scholarly journals Identification of eQTL and sQTL associated with meat quality in beef

2019 ◽  
Author(s):  
Joel David Leal Gutierrez ◽  
Mauricio A. Elzo ◽  
Raluca G. Mateescu
Keyword(s):  
Qtl Mapping ◽  
Meat Quality ◽  
Transcriptional Activation ◽  
Network Architecture ◽  
R Package ◽  
Cytoskeletal Proteins ◽  
Genetic Dissection ◽  
Rna Seq ◽  
Master Regulators ◽  
Longissimus Dorsi Muscle

Abstract Background: Transcription has a substantial genetic control and genetic dissection of gene expression could help us understand the genetic architecture of complex phenotypes such as meat quality in cattle.Results: A total of 80 steers were selected for phenotyping, genotyping and RNA-seq evaluation. A panel of traits related to meat quality were recorded. Information on 112,042 SNPs and expression data on 8,588 autosomal genes and 87,770 exons from 8,467 genes were included in an expression and splicing quantitative trait loci (QTL) mapping (eQTL and sQTL, respectively). Expression of 1,352 genes was previously identified as associated with meat quality traits using a gene, exon and isoform differential expression (DE) analysis. The R package Matrix eQTL was used to perform the QTL mapping using linear regression. The identified QTLs were classified as cis or trans using 1 Mb as maximum distance between the associated SNP and the gene. Polymorphisms associated with expression of at least 20 genes, and splicing of at least 20 exons were considered QTL hot spots. A total of 8,377 eQTLs were identified, including 75.6% trans, 10.4% cis, 12.5% DE trans and 1.5% DE cis; 11,929 sQTLs were uncovered: 66.1% trans, 16.9% DE trans, 14% cis and 3% DE cis. Twenty seven expression master regulators and 13 splicing master regulators were identified and were classified as membrane associated or cytoskeletal proteins, transcription factors or DNA methylases These genes could control expression of other genes through cell signaling or by a direct transcriptional activation/repression mechanism. The ZNF804A, ALAD, OR13F1 and ENSBTAG00000000336 genes were identified as both expression and splicing master regulators.Conclusion: In the present analysis, we show that eQTL and sQTL mapping makes possible positional identification of gene and isoform expression regulators. Additionally, this mapping provides new insight into the regulatory network architecture in longissimus dorsi muscle in an Angus-Brahman multibreed population.

scholarly journals Identification of eQTLs and sQTLs associated with meat quality in beef

2019 ◽  
Author(s):  
Joel David Leal Gutierrez ◽  
Mauricio A. Elzo ◽  
Raluca G. Mateescu
Keyword(s):  
Meat Quality ◽  
Fixed Effects ◽  
Differential Expression Analysis ◽  
Cytoskeletal Proteins ◽  
Longissimus Dorsi ◽  
Quality Traits ◽  
Master Regulators ◽  
Longissimus Dorsi Muscle ◽  
Meat Quality Traits ◽  
Dorsi Muscle

Abstract Background: Transcription has a substantial genetic control and genetic dissection of gene expression could help us understand the genetic architecture of complex phenotypes such as meat quality in cattle. The objectives of the present research were: 1) to perform eQTL and sQTL mapping analyses for meat quality traits in longissimus dorsi muscle; 2) to uncover genes whose expression is influenced by local or distant genetic variation; 3) to identify expression and splicing hot spots; and 4) to uncover genomic regions affecting the expression of multiple genes. Results: Eighty steers were selected for phenotyping, genotyping and RNA-seq evaluation. A panel of traits related to meat quality was recorded in longissimus dorsi muscle. Information on 112,042 SNPs and expression data on 8,588 autosomal genes and 87,770 exons from 8,467 genes were included in an expression and splicing quantitative trait loci (QTL) mapping (eQTL and sQTL, respectively). A gene, exon and isoform differential expression analysis previously carried out in this population identified 1,352 genes, referred to as DEG, as explaining part of the variability associated with meat quality traits. The eQTL and sQTL mapping was performed using a linear regression model in the R package Matrix eQTL. Genotype and year of birth were included as fixed effects, and population structure was accounted for by including as a covariate the first PC from a PCA analysis on genotypic data. The identified QTLs were classified as cis or trans using 1 Mb as the maximum distance between the associated SNP and the gene being analyzed. A total of 8,377 eQTLs were identified, including 75.6% trans, 10.4% cis, 12.5% DEG trans and 1.5% DEG cis; while 11,929 sQTLs were uncovered: 66.1% trans, 16.9% DEG trans, 14% cis and 3% DEG cis. Twenty-seven expression master regulators and 13 splicing master regulators were identified and were classified as membrane-associated or cytoskeletal proteins, transcription factors or DNA methylases. These genes could control the expression of other genes through cell signaling or by a direct transcriptional activation/repression mechanism. Conclusion: In the present analysis, we show that eQTL and sQTL mapping makes possible positional identification of gene and isoform expression regulators.

scholarly journals RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef

2019 ◽  
Author(s):  
Joel David Leal Gutierrez ◽  
Mauricio A. Elzo ◽  
Raluca G. Mateescu
Keyword(s):  
Meat Quality ◽  
Quality Index ◽  
Transcriptional Profiling ◽  
Cytoskeletal Proteins ◽  
P Value ◽  
Rna Seq ◽  
Microtubule Network ◽  
Illumina Hiseq ◽  
Exon Expression ◽  
Longissimus Dorsi Muscle

Abstract Background RNA sequencing (RNA-seq) has allowed for transcriptional profiling of biological systems through identification of differentially expressed (DE) genes and pathways. Results A total of 80 steers were selected from the multibreed Angus-Brahman herd of the University of Florida. Sensory panel tenderness, juiciness and connective tissue as well as marbling, WBSF and cooking loss were assessed in longissimus dorsi muscle. Nuclear RNA was extracted from muscle and an RNA-seq library for each sample was constructed, multiplexed, and sequenced based on protocols by Illumina HiSeq 3000 PE100 platform to generate 2 × 101 bp paired-end reads. On average, 34.9 million high-quality paired reads were uniquely mapped to the Btau_4.6.1 reference genome and a total of 8,799 genes were analyzed. Including all 80 animals, gene and exon expression analysis was carried out using a meat quality index as a continuous response variable. The expression of 208 genes and 3,280 exons from 1,565 genes was associated with the meat quality index (p-value ≤ 0.05). Out of the 80 samples sequenced, 40 animals with extreme low and high WBSF, tenderness and marbling values were selected for a differential expression (DE) analysis for gene and isoforms. A total of 676 (adjusted p-value ≤ 0.05), 70 (adjusted p-value ≤ 0.1) and 198 (adjusted p-value ≤ 0.1) genes were DE for WBSF, tenderness and marbling, respectively. A total of 106 isoforms from 98 genes for WBSF, 13 isoforms from 13 genes for tenderness and 43 isoforms from 42 genes for marbling (FDR ≤ 0.1) were DE. Conclusion A number of cytoskeletal and transmembrane anchoring related genes and pathways were identified in the expression, DE and gene enrichment analyses, and these proteins can have a direct effect on meat quality. Cytoskeletal proteins and transmembrane anchoring molecules can influence meat quality by allowing cytoskeletal filament interaction with myocyte and organelle membranes, contributing to cytoskeletal structure, microtubule network stability, and cellular architecture maintenance during the postmortem.

scholarly journals PSII-22 Comparison of the meat quality traits of crossbred pigs and the Large Black pigs

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 241-242
Author(s):  
Yongjie Wang ◽  
Keshari Thakali ◽  
Sarah Shelby ◽  
Jason Apple ◽  
Yan Huang
Keyword(s):  
Meat Quality ◽  
Genomic Diversity ◽  
Longissimus Dorsi ◽  
Rna Seq ◽  
Longissimus Dorsi Muscle ◽  
A Value ◽  
Dorsi Muscle ◽  
Body Weights ◽  
C Value ◽  
Crossbred Pigs

Abstract The purpose of this study was to compare the meat quality and genomic differences between cross-bred commercial pig (CP) and domestic Large Black pig (BP). Seven cross-bred commercial pigs and eight British Large Black pigs were assigned to CP group and BP group, with initial mean body weights of 18.82±1.412 kg for CP group and 23.31±1.935 kg for BP group, P = 0.061, and fed ad libitum. The final BW of the CP at d101 was similar to the BP (130.0±8.16 kg vs. 121.1±2.80 kg, P = 0.132). However, the BP group took 108 days to reach the final BW. The ADG in the CP was higher than BP (1.102±0.0599 kg vs. 0.905±0.0138 kg, P = 0.003). The hot carcass weight of CP was higher (P < 0.01) than BP, but the backfat of BP was higher (P < 0.01) than CP. The a* value of CP was higher (P < 0.05) than BP, and the c* value of CP was tended to be higher (P < 0.10) than BP. However, the h value of BP was higher (P < 0.05) than CP. The longissimus dorsi muscle fat content of BP was higher (P < 0.05) than CP. For the fatty acid composition, the SFA and MUFA of BP were higher (P < 0.05) than CP, but the PUFA of CP was higher (P < 0.05) than BP. The metmyoglobin content of CP was tended to be higher (P < 0.10) than BP. For the meat metabolism, the oxygen consumption of longissimus dorsi muscle of BP was higher (P < 0.01) than CP. The RNA-Seq data showed that the expression of the genes related to lipid metabolism is higher in BP (fold change > 3, P < 0.05). To conclude, BP has higher meat quality, while CP has its advantages in growth performance. And the differences between these two breeds may due to the genomic diversity.

scholarly journals RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0240895
Author(s):  
Joel D. Leal-Gutiérrez ◽  
Mauricio A. Elzo ◽  
Chad Carr ◽  
Raluca G. Mateescu
Keyword(s):  
Meat Quality ◽  
Quality Index ◽  
Transcriptional Profiling ◽  
Cytoskeletal Proteins ◽  
P Value ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Exon Expression ◽  
Continuous Response ◽  
Slaughter Age

RNA sequencing (RNA-seq) has allowed for transcriptional profiling of biological systems through the identification of differentially expressed (DE) genes and pathways. A total of 80 steers with extreme phenotypes were selected from the University of Florida multibreed Angus-Brahman herd. The average slaughter age was 12.91±8.69 months. Tenderness, juiciness and connective tissue assessed by sensory panel, along with marbling, Warner-Bratzler Shear Force (WBSF) and cooking loss, were measured in longissimus dorsi muscle. Total RNA was extracted from muscle and one RNA-seq library per sample was constructed, multiplexed, and sequenced based on protocols by Illumina HiSeq-3000 platform to generate 2×101 bp paired-end reads. The overall read mapping rate using the Btau_4.6.1 reference genome was 63%. A total of 8,799 genes were analyzed using two different methodologies, an expression association and a DE analysis. A gene and exon expression association analysis was carried out using a meat quality index on all 80 samples as a continuous response variable. The expression of 208 genes and 3,280 exons from 1,565 genes was associated with the meat quality index (p-value ≤ 0.05). A gene and isoform DE evaluation was performed analyzing two groups with extreme WBSF, tenderness and marbling. A total of 676 (adjusted p-value≤0.05), 70 (adjusted p-value≤0.1) and 198 (adjusted p-value≤0.1) genes were DE for WBSF, tenderness and marbling, respectively. A total of 106 isoforms from 98 genes for WBSF, 13 isoforms from 13 genes for tenderness and 43 isoforms from 42 genes for marbling (FDR≤0.1) were DE. Cytoskeletal and transmembrane anchoring genes and pathways were identified in the expression association, DE and the gene enrichment analyses; these proteins can have a direct effect on meat quality. Cytoskeletal proteins and transmembrane anchoring molecules can influence meat quality by allowing cytoskeletal interaction with myocyte and organelle membranes, contributing to cytoskeletal structure and architecture maintenance postmortem.

scholarly journals PSV-27 Program Chair Poster Pick: Expression QTL mapping for meat quality in beef cattle

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 359-360
Author(s):  
Raluca G Mateescu ◽  
Joel Leal-Gutiérrez ◽  
Mauricio Elzo
Keyword(s):  
Qtl Mapping ◽  
Meat Quality ◽  
Quality Index ◽  
Principal Component ◽  
Eqtl Mapping ◽  
Expression Qtl ◽  
Longissimus Dorsi Muscle ◽  
Associated Proteins ◽  
Regulator Genes ◽  
Genomic Regions

Abstract Expression QTL mapping provides information about genetic variant with modulatory effects on gene expression which are useful for understanding the genetic architecture of complex phenotypes. This mapping allows for uncovering of genomic regions associated with transcription regulation of genes which can be related to phenotypic variation when they colocalize with QTLs (cis and trans effects), providing a molecular basis for the phenotype-genotype association. The objectives of the present research were to perform eQTL mapping for meat quality traits in longissimus dorsi muscle and to uncover genes whose expression is influenced by local or distant genetic variation. A total of 120 steers from the University of Florida Beef Unit multibreed Angus-Brahman herd born between 2013 and 2014 were used in this study. The first three principal components from a principal component analysis for all meat quality phenotypes were used to construct a meat quality index. Eighty animals were selected based on extreme meat quality index for mRNA sequencing and 100 bp paired-end reads were mapped against to the Btau_4.6.1 reference genome. eQTL mapping was performed using 112,042 SNPs and 8,588 genes. A cis QTL was defined as an SNP located no more than 1 Mb upstream of the transcription start site or downstream of the transcription end site of an annotated gene. Polymorphisms associated with expression of at least 20 genes in the case of eQTL were considered hot spots. The harboring or adjacent gene was defined as master regulators. Multiple cis eQTLs and sQTLs effects were identified and genes such as LSM2, SOAT1, TTN and TEK are a few examples of potential expression and splicing regulatory genes. A total of 27 expression and 13 splicing master regulator genes were uncovered, mainly cytoskeletal or membrane-associated proteins, transcription factors and DNA methylases.

ExperimentSubset: an R package to manage subsets of Bioconductor Experiment objects

2021 ◽  
Author(s):  
Irzam Sarfraz ◽  
Muhammad Asif ◽  
Joshua D Campbell
Keyword(s):  
Single Cell ◽  
R Package ◽  
Poor Quality ◽  
Data Matrix ◽  
Supplementary Information ◽  
Data Provenance ◽  
Rna Seq ◽  
Efficient Management ◽  
The Matrix ◽  
The Relationship

Abstract Motivation R Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for storing one or more matrix-like assays along with associated row and column data. These objects have been used to facilitate the storage and analysis of high-throughput genomic data generated from technologies such as single-cell RNA sequencing. One common computational task in many genomics analysis workflows is to perform subsetting of the data matrix before applying down-stream analytical methods. For example, one may need to subset the columns of the assay matrix to exclude poor-quality samples or subset the rows of the matrix to select the most variable features. Traditionally, a second object is created that contains the desired subset of assay from the original object. However, this approach is inefficient as it requires the creation of an additional object containing a copy of the original assay and leads to challenges with data provenance. Results To overcome these challenges, we developed an R package called ExperimentSubset, which is a data container that implements classes for efficient storage and streamlined retrieval of assays that have been subsetted by rows and/or columns. These classes are able to inherently provide data provenance by maintaining the relationship between the subsetted and parent assays. We demonstrate the utility of this package on a single-cell RNA-seq dataset by storing and retrieving subsets at different stages of the analysis while maintaining a lower memory footprint. Overall, the ExperimentSubset is a flexible container for the efficient management of subsets. Availability and implementation ExperimentSubset package is available at Bioconductor: https://bioconductor.org/packages/ExperimentSubset/ and Github: https://github.com/campbio/ExperimentSubset. Supplementary information Supplementary data are available at Bioinformatics online.

movAPA: modeling and visualization of dynamics of alternative polyadenylation across biological samples

2020 ◽  
Author(s):  
Wenbin Ye ◽  
Tao Liu ◽  
Hongjuan Fu ◽  
Congting Ye ◽  
Guoli Ji ◽  
...  
Keyword(s):  
Biological Samples ◽  
Tissue Specificity ◽  
Single Cells ◽  
Alternative Polyadenylation ◽  
R Package ◽  
Supplementary Information ◽  
Rna Seq ◽  
Mouse Sperm ◽  
High Scalability ◽  
A Site

Abstract Motivation Alternative polyadenylation (APA) has been widely recognized as a widespread mechanism modulated dynamically. Studies based on 3′ end sequencing and/or RNA-seq have profiled poly(A) sites in various species with diverse pipelines, yet no unified and easy-to-use toolkit is available for comprehensive APA analyses. Results We developed an R package called movAPA for modeling and visualization of dynamics of alternative polyadenylation across biological samples. movAPA incorporates rich functions for preprocessing, annotation and statistical analyses of poly(A) sites, identification of poly(A) signals, profiling of APA dynamics and visualization. Particularly, seven metrics are provided for measuring the tissue-specificity or usages of APA sites across samples. Three methods are used for identifying 3′ UTR shortening/lengthening events between conditions. APA site switching involving non-3′ UTR polyadenylation can also be explored. Using poly(A) site data from rice and mouse sperm cells, we demonstrated the high scalability and flexibility of movAPA in profiling APA dynamics across tissues and single cells. Availability and implementation https://github.com/BMILAB/movAPA. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MUREN: a robust and multi-reference approach of RNA-seq transcript normalization

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yance Feng ◽  
Lei M. Li
Keyword(s):  
Biological Significance ◽  
Housekeeping Genes ◽  
R Package ◽  
Data Sets ◽  
Statistical Regression ◽  
Rna Seq ◽  
Least Trimmed Squares ◽  
Standard Data ◽  
Wide Range ◽  
Multiple References

Abstract Background Normalization of RNA-seq data aims at identifying biological expression differentiation between samples by removing the effects of unwanted confounding factors. Explicitly or implicitly, the justification of normalization requires a set of housekeeping genes. However, the existence of housekeeping genes common for a very large collection of samples, especially under a wide range of conditions, is questionable. Results We propose to carry out pairwise normalization with respect to multiple references, selected from representative samples. Then the pairwise intermediates are integrated based on a linear model that adjusts the reference effects. Motivated by the notion of housekeeping genes and their statistical counterparts, we adopt the robust least trimmed squares regression in pairwise normalization. The proposed method (MUREN) is compared with other existing tools on some standard data sets. The goodness of normalization emphasizes on preserving possible asymmetric differentiation, whose biological significance is exemplified by a single cell data of cell cycle. MUREN is implemented as an R package. The code under license GPL-3 is available on the github platform: github.com/hippo-yf/MUREN and on the conda platform: anaconda.org/hippo-yf/r-muren. Conclusions MUREN performs the RNA-seq normalization using a two-step statistical regression induced from a general principle. We propose that the densities of pairwise differentiations are used to evaluate the goodness of normalization. MUREN adjusts the mode of differentiation toward zero while preserving the skewness due to biological asymmetric differentiation. Moreover, by robustly integrating pre-normalized counts with respect to multiple references, MUREN is immune to individual outlier samples.

scholarly journals DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq experiments

2016 ◽  
Vol 32 (24) ◽  
pp. 3844-3846 ◽  
Author(s):  
Aristidis G. Vrahatis ◽  
Panos Balomenos ◽  
Athanasios K. Tsakalidis ◽  
Anastasios Bezerianos
Keyword(s):  
R Package ◽  
Differentially Expressed ◽  
Rna Seq
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