Selection of candidate genes for differences in fat metabolism between cattle subcutaneous and perirenal adipose tissue based on RNA-seq

2021 ◽  
pp. 1-12
Author(s):  
Siyuan Wang ◽  
Jie Liu ◽  
Weiming Zhao ◽  
Guofu Wang ◽  
Shuxin Gao
2017 ◽  
Vol 114 (9) ◽  
pp. 2373-2378 ◽  
Author(s):  
Budhaditya Chowdhury ◽  
Yick-Bun Chan ◽  
Edward A. Kravitz

By selection of winners of dyadic fights for 35 generations, we have generated a hyperaggressive Bully line of flies that almost always win fights against the parental wild-type Canton-S stock. Maintenance of the Bully phenotype is temperature dependent during development, with the phenotype lost when flies are reared at 19 °C. No similar effect is seen with the parent line. This difference allowed us to carry out RNA-seq experiments and identify a limited number of genes that are differentially expressed by twofold or greater in the Bullies; one of these was a putative transmembrane transporter, CG13646, which showed consistent and reproducible twofold down-regulation in Bullies. We examined the causal effect of this gene on the phenotype with a mutant line for CG13646, and with an RNAi approach. In all cases, reduction in expression of CG13646 by approximately half led to a hyperaggressive phenotype partially resembling that seen in the Bully flies. This gene is a member of a very interesting family of solute carrier proteins (SLCs), some of which have been suggested as being involved in glutamine/glutamate and GABA cycles of metabolism in excitatory and inhibitory nerve terminals in mammalian systems.


Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1423
Author(s):  
André Albuquerque ◽  
Cristina Óvilo ◽  
Yolanda Núñez ◽  
Rita Benítez ◽  
Adrián López-Garcia ◽  
...  

Gene expression is one of the main factors to influence meat quality by modulating fatty acid metabolism, composition, and deposition rates in muscle tissue. This study aimed to explore the transcriptomics of the Longissimus lumborum muscle in two local pig breeds with distinct genetic background using next-generation sequencing technology and Real-Time qPCR. RNA-seq yielded 49 differentially expressed genes between breeds, 34 overexpressed in the Alentejano (AL) and 15 in the Bísaro (BI) breed. Specific slow type myosin heavy chain components were associated with AL (MYH7) and BI (MYH3) pigs, while an overexpression of MAP3K14 in AL may be associated with their lower loin proportion, induced insulin resistance, and increased inflammatory response via NFkB activation. Overexpression of RUFY1 in AL pigs may explain the higher intramuscular (IMF) content via higher GLUT4 recruitment and consequently higher glucose uptake that can be stored as fat. Several candidate genes for lipid metabolism, excluded in the RNA-seq analysis due to low counts, such as ACLY, ADIPOQ, ELOVL6, LEP and ME1 were identified by qPCR as main gene factors defining the processes that influence meat composition and quality. These results agree with the fatter profile of the AL pig breed and adiponectin resistance can be postulated as responsible for the overexpression of MAP3K14′s coding product NIK, failing to restore insulin sensitivity.


2020 ◽  
Vol 241 ◽  
pp. 104255
Author(s):  
I. Argemí-Armengol ◽  
D. Villalba ◽  
Marc Tor ◽  
Juan Ramón Bertolín ◽  
M.A. Latorre ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Go-Eun Yu ◽  
Younhee Shin ◽  
Sathiyamoorthy Subramaniyam ◽  
Sang-Ho Kang ◽  
Si-Myung Lee ◽  
...  

AbstractBellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.


2018 ◽  
Vol 132 (2) ◽  
pp. 515-529 ◽  
Author(s):  
Minjeong Park ◽  
Joung-Ho Lee ◽  
Koeun Han ◽  
Siyoung Jang ◽  
Jiwoong Han ◽  
...  

1998 ◽  
Vol 38 (5) ◽  
pp. 489-498 ◽  
Author(s):  
François Bocquier ◽  
Muriel Bonnet ◽  
Yannick Faulconnier ◽  
Michèle Guerre-Millo ◽  
Patrice Martin ◽  
...  

2006 ◽  
Vol 69 (5) ◽  
pp. 999-1006 ◽  
Author(s):  
LUCIA RIVAS ◽  
GARY A. DYKES ◽  
NARELLE FEGAN

Shiga toxigenic Escherichia coli (STEC) serotypes are important foodborne pathogens that cause gastrointestinal disease worldwide. An understanding of how STEC strains attach to surfaces may provide insight into the potential persistence of and contamination with STEC in food environments. The initial attachment of a selection of STEC serotypes to beef muscle and adipose tissue was evaluated for isolates grown in planktonic and sessile culture. Initial experiments were performed to determine whether attachment differed among STEC strains and between the two modes of growth. Viable counts were obtained for loosely and strongly attached cells, and the strength of attachment (Sr) was calculated. All bacterial isolates grown in sessile culture attached in higher numbers to muscle and adipose tissue than did bacteria in planktonic cultures. For all attachment assays performed, mean concentrations for loosely attached cells were consistently higher than concentrations for strongly attached cells. The mean concentrations for strongly attached bacteria for planktonic and sessile cultures were significantly higher (P < 0.05) on adipose than on muscle tissue. However, some strains of STEC, particularly those from sessile culture, did not differ in their attachment to muscle or adipose tissue. Sr values were not significantly different (P > 0.05) among STEC isolates for all assays. No correlation was found between bacterial hydrophobicity and surface charge values (previously determined) and production of surface structures, viable counts, and Sr values. STEC grown in planktonic and sessile culture seems to behave differently with respect to attachment to muscle and adipose tissue. Cells in sessile culture may have a greater potential to strongly attach to meat surfaces.


2018 ◽  
Vol 75 (6) ◽  
pp. 1042-1049
Author(s):  
Seongjoon Park ◽  
Erkhembayar Nayantai ◽  
Toshimitsu Komatsu ◽  
Hiroko Hayashi ◽  
Ryoichi Mori ◽  
...  

Abstract The orexigenic hormone neuropeptide Y (NPY) plays a pivotal role in the peripheral regulation of fat metabolism. However, the mechanisms underlying the effects of sex on NPY function have not been extensively analyzed. In this study, we examined the effects of NPY deficiency on fat metabolism in male and female mice. Body weight was slightly decreased, whereas white adipose tissue (WAT) mass was significantly decreased as the thermogenic program was upregulated in NPY-/- female mice compared with that in wild-type mice; these factors were not altered in response to NPY deficiency in male mice. Moreover, lack of NPY resulted in an increase in luteinizing hormone (LH) expression in the pituitary gland, with concomitant activation of the estradiol-mediated thermogenic program in inguinal WAT, and alleviated age-related modification of adiposity in female mice. Taken together, these data revealed a novel intracellular mechanism of NPY in the regulation of fat metabolism and highlighted the sexual dimorphism of NPY as a promising target for drug development to reduce postmenopausal adiposity.


Endocrinology ◽  
2017 ◽  
Vol 159 (1) ◽  
pp. 227-237 ◽  
Author(s):  
Chunyan Wu ◽  
Huijian Zhang ◽  
Jiajun Zhang ◽  
Cuihua Xie ◽  
Cunxia Fan ◽  
...  

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