Pklr Is a Genetic Modifier of Sickle Cell Disease

Abstract Background: Acute pain, the most prominent complication of sickle cell disease (SCD), results from vasoocclusion triggered by sickling of deoxygenated red blood cells (RBCs). A key factor influencing HbS oxygenation is the intracellular concentration of 2,3- diphosphoglycerate (2,3-DPG). 2,3-DPG, an intermediate substrate in the glycolytic pathway, decreases oxygen binding and stabilizes the deoxygenated hemoglobin. Pyruvate kinase (gene PKLR, protein PKR) is a rate-limiting enzyme in glycolysis; variants in PKLR may affect PKR activity, 2,3-DPG levels in RBCs, subsequent frequency of sickling and acute pain episodes (APE). There is thus a strong biological basis for exploring PKLR as a candidate gene affecting acute pain in SCD. Methods: The study population for genetic association consists of 2 cohorts: 1) 242 adults with HbSS from King's College Hospital (KCH), London, UK, with complete hospitalisation records over 10 years (2004-2013 inclusive) as the "discovery" cohort; 2) 977 children with HbSS or HbSb 0 thalassemia from the Silent Infarct Transfusion (SIT) trial, with a 3-year history of severe vasoocclusive pain based on hospitalization, as the "validation" cohort. Both studies were approved by the local Institutional Review Boards at KCH and Vanderbilt University Medical Center, respectively. An independent cohort comprises 52 adults with SCD enrolled under 3 protocols - NCT00011648, NCT00081523, and NCT03685721 - approved by the NHLBI Review Board (NIH), for evaluation of imbalance in allele expression. Genome scan for the KCH cohort was performed using llumina's Infinium "MEGA" chip (1.7m markers). The SIT DNA samples were genotyped using Illumina HumanHap650Y array 5 (661K markers) or Illumina Infinium HumanOmni1-Quad array (1.1m markers). The results were quality controlled followed by genotype imputation based on the 1000 Genomes Project phase 3 data. An annualised "hospitalisation rate" as a measure of pain incidence rate, was calculated by dividing the number of hospital admissions for severe acute pain by the number of years of observation for KCH and SIT cohorts (Fig A). We performed association analysis with common SNPs at PKLR locus using data from our genome-wide SNP set and a linear mixed modelling approach incorporating a genetic relatedness matrix to take account of relatedness, plus sex and age as fixed covariates. We corrected for multiple testing after quantifying the linkage disequilibrium (LD) within PKLR and used this to calculate appropriate significance levels. For the PKLR region and hospitalisation rate, the modified significance level was p<0.001268 for the discovery (KCH) cohort. For the allele expression assays, a synonymous variant, rs1052176 (R596R), in exon 11 of PKLR acted as a marker of relative expression levels of the 2 alleles of the gene. Allele specific expression was carried using the Bio-Rad digital droplet PCR system. Results: 7 of 47 variants evaluated in PKLR were associated with hospitalization rate (LnLnHospRate) in the discovery cohort: intron 4 - rs071053, and intron 2 - rs8177970, rs116244351, rs114455416, rs12741350, rs3020781, and rs8177964). All 7 were validated in Fisher's meta-analyses of the KCH and the SIT cohorts using p<0.0071 as threshold to correct for multiple testing (Fig B). We examined the pairwise LD between PKLR variants, and found all the intron 2 variants in tight LD, while R596R belongs to another LD block (Fig C). 52 SCD individuals had the R596R variant, of which 29 were heterozygous and 23 homozygous for the intron 2 haplotype associated with APE in SCD. We performed a Wilcoxon rank sum test and compared the variation in PKLR expression between the 2 alleles in subjects homozygous and heterozygous for the wildtype intron 2 haplotype, using genomic DNA as internal control for each subject. The results reveal a significant deviation from the expected expression ratio in those heterozygous for the intron 2 haplotype (mean 0.2073, +/- SD 0.0135) when compared with to those without the variant (mean 0.1239, +/- SD 0.0682), p=0.0297 (Fig D). Conclusion: Intronic variants of PKLR are associated with hospitalization rate for acute pain episodes in adults and children with SCD. We show that the intronic variants are likely to influence acute pain by affecting expression of the PKLR gene using allele-specific expression analyses, although the causal variant is unclear. These results support PKLR as a genetic modifier of SCD. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data

Genes ◽

10.3390/genes11030240 ◽

2020 ◽

Vol 11 (3) ◽

pp. 240 ◽

Cited By ~ 2

Author(s):

Prashant N. M. ◽

Hongyu Liu ◽

Pavlos Bousounis ◽

Liam Spurr ◽

Nawaf Alomran ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Single Cells ◽

Sequencing Data ◽

Specific Expression ◽

Single Nucleotide ◽

Healthy Donors ◽

Allele Expression ◽

Single Cell Rna Sequencing ◽

Allele Specific

With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAFRNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAFRNA estimation from current scRNA-seq datasets and shows that the 3′-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.

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APC germ-line allele-specific expression in familial adenomatous polyposis

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.15_suppl.e22037 ◽

2009 ◽

Vol 27 (15_suppl) ◽

pp. e22037-e22037

Author(s):

E. Castellsague ◽

S. González ◽

I. Blanco ◽

E. Guinó ◽

C. Lázaro ◽

...

Keyword(s):

Familial Adenomatous Polyposis ◽

Germ Line ◽

Significant Proportion ◽

Adenomatous Polyposis ◽

Specific Expression ◽

Nonsense Mediated Decay ◽

Allele Expression ◽

Fresh Frozen ◽

Specific Allele ◽

Allele Specific

e22037 Background: About 13% of Familial Adenomatous Polyposis (FAP) families and 70% of Attenuated FAP families remain with unknown molecular pathogenic cause after APC and MYH mutational analyses. Also, mutations can affect specific allele expression (ASE) at the germline level. The aim of the study was to determine the presence of germline ASE in the APC gene in FAP and AFP with and without detectable APC or MYH mutations. Methods: Germline RNA from fresh frozen and/or cultured lymphocytes of 17 APC/MYH-negative Polyposis (7 FAP, 10 AFAP) families (21 individuals) and 35 APC-mutated Polyposis (30 FAP, 5 AFAP) families (60 individuals) was analyzed. Fourteen controls were also studied. ASE was investigated by single nucleotide primer extension (SNuPE) of rs2229992 APC coding SNP. Results: In controls ASE was 1.04± 0.3. We found that 17% (3 of 17) APC/MYH(-) FAP and AFAP families showed ASE (range=1.17–1.39) and ASE co-segregated with disease. ASE was more intense in short-cultured lymphocytes except for two cases and completely reversed by puromycin treatment. Eleven of 35 (31%) APC-FAP/AFAP harbored ASE (range=1.20–7.76), and the mutant allele was underexpressed in each case. ASE was restricted to splicing (4 families), nonsense (3 families) and frameshift (3 families) mutations outside of exon 15. Puromycin reversed ASE in all cases analyzed. Conclusions: APC ASE is present in a significant proportion (17%) of APC/MYH(-) FAP or AFAP. ASE, due to nonsense-mediated decay (NMD), is present in APC-FAP and is associated with specific mutation location, similar to reports for other hereditary syndromes. No significant financial relationships to disclose.

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Unequal allele expression (asymmetric allele-specific expression)

The Dictionary of Genomics, Transcriptomics and Proteomics ◽

10.1002/9783527678679.dg14051 ◽

2015 ◽

pp. 1-1

Keyword(s):

Specific Expression ◽

Allele Specific Expression ◽

Allele Expression ◽

Allele Specific

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Nonfluorescent Denaturing HPLC–Based Primer-Extension Method for Allele-Specific Expression: Application to Analysis of Mismatch Repair Genes

Clinical Chemistry ◽

10.1373/clinchem.2009.126300 ◽

2009 ◽

Vol 55 (9) ◽

pp. 1711-1718 ◽

Cited By ~ 3

Author(s):

Gitana M Aceto ◽

Laura De Lellis ◽

Teresa Catalano ◽

Serena Veschi ◽

Paolo Radice ◽

...

Keyword(s):

Colon Cancer ◽

Mismatch Repair ◽

Primer Extension ◽

Mismatch Repair Genes ◽

Specific Expression ◽

Allele Specific Expression ◽

E Coli ◽

Allele Expression ◽

Allele Specific ◽

Repair Genes

Abstract Background: Altered germline expression of genes may represent a powerful marker of genetic or epigenetic predisposition to cancer or other diseases. Methods: We developed and validated a method of nonfluorescent primer extension that uses a single dideoxynucleotide and denaturing HPLC (DHPLC) to analyze the relative allele expression. We devised 5 independent assays for measuring allele-specific expression (ASE) to exploit different markers of mismatch repair genes MLH1 [mutL homolog 1, colon cancer, nonpolyposis type 2 (E. coli)] and MSH2 [mutS homolog 2, colon cancer, nonpolyposis type 1 (E. coli)]. We initially confirmed method reproducibility with genomic DNA (gDNA) from individuals heterozygous for a frequent single-nucleotide polymorphism in the MLH1 gene. After this preliminary validation with gDNA, we confirmed assay reproducibility with cDNA templates from control individuals. Relative allele expression was estimated by comparing the heights of the peaks corresponding to the 2 alleles. Results obtained with gDNA templates were used to normalize cDNA results. Results: With these DHPLC-based primer-extension assays, we detected and confirmed a 5-fold imbalance in MLH1 allele expression in a mutation-negative patient with hereditary nonpolyposis colorectal cancer and in another patient with a modest degree of imbalance in MLH1 expression. Among control individuals, the relative expression of MLH1 alleles displayed a narrow range of variation. Conclusions: Independent DHPLC-based primer-extension assays for measuring and confirming ASE can be developed for different sequence variants of interest. This DHPLC application provides a cost-effective method for detecting ASE in cases for which conventional screening fails to detect pathogenic mutations in candidate genes and may be applicable for confirming ASE revealed by other methods, such as those used for transcriptome-wide analyses. .

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Heterogeneous allele expression of pulmonary SP-D gene in rat large intestine and other tissues

Physiological Genomics ◽

10.1152/physiolgenomics.00061.2002 ◽

2002 ◽

Vol 11 (3) ◽

pp. 235-243 ◽

Cited By ~ 15

Author(s):

Zhenwu Lin ◽

Joanna Floros

Keyword(s):

Large Intestine ◽

Family Background ◽

Surfactant Protein ◽

Surfactant Protein D ◽

Epigenetic Factors ◽

Specific Expression ◽

Tissue Specific ◽

Allele Expression ◽

Allele Specific ◽

Parent Of Origin

Random allele expression has recently been observed for several genes including interleukins and genes of the lymphoid system. We studied the hypothesis that the surfactant protein D ( SP-D) gene, an innate host defense molecule, exhibits random allele expression in a tissue-specific manner. SP-D gene expression is tissue specific in the 14 tissues studied. Study of SP-D allelic expression in several tissues revealed a balanced biallelic (BB) in lung, and, in several extrapulmonary tissues, a heterogeneous pattern: BB, imbalanced biallelic (IB), and monoallelic (MO). The results from 103 heterozygous rats showed an expression profile in large intestine of BB (22%), IB (58%), and MO (20%). Among eight families, the percent of BB in siblings varied from 0 to 41%, MO from 0 to 33%, and IB from 49 to 83%. The parent-of-origin does not play a role in SP-D allele-specific expression. However, acquired epigenetic factors, family background, or other factors may contribute to the overall pattern of expression.

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Allele expression biases in mixed-ploid sugarcane accessions

10.1101/2021.08.26.457296 ◽

2021 ◽

Author(s):

Fernando Henrique Correr ◽

Agnelo Furtado ◽

Antonio Augusto Franco Garcia ◽

Robert James Henry ◽

Gabriel Rodrigues Alves Margarido

Keyword(s):

Allelic Imbalance ◽

Accurate Estimation ◽

Binomial Model ◽

Specific Expression ◽

General Metabolism ◽

Allele Dosage ◽

Allele Expression ◽

Allele Specific ◽

Sugarcane Hybrids ◽

High Level

Allele-specific expression (ASE) represents differences in the magnitude of expression between alleles of the same gene. This is not straightforward for polyploids, especially autopolyploids, as knowledge about the dose of each allele is required for accurate estimation of ASE. This is the case for the genomically complex Saccharum species, characterized by high levels of ploidy and aneuploidy. We used a Beta-Binomial model to test for allelic imbalance in Saccharum, with adaptations for mixed-ploid organisms. The hierarchical Beta-Binomial model was used to test if allele expression followed the expectation based on genomic allele dosage. The highest frequencies of ASE occurred in sugarcane hybrids, suggesting a possible influence of interspecific hybridization in these genotypes. For all accessions, ASEGs were less frequent than those with balanced allelic expression. These genes were related to a broad range of processes, mostly associated with general metabolism, organelles, responses to stress and responses to stimuli. In addition, the frequency of ASEGs in high-level functional terms was similar among the genotypes, with a few genes associated with more specific biological processes. We hypothesize that ASE in Saccharum is largely a genotype-specific phenomenon, as a large number of ASEGs were exclusive to individual accessions.

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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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Replicate sequencing libraries are important for quantification of allelic imbalance

Nature Communications ◽

10.1038/s41467-021-23544-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Asia Mendelevich ◽

Svetlana Vinogradova ◽

Saumya Gupta ◽

Andrey A. Mironov ◽

Shamil R. Sunyaev ◽

...

Keyword(s):

Allelic Imbalance ◽

False Positive Rate ◽

Error Rates ◽

Differential Analysis ◽

Rna Seq ◽

Specific Expression ◽

Technical Noise ◽

Specific Analysis ◽

Positive Rate ◽

Allele Specific

AbstractA sensitive approach to quantitative analysis of transcriptional regulation in diploid organisms is analysis of allelic imbalance (AI) in RNA sequencing (RNA-seq) data. A near-universal practice in such studies is to prepare and sequence only one library per RNA sample. We present theoretical and experimental evidence that data from a single RNA-seq library is insufficient for reliable quantification of the contribution of technical noise to the observed AI signal; consequently, reliance on one-replicate experimental design can lead to unaccounted-for variation in error rates in allele-specific analysis. We develop a computational approach, Qllelic, that accurately accounts for technical noise by making use of replicate RNA-seq libraries. Testing on new and existing datasets shows that application of Qllelic greatly decreases false positive rate in allele-specific analysis while conserving appropriate signal, and thus greatly improves reproducibility of AI estimates. We explore sources of technical overdispersion in observed AI signal and conclude by discussing design of RNA-seq studies addressing two biologically important questions: quantification of transcriptome-wide AI in one sample, and differential analysis of allele-specific expression between samples.

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