Skip to main content
construction release_alert
Scholars@Duke will be undergoing maintenance April 11-15. Some features may be unavailable during this time.
cancel

High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE.

Publication ,  Journal Article
Majoros, WH; Campbell, MS; Holt, C; DeNardo, EK; Ware, D; Allen, AS; Yandell, M; Reddy, TE
Published in: Bioinformatics
May 15, 2017

MOTIVATION: The accurate interpretation of genetic variants is critical for characterizing genotype-phenotype associations. Because the effects of genetic variants can depend strongly on their local genomic context, accurate genome annotations are essential. Furthermore, as some variants have the potential to disrupt or alter gene structure, variant interpretation efforts stand to gain from the use of individualized annotations that account for differences in gene structure between individuals or strains. RESULTS: We describe a suite of software tools for identifying possible functional changes in gene structure that may result from sequence variants. ACE ('Assessing Changes to Exons') converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detects gene-structure changes and their possible repercussions, and identifies several classes of possible loss of function. Novel transcripts predicted by ACE are commonly supported by spliced RNA-seq reads, and can be used to improve read alignment and transcript quantification when an individual-specific genome sequence is available. Using publicly available RNA-seq data, we show that ACE predictions confirm earlier results regarding the quantitative effects of nonsense-mediated decay, and we show that predicted loss-of-function events are highly concordant with patterns of intolerance to mutations across the human population. ACE can be readily applied to diverse species including animals and plants, making it a broadly useful tool for use in eukaryotic population-based resequencing projects, particularly for assessing the joint impact of all variants at a locus. AVAILABILITY AND IMPLEMENTATION: ACE is written in open-source C ++ and Perl and is available from geneprediction.org/ACE. CONTACT: myandell@genetics.utah.edu or tim.reddy@duke.edu. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Bioinformatics

DOI

EISSN

1367-4811

Publication Date

May 15, 2017

Volume

33

Issue

10

Start / End Page

1437 / 1446

Location

England

Related Subject Headings

  • Software
  • Sequence Analysis, RNA
  • RNA Splicing
  • Polymorphism, Genetic
  • Mutation
  • Humans
  • Haplotypes
  • Genomics
  • Exons
  • Eukaryota
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Majoros, W. H., Campbell, M. S., Holt, C., DeNardo, E. K., Ware, D., Allen, A. S., … Reddy, T. E. (2017). High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE. Bioinformatics, 33(10), 1437–1446. https://doi.org/10.1093/bioinformatics/btw799
Majoros, William H., Michael S. Campbell, Carson Holt, Erin K. DeNardo, Doreen Ware, Andrew S. Allen, Mark Yandell, and Timothy E. Reddy. “High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE.Bioinformatics 33, no. 10 (May 15, 2017): 1437–46. https://doi.org/10.1093/bioinformatics/btw799.
Majoros WH, Campbell MS, Holt C, DeNardo EK, Ware D, Allen AS, et al. High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE. Bioinformatics. 2017 May 15;33(10):1437–46.
Majoros, William H., et al. “High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE.Bioinformatics, vol. 33, no. 10, May 2017, pp. 1437–46. Pubmed, doi:10.1093/bioinformatics/btw799.
Majoros WH, Campbell MS, Holt C, DeNardo EK, Ware D, Allen AS, Yandell M, Reddy TE. High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE. Bioinformatics. 2017 May 15;33(10):1437–1446.

Published In

Bioinformatics

DOI

EISSN

1367-4811

Publication Date

May 15, 2017

Volume

33

Issue

10

Start / End Page

1437 / 1446

Location

England

Related Subject Headings

  • Software
  • Sequence Analysis, RNA
  • RNA Splicing
  • Polymorphism, Genetic
  • Mutation
  • Humans
  • Haplotypes
  • Genomics
  • Exons
  • Eukaryota