Publications

@article{Liao2023-do,

title = {A draft human pangenome reference},

author = {Wen-Wei Liao and Mobin Asri and Jana Ebler and Daniel Doerr and Marina Haukness and Glenn Hickey and Shuangjia Lu and Julian K Lucas and Jean Monlong and Haley J Abel and Silvia Buonaiuto and Xian H Chang and Haoyu Cheng and Justin Chu and Vincenza Colonna and Jordan M Eizenga and Xiaowen Feng and Christian Fischer and Robert S Fulton and Shilpa Garg and Cristian Groza and Andrea Guarracino and William T Harvey and Simon Heumos and Kerstin Howe and Miten Jain and Tsung-Yu Lu and Charles Markello and Fergal J Martin and Matthew W Mitchell and Katherine M Munson and Moses Njagi Mwaniki and Adam M Novak and Hugh E Olsen and Trevor Pesout and David Porubsky and Pjotr Prins and Jonas A Sibbesen and Jouni Sirén and Chad Tomlinson and Flavia Villani and Mitchell R Vollger and Lucinda L Antonacci-Fulton and Gunjan Baid and Carl A Baker and Anastasiya Belyaeva and Konstantinos Billis and Andrew Carroll and Pi-Chuan Chang and Sarah Cody and Daniel E Cook and Robert M Cook-Deegan and Omar E Cornejo and Mark Diekhans and Peter Ebert and Susan Fairley and Olivier Fedrigo and Adam L Felsenfeld and Giulio Formenti and Adam Frankish and Yan Gao and Nanibaa' A Garrison and Carlos Garcia Giron and Richard E Green and Leanne Haggerty and Kendra Hoekzema and Thibaut Hourlier and Hanlee P Ji and Eimear E Kenny and Barbara A Koenig and Alexey Kolesnikov and Jan O Korbel and Jennifer Kordosky and Sergey Koren and Hojoon Lee and Alexandra P Lewis and Hugo Magalhães and Santiago Marco-Sola and Pierre Marijon and Ann McCartney and Jennifer McDaniel and Jacquelyn Mountcastle and Maria Nattestad and Sergey Nurk and Nathan D Olson and Alice B Popejoy and Daniela Puiu and Mikko Rautiainen and Allison A Regier and Arang Rhie and Samuel Sacco and Ashley D Sanders and Valerie A Schneider and Baergen I Schultz and Kishwar Shafin and Michael W Smith and Heidi J Sofia and Ahmad N Abou Tayoun and Françoise Thibaud-Nissen and Francesca Floriana Tricomi and Justin Wagner and Brian Walenz and Jonathan M D Wood and Aleksey V Zimin and Guillaume Bourque and Mark J P Chaisson and Paul Flicek and Adam M Phillippy and Justin M Zook and Evan E Eichler and David Haussler and Ting Wang and Erich D Jarvis and Karen H Miga and Erik Garrison and Tobias Marschall and Ira M Hall and Heng Li and Benedict Paten},

doi = {10.1038/s41586-023-05896-x},

isbn = {1476-4687},

year  = {2023},

date = {2023-05-01},

urldate = {2023-05-01},

journal = {Nature},

volume = {617},

number = {7960},

pages = {312–324},

publisher = {Springer Science and Business Media LLC},

abstract = {Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.},

keywords = {WP3: Translational CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Forgia2023,

title = {Hybrids of RNA viruses and viroid-like elements replicate in fungi},

author = {Marco Forgia and Beatriz Navarro and Stefania Daghino and Amelia Cervera and Andreas Gisel and Silvia Perotto and Dilzara N. Aghayeva and Mary F. Akinyuwa and Emanuela Gobbi and Ivan N. Zheludev and Robert C. Edgar and Rayan Chikhi and Massimo Turina and Artem Babaian and Francesco Di Serio and Marcos Peña},

doi = {10.1038/s41467-023-38301-2},

issn = {2041-1723},

year  = {2023},

date = {2023-05-01},

urldate = {2023-05-01},

journal = {Nature Communications},

volume = {14},

number = {1},

pages = {2591},

publisher = {Springer Science and Business Media LLC},

abstract = {Earth’s life may have originated as self-replicating RNA, and it has been argued that RNA viruses and viroid-like elements are remnants of such pre-cellular RNA world. RNA viruses are defined by linear RNA genomes encoding an RNA-dependent RNA polymerase (RdRp), whereas viroid-like elements consist of small, single-stranded, circular RNA genomes that, in some cases, encode paired self-cleaving ribozymes. Here we show that the number of candidate viroid-like elements occurring in geographically and ecologically diverse niches is much higher than previously thought. We report that, amongst these circular genomes, fungal ambiviruses are viroid-like elements that undergo rolling circle replication and encode their own viral RdRp. Thus, ambiviruses are distinct infectious RNAs showing hybrid features of viroid-like RNAs and viruses. We also detected similar circular RNAs, containing active ribozymes and encoding RdRps, related to mitochondrial-like fungal viruses, highlighting fungi as an evolutionary hub for RNA viruses and viroid-like elements. Our findings point to a deep co-evolutionary history between RNA viruses and subviral elements and offer new perspectives in the origin and evolution of primordial infectious agents, and RNA life.},

keywords = {WP1: Primary CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Mille2023-mj,

title = {dipwmsearch: a Python package for searching di-PWM motifs},

author = {Marie Mille and Julie Ripoll and Bastien Cazaux and Eric Rivals},

url = {https://rivals.lirmm.net/dipwmsearch/},

doi = {10.1093/bioinformatics/btad141},

issn = {1367-4811},

year  = {2023},

date = {2023-04-01},

urldate = {2023-04-01},

journal = {Bioinformatics},

volume = {39},

number = {4},

abstract = {Seeking probabilistic motifs in a sequence is a common task to annotate putative transcription factor binding sites or other RNA/DNA binding sites. Useful motif representations include position weight matrices (PWMs), dinucleotide PWMs (di-PWMs), and hidden Markov models (HMMs). Dinucleotide PWMs not only combine the simplicity of PWMs—a matrix form and a cumulative scoring function—but also incorporate dependency between adjacent positions in the motif (unlike PWMs which disregard any dependency). For instance to represent binding sites, the HOCOMOCO database provides di-PWM motifs derived from experimental data. Currently, two programs, SPRy-SARUS and MOODS, can search for occurrences of di-PWMs in sequences.



We propose a Python package called dipwmsearch, which provides an original and efficient algorithm for this task (it first enumerates matching words for the di-PWM, and then searches these all at once in the sequence, even if the latter contains IUPAC codes). The user benefits from an easy installation via Pypi or conda, a comprehensive documentation, and executable scripts that facilitate the use of di-PWMs.



dipwmsearch is available at https://pypi.org/project/dipwmsearch/ and https://gite.lirmm.fr/rivals/dipwmsearch/ under Cecill license.},

keywords = {WP1: Primary CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Denti2023-xa,

title = {SVDSS: structural variation discovery in hard-to-call genomic regions using sample-specific strings from accurate long reads},

author = {Luca Denti and Parsoa Khorsand and Paola Bonizzoni and Fereydoun Hormozdiari and Rayan Chikhi},

doi = {10.1038/s41592-022-01674-1},

isbn = {1548-7105},

year  = {2023},

date = {2023-04-01},

urldate = {2023-04-01},

journal = {Nat. Methods},

volume = {20},

number = {4},

pages = {550–558},

publisher = {Springer Science and Business Media LLC},

abstract = {Structural variants (SVs) account for a large amount of sequence variability across genomes and play an important role in human genomics and precision medicine. Despite intense efforts over the years, the discovery of SVs in individuals remains challenging due to the diploid and highly repetitive structure of the human genome, and by the presence of SVs that vastly exceed sequencing read lengths. However, the recent introduction of low-error long-read sequencing technologies such as PacBio HiFi may finally enable these barriers to be overcome. Here we present SV discovery with sample-specific strings (SVDSS)—a method for discovery of SVs from long-read sequencing technologies (for example, PacBio HiFi) that combines and effectively leverages mapping-free, mapping-based and assembly-based methodologies for overall superior SV discovery performance. Our experiments on several human samples show that SVDSS outperforms state-of-the-art mapping-based methods for discovery of insertion and deletion SVs in PacBio HiFi reads and achieves notable improvements in calling SVs in repetitive regions of the genome.},

keywords = {WP2: Evolutionary/Comparative CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Porubsky2023-ue,

title = {Gaps and complex structurally variant loci in phased genome  assemblies},

author = {David Porubsky and Mitchell R Vollger and William T Harvey and Allison N Rozanski and Peter Ebert and Glenn Hickey and Patrick Hasenfeld and Ashley D Sanders and Catherine Stober and Human Pangenome Reference Consortium and Jan O Korbel and Benedict Paten and Tobias Marschall and Evan E Eichler},

doi = {10.1101/gr.277334.122},

issn = {1549-5469},

year  = {2023},

date = {2023-04-01},

urldate = {2023-04-01},

journal = {Genome Res.},

volume = {33},

number = {4},

pages = {496–510},

abstract = {There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.},

keywords = {WP3: Translational CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Carr2023-za,

title = {Palidis: fast discovery of novel insertion sequences},

author = {Victoria R Carr and Solon P Pissis and Peter Mullany and Saeed Shoaie and David Gomez-Cabrero and David L Moyes},

doi = {10.1099/mgen.0.000917},

issn = {2057-5858},

year  = {2023},

date = {2023-03-01},

urldate = {2023-03-01},

journal = {Microb. Genom.},

volume = {9},

number = {3},

abstract = {The diversity of microbial insertion sequences, crucial mobile genetic elements in generating diversity in microbial genomes, needs to be better represented in current microbial databases. Identification of these sequences in microbiome communities presents some significant problems that have led to their underrepresentation. Here, we present a bioinformatics pipeline called Palidis that recognizes insertion sequences in metagenomic sequence data rapidly by identifying inverted terminal repeat regions from mixed microbial community genomes. Applying Palidis to 264 human metagenomes identifies 879 unique insertion sequences, with 519 being novel and not previously characterized. Querying this catalogue against a large database of isolate genomes reveals evidence of horizontal gene transfer events across bacterial classes. We will continue to apply this tool more widely, building the Insertion Sequence Catalogue, a valuable resource for researchers wishing to query their microbial genomes for insertion sequences.},

keywords = {WP2: Evolutionary/Comparative CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Luo2023-le,

title = {Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks},

author = {Xiao Luo and Xiongbin Kang and Alexander Schönhuth},

doi = {10.1038/s42256-022-00604-2},

isbn = {2522-5839},

year  = {2023},

date = {2023-02-01},

urldate = {2023-02-01},

journal = {Nat. Mach. Intell.},

volume = {5},

number = {2},

pages = {114–125},

publisher = {Springer Science and Business Media LLC},

abstract = {Diseases that have a complex genetic architecture tend to suffer from considerable amounts of genetic variants that, although playing a role in the disease, have not yet been revealed as such. Two major causes for this phenomenon are genetic variants that do not stack up effects, but interact in complex ways; in addition, as recently suggested, the omnigenic model postulates that variants interact in a holistic manner to establish disease phenotypes. Here we present DiseaseCapsule, as a capsule-network-based approach that explicitly addresses to capture the hierarchical structure of the underlying genome data, and has the potential to fully capture the non-linear relationships between variants and disease. DiseaseCapsule is the first such approach to operate in a whole-genome manner when predicting disease occurrence from individual genotype profiles. In experiments, we evaluated DiseaseCapsule on amyotrophic lateral sclerosis (ALS) and Parkinson’s disease, with a particular emphasis on ALS, which is known to have a complex genetic architecture and is affected by 40% missing heritability. On ALS, DiseaseCapsule achieves 86.9% accuracy on hold-out test data in predicting disease occurrence, thereby outperforming all other approaches by large margins. Also, DiseaseCapsule required sufficiently less training data for reaching optimal performance. Last but not least, the systematic exploitation of the network architecture yielded 922 genes of particular interest, and 644 ‘non-additive’ genes that are crucial factors in DiseaseCapsule, but remain masked within linear schemes.},

keywords = {WP3: Translational CPG},

pubstate = {published},

tppubtype = {article}

}

@article{10.1093/bioinformatics/btad388,

title = {WarpSTR: determining tandem repeat lengths using raw nanopore signals},

author = {Jozef Sitarčík and Tomáš Vinař and Broňa Brejová and Werner Krampl and Jaroslav Budiš and Ján Radvánszky and Mária Lucká},

url = {https://github.com/fmfi-compbio/warpstr},

doi = {10.1093/bioinformatics/btad388},

issn = {1367-4811},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Bioinformatics},

volume = {39},

number = {6},

pages = {btad388},

abstract = {Short tandem repeats (STRs) are regions of a genome containing many consecutive copies of the same short motif, possibly with small variations. Analysis of STRs has many clinical uses but is limited by technology mainly due to STRs surpassing the used read length. Nanopore sequencing, as one of long-read sequencing technologies, produces very long reads, thus offering more possibilities to study and analyze STRs. Basecalling of nanopore reads is however particularly unreliable in repeating regions, and therefore direct analysis from raw nanopore data is required. Here, we present WarpSTR, a novel method for characterizing both simple and complex tandem repeats directly from raw nanopore signals using a finite-state automaton and a search algorithm analogous to dynamic time warping. By applying this approach to determine the lengths of 241 STRs, we demonstrate that our approach decreases the mean absolute error of the STR length estimate compared to basecalling and STRique. WarpSTR is freely available at https://github.com/fmfi-compbio/warpstr},

keywords = {WP2: Evolutionary/Comparative CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Blassel2022,

title = {Mapping-friendly sequence reductions: Going beyond homopolymer compression},

author = {Luc Blassel and Paul Medvedev and Rayan Chikhi},

doi = {10.1016/j.isci.2022.105305},

issn = {2589-0042},

year  = {2022},

date = {2022-11-01},

urldate = {2022-11-01},

journal = {iScience},

volume = {25},

number = {11},

pages = {105305},

abstract = {Sequencing errors continue to pose algorithmic challenges to methods working with sequencing data. One of the simplest and most prevalent techniques for ameliorating the detrimental effects of homopolymer expansion/contraction errors present in long reads is homopolymer compression. It collapses runs of repeated nucleotides, to remove some sequencing errors and improve mapping sensitivity. Though our intuitive understanding justifies why homopolymer compression works, it in no way implies that it is the best transformation that can be done. In this paper, we explore if there are transformations that can be applied in the same pre-processing manner as homopolymer compression that would achieve better alignment sensitivity. We introduce a more general framework than homopolymer compression, called mapping-friendly sequence reductions. We transform the reference and the reads using these reductions and then apply an alignment algorithm. We demonstrate that some mapping-friendly sequence reductions lead to improved mapping accuracy, outperforming homopolymer compression.},

keywords = {WP1: Primary CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Luo2022b,

title = {VeChat: correcting errors in long reads using variation graphs},

author = {Xiao Luo and Xiongbin Kang and Alexander Schönhuth},

doi = {10.1038/s41467-022-34381-8},

issn = {2041-1723},

year  = {2022},

date = {2022-11-01},

urldate = {2022-11-01},

journal = {Nat Commun},

volume = {13},

number = {1},

pages = {6657},

abstract = {Error correction is the canonical first step in long-read sequencing data analysis. Current self-correction methods, however, are affected by consensus sequence induced biases that mask true variants in haplotypes of lower frequency showing in mixed samples. Unlike consensus sequence templates, graph-based reference systems are not affected by such biases, so do not mistakenly mask true variants as errors. We present VeChat, as an approach to implement this idea: VeChat is based on variation graphs, as a popular type of data structure for pangenome reference systems. Extensive benchmarking experiments demonstrate that long reads corrected by VeChat contain 4 to 15 (Pacific Biosciences) and 1 to 10 times (Oxford Nanopore Technologies) less errors than when being corrected by state of the art approaches. Further, using VeChat prior to long-read assembly significantly improves the haplotype awareness of the assemblies. VeChat is an easy-to-use open-source tool and publicly available at https://github.com/HaploKit/vechat .},

keywords = {WP1: Primary CPG},

pubstate = {published},

tppubtype = {article}

}

@article{Lemane2022,

title = {kmdiff, large-scale and user-friendly differential k-mer analyses},

author = {Téo Lemane and Rayan Chikhi and Pierre Peterlongo},

url = {https://github.com/tlemane/kmdiff},

doi = {10.1093/bioinformatics/btac689},

issn = {1367-4803},

year  = {2022},

date = {2022-10-01},

urldate = {2022-10-01},

journal = {Bioinformatics},

volume = {38},

number = {24},

pages = {5443-5445},

abstract = {Genome Wide Association Studies (GWAS) elucidate links between genotypes and phenotypes. Recent studies point out the interest of conducting such experiments using k-mers as the base signal instead of single-nucleotide polymorphisms. We propose a tool, kmdiff, that performs differential k-mer analyses on large sequencing cohorts in an order of magnitude less time and memory than previously possible.



AVAILABILITY: https://github.com/tlemane/kmdiff.},

keywords = {WP1: Primary CPG},

pubstate = {published},

tppubtype = {article}

}