The NT5E gene variant strongly affects the degradation rate of inosine 5′-monophosphate under postmortem conditions in Japanese Black beef

Komatsu, Takafumi; Komatsu, Masataka; Uemoto, Yoshinobu

doi:10.1016/j.meatsci.2019.107893

Cited by 9 publications

(17 citation statements)

References 23 publications

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“…In beef, GWAS was conducted on JB cattle to explore genes responsible for the palatability of beef, which revealed that SNPs in the ecto-5 -nucleotidase (NT5E) gene affected the content of IMP in the postmortem aged beef, due to the modulating effects of NT5E enzymatic activity. This is a result of which GC-and LC-based metabolomics contributed to GWAS on meat [52,53]. In these comprehensive omics approaches such as GWAS, metabolomics is useful to capture phenotypic metabolites for the candidate genes, due to its wide range of phenotypic molecular measurements.…”

Section: Animal Species Breeds and Genetic Backgroundsmentioning

confidence: 99%

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

et al. 2020

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In the past decades, metabolomics has been used to comprehensively understand a variety of food materials for improvement and assessment of food quality. Farm animal skeletal muscles and meat are one of the major targets of metabolomics for the characterization of meat and the exploration of biomarkers in the production system. For identification of potential biomarkers to control meat quality, studies of animal muscles and meat with metabolomics (MEATabolomics) has been conducted in combination with analyses of meat quality traits, focusing on specific factors associated with animal genetic background and sensory scores, or conditions in feeding system and treatments of meat in the processes such as postmortem storage, processing, and hygiene control. Currently, most of MEATabolomics approaches combine separation techniques (gas or liquid chromatography, and capillary electrophoresis)–mass spectrometry (MS) or nuclear magnetic resonance (NMR) approaches with the downstream multivariate analyses, depending on the polarity and/or hydrophobicity of the targeted metabolites. Studies employing these approaches provide useful information to monitor meat quality traits efficiently and to understand the genetic background and production system of animals behind the meat quality. MEATabolomics is expected to improve the knowledge and methodologies in animal breeding and feeding, meat storage and processing, and prediction of meat quality.

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Section: Animal Species Breeds and Genetic Backgroundsmentioning

confidence: 99%

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

et al. 2020

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“…There was a high concentration of IMP in Korean native chicken (Kavitha & Modi, 2007), but it may be degraded into hypoxanthine and inosine by enzymes, which results in a bitter taste (Feng et al., 2016). It was also generally affected by water activity, pH, environmental factors, and genetic factors (Komatsu et al., 2019). The content of 5′‐AMP in boneless cold‐eating rabbit was also relatively high, which was beneficial to the enhancement of umami taste or to interact with other substances.…”

Section: Resultsmentioning

confidence: 99%

Analysis of the characteristic flavor substances of boneless cold‐eating rabbit under different preprocessing treatments

Yuan

Peng

Zhong

et al. 2021

J. Food Process. Preserv.

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Cold‐eating rabbit is a local specialty, combined with three different pretreatment methods commonly used in the industry such as directly making, fried after removing blood, and stir‐fry after marinating to study the main flavor substances and effects of preconditioning on characteristic flavor compounds. Sensory analysis showed that umami was the strongest, which was the characteristic taste flavor, obtained from the taste substance detection experiment that Glu and 5′‐IMP were the characteristic taste substances. Marinating process had a strong umami taste. Volatile flavor compounds were detected, and alcohols and aldehydes were the main volatile flavor substances. There were 23 kinds of volatile flavor substances and nine characteristic volatile flavor substances. The characteristic flavors were lemon, fat, barbecue, fruit, floral, fennel, and smoky flavor; among these, fat, barbecue, and floral flavor were the most obvious. Novelty impact statement This experiment was the first time to study the flavor substances and physical and chemical indexes of cold‐eating rabbits, providing theoretical guidance for the industrial production of cold‐eating rabbits in Zigong, China. Combined with three different preprocessing methods commonly used in the industrial production of cold‐eating rabbits at the present stage, the influence of cold‐eating rabbits' product flavor substances and the exploration of characteristic flavor substances were analyzed. This study concluded that the characteristics of the volatile flavor substances were lemon flavor, fat flavor, barbecue flavor, fruit flavor, flower flavor, fennel flavor, and smoke flavor; among these, fat flavor, the roasted meat, and floral aroma were the most obvious, and Glu and 5′‐IMP were the characteristic taste substances.

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“…Genomic DNA was extracted using a DNeasy® Blood & Tissue Kit (Qiagen, Hilden, Germany). The rs207860446 SNP reported by Uemoto et al (2017) was genotyped as NT5E genotype by using PCR‐RFLP, based on the method described by Komatsu et al (2019). The forward and reverse primer sequences were 5′‐CAAGCCATTTTCCCTCTGG‐3′ and 5′‐TTGGTGTTGGGTGTGTGAAG‐3′, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…T A B L E 2 Descriptive statistics and heritability estimates by using the models with or without the ecto-5 0 -nucleotidase (NT5E) genotype for adenosine triphosphate-related compounds (ATPRCs) and carcass traits Japanese Black beef (Komatsu et al, 2019). Therefore, this study estimated the genetic parameters of ATPRCs in beef on Postmortem Days 4 and 7 using the model with or without the NT5E genotype.…”

Section: Estimated Breeding Values (Ebvs) For Atprcsmentioning

confidence: 99%

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Estimates of genetic parameters for adenosine triphosphate‐related compounds at different aging periods and NT5E genotypes in Japanese Black beef

Komatsu

Toita²,

Uemoto

2022

Animal Science Journal

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Previous studies on Japanese Black beef showed that single nucleotide polymorphisms in the ecto-5 0 -nucleotidase (NT5E) gene affected the degradation rate of inosine 5 0monophosphate (IMP), which has contributed to the umami taste, especially between Postmortem Days 4 and 7. Therefore, this study estimated the genetic parameters of IMP and its degradation products on Postmortem Days 4 and 7 using the model with or without the NT5E genotype. The heritability estimates of IMP on Postmortem Days 4 and 7 were moderate by the model without the NT5E genotype (0.44 and 0.32, respectively). When the NT5E genotype was included in the model, the heritability of IMP on Postmortem Day 4 did not change, whereas that on Day 7 decreased from 0.32 to 0.08. The genetic correlation of IMP between Postmortem Days 4 and 7 was highly positive using the model with the NT5E genotype. Regarding the estimated breeding values (EBVs) of IMP, the ranking of EBVs among NT5E genotypes was not changed between Postmortem Days 4 and 7, when the model with the NT5E genotype was used. The study suggested that the model including NT5E genotype would allow for appropriate genetic parameter estimation and breeding value evaluation in adenosine triphosphate-related compounds (ATPRCs) under different aging periods.

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The NT5E gene variant strongly affects the degradation rate of inosine 5′-monophosphate under postmortem conditions in Japanese Black beef

Cited by 9 publications

References 23 publications

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

Analysis of the characteristic flavor substances of boneless cold‐eating rabbit under different preprocessing treatments

Estimates of genetic parameters for adenosine triphosphate‐related compounds at different aging periods and NT5E genotypes in Japanese Black beef

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