Biology subjects

Lajoie, B.

Publications and source records attributed to Lajoie, B..

8 recordsLinked to original sources

bioRxiv2025

Direct In-Sample Sequencing of the 3' Transcriptome Expands the Capabilities of Optical Pooled Screens

We present a platform that directly sequences single guide RNAs and endogenous 3'UTRs in fixed cells while simultaneously measuring protein abundance and cellular morphology. We demonstrate platform capability by performing optical pooled screening of CRISPR-perturbed lung cancer cells. This approach unites direct in-sample RNA sequencing with complementary phenotypic readouts, enabling comprehensive, scalable, and functional genomics analyses within a single experiment.

genomics↗

bioRxiv2025

A simplified hybrid capture approach retains high specificity and enables PCR-free workflow

Hybrid capture is a critical technology for selective enrichment of genomic regions of interest, enabling cost-effective focused sequencing in both clinical and research applications. We present a simplified hybrid capture approach that eliminates complexities typically associated with hybridization-based selection methods by directly loading the hybridization product onto the sequencing flow cell. The workflow removes bead-based steps, washes, and post-hybridization PCR, while retaining high capture specificity and library complexity. The approach is enabled by the development of a streptavidin flow cell surface, a method to circularize and amplify captured targets on the flow cell, and a fast hybridization protocol. We demonstrate application across targeted panel sizes and improvements to library complexity and variant calling. We also show how the approach can be used to create an entirely PCR-free targeted sequencing workflow that further improves variant calling and enables the detection of repeat expansions.

genomics↗

bioRxiv2024

A robust benchmark for detecting low-frequency variants in the HG002 Genome In A Bottle NIST reference material.

Somatic mosaicism is an important cause of disease, but mosaic and somatic variants are often challenging to detect because they exist in only a fraction of cells. To address the need for benchmarking subclonal variants in normal cell populations, we developed a benchmark containing mosaic variants in the Genome in a Bottle Consortium (GIAB) HG002 reference material DNA from a large batch of a normal lymphoblastoid cell line. First, we used a somatic variant caller with high coverage (300x) Illumina whole genome sequencing data from the Ashkenazi Jewish trio to detect variants in HG002 not detected in at least 5% of cells from the combined parental data. These candidate mosaic variants were subsequently evaluated using >100x BGI, Element, and PacBio HiFi data. High confidence candidate SNVs with variant allele fractions above 5% were included in the HG002 draft mosaic variant benchmark, with 13/85 occurring in medically relevant gene regions. We also delineated a 2.45 Gbp subset of the previously defined germline autosomal benchmark regions for HG002 in which no additional mosaic variants >2% exist, enabling robust assessment of false positives. The variant allele fraction of some mosaic variants is different between batches of cells, so using data from the homogeneous batch of reference material DNA is critical for benchmarking these variants. External validation of this mosaic benchmark showed it can be used to reliably identify both false negatives and false positives for a variety of technologies and detection algorithms, demonstrating its utility for optimization and validation. By adding our characterization of mosaic variants in this widely-used cell line, we support extensive benchmarking efforts using it in simulation, spike-in, and mixture studies.

bioinformatics↗

bioRxiv2024

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair for somatic benchmarks

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

genomics↗

bioRxiv2023

Enhancer-driven local 3D chromatin domain folding modulates transcription in human mammary tumor cells

The genome is organized in functional compartments and structural domains at the sub-megabase scale. How within these domains interactions between numerous cis-acting enhancers and promoters regulate transcription remains an open question. Here, we determined chromatin folding and composition over several hundred kb around estrogen responsive genes in human breast cancer cell lines following hormone stimulation. Modeling of 5C data at 1.8 kb resolution was combined with quantitative 3D analysis of multicolor FISH measurements at 100 nm resolution and integrated with ChIP-seq data on transcription factor binding and histone modifications. We found that rapid estradiol induction of the progesterone gene (PGR) expression occurs in the context of pre-existing, cell type specific chromosomal architectures encompassing the 90 kb PGR coding region and an enhancer-spiked 5 300 kb upstream genomic region. In response to estradiol, interactions between estrogen-receptor (ER) bound regulatory elements are re-enforced. While initial enhancer - gene contacts coincide with RNA Pol 2 binding and transcription initiation, sustained hormone stimulation promotes ER accumulation creating a regulatory hub stimulating transcript synthesis. In addition to implications for estrogen receptor signaling, we uncover that preestablished chromatin architectures efficiently regulate gene expression upon stimulation without the need for de-novo extensive rewiring of long-range chromatin interactions.

cell biology↗

bioRxiv2019

ExpansionHunter Denovo: A computational method for locating known and novel repeat expansions in short-read sequencing data

Expansions of short tandem repeats are responsible for over 40 monogenic disorders, and undoubtedly many more pathogenic repeat expansions (REs) remain to be discovered. Existing methods for detecting REs in short-read sequencing data require predefined repeat catalogs. However recent discoveries have emphasized the need for detection methods that do not require candidate repeats to be specified in advance. To address this need, we introduce ExpansionHunter Denovo, an efficient catalog-free method for genome-wide detection of REs. Analysis of real and simulated data shows that our method can identify large expansions of 41 out of 44 pathogenic repeats, including nine recently reported non-reference REs not discoverable via existing methods. ExpansionHunter Denovo is freely available at https://github.com/Illumina/ExpansionHunterDenovo

bioinformatics↗

bioRxiv2019

ExpansionHunter: A sequence-graph based tool to analyze variation in short tandem repeat regions

We describe a novel computational method for genotyping repeats using sequence graphs. This method addresses the long-standing need to accurately genotype medically important loci containing repeats adjacent to other variants or imperfect DNA repeats such as polyalanine repeats. Here we introduce a new version of our repeat genotyping software, ExpansionHunter, that uses this method to perform targeted genotyping of a broad class of such loci.\n\nAvailability and implementationExpansionHunter is implemented in C++ and is available under the Apache License Version 2.0. The source code, documentation, and Linux/macOS binaries are available at https://github.com/Illumina/ExpansionHunter/.\n\nContactmeberle@illumina.com

bioinformatics↗

bioRxiv2018

Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease

PurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.\n\nMethodsUsing a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.\n\nResultsWe found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing of de-novo CNVs.\n\nConclusionRobust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.

genomics↗