Search

Most protein coding genes generate multiple RNA transcripts through alternative splicing, variable 3' and 5'UTRs, and RNA editing. Although drug design typically targets the main transcript, alternative transcripts can have profound physiological effects, encoding proteins with distinct functions or regulatory properties. Formation of these alternative transcripts is tissue-selective and context-dependent, creating opportunities for more effective and targeted therapies with reduced adverse effects. Moreover, genetic variation can tilt the balance of alternative versus constitutive transcripts or generate aberrant transcripts that contribute to disease risk. In addition, environmental factors and drugs modulate RNA splicing, affording new opportunities for the treatment of splicing disorders. For example, therapies targeting specific mRNA transcripts with splice-site-directed oligonucleotides that correct aberrant splicing are already in clinical trials for genetic disorders such as Duchenne muscular dystrophy. High-throughput sequencing technologies facilitate discovery of novel RNA transcripts and protein isoforms, applications ranging from neuromuscular disorders to cancer. Consideration of a gene's transcript diversity should become an integral part of drug design, development, and therapy.

Abstract: Background: Multiple variants in SNCA, encoding alpha‐synuclein, a main component of Lewy bodies, are implicated in Parkinson's disease. Methods: We searched for cis‐acting SNCA variants using allelic mRNA ratios in human brain tissues. In a SNCA 3′UTR (2,520 bp) luciferase reporter gene assay, translation in SH‐SY5Y cells in the presence of the rs17016074 G/A alleles was measured. To assess clinical impact, we queried neurocognitive genome‐wide association studies. Results: Allelic ratios deviated up to twofold, measured at a marker SNP in the middle of a long 3′ untranslated region (3′UTR), but not at a marker at its start, suggesting regulation of 3′UTR processing. 3′UTR SNP rs17016074 G/A, minor allele frequency (MAF) <1% in Caucasians, 13% in Africans, strongly associates with large allelic mRNA expression imbalance (AEI), resulting in reduced expression of long 3′UTR isoforms. A second 3′UTR SNP (rs356165) associates with moderate AEI and enhances SNCA mRNA expression. The rs17016074 A allele reduces overall 3′UTR expression in luciferase reporter gene assays but supports more efficient translation, resolving previous contradictory results. We failed to detect significant genome‐wide associations for rs17016074, possibly a result of low MAF in Caucasians or its absence from most genotyping panels. In the “Genome Wide Association Study of Yoruba in Nigeria,” rs356165 was associated with reduced memory performance. Conclusions: Here, we identify two cis‐acting regulatory variants affecting SNCA mRNA expression, measured by allelic ratios in the 3′UTR. The rs17016074 minor A allele is associated with higher expression of luciferase protein activity. Resolving the genetic influence of SNCA polymorphisms requires study of the interactions between multiple regulatory variants with distinct frequencies among populations. [ABSTRACT FROM AUTHOR]

ABSTRACT Functionally related genes often cluster into a genome region under coordinated regulation, forming a local regulome. To understand regulation of the CHRNA5/CHRNA3/CHRNB4 nicotinic receptor gene cluster, we integrate large-scale RNA expression data (brain and peripheral) from GTEx (Genotype Tissue Expression), clinical associations (GRASP), and linkage disequilibrium data (1000 Genomes) to find candidate SNPs representing independent regulatory variants. CHRNA3, CHRNA5, CHRNB4 mRNAs, and a well-expressed CHRNA5 antisense RNA (RP11-650L12.2) are co-expressed in many human tissues, suggesting common regulatory elements. The CHRNA5 enhancer haplotype tagged by rs880395 not only increases CHRNA5 mRNA expression in all tissues, but also enhances RP11-650L12.2 and CHRNA3 expression, suggesting DNA looping to multiple promoters. However, in nucleus accumbens and putamen, but not other brain regions, CHRNA3 expression associates uniquely with a haplotype tagged by rs1948 (located in the CHRNB4 3′UTR). Haplotype/diplotype analysis of rs880395 and rs1948 plus rs16969968 (a nonsynonymous CHRNA5 risk variant) in GWAS (COGEND, UW-TTURC, SAGE) yields a nicotine dependence risk profile only partially captured by rs16969968 alone. An example of local gene clusters, this nicotinic regulome is controlled by complex genetic variation, with broad implications for interpreting GWAS. [ABSTRACT FROM AUTHOR]