Biology subjects

Thiery, A.

Publications and source records attributed to Thiery, A..

10 recordsLinked to original sources

bioRxiv2022

Comparison of calling pipelines for whole genome sequencing: an empirical study demonstrating the importance of mapping and alignment

Rapid advances in high-throughput DNA sequencing technologies have enabled the conduct of whole genome sequencing (WGS) studies, and several bioinformatics pipelines have become available. The aim of this study was the comparison of 6 WGS data pre-processing pipelines, involving two mapping and alignment approaches (GATK utilizing BWA-MEM2 2.2.1, and DRAGEN 3.8.4) and three variant calling pipelines (GATK 4.2.4.1, DRAGEN 3.8.4 and DeepVariant 1.1.0). We sequenced one genome in a bottle (GIAB) sample 70 times in different runs, and one GIAB trio in triplicate. The truth set of the GIABs was used for comparison, and performance was assessed by computation time, F1 score, precision, and recall. In the mapping and alignment step, the DRAGEN pipeline was faster than the GATK with BWA-MEM2 pipeline. DRAGEN showed systematically higher F1 score, precision, and recall values than GATK for single nucleotide variations (SNVs) and Indels in simple-to-map, complex-to-map, coding and non-coding regions. In the variant calling step, DRAGEN was fastest. In terms of accuracy, DRAGEN and DeepVariant performed similarly and both superior to GATK, with slight advantages for DRAGEN for Indels and for DeepVariant for SNVs. The DRAGEN pipeline showed the lowest Mendelian inheritance error fraction for the GIAB trios. Mapping and alignment played a key role in variant calling of WGS, with the DRAGEN outperforming GATK.

bioinformatics↗

bioRxiv2022

A gradient border model for cell fate decisions at the neural plate border

The vertebrate neural plate border is a transient territory located at the edge of the neural plate containing precursors for all ectodermal derivatives: the neural plate; neural crest; placodes; and epidermis. Elegant functional experiments in a range of vertebrate models have provided an in-depth understanding of gene regulatory interactions within the ectoderm. However, these experiments conducted at tissue level raise seemingly contradictory models for fate allocation of individual cells. Here, we carry out single cell RNA sequencing of chick ectoderm from primitive streak to neurulation stage, to explore cell state diversity and heterogeneity. We characterise the dynamics of gene modules containing key factors known to regulate ectodermal cell fates, allowing us to model the order in which these fates are specified. Furthermore, we find that genes previously classified as neural plate border specifiers typically exhibit dynamic expression patterns and are biased towards either placodal or neural crest fates, revealing that the neural plate border should be seen as an anatomical region of the ectoderm and not a discrete transcriptional state. Through co-expression of placodal and neural crest markers, we identify a population of border located unstable progenitors (BLUPs) which gradually reduces in size as fate segregation occurs. Considering our findings, we propose a gradient border model for cell fate choice at the neural plate border, with the probability of cell fate allocation closely tied to the spatiotemporal positioning of cells.

developmental biology↗

bioRxiv2021

Detection of m6A from direct RNA sequencing using a Multiple Instance Learning framework

RNA modifications such as m6A methylation form an additional layer of complexity in the transcriptome. Nanopore direct RNA sequencing captures this information in the raw current signal for each RNA molecule, enabling the detection of RNA modifications using supervised machine learning. However, experimental approaches provide only site-level training data, whereas the modification status for each single RNA molecule is missing. Here we present m6Anet, a neural network-based method that leverages the Multiple Instance Learning framework to specifically handle missing read-level modification labels in site-level training data. m6Anet outperforms existing computational methods, shows similar accuracy as experimental approaches, and generalises to different cell lines with almost identical accuracy. We demonstrate that m6Anet captures the underlying read-level stoichiometry that can be used to approximate differences in modification rates. m6Anet achieves this without retraining model parameters, enabling the transcriptome-wide identification and quantification of m6A from a single run of direct RNA sequencing. Code AvailabilityThe source code for m6Anet is available at https://github.com/GoekeLab/m6anet. Installation instructions and online documentation is available at https://m6anet.readthedocs.io/en/latest/.

bioinformatics↗

bioRxiv2021

A systematic benchmark of Nanopore long read RNA sequencing for transcript level analysis in human cell lines

The human genome contains more than 200,000 gene isoforms. However, different isoforms can be highly similar, and with an average length of 1.5kb remain difficult to study with short read sequencing. To systematically evaluate the ability to study the transcriptome at a resolution of individual isoforms we profiled 5 human cell lines with short read cDNA sequencing and Nanopore long read direct RNA, amplification-free direct cDNA, PCR-cDNA sequencing. The long read protocols showed a high level of consistency, with amplification-free RNA and cDNA sequencing being most similar. While short and long reads generated comparable gene expression estimates, they differed substantially for individual isoforms. We find that increased read length improves read-to-transcript assignment, identifies interactions between alternative promoters and splicing, enables the discovery of novel transcripts from repetitive regions, facilitates the quantification of full-length fusion isoforms and enables the simultaneous profiling of m6A RNA modifications when RNA is sequenced directly. Our study demonstrates the advantage of long read RNA sequencing and provides a comprehensive resource that will enable the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.

genomics↗

bioRxiv2021

Sox8 is sufficient to reprogram ectoderm into ear vesicles and associated neurons

The vertebrate inner ear arises from a pool of progenitors with the potential to contribute to all the sense organs and cranial ganglia in the head. Here we explore the molecular mechanisms that control ear specification from these precursors. Using a multi-omics approach combined with loss-of-function experiments we identify a core transcriptional circuit that imparts ear identity, along with the first genome-wide characterization of non-coding elements that integrate this information. This analysis places the transcription factor Sox8 at the top of the ear determination network. Introducing Sox8 into cranial ectoderm not only converts non-ear cells into ear progenitors, but also activates the cellular programs for ear morphogenesis and neurogenesis. Thus, Sox8 has the unique ability to remodel transcriptional networks in the cranial ectoderm towards ear identity.

developmental biology↗

bioRxiv2021

A gene regulatory network for neural induction

During early vertebrate development, signals from a special region of the embryo, the organizer, can re-direct the fate of non-neural ectoderm cells to form a complete, patterned nervous system. This is called neural induction and has generally been imagined as a single signalling event, causing a switch of fate. Here we undertake a comprehensive analysis, in very fine time-course, of the events following exposure of ectoderm to the organizer. Using transcriptomics and epigenomics we generate a Gene Regulatory Network comprising 175 transcriptional regulators and 5,614 predicted interactions between them, with fine temporal dynamics from initial exposure to the signals to expression of mature neural plate markers. Using in situ hybridization, single-cell RNA-sequencing and reporter assays we show that neural induction by a grafted organizer closely resembles normal neural plate development. The study is accompanied by a comprehensive resource including information about conservation of the predicted enhancers in different vertebrate systems.

developmental biology↗

bioRxiv2020

The mixed genetic origin of the first farmers of Europe

The precise genetic origins of the first Neolithic farming populations, as well as the processes and the timing of their differentiation, remain largely unknown. Based on demogenomic modeling of high-quality ancient genomes, we show that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Near Eastern population with a strongly bottlenecked Western hunter-gatherer population after the Last Glacial Maximum. Moreover, the population branch leading to the first farmers of Europe and Anatolia is characterized by a 2,500-year period of extreme genetic drift during its westward range expansion. Based on these findings, we derive a spatially explicit model of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene. One-Sentence SummaryEarly European farmers emerged from multiple post LGM mixtures and experienced extreme drift during their westward expansion.

evolutionary biology↗

bioRxiv2020

Detection of differential RNA modifications from direct RNA sequencing of human cell lines

Differences in RNA expression can provide insights into the molecular identity of a cell, pathways involved in human diseases, and variation in RNA levels across patients associated with clinical phenotypes. RNA modifications such as m6A have been found to contribute to molecular functions of RNAs. However, quantification of differences in RNA modifications has been challenging. Here we develop a computational method (xPore) to identify differential RNA modifications from direct RNA sequencing data. We evaluate our method on transcriptome-wide m6A profiling data, demonstrating that xPore identifies positions of m6A sites at single base resolution, estimates the fraction of modified RNAs in the cell, and quantifies the differential modification rate across conditions. We apply the method to direct RNA-Sequencing data from 6 cell lines and find that many m6A sites are preserved, while a subset of m6A sites show significant differences in their modification rates across cell types. Together, we show that RNA modifications can be identified from direct RNA-sequencing with high accuracy, enabling the analysis of differential modifications and expression from a single high throughput experiment. AvailabilityxPore is available as open source software (https://github.com/GoekeLab/xpore)

bioinformatics↗

bioRxiv2019

Recent evolutionary history of tigers highlights contrasting roles of genetic drift and selection

Formulating strategies for species conservation requires knowledge of evolutionary and genetic history. Tigers are among the most charismatic of endangered species and garner significant conservation attention. However, the evolutionary history and genomic variation of tigers remain poorly known. With 70% of the worlds wild tigers living in India, such knowledge is critical for tiger conservation. We re-sequenced 65 individual tiger genomes across their extant geographic range, representing most extant subspecies with a specific focus on tigers from India. As suggested by earlier studies, we found strong genetic differentiation between the putative tiger subspecies. Despite high total genomic diversity in India, individual tigers host longer runs of homozygosity, potentially suggesting recent inbreeding, possibly because of small and fragmented protected areas. Surprisingly, demographic models suggest recent divergence (within the last 10,000 years) between populations, and strong population bottlenecks. Amur tiger genomes revealed the strongest signals of selection mainly related to metabolic adaptation to cold, while Sumatran tigers show evidence of evolving under weak selection for genes involved in body size regulation. Depending on conservation objectives, our results support the isolation of Amur and Sumatran tigers, while geneflow between Malayan and South Asian tigers may be considered. Further, the impacts of ongoing connectivity loss on the health and persistence of tigers in India should be closely monitored.

genomics↗

bioRxiv2019

NanoVar: Accurate Characterization of Patients’ Genomic Structural Variants Using Low-Depth Nanopore Sequencing

Despite the increasing relevance of structural variants (SV) in the development of many human diseases, progress in novel pathological SV discovery remains impeded, partly due to the challenges of accurate and routine SV characterization in patients. The recent advent of third-generation sequencing (3GS) technologies brings promise for better characterization of genomic aberrations by virtue of having longer reads. However, the applications of 3GS are restricted by their high sequencing error rates and low sequencing throughput. To overcome these limitations, we present NanoVar, an accurate, rapid and low-depth (4X) 3GS SV caller utilizing long-reads generated by Oxford Nanopore Technologies. NanoVar employs split-reads and hard-clipped reads for SV detection and utilizes a neural network classifier for true SV enrichment. In simulated data, NanoVar demonstrated the highest SV detection accuracy (F1 score = 0.91) amongst other long-read SV callers using 12 gigabases (4X) of sequencing data. In patient samples, besides the detection of genomic aberrations, NanoVar also uncovered many normal alternative sequences or alleles which were present in healthy individuals. The low sequencing depth requirements of NanoVar enable the use of Nanopore sequencing for accurate SV characterization at a lower sequencing cost, an approach compatible with clinical studies and large-scale SV-association research.

bioinformatics↗