Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits

BackgroundIntramuscular fat (IMF) content is a determining factor for meat taste. The Luchuan pig is a fat-type local breed in southern China that is famous for its desirable meat quality due to high IMF, however, the crossbred offspring of Luchuan sows and Duroc boars displayed within-population variation on meat quality, and the reason remains unknown.ResultsIn the present study, we identified 212 IMF-correlated genes (FDR ≤ 0.01) using correlation analysis between gene expression level and the value of IMF content. The IMF-correlated genes were significantly enriched in the processes of lipid metabolism and mitochondrial energy metabolism, as well as the AMPK/PPAR signaling pathway. From the IMF-correlated genes, we identified 99 genes associated with expression quantitative trait locus (eQTL) or allele-specific expression (ASE) signals, including 21 genes identified by both cis-eQTL and ASE analyses and 12 genes identified by trans-eQTL analysis. Genome-wide association study (GWAS) of IMF identified a significant QTL on SSC14 (p-value = 2.51E−7), and the nearest IMF-correlated gene SFXN4 (r = 0.28, FDR = 4.00E−4) was proposed as the candidate gene. Furthermore, we highlighted another three novel IMF candidate genes, namely AGT, EMG1, and PCTP, by integrated analysis of GWAS, eQTL, and IMF-gene correlation analysis.ConclusionsThe AMPK/PPAR signaling pathway together with the processes of lipid and mitochondrial energy metabolism plays a vital role in regulating porcine IMF content. Trait correlated expression combined with eQTL and ASE analysis highlighted a priority list of genes, which compensated for the shortcoming of GWAS, thereby accelerating the mining of causal genes of IMF.

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq), and introns are under lower purifying selection and thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. To further investigate ASE in the context of human disease, we applied our methods to a Parkinson’s disease cohort of 94 individuals and show that ASE analysis had more power than eQTL analysis to identify significant SNP/gene pairs in our direct comparison of the two methods. Overall, we provide an end-to-end experimental and computational approach for future studies.

Linkage analyses enable identifying genomic regions that exhibit quantitative trait loci (QTL) without prior hypothesis on the physiology of a trait. Function-oriented expression analyses are a complementary approach to derive hypothesis on the genetic background of phenotypic variation. Muscle fibre types and size affect body composition and meat quality traits. The number and proportion of muscle fibres are to a large extent determined during the prenatal development. Consequently, QTL for muscle fibre, meat quality and carcass traits were detected in a porcine experimental population based on Duroc and Berlin Miniature Pig. Regions with either significant QTL for muscle fibre traits or significant QTL for meat quality and muscularity or both were detected on SSC1, 2, 3, 4, 5, 13, 14, 15 and 16. Here, effects on the complex traits of muscularity and meat quality might be the result of genetic variation primarily affecting fibre type distribution traits. To complement the QTL study expression profiling of prenatal muscle tissue of Duroc and Pietrain was conducted that revealed a list of functional candidate genes for meat quality and carcass traits of various physiological networks. Assignments of these genes to QTL regions highlight them as positional functional candidates. Exemplarily, five genes were analysed further and shown to be associated with meat quality and carcass traits. Further, the relative MYH isotype transcript abundance was found to be associated with muscularity. Relative MYH isotype transcript abundance is proposed as a new phenotype to unravel the genetic background of variation in traits related to muscle and meat properties.

Combining allele-specific expression (ASE) analysis with single-cell RNA-seq can elucidate how genomic variation affects RNA expression at the single-cell level. We explore how experimental and computational choices impact the power of ASE-based methods and develop a suite of single-cell ASE computational tools. With single-nucleus RNA-Seq, we extract more ASE information from reads in intronic than exonic regions. We show how read length can increase power and that hybrid selection improves power to detect ASE in targeted genes. We apply our methods to a Parkinson's disease cohort and show that ASE analysis has more power than eQTL analysis.

Allele-specific expression (ASE) analysis detects the relative abundance of alleles at heterozygous loci as a proxy for cis-regulatory variation, which affects the personal transcriptome and proteome. This study describes the development and application of an ASE analysis pipeline on a unique cohort of 87 well phenotyped and RNA sequenced patients from the Maastricht Cardiomyopathy Registry with dilated cardiomyopathy (DCM), a complex genetic disorder with a remaining gap in explained heritability. Regulatory processes for which ASE is a proxy might explain this gap. We found an overrepresentation of known DCM-associated genes among the significant results across the cohort. In addition, we were able to find genes of interest that have not been associated with DCM through conventional methods such as genome-wide association or differential gene expression studies. The pipeline offers RNA sequencing data processing, individual and population level ASE analyses as well as group comparisons and several intuitive visualizations such as Manhattan plots and protein–protein interaction networks. With this pipeline, we found evidence supporting the case that cis-regulatory variation contributes to the phenotypic heterogeneity of DCM. Additionally, our results highlight that ASE analysis offers an additional layer to conventional genomic and transcriptomic analyses for candidate gene identification and biological insight.

Background: Genome-wide association study (GWAS) have identified over 45 susceptibility loci for lung cancer; many studies including our own group, have focused on low-frequency and rare coding variants using fine mapping and exome sequencing. This strategy, however, has met with limited success as about 90% of GWAS hits are noncoding and act primarily through altering transcriptional regulation in an allele-specific manner. The RNA-Seq based allele-specific expression (ASE) analysis affords an innovative approach to study preferential expression of an allele in direct relationship to its genotype, providing information on cis-regulatory effects for the expression of putative genes. However currently, there are no lung cancer studies that have rigorously evaluated the ASE variation in lung tumor and adjacent tissues. Methods: Leveraging The Cancer Genome Atlas (TCGA) resource, we performed transcriptomic-wide ASE analysis using existing RNA-Seq datasets of paired tumor and adjacent tissues from 54 lung adenocarcinoma patients. We first quantified the RNA read counts of Referent and Alternate alleles of heterozygous variants, then evaluated the allelic imbalance on a per-sample basis using Beta-binomial test, and explored the differential ASE between tumor and adjacent tissues using paired Wilcoxon test. Functional regulatory consequences were generated from Ensembl Variant Effect Predictor. Results: We identified total 208 significant ASEs, including 35 tissue-specific (only in tumor or only in adjacent), 28 sharing, and 145 differential variants. Of the 208 candidates, 41 were from the human leukocyte antigen (HLA) locus (primary DQA2, DQB1, DRB1, H and J), 26 were from the immunoglobulin (IG) superfamily (primary IGH, IGL, IGK and F11R). About 80% candidates were noncoding (mostly in 5’ and 3’ untranslated regions) and with regulatory features (21 promoter, seven enhancer, seven open chromatin region, two induce nonsense-mediated mRNA decay, one CTCF-binding site, and one transcription factor binding site). Other top genes included MDM2, APOL1, and CTSB. Pathway analyses revealed 27 genes involved in immune response pathway, and 12 genes involved in HLA antigen processing and presentation pathway. Conclusion: This study is the first transcriptomics ASE analysis in lung adenocarcinoma. The key somatic cis-regulatory ASE variants identified from this study, especially immunogenic allelic variations from HLA and IG genes, could be used for identifying high-risk individuals for targeted lung cancer checkpoint blockade and related immunotherapies. Citation Format: Yanhong Liu, Spiridon Tsavachidis, Farrah Kheradmand, Margaret R. Spitz, Chris Amos. Transcriptome analysis links immune genes allelic expression imbalances to lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1584.

Peroxisome proliferator-activated receptor gamma (PPARG) is a key transcription factor that controls adipocyte differentiation and fat deposition in mammals. The primary goal of this study was to investigate PPARG as a candidate gene for meat quality and carcass traits in swine. Part of the PPARG promoter, along with the most 5'-proximal exon of the gene, was amplified by PCR and subsequently screened for polymorphisms by sequencing. A Met59Val substitution was detected in the porcine PPARG gene along with four polymorphisms in the promoter region of the adipose-specific PPARG2. Three of these polymorphisms were chosen for genotyping and tested for association with meat quality, carcass and growth traits, according to the candidate gene approach. More than 1500 animals from different lines and populations were used in the study with records for meat quality and carcass traits. No convincing associations were found between the traits investigated and the PPARG genotypes. It does not appear that variation at the PPARG locus is affecting meat quality, carcass or growth traits in the pig populations studied.

Allele-specific expression (ASE) analysis improves the understanding of transcription’s cis-regulation. Herein, we used imputed SNPs along with RNA-Seq data from the Longissiumus thoracis muscle of 190 Nelore steers to identify functional cis-regulatory variants from ASE analysis. Using a Binomial Test, we identified 38,177 SNPs in ASE regions (ASE SNPs; FDR ≤0.05). We then searched for aseQTLs (SNPs potentially regulating the ASE) by comparing their heterozygosity to the measured allelic ratio under a Wilcoxon Rank Sum test. We identified 21,543 aseQTLs potentially regulating a total of 430 ASE SNPs (FDR ≤0.05). Based on a linear model, ASE SNPs and aseQTLs were associated with transcript abundance. We identified 3,333 SNPs acting as cis-eQTLs (FDR≤0.05). Results were integrated with previous ASE, functional regions, and meat quality-related differentially expressed genes data. This study described novel SNPs potentially regulating the transcription of genes that may affect beef traits.

Simple SummaryYaks (Bos grunniens) inhabit the Qinghai-Tibetan Plateau and adjacent highlands at elevations between 2000 and 5000 m, where they are important domestic animals, as they provide meat, milk, fuel, and other necessities for Tibetans and nomads in China. Yak meat is fine in texture and high in protein, yet poor in muscular marbling and tenderness. Diacylglycerol acyltransferase-2 (DGAT2), which regulates fat deposition in animals, is a candidate gene for meat quality and quantity traits. However, there have been few reports on the effects of the DGAT2 gene on the meat quality of yak. Our study elucidated tissue expression of the yak DGAT2 gene and association of variation in the gene with Warner–Bratzler shear force of longissimus muscle. The results provide guidance for the molecular-assisted selection of meat tenderness in yak.Diacylglycerol acyltransferase-2 (DGAT2) plays a key role in the synthesis of animal triglycerides (TGs). This study investigated the relative expression of the DGAT2 gene in tissues, variation in the gene, and its association with carcass and meat quality traits in yaks (Bos grunniens). DGAT2 was found to be expressed in twelve tissues investigated, but the highest expression was detected in subcutaneous fat, and moderate levels were observed in the liver, heart, longissimus dorsi muscle, and abomasum. Three variants (A1 to C1) were found in intron 5 and another three variants (A2 to C2) were found in intron 6, with two single-nucleotide polymorphisms (SNPs) being identified in each region in 694 Gannan yaks. Variants B1 and C2 were associated with a decrease in Warner–Bratzler shear force (WBSF) (p = 0.0020 and p = 0.0441, respectively), and variant C1 was associated with an increase in WBSF (p = 0.0434) and a decrease in drip loss rate (p = 0.0271), whereas variant B2 was associated with a decrease in cooking loss rate (p = 0.0142). Haplotypes A1-A2 and B1-A2 were found to be, respectively, associated with an increase and a decrease in WBSF (p = 0.0191 and p = 0.0010, respectively). These results indicate that DGAT2 could be a useful gene marker for improving meat tenderness in yaks.

In recent years, large-scale international studies have provide comprehensive catalogues of genomic alterations in cancers including Esophageal Squamous Cell Cancer(ESCC). They revealed that some gene associated with cell cycle/apoptosis pathway, NOTCH pathway, WNT pathway, such as TP53 and NOTCH1, harbored genetic abnormalities frequently. As the next step clinical sequencing studies are starting to evaluate efficacy of using targeted agents to patients with specific molecular aberrations. We performed exome sequencing and RNA sequencing for 25 Japanese patients with esophageal squamous cell carcinoma (ESCC) to provide a comprehensive catalogue of genomic abnormalities in ESCC and found TP53 and ZNF750 significantly mutated genes. Additionally, we performed allele specific expression analysis of TP53, integrating mRNA sequencing data into the information of genomic abnormality. This analysis revealed that levels of expression changes depending on mutation types and nearly mono-allelic expression of TP53 was a common signature of ESCC patients with somatic mutations. And pattern of mono-allelic expression was dependent on mutation types. We expanded this analysis to all genes with somatic SNV mutations and revealed that mutant allele specific expression was observed in other genes including ZNF750, and many of them were belonged to cancer pathway in KEGG database. About TP53, our investigation might provide better understanding of the involvement of somatic mutations. And fluctuations in transcriptional regulation of TP53 could be predicted based on type of somatic mutation. In addition to this, analysis of allele specific expression suggested that not only somatic mutation of DNA, but also mutant allele expression should be considered to understand cancer genetic pathophysiology better and build more effective therapeutic strategies. Citation Format: Masahiko Takahashi, Hirofumi Nakaoka, Yasunori Akutsu, Naoyuki Hanari, Kentaro Murakami, Masayuki Kano, Yasunori Matsumoto, Ryota Otsuka, Nobufumi Sekino, Masaya Yokoyama, Itsuro Inoue, Hisahiro Matsubara. Analysis of allele specific expression in esophageal squamous cell carcinoma with combination of exome sequencing and mRNA Sequencing [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr B07.

Polymorphism in cis-regulatory sequences can lead to different levels of expression for the two alleles of a gene, providing a starting point for the evolution of gene expression. Little is known about the genome-wide abundance of genetic variation in gene regulation in natural populations but analysis of allele-specific expression (ASE) provides a means for investigating such variation. We performed RNA-seq of multiple tissues from population samples of two closely related flycatcher species and developed a Bayesian algorithm that maximizes data usage by borrowing information from the whole data set and combines several SNPs per transcript to detect ASE. Of 2,576 transcripts analyzed in collared flycatcher, ASE was detected in 185 (7.2%) and a similar frequency was seen in the pied flycatcher. Transcripts with statistically significant ASE commonly showed the major allele in >90% of the reads, reflecting that power was highest when expression was heavily biased toward one of the alleles. This would suggest that the observed frequencies of ASE likely are underestimates. The proportion of ASE transcripts varied among tissues, being lowest in testis and highest in muscle. Individuals often showed ASE of particular transcripts in more than one tissue (73.4%), consistent with a genetic basis for regulation of gene expression. The results suggest that genetic variation in regulatory sequences commonly affects gene expression in natural populations and that it provides a seedbed for phenotypic evolution via divergence in gene expression.

SNP identification in swine candidate genes for meat quality

In the current study, allele specific expression analysis was performed in two subspecies cows (Bos taurus and Bos indicus) at SNP and gene levels. RNA-Seq data of 21,078,477 and 20940063 paired end reads from pooling of whole blood samples (Leukocyte) from 40 US Holstein (Bos Taurus) and 45 Cholistani cows (Bos indicus) obtained from SRA database in NCBI. Quality control and trimming of row RNA-Seq data were processed by FASTQC and Trimmomatic softwares. The transcriptome was assembled by TopHat2 software in two cow's population by aligning and mapping the RNA-Seq reads on bovine reference genome. The SNPs were discovered by Samtools software and ASE analysis was performed by Chi-square test. Results showed that 50183 and 137954 SNPs were discovered on the assembled transcriptome of Holstein and Cholistani cow samples, respectively, and 15308 SNPs were common in both breeds. 10158 SNPs from 50183 (20%) in Holstein and 31523 SNPs from 137954 (23%) in Cholistani cows were identified as ASE-SNPs. Reference allele and alternative allele count in Holstein and Cholistani cows were 3041 and 7155, respectively. Among 131 discovered SNPs in 41 genes with different expression in Holstein and Cholistani cows, 31 ASE-SNPs (5 in Holstein; 26 in Cholistani cows) were discovered.

Differential 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.

(1) Background: Goose meat is highly valued for its economic significance and vast market potential due to its desirable qualities, including a rich nutritional profile, tender texture, relatively low-fat content, and high levels of beneficial unsaturated fatty acids. However, there is an urgent need to improve goose breeding by identifying molecular markers associated with meat quality. (2) Methods: We evaluated meat quality traits, such as meat color, shear force (SF), cooking loss rate (CLR), and crude fat content (CFC), in a population of 215 male Sichuan white geese at 70 days of age. A GWAS was performed to identify potential molecular markers associated with goose meat quality. Furthermore, the selected SNPs linked to meat quality traits were genotyped using the MALDI-TOP MS method. (3) Results: A dataset of 2601.19 Gb of WGS data was obtained from 215 individuals, with an average sequencing depth of 10.89×. The GWAS revealed the identification of 43 potentially significant SNP markers associated with meat quality traits in the Sichuan white goose population. Additionally, 28 genes were identified as important candidate genes for meat quality. The gene enrichment analysis indicated a substantial enrichment of genes within a 1Mb vicinity of SNPs in both the protein digestion and absorption pathway and the Glycerolipid metabolism pathway. (4) Conclusion: This study provides valuable insights into the genetic and molecular mechanisms underlying goose meat quality traits, offering crucial references for molecular breeding in this field.