implies that transposons were added to repetitive regions of the genome that remain difficult to assemble. Future studies will need to evaluate whether recombination-based mechanisms rather than genomewide transposition may explain the majority of the recent transposon proliferation in the hybrid lineage. Irrespectively of the underlying mechanism, the observed overabundance in repetitive parts of the genome suggests that gene-rich regions are unlikely to be directly affected.

}, issn = {1365-294X}, doi = {10.1111/mec.14969}, author = {Dennenmoser, Stefan and Sedlazeck, Fritz J and Schatz, Michael C and Altm{\"u}ller, Janine and Zytnicki, Matthias and Nolte, Arne W} } @article {52, title = {A multi-task convolutional deep neural network for variant calling in single molecule sequencing.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 03 01}, pages = {998}, abstract = {

The accurate identification of DNA sequence variants is an important, but challenging task in genomics. It is particularly difficult for single molecule sequencing, which has a per-nucleotide error rate of ~5-15\%. Meeting this demand, we developed Clairvoyante, a multi-task five-layer convolutional neural network model for predicting variant type (SNP or indel), zygosity, alternative allele and indel length from aligned reads. For the well-characterized NA12878 human sample, Clairvoyante achieves 99.67, 95.78, 90.53\% F1-score on 1KP common variants, and 98.65, 92.57, 87.26\% F1-score for whole-genome analysis, using Illumina, PacBio, and Oxford Nanopore data, respectively. Training on a second human sample shows Clairvoyante is sample agnostic and finds variants in less than 2 h on a standard server. Furthermore, we present 3,135 variants that are missed using Illumina but supported independently by both PacBio and Oxford Nanopore reads. Clairvoyante is available open-source ( https://github.com/aquaskyline/Clairvoyante ), with modules to train, utilize and visualize the model.

}, keywords = {Base Sequence, Computational Biology, DNA Mutational Analysis, Genome, Human, Genome-Wide Association Study, Genomics, Genotype, Genotyping Techniques, Humans, INDEL Mutation, Nanopores, Neural Networks (Computer), Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software}, issn = {2041-1723}, doi = {10.1038/s41467-019-09025-z}, author = {Luo, Ruibang and Sedlazeck, Fritz J and Lam, Tak-Wah and Schatz, Michael C} } @article {82, title = {RaGOO: fast and accurate reference-guided scaffolding of draft genomes.}, journal = {Genome Biol}, volume = {20}, year = {2019}, month = {2019 Oct 28}, pages = {224}, abstract = {

We present RaGOO, a reference-guided contig ordering and orienting tool that leverages the speed and sensitivity of Minimap2 to accurately achieve chromosome-scale assemblies in minutes. After the pseudomolecules are constructed, RaGOO identifies structural variants, including those spanning sequencing gaps. We show that RaGOO accurately orders and orients 3 de novo tomato genome assemblies, including the widely used M82 reference cultivar. We then demonstrate the scalability and utility of RaGOO with a pan-genome analysis of 103 Arabidopsis thaliana accessions by examining the structural variants detected in the newly assembled pseudomolecules. RaGOO is available open source at https://github.com/malonge/RaGOO .

}, issn = {1474-760X}, doi = {10.1186/s13059-019-1829-6}, author = {Alonge, Michael and Soyk, Sebastian and Ramakrishnan, Srividya and Wang, Xingang and Goodwin, Sara and Sedlazeck, Fritz J and Lippman, Zachary B and Schatz, Michael C} } @article {37, title = {Accurate detection of complex structural variations using single-molecule sequencing.}, journal = {Nat Methods}, volume = {15}, year = {2018}, month = {2018 Jun}, pages = {461-468}, abstract = {

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr ) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles ) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings.

}, keywords = {DNA Mutational Analysis, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA}, issn = {1548-7105}, doi = {10.1038/s41592-018-0001-7}, author = {Sedlazeck, Fritz J and Rescheneder, Philipp and Smolka, Moritz and Fang, Han and Nattestad, Maria and von Haeseler, Arndt and Schatz, Michael C} } @article {40, title = {Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line.}, journal = {Genome Res}, volume = {28}, year = {2018}, month = {2018 08}, pages = {1126-1135}, abstract = {

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important oncogene (also known as ), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

}, keywords = {Breast Neoplasms, Female, Gene Amplification, Gene Rearrangement, Genome, Human, Genomic Structural Variation, High-Throughput Nucleotide Sequencing, Humans, MCF-7 Cells, Oncogenes, Receptor, ErbB-2, Repetitive Sequences, Nucleic Acid, Transcriptome}, issn = {1549-5469}, doi = {10.1101/gr.231100.117}, author = {Nattestad, Maria and Goodwin, Sara and Ng, Karen and Baslan, Timour and Sedlazeck, Fritz J and Rescheneder, Philipp and Garvin, Tyler and Fang, Han and Gurtowski, James and Hutton, Elizabeth and Tseng, Elizabeth and Chin, Chen-Shan and Beck, Timothy and Sundaravadanam, Yogi and Kramer, Melissa and Antoniou, Eric and McPherson, John D and Hicks, James and McCombie, W Richard and Schatz, Michael C} }