Biology subjects

Faraut, T.

Publications and source records attributed to Faraut, T..

8 recordsLinked to original sources

bioRxiv2026

Integrating Structural Variants into Sequence-Based GWAS Using a Pangenome and Imputation Framework in French Dairy Cattle

BackgroundStructural variants (SVs) are most effectively identified using long-read (LR) sequenc-ing. However, such data remain scarce, and sequenced samples often lack associated phenotypic information. To overcome this limitation, we integrated pangenome-based (variation graph-based) and imputation approaches to enable large-scale SV association studies in the three main French dairy cattle breeds. ResultsA variation graph was constructed using 69,892 deletions, 89,900 insertions, and 17,402 duplications detected in 176 LR samples. We subsequently genotyped 939 samples for each SV in the panel by realigning their short read (SR) sequences to the graph. Validation analyses showed high genotype concordance rates for deletions (0.79) and insertions (0.79); however, concordance for duplications was low (0.14), leading to their exclusion from further analyses. The retained SVs were combined with single nucleotide variants (SNVs) to build a sequence-level imputation reference panel. Using SNP genotyping array data, we imputed SVs and SNVs for 11,902 Holstein, 3,753 Montbeliarde, and 3,053 Normande bulls. After quality control, more than 14 million SNVs and 40 thousand SVs were retained for within-breed genome-wide association studies (GWAS) us-ing daughter yield deviations for stature and four milk production and composition traits. The GWAS results reveled genetic architectures consistent with previous findings and identified 40 genome-wide significant associations between structural variant and key phenotypes. Conditional analyses showed that ten of these SVs as strong candidates associated with milk fat and protein contents, as well as stature. ConclusionsBy integrating LR, SR, and SNP genotyping data within a unified pangenome and imputation framework, we demonstrate a scalable strategy to systematically interrogate the contribution of SVs to complex traits. The resulting genetic architectures were highly consistent with previous findings, validating both the robustness and transferability of our approach. Our findings highlight the added value of integrating SVs into routine genomic analyses and provide a scalable framework for incorporating SVs into genomic selection in dairy cattle.

genomics↗

bioRxiv2025

Comprehensive detection of structural variations in long and short reads dataset of French cattle

Structural variants (SVs) correspond to different types of genomic variants larger than 50 bp. Many findings suggest the use of long rather than short reads to improve the accuracy of SV detection. Here, we present the results of an in-depth analysis for detection of SVs, mainly large insertions and deletions, in 14 French bovine breeds, based on whole-genome data comprising 176 long-read and 571 short-read samples, with 154 individuals having both long- and short-read data available. We first investigated possible biases on the performances of well-known SV detection tools, namely CUTESV, PBSV, and SNIFFLES, using long reads from different technologies, including PacBio HiFi, Oxford ONT, and PacBio CLR. We subsequently highlighted the abilities of tools for detecting SVs (DELLY, LUMPY, and MANTA) and for genotyping known SVs (GRAPHTYPER, SVTYPER, PARAGRAPH, and VG toolkit) using short-read data. We then show how the incremental composition of samples in the reference panel affected the SV genotyping for six validation individuals sequenced in short reads. We then searched for the optimal parameters and created the final SV reference panel consisting of 25,191 deletions and 30,118 insertions. Finally, we emphasized the landscape of the genotyped SVs segregating across 571 short-read individuals of 14 breeds.

genomics↗

bioRxiv2025

An extensive and unbiased genome-wide scan for parent-of-origin expressed genes in the pig clarifies the conservation landscape of genomic imprinting

Genomic imprinting, a mechanism resulting in parent-of-origin expression of genes through epigenetic regulation, intersects with a broad range of biological fields including evolution, molecular genetics and epigenetics and determinism of complex traits. Although next generation sequencing technologies enable nowadays to detect imprinted genes in a genome-wide manner, a wide spectrum of this phenomena is evaluated only in humans and mice. Here, we propose to map genes showing a parental expression bias in hypothalamus, muscle and placenta in piglets around birth using an extensive and unbiased strategy that relied on reciprocal crosses, genetics reconstruction of parental phases after imputation and statistical analyses discriminating parent-of-origin from allele-specific expression. We detected 440 unique genes with a weak to exclusive parental expression bias including 114 unique genes with an imbalance ratio above 25:75. About thirty imprinted genes are common to human and/or mice and an equivalent number is shared between tissues, suggesting an overall weak conservation landscape of genomic imprinting. Interestingly, we identified novel parent-of-origin expressed genes involved in neurodevelopmental (PITRM1, Pitrilysin Metallopeptidase 1) and fetal growth (FAM20B, Glycosaminoglycan Xylosylkinase and POU6F2, POU Class 6 Homeobox 2) functions. In addition, deeper analyses of specific loci likely highlighted lineage-specific imprinted genes such as a Zinc Finger Protein 300-like gene as well as specific imprinted isoforms of COPG2 (COPI Coat Complex Subunit Gamma 2), a gene showing conflicting data in the literature. Altogether, our results bring pig as the most comprehensively and exhaustively documented species for genomic imprinting after human and mice organisms. A weak conservation of this mechanism across species and tissues suggested a distinction between a small number of core imprinted genes and others parent-of-origin expressed genes that seemed subjected to evolutionary forces for acquiring their imprinting status either in a lineage-specific or tissue-specific manner.

genomics↗

bioRxiv2024

Pairwise graph edit distance characterizes the impact of the construction method on pangenome graphs

MotivationPangenome variation graphs are an increasingly used tool to perform genome analysis, aiming to replace a linear reference in a wide variety of genomic analyses. The construction of a variation graph from a collection of chromosome-size genome sequences is a difficult task that is generally addressed using a number of heuristics. The question that arises is to what extent the construction method influences the resulting graph, and the characterization of variability. ResultsWe aim to characterize the differences between variation graphs derived from the same set of genomes with a metric which expresses and pinpoint differences. We designed a pairwise variation graph comparison algorithm, which establishes an edit distance between variation graphs, threading the genomes through both graphs. We applied our method to pangenome graphs built from yeast and human chromosome collections, and demonstrate that our method effectively characterizes discordances between pangenome graph construction methods and scales to real datasets. Availabilitypancat compare is published as free Rust software under the AGPL3.0 open source license. Source code and documentation are available at https://github.com/dubssieg/rs-pancat-compare. Contactsiegfried.dubois@inria.fr Supplementary informationSupplementary data are available online at https://doi.org/10.5281/zenodo.10932490. Code to replicate figures and analysis is available online at https://github.com/dubssieg/pancat_paper.

bioinformatics↗

bioRxiv2024

Particular sequence characteristics induce bias in the detection of polymorphic transposable element insertions

Transposable elements (TEs) have an important role in genome evolution but are challenging for bioinformatics detection due to their repetitive nature and ability to move and replicate within genomes. New sequencing technologies now enable the characterization of nucleotide and structural variations within species. Among them, TE polymorphism is critical to identify as it may influence species adaptation or trigger diseases. Despite the development of numerous bioinformatic programs, identifying the most effective tool is challenging due to non-overlapping results and varying efficiency across studies. Benchmarking efforts have highlighted some of the limitations of these tools, often evaluated on either real or simulated data. However, real data may be incomplete or contain unannotated TEs, while simulated data may not accurately reflect real genomes. This study introduces a simulation method generating data based on real genomes to control all genomic parameters. Evaluating several TE polymorphic detection tools using data from Drosophila melanogaster and Arabidopsis thaliana, our study investigates factors like copy size, sequence divergence, and GC content that influence detection efficiency. Our results indicate that only a few programs perform satisfactorily and that all are sensitive to TE and genomic characteristics that may differ according to the species considered. Using Bos taurus population data as a case study to identify polymorphic LTR-retrotransposon insertions, we found low-frequency insertions particularly challenging to detect due to a high number of false positives. Increased sequencing coverage improved sensitivity but reduced precision. Our work underscores the importance of selecting appropriate tools and thresholds according to the specific research questions.

bioinformatics↗

bioRxiv2024

A genome-wide study of ruminants reveals two endogenous retrovirus families still active in goats

BackgroundEndogenous retroviruses (ERV) are traces of ancestral retroviral germline infections that constitute a significant portion of mammalian genomes and function as LTR-retrotransposons. ERVs remain understudied in ruminants and usually focus on specific families, highlighting a need for comprehensive and thorough exploration of the ERV landscape in these species. ResultsWe characterized 23 de novo Class I and II ERV families across four reference assemblies of domestic and wild sheep and goats, and one assembly of cattle. Among these families, 15 were shared by the five ruminant species, while six were exclusive to small ruminants and two were exclusive to cattle. The presence of these families in other ruminant species revealed multiple endogenization events over 40 million years. We identified a total of 113,812 ERV insertions across the five genomes, representing between 0.5 and 1% of their genomes. Solo-LTRs account for 84.5% of the annotated copies demonstrating that most of the ERVs are relics of past events. Although Class I ERVs showed similar sequence divergence landscapes between species, Class II ERVs displayed contrasting evolutionary dynamics. Families II-3 and II-5 showed higher abundance and copy conservation in small ruminants. Family II-5 was closely related to circulating exogenous retroviruses and was identified with 22 copies sharing identical LTRs and 12 with complete coding capacities in the domestic goat. ConclusionsOur results indicate that two ERV families may have retain their transpositional activity within ruminants, particularly in domestic goats, illustrating distinct evolutionary dynamics among ruminant species. This work highlights the ongoing influence of ERVs on genomic landscapes and provides further insights into their evolutionary trajectories in ruminant genomes.

evolutionary biology↗

bioRxiv2022

Enhancer/gene relationships: need for more reliable genome-wide reference sets

Differences in cells functions arise from differential action of regulatory elements, in particular enhancers. Like promoters, enhancers are genomic regions bound by transcription factors (TF) that activate the expression of one or several genes by getting physically close to them in the 3D space of the nucleus. As there is increasing evidence that variants associated with common diseases are located in enhancers active in cell types relevant to these diseases, knowing the set of enhancers and more importantly the sets of genes activated by each enhancer (the so-called enhancer/gene or E/G relationships) in a cell type, will certainly help understanding these diseases. There are three broad approaches for the genome-wide identification of E/G relationships in a cell type: (1) genetic link methods or eQTL, (2) functional link methods based on 1D functional data such as open chromatin, histone mark and gene expression and (3) spatial link methods based on 3D data such as HiC. Since (1) and (3) are costly, there has been a focus on developing functional link methods and using data from (1) and (3) to evaluate them, however there is still no consensus on the best functional link method to date. For this reason we decided to start from the two latest benchmarks of the field, namely from the CRISPRi-FlowFISH (CRiFF) technique and from 3D and eQTL data in BENGI, and to evaluate the two methods claimed to be the best one on each of these benchmark studies, namely the ABC model and the Average-Rank method respectively, on the other methods reference data. Not only did we manage to reproduce the results of the two benchmarks but we also saw that none of the two methods performed best on the two reference data. While CRiFF reference data are very reliable, it is not genome-wide and is mostly available on a cancer cell type. On the other hand BENGI is genome-wide but may contain many false positives. This study therefore calls for new reliable and genome-wide E/G reference data rather than new functional link E/G identification methods.

bioinformatics↗

bioRxiv2019

RH mapping by sequencing: chromosome-scale assembly of the duck genome

Like many other species, the duck genome has been sequenced thanks to the technological breakthrough provided by the emergence of Next Generation Sequencing (NGS). The resulting de novo assemblies are however made of thousands of scattered scaffolds. To achieve chromosome-scale contiguity, long-range intermediate genome maps remain indispensable. Radiation Hybrid (RH) maps have been used to assist the generation of chromosome-scale genome assemblies by taking advantage of the high density SNP chips that provide a large number of markers that can be efficiently genotyped on the panel. In the absence of such a resource in duck, we sequenced 100 hybrid clones of a duck RH panel enabling direct genotyping of the assembly scaffolds on the panel. The rationale is to use scaffolds as markers and to genotype the scaffolds by sequencing the clones: the presence/absence of a scaffold in a particular sequenced hybrid is attested by the presence/absence of reads mapping specifically to this scaffold. The detection of scaffolds exhibiting a chromosomal breakage resulting from the irradiation process revealed itself to be a critical issue of this genotyping by sequencing process. This process resulted in the construction of RH vectors for 2,027 scaffolds, representing a total of about 1 Gb of sequences (95% of the current Duck genome assembly). The subsequent linkage analysis enabled the construction of RH maps and therefore to organize, i.e. order and orient, the scaffolds into pseudomolecules associated to the corresponding duck chromosomes. We describe here the whole mapping process, from sequence-based genotyping to the construction of comparative maps, as well as few examples of intra-chromosomal rearrangements that have been identified by the comparison with the chicken, turkey and zebra finch genomes and subsequently confirmed by FISH. We describe a method to order and orient sequence scaffolds into super-scaffolds spanning entire chromosomes. The method, which requires a pre-existing RH panel and sequence scaffolds from an NGS assembly, relies on a shallow sequencing of the RH clones. This approach was applied to the duck genome and produced chromosome-scale scaffolds for 29 out of the 41 duck chromosomes.

genomics↗