scholarly journals Elimination of Reference Mapping Bias Reveals Robust Immune Related Allele-Specific Expression in Crossbred Sheep

2019 ◽  
Vol 10 ◽  
Author(s):  
Mazdak Salavati ◽  
Stephen J. Bush ◽  
Sergio Palma-Vera ◽  
Mary E. B. McCulloch ◽  
David A. Hume ◽  
...  
2021 ◽  
Author(s):  
S. Sánchez-Ramírez ◽  
A. D. Cutter

ABSTRACTSummaryChanges to regulatory sequences account for important phenotypic differences between species and populations. In heterozygote individuals, regulatory polymorphism typically manifests as allele-specific expression (ASE) of transcripts. ASE data from inter-species and inter-population hybrids, in conjunction with expression data from the parents, can be used to infer regulatory changes in cis and trans throughout the genome. Improper data handling, however, can create problems of mapping bias and excessive loss of information, which are prone to arise unintentionally from the cumbersome pipelines with multiple dependencies that are common among current methods. Here, we introduce a new, selfcontained method implemented in Python that generates allele-specific expression counts from genotype-specific map alignments. Rather than assessing individual SNPs, our approach sorts and counts reads within a given homologous region by comparing individual read-mapping statistics from each parental alignment. Reads that are aligned ambiguously to both references are resolved proportionally to the allele-specific matching read counts or statistically using a binomial distribution. Using simulations, we show CompMap has low error rates in assessing regulatory divergence.AvailabilityThe Python code with examples and installation instructions is available on the GitHub repository https://github.com/santiagosnchez/[email protected] information


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Joseph Tomlinson ◽  
Shawn W. Polson ◽  
Jing Qiu ◽  
Juniper A. Lake ◽  
William Lee ◽  
...  

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.


Genetics ◽  
2013 ◽  
Vol 195 (3) ◽  
pp. 1157-1166 ◽  
Author(s):  
Sandrine Lagarrigue ◽  
Lisa Martin ◽  
Farhad Hormozdiari ◽  
Pierre-François Roux ◽  
Calvin Pan ◽  
...  

PLoS Genetics ◽  
2018 ◽  
Vol 14 (11) ◽  
pp. e1007690
Author(s):  
Sofie Y. N. Delbare ◽  
Andrew G. Clark

PLoS ONE ◽  
2013 ◽  
Vol 8 (1) ◽  
pp. e55261 ◽  
Author(s):  
Quan-Xiang Wei ◽  
Rainer Claus ◽  
Thomas Hielscher ◽  
Daniel Mertens ◽  
Aparna Raval ◽  
...  

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