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Updated: Jan 10, 2026

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets
Published on: July 7, 2010
Integrating whole genome and transcriptome sequencing to characterize the genetic architecture of isoform variation
Chunyu Liu1,2, Roby Joehanes3, Jiantao Ma4
1Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA. liuc@bu.edu.
Abstract:
We present a whole-blood isoform ratio QTL (irQTL) resource by analyzing genome-wide isoform-to-gene expression ratios using sequencing data. In Framingham Heart Study (FHS, n = 2622) discovery, we identify over 1.1 million cis-irQTLs (minor allele frequency [MAF] ≥ 0.01, ±1 Mb of 10,883 isoform transcripts, P < 5 × 10-8) across 4,971 genes. Among 11,425 sentinel cis-irQTLs, 72% replicate (P < 1 × 10-4) in the Women's Health Initiative (WHI; n = 2005). Notably, 20% of cis-irQTLs have no significant association with overall gene expression, indicating isoform-specific regulation. These variants are enriched at splice donor/acceptor sites and genome-wide association study loci (P < 1 × 10-10). We also identify 1870 sentinel trans-irQTLs (MAF ≥ 0.01, P < 1.5 × 10-13) for 1,084 isoforms across 590 genes, and 2327 rare cis-irQTLs (0.003 < MAF < 0.01) for 2467 isoforms of 1428 genes in FHS, with external replication rates of 61% and 41% in WHI, respectively. We highlight rs12898397 in ULK3, which alters splice site usage and reduces expression of a full-length isoform. Mendelian randomization supports a causal role between this isoform shift and reduced diastolic blood pressure. These findings highlight the power of irQTL mapping to uncover transcript-specific regulatory mechanisms underlying complex traits.
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