Biology subjects

Rechavi, G.

Publications and source records attributed to Rechavi, G..

4 recordsLinked to original sources

bioRxiv2026

DNT: Diploid Genomic Foundation Model

Clinical interpretation of genetic variation depends on the diploid genotype, including zygosity, allele dosage and whether multiple variants occur in cis on the same homologue or in trans on different homologues. Most genomic language models process haploid sequences or combine independently encoded haplotypes downstream, so they do not directly represent the paired genotype in a single sequence. We introduce a reference-aligned diploid encoding for single-nucleotide variants (SNVs) and short insertions and deletions (indels), together with unphased and phase-retaining tokenizers that accept phased genotypes and convert them to single-sequence diploid representation. Using Nucleotide Transformer v3 backbones, we continue training 8-million- and 100-million-parameter models and evaluate an auxiliary Contrastive Phase Loss (CPL) designed to retain the phasing information of the variants in contextual representations. We evaluate on a novel compound-heterozygous benchmark containing 9,460 examples. Models whose inputs did not distinguish relative phase remained near chance, whereas our diploidic models improved discrimination with AUROC 0.649, compared to 0.506 for the vocabulary-adapted control. These findings establish a method for making diploid genotype information accessible to genomic language models, rather than a universal improvement in variant prediction; validation in naturally observed, accurately phased clinical cohorts remains necessary.

bioinformatics↗

bioRxiv2026

GFMBench-API: A Standardized Interface for Benchmarking Genomic Foundation Models

The rapid scaling of Genomic Foundation Models (GFMs) has created a critical need for standardized evaluation frameworks. Current benchmarking practices are often fragmented, relying on model-specific preprocessing and inconsistent metric implementations that hinder reproducible comparisons. We present GFMBench-API, a high-level Python interface designed to unify the evaluation lifecycle of GFMs. GFMBench-API provides a modular "middleware" architecture that decouples model-specific tokenization and embedding logic from task-specific data streams and performance metrics. By standardizing the input/output schemas for common genomic tasks, such as regulatory element prediction, variant effect scoring, and long-range interaction mapping, GFMBench-API enables researchers to integrate new models or tasks with minimal "glue code." Our interface ensures mathematical consistency across evaluations, providing a robust foundation for the transparent and systematic benchmarking of GFMs.

genomics↗

bioRxiv2025

i6A-seq maps N6-isopentenyladenosine and uncovers its role as a regulator of mRNA stability through recruitment of DIS3L2

Dynamic post-transcriptional RNA modifications are crucial regulators of RNA metabolism and cell fate. Recent advances in sequencing, combined with antibody, enzymatic, or chemical approaches, have enabled transcriptome-wide mapping of these modifications. While prevalent in tRNAs and rRNAs, a growing number of modifications also adorn lower-abundance mRNA transcripts. Global mapping efforts, particularly for N6-methyladenosine (m6A), uncovered the affected mechanisms governing RNA metabolism, shedding light on novel, modification-dependent, modes of gene regulation. N6-isopentenyladenosine (i6A) is a conserved tRNA modification involved in translation fidelity and efficiency. i6A depletion is linked to mitochondrial defects and human diseases. Current i6A detection methods are low-throughput, and its lack of base-pairing effects makes sequencing-based identification challenging. Here we developed a novel and robust mapping technique, i6A-seq, a method that utilizes antibody-mediated enrichment and iodine chemical labeling to generate a reverse transcription signature, enabling transcriptome-wide i6A detection. Our global mapping revealed hundreds of i6A sites in human and mouse mRNA, indicating its presence in this RNA species, with conserved isopentenylome features. These sites exhibit a typical consensus sequence, primarily in coding transcripts (CDS), preferentially within lysine codons. Consistent with its role in tRNA, tRNA-isopentenyltransferase (TRIT1) also appears to install i6A in mRNA. Manipulation of TRIT1 revealed that i6A regulates the expression of a subset of genes through mRNA decay, specifically those isopentenylated at the CDS and translated on ER-bound ribosomes. Importantly, DIS3 like 3-5 exoribonuclease 2 (DIS3L2), an RNA exoribonuclease known to regulate ER-translated mRNA, was identified as the first i6A reader protein. Our findings introduce i6A as a new modified nucleotide that decorates mRNA, allowing us to decipher its regulatory roles in gene expression. This study not only establishes the presence and location of i6A in mRNA, but also uncovers its first functional mechanism. Similar to the knowledge accumulated on m6A, this work paves the way for further discoveries with potential relevance for understanding gene regulation, disease diagnosis, and therapy.

molecular biology↗

bioRxiv2020

Transcriptomic profiling of human corona virus (HCoV)-229E -infected human cells and genomic mutational analysis of HCoV-229E and SARS-CoV-2

Human coronaviruses (HCoVs) cause mild to severe respiratory infection. Most of the common cold illnesses are caused by one of four HCoVs, namely HCoV-229E, HCoV-NL63, HCoV-HKU1 and HCoV-OC43. Several studies have applied global transcriptomic methods to understand host responses to HCoV infection, with most studies focusing on the pandemic severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV) and the newly emerging SARS-CoV-2. In this study, Next Generation Sequencing was used to gain new insights into cellular transcriptomic changes elicited by alphacoronavirus HCoV-229E. HCoV-229E-infected MRC5 cells showed marked downregulation of superpathway of cholesterol biosynthesis and eIF2 signaling pathways. Moreover, upregulation of cyclins, cell cycle control of chromosomal replication, and the role of BRCA1 in DNA damage response, alongside downregulation of the cell cycle G1/S checkpoint, suggest that HCoV-229E favors S phase for viral infection. Intriguingly, a significant portion of key factors of cell innate immunity, interferon-stimulated genes (ISGs) and other transcripts of early antiviral response genes were downregulated early in HCoV-229E infection. On the other hand, early upregulation of the antiviral response factor Apolipoprotein B mRNA editing enzyme catalytic subunit 3B (APOBEC3B) was observed. APOBEC3B cytidine deaminase signature (C-to-T) was previously observed in genomic analysis of SARS-CoV-2 but not HCoV-229E. Higher levels of C-to-T mutations were found in countries with high mortality rates caused by SARS-CoV-2. APOBEC activity could be a marker for new emerging CoVs. This study will enhance our understanding of commonly circulating HCoVs and hopefully provide critical information about still-emerging coronaviruses. Author summaryHuman coronaviruses (HCoVs) generate respiratory tract infections. HCoV-229E is one of four known HCoV strains that circulate annually in the population for several decades. Beside these, three pandemic CoV emerged since year 2002, the Severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and SARS-CoV-2. These three strains attracted most attention for extensive research and less consideration has been given to the commonly infecting HCoVs. In this study we use Next generation sequencing analysis to understand global transcriptomic changes in human host cells following HCoV-229E infection. We found several cellular pathways that change during infection that involve cholesterol biosynthesis, cell cycle control, DNA replication, DNA repair, innate immune response and an interesting RNA editing enzyme which could be involve in CoVs pathogenesis.

microbiology↗