Pejman Mohammadi

This paper expands the RatGTEx resource with transcriptome-wide associations across 3,160 RNA-seq samples, identifying 7,473 gene-trait links and 144,876 QTLs for 22,599 genes.

The paper identifies genetic factors associated with balance in the elderly through GWAS and multimodal transcriptomic analysis of otolithic organs.

LaDDR improves xQTL and GWAS discovery by generating latent RNA phenotypes without requiring complete gene annotations, outperforming existing knowledge-driven methods in multiple tissues.

This study benchmarks RNA-seq tools for diagnostic applications, finding they identify 28 diagnoses from 68 samples but only 9 out of 74 undiagnosed cases.

ANEVA-h improves detection of rare regulatory variants by analyzing haplotype-level ASE data, increasing testable genes and reducing false positives in GTEx and clinical cohorts.

This paper recalibrates differential gene expression by genetic dosage variance to prioritize functionally relevant genes, showing enrichment in metabolic and regulatory pathways.

aseQC identifies low-quality samples in transcriptome data by quantifying allele-specific expression variation, improving rare variant interpretation.

The paper introduces Pantry, a framework for generating diverse RNA phenotypes from RNA-seq data and integrating them with genetic data, leading to increased gene-trait association discoveries.

The paper introduces SuShiE, a model that improves multi-ancestry fine-mapping of cis-molQTLs, identifying more genes and prioritizing functionally enriched variants.

The paper presents an improved rat reference genome, mRatBN7.2, which enhances genomic, transcriptomic, and proteomics data mapping and identifies millions of genetic variations across rat strains.

The paper introduces aFC-n, a method to improve eQTL effect size estimation and gene expression prediction, revealing significant residual allelic imbalance in many genes.

This study shows that common splice-regulatory variants can reduce the pathogenicity of rare exonic variants by modulating mRNA splicing.

This study performs a GWAS in HS rats to identify genetic loci associated with intraocular pressure, finding three genome-wide significant loci and five candidate genes, including novel ones.

The paper simulates GWAS in rats to show that larger sample sizes lead to an exponential increase in the number of significant loci detected.

The paper identifies cis-QTLs and eQTLs in HS rats across five brain regions, finds colocalization with human GWAS results, and shows higher eQTL density compared to human data.

The paper identifies cell type-specific gene regulatory changes in the amygdala of rats with varying cocaine addiction-like behaviors, linking them to energy metabolism, GABAergic inhibition, and chromatin accessibility.

The paper uses long-read RNA-seq data to identify new transcripts and develop a tool to analyze genetic effects on transcript structure, revealing insights into splicing regulation and variant interpretation.

The paper identifies gene expression patterns in the hippocampus of rats that predict internalizing and externalizing behaviors, linking them to genetic variation and biological processes.

The paper identifies 6,262 TF-eQTL interactions across 1,598 genes using GTEx data, linking genetic variants to transcription factor regulation and GWAS loci.

Genome-wide association study and integrative analyses identify 27 genes in inflammation and coagulation pathways linked to COVID-19 hospitalization risk and symptomology.

The paper presents a large ASE resource from GTEx v8 with 431 million SNP-level and 153 million haplotype-level measurements, and extends phASER to estimate cis regulatory variant effect sizes.

The paper uses bulk RNA-seq data to estimate cell type abundances and identifies cell type interaction QTLs that provide finer resolution of tissue specificity than bulk cis-eQTLs.

The paper examines telomere length variation across 6,391 tissue samples from 952 individuals, showing tissue-specific differences, positive correlations between tissues, and associations with age and ancestry.

Integrating expression, allelic expression and splicing across tissues identifies rare variants with relevance to traits.

The paper quantifies protein levels across 32 human tissues and compares them to transcriptome data, revealing insights into post-transcriptional regulation and disease mechanisms.

EdiTyper analyzes targeted sequencing data from genome editing experiments to detect mutations and indels with high accuracy and scalability.

This study identifies a genetic variant near CXCL12 associated with increased susceptibility to HIV-related non-Hodgkin lymphoma.

ANEVA quantifies genetic regulatory variation using allelic expression data, improving transcriptome analysis and aiding in rare disease diagnosis.

GTEx v8 maps expression and splicing QTLs in 49 tissues from 838 donors: cis-eQTLs cover 94.7% of protein-coding genes, and cross-tissue QTL sharing mirrors cell-type composition.

The paper shows that cis-regulatory variation modifies the penetrance of coding variants, affecting disease risk in cancer and autism, and demonstrates this through experimental validation.