Biology subjects

Ibn-Salem, J.

Publications and source records attributed to Ibn-Salem, J..

5 recordsLinked to original sources

bioRxiv2026

Computing tumor specificity of cancer antigen targets by k-mer indexing of healthy tissue transcriptomes

Individualized cancer immunotherapies rely on tumor-specific T-cell antigens, often predicted from somatic mutations as neoantigens. For tumors with low mutational burden, mRNA transcript variants, including gene fusions and novel splice junctions, can serve as important alternative targets. A main challenge in their identification from tumor RNA-seq is to confirm that their expression is tumor-restricted. Although large public collections of healthy-tissue RNA-seq exist, verifying tumor-specific expression requires computationally expensive re-analysis of these data for every novel candidate. To address this, we benchmarked nine k-mer indexing algorithms and developed k4neo, which leverages k-mer indexing of raw RNA-seq reads to compute the tumor specificity of any transcript variant. This mapping-free and transcript-class agnostic approach screens any candidate sequence against 18,960 samples across 51 healthy tissue types. We confirmed k4neos detection accuracy with qRT-PCR and showed that k4neo accurately classifies somatic and germline variants, gene fusions, and isoforms by tumor specificity. Applied to nine tumor cohorts, it nominated a median of 4-80 tumor-specific splice junctions per patient, including recurrent, long-read-confirmed novel antigen candidates. Together, k4neo enables efficient access to large-scale sequencing cohorts and accurately computes tumor specificity for any input transcript sequence, thereby expanding the repertoire of individual and shared cancer antigen targets.

bioinformatics↗

bioRxiv2023

Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates

Splicing is dysregulated in many tumors and may result in tumor-specific transcripts that can encode neoantigens, which are promising targets for cancer immunotherapy. Detecting tumor-specific splicing is challenging because many non-canonical splice junctions identified in tumor transcriptomes also appear in healthy tissues. Here, we developed splice2neo to integrate the predicted splice effects from somatic mutations with splice junctions detected in tumor RNA-seq for individual cancer patients. Splice2neo excludes splice junctions from healthy tissue samples, annotates resulting transcript and peptide sequences, and provides targeted re-quantification of supporting RNA-seq reads. We developed a stringent detection rule to predict splice junctions as mutation-derived targets and identified 1.7 target splice junctions per tumor with a false discovery rate below 5% in a melanoma cohort. We confirmed tumor-specificity using independent, healthy tissue samples. Furthermore, using tumor-derived RNA, we confirmed individual exon skipping events experimentally. Most target splice junctions encoded neoepitope candidates with predicted MHC-I or MHC-II binding. Compared to neoepitope candidates derived from non-synonymous point mutations, the splicing-derived MHC-I neoepitope candidates had a lower self-similarity to corresponding wild-type peptides. In conclusion, we demonstrate that identifying mutation-derived and tumor-specific splice junctions can lead to additional neoantigen candidates to expand the target repertoire for cancer immunotherapies. Key PointsO_LIsplice2neo is a versatile tool for identifying and analyzing of splice junctions as a source of neoantigen candidates C_LIO_LIWe identified mutation-retrieved splice junctions supported by RNA-seq in melanoma samples C_LIO_LIThe predicted target splice junctions exhibited a strong tumor-specificity as they were absent in healthy tissues. C_LIO_LITarget splice junctions often lead to frame-shift peptides and encode promising neoantigen candidates C_LI

bioinformatics↗

bioRxiv2019

The Developmental Transcriptome for Lytechinus variegatus Exhibits Temporally Punctuated Gene Expression Changes

Embryonic development is arguably the most complex process an organism undergoes during its lifetime, and understanding this complexity is best approached with a systems-level perspective. The sea urchin has become a highly valuable model organism for understanding developmental specification, morphogenesis, and evolution. As a non-chordate deuterostome, the sea urchin occupies an important evolutionary niche between protostomes and vertebrates. Lytechinus variegatus (Lv) is an Atlantic species that has been well studied, and which has provided important insights into signal transduction, patterning, and morphogenetic changes during embryonic and larval development. The Pacific species, Strongylocentrotus purpuratus (Sp), is another well-studied sea urchin, particularly for gene regulatory networks (GRNs) and cis-regulatory analyses. A well-annotated genome and transcriptome for Sp are available, but similar resources have not been developed for Lv. Here, we provide an analysis of the Lv transcriptome at 11 timepoints during embryonic and larval development. The data indicate that the gene regulatory networks that underlie specification are well-conserved among sea urchin species. We show that the major transitions in variation of embryonic transcription divide the developmental time series into four distinct, temporally sequential phases. Our work shows that sea urchin development occurs via sequential intervals of relatively stable gene expression states that are punctuated by abrupt transitions.

developmental biology↗

bioRxiv2018

Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs

BackgroundKnowledge of the three-dimensional structure of the genome is necessary to understand how gene expression is regulated. Recent experimental techniques such as Hi-C or ChIA-PET measure long-range interactions genome-wide but are experimentally elaborate and have limited resolution. Here, we present Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs (7C).\n\nResultsWhile ChIP-seq was not designed to detect contacts, the formaldehyde treatment in the ChIP-seq protocol cross-links proteins with each other and with DNA. Consequently, also regions that are not directly bound by the targeted TF but interact with the binding site via chromatin looping are co-immunoprecipitated and sequenced. This produces minor ChIP-seq signals at loop anchor regions close to the directly bound site. We use the position and shape of ChIP-seq signals around CTCF motif pairs to predict whether they interact or not.\n\nWe applied 7C to all CTCF motif pairs within 1 MB in the human genome and validated predicted interactions with high-resolution Hi-C and ChIA-PET. A single ChIP-seq experiment from known architectural proteins (CTCF, Rad21, Znf143) but also from other TFs (like TRIM22 or RUNX3) predicts loops accurately. Importantly, 7C predicts loops in cell types and for TF ChIP-seq datasets not used in training.\n\nConclusion7C predicts chromatin loops with base-pair resolution and can be used to associate TF binding sites to regulated genes in a condition-specific manner. Furthermore, profiling of hundreds of ChIP-seq datasets results in novel candidate factors functionally involved in chromatin looping. Our method is available as an R package: https://ibn-salem.github.io/sevenC/

genomics↗

bioRxiv2017

Evolutionary stability of topologically associating domains is associated with conserved gene regulation

BackgroundThe human genome is highly organized in the three-dimensional nucleus. Chromosomes fold locally into topologically associating domains (TADs) defined by increased intra-domain chromatin contacts. TADs contribute to gene regulation by restricting chromatin interactions of regulatory sequences, such as enhancers, with their target genes. Disruption of TADs can result in altered gene expression and is associated to genetic diseases and cancers. However, it is not clear to which extent TAD regions are conserved in evolution and whether disruption of TADs by evolutionary rearrangements can alter gene expression.\n\nResultsHere, we hypothesize that TADs represent essential functional units of genomes, which are selected against rearrangements during evolution. We investigate this using whole-genome alignments to identify evolutionary rearrangement breakpoints of different vertebrate species. Rearrangement breakpoints are strongly enriched at TAD boundaries and depleted within TADs across species. Furthermore, using gene expression data across many tissues in mouse and human, we show that genes within TADs have more conserved expression patterns. Disruption of TADs by evolutionary rearrangements is associated with changes in gene expression profiles, consistent with a functional role of TADs in gene expression regulation.\n\nConclusionsTogether, these results indicate that TADs are conserved building blocks of genomes with regulatory functions that are often reshuffled as a whole instead of being disrupted by rearrangements.

genomics↗