• Asian-Australasian Journal of Animal Sciences
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• v.27 no.8
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• pp.1075-1081
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• 2014

CRBP1 (cellular retinol binding protein 1) and CRBP3 (cellular retinol binding protein 3), are important components of the retinoid signaling pathway and take part in vitamin A absorption, transport and metabolism. Based on the role of vitamin A in chicken laying performance, we investigated the polymorphism of CRBP1 and CRBP3 genes in 349 chickens using single strand conformation polymorphism and DNA sequencing methods. Only one polymorphism was identified in the third intron of CRBP1, two polymorphisms were detected in CRBP3; they were located in the second intron and the third intron respectively. The association studies between these three SNPs and laying performance traits were performed in Erlang mountainous chicken. Notably, the SNP g.14604G>T of CRBP1 was shown to be significantly associated with body weight at first egg (BWFE), age at first egg (AFE), weight at first egg (WFE) and total number of eggs with 300 age (EN). The CRBP3 polymorphism g.934C>G was associated with AFE, and the g.1324A>G was associated with AFE and BWFE, but none of these polymorphisms were associated with egg quality traits. Haplotype combinations constructed on these two SNPs of CRBP3 gene were associated with BWFE and AFE. In particular, diplotype H2H2 had positive effect on AFE, BWFE, EN, and average egg-laying interval. We herein describe for the first time basic research on the polymorphism of chicken CRBP1 and CRBP3 genes that is predictive of genetic potential for laying performance in chicken.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.3
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• pp.310-315
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• 2014

Cellular retinol-binding protein II (CRBP II) belongs to the family of cellular retinol-binding proteins and plays a major role in absorption, transport, and metabolism of vitamin A. In addition, because vitamin A is correlated with reproductive performance, we measured CRBP II mRNA abundance in erlang mountainous chickens by real-time PCR using the relative quantification method. The expression of CRBP II showed a tissue-specific pattern and egg production rate-dependent changes. The expression was very high (p<0.05) in jejunum and liver, intermediate in kidney, ovary, and oviduct, and lowest (p<0.05) in heart, hypothalamus, and pituitary. In the hypothalamus, oviduct, ovary, and pituitary, CRBP II mRNA abundance were correlated to egg production rate, which increased from 12 wk to 32 wk, peaked at 32 wk relative to the other time points, and then decreased from 32 wk to 45 wk. In contrast, the expression of CRBP II mRNA in heart, jejunum, kidney, and liver was not different at any of the ages evaluated in this study. These data may help to understand the genetic basis of vitamin A metabolism, and suggest that CRBP II may be a candidate gene to affect egg production traits in chickens.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.154.1-154.1
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• 2003

TCTP is presented to have a retinol binding protein (RBP)-like structure by domain search. Human cellular RBP (CRBP) plays a key role in the intercellular transfer of retinol. Modulation of its expression is known to contribute to tumor growth and progression via retinoid-mediated signaling. Changes in the expression of TCTP have also been reported to be associated with carcinogenesis. Therefore, the attempt to establish the interactive relationship between the human TCTP and CRBP with retinol will be helpful in further understanding the cell signaling of TCTP. (omitted)

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.27-38
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• 2000

This paper proposes how the recurrent neural network controller for a Khepera mobile robot with an obstacle avoiding ability can be determined by co-adaptation of the evolution and learning, The proposed co-adaptation scheme consists of two folds： a population of NN controllers are evolved by the genetic algorithm so that the degree of obstacle avoidance might be reduced through the global searching and each NN controller is trained by CRBP learning so that the running behavior is adapted to its outer environment through the local searching. Experimental results shows that the NN controller coadapted by evolution and learning outperforms its non-learning equivalent evolved by only genetic algorithm in both the ability of obstacle avoidance and the convergence speed reaching to the required running behavior.