BYASE: a Python library for estimating gene and isoform level allele-specific expression

Abstract Summary Allele-specific expression (ASE) is involved in many important biological mechanisms. We present a python package BYASE and its graphical user interface (GUI) tool BYASE-GUI for the identification of ASE from single-end and paired-end RNA-seq data based on Bayesian inference, which can simultaneously report differences in gene-level and isoform-level expression. BYASE uses both phased SNPs and non-phased SNPs, and supports polyploid organisms. Availability and implementation The source codes of BYASE and BYASE-GUI are freely available at https://github.com/ncjllld/byase and https://github.com/ncjllld/byase_gui. Supplementary information Supplementary data are available at Bioinformatics online.

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ASEP: gene-based detection of allele-specific expression in a population by RNA-seq

10.1101/798124 ◽

2019 ◽

Author(s):

Jiaxin Fan ◽

Jian Hu ◽

Chenyi Xue ◽

Hanrui Zhang ◽

Muredach P. Reilly ◽

...

Keyword(s):

Association Studies ◽

Genome Wide Association Studies ◽

Rna Seq ◽

Specific Expression ◽

Allele Specific Expression ◽

Wide Range ◽

Gene Level ◽

Shared Information ◽

Allele Specific ◽

Regulated Gene Expression

ABSTRACTAllele-specific expression (ASE) analysis, which quantifies the relative expression of two alleles in a diploid individual, is a powerful tool for identifying cis-regulated gene expression variations that underlie phenotypic differences among individuals. Existing methods for gene-level ASE detection analyze one individual at a time, therefore wasting shared information across individuals. Failure to accommodate such shared information not only loses power, but also makes it difficult to interpret results across individuals. However, ASE detection across individuals is challenging because the data often include individuals that are either heterozygous or homozygous for the unobserved cis-regulatory SNP, leading to heterogeneity in ASE as only those heterozygous individuals are informative for ASE, whereas those homozygous individuals have balanced expression. To simultaneously model multi-individual information and account for such heterogeneity, we developed ASEP, a mixture model with subject-specific random effect accounting for multi-SNP correlations within the same gene. ASEP is able to detect gene-level ASE under one condition and differential ASE between two conditions (e.g., pre-versus post-treatment). Extensive simulations have demonstrated the convincing performance of ASEP under a wide range of scenarios. We further applied ASEP to RNA-seq data of human macrophages, and identified genes showing evidence of differential ASE pre-versus post-stimulation, which were extended through findings in cardiometabolic trait-relevant genome-wide association studies. To the best of our knowledge, ASEP is the first method for gene-level ASE detection at the population level. With the growing adoption of RNA-seq, we believe ASEP will be well-suited for various ASE studies for human diseases.

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Allele Specific Expression (ASE) analysis between Bos Taurus and Bos Indicus cows using RNA-Seq data at SNP level and gene level

Anais da Academia Brasileira de Ciências ◽

10.1590/0001-3765202120191453 ◽

2021 ◽

Vol 93 (3) ◽

Author(s):

SHEIDA VARKOOHI ◽

MOHAMMAD HOSSEIN BANABAZI ◽

MOJGAN GHSEMI-SIAB

Keyword(s):

Bos Taurus ◽

Bos Indicus ◽

Rna Seq ◽

Specific Expression ◽

Allele Specific Expression ◽

Gene Level ◽

Allele Specific

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Investigation of allele specific expression in various tissues of broiler chickens using the detection tool VADT

Scientific Reports ◽

10.1038/s41598-021-83459-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

M. Joseph Tomlinson ◽

Shawn W. Polson ◽

Jing Qiu ◽

Juniper A. Lake ◽

William Lee ◽

...

Keyword(s):

Broiler Chickens ◽

Nucleotide Polymorphisms ◽

Rna Seq ◽

Specific Expression ◽

Single Nucleotide ◽

Allele Specific Expression ◽

Detection Tool ◽

Commercial Broiler ◽

Significant Phenomenon ◽

Allele Specific

AbstractDifferential abundance of allelic transcripts in a diploid organism, commonly referred to as allele specific expression (ASE), is a biologically significant phenomenon and can be examined using single nucleotide polymorphisms (SNPs) from RNA-seq. Quantifying ASE aids in our ability to identify and understand cis-regulatory mechanisms that influence gene expression, and thereby assist in identifying causal mutations. This study examines ASE in breast muscle, abdominal fat, and liver of commercial broiler chickens using variants called from a large sub-set of the samples (n = 68). ASE analysis was performed using a custom software called VCF ASE Detection Tool (VADT), which detects ASE of biallelic SNPs using a binomial test. On average ~ 174,000 SNPs in each tissue passed our filtering criteria and were considered informative, of which ~ 24,000 (~ 14%) showed ASE. Of all ASE SNPs, only 3.7% exhibited ASE in all three tissues, with ~ 83% showing ASE specific to a single tissue. When ASE genes (genes containing ASE SNPs) were compared between tissues, the overlap among all three tissues increased to 20.1%. Our results indicate that ASE genes show tissue-specific enrichment patterns, but all three tissues showed enrichment for pathways involved in translation.

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