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Liu, Zhangguo,Zheng, Qi,Zhang, Xueyu,Lu, Lizhi Asian Australasian Association of Animal Productio 2013 Animal Bioscience Vol.26 No.5
The objective of this study was to get a comprehensive understanding of how genes in chicken shell gland modulate eggshell strength at the early stage of active calcification. Four 32-week old of purebred Xianju hens with consistent high or low shell breakage strength were grouped into two pairs. Using Affymetrix Chicken Array, a whole-transcriptome analysis was performed on hen's shell gland at 9 h post oviposition. Gene ontology enrichment analysis for differentially expressed (DE) transcripts was performed using the web-based GOEAST, and the validation of DE-transcripts was tested by qRT-PCR. 1,195 DE-transcripts, corresponding to 941 unique genes were identified in hens with strong eggshell compared to weak shell hens. According to gene ontology annotations, there are 77 DE-transcripts encoding ion transporters and secreted extracellular matrix proteins, and at least 26 DE-transcripts related to carbohydrate metabolism or post-translation glycosylation modification; furthermore, there are 88 signaling DE-transcripts. GO term enrichment analysis suggests that some DE-transcripts mediate reproductive hormones or neurotransmitters to affect eggshell quality through a complex suite of biophysical processes. These results reveal some candidate genes involved with eggshell strength at the early stage of active calcification which may facilitate our understanding of regulating mechanisms of eggshell quality.
Human Activities Recognition Based on Skeleton Information via Sparse Representation
Liu, Suolan,Kong, Lizhi,Wang, Hongyuan Korean Institute of Information Scientists and Eng 2018 Journal of Computing Science and Engineering Vol.12 No.1
Human activities recognition is a challenging task due to its complexity of human movements and the variety performed by different subjects for the same action. This paper presents a recognition algorithm by using skeleton information generated from depth maps. Concatenating motion features and temporal constraint feature produces feature vector. Reducing dictionary scale proposes an improved fast classifier based on sparse representation. The developed method is shown to be effective by recognizing different activities on the UTD-MHAD dataset. Comparison results indicate superior performance of our method over some existing methods.
The impact of diet on the composition and relative abundance of rumen microbes in goat
Kaizhen Liu,Qin Xu,Lizhi Wang,Jiwen Wang,Wei Guo,Meili Zhou 아세아·태평양축산학회 2017 Animal Bioscience Vol.30 No.4
Objective: This experiment was conducted to explore the impact of diet on the ruminal microbial community in goats. Methods: Twelve goats were divided into two groups and fed complete feed (CF) or all forage (AF) diet. The total microbial DNAs in the rumen liquid were extracted. The V4 region of microbial 16S rRNA genes was amplified and sequenced using high-throughput. Information of sequences was mainly analyzed by QIIME 1.8.0. Results: The results showed that Bacteroidetes and Firmicutes were the most predominant microbial phyla in the rumen of all goats. At genus level, the abundance of fiber-digesting bacteria such as Ruminococcus and Lachnospiracea incertae sedis was significantly higher in AF than that in CF, while the levels of fat-degrading bacterium Anaerovibrio and protein-degrading bacterium Pseudomonas were opposite. The core shared genera, Prevotella and Butyrivibrio were widespread in the rumen of goats and no significant difference was observed in relative abundance between groups. Conclusion: We concluded that the richness of fiber-, protein-, and fat-digesting bacteria was affected by diet and tended to increase with the rise of their corresponding substrate contents in the ration; some bacteria shared by all goats maintained stable despite the difference in the ration, and they might be essential in maintaining the normal function of rumen.
Transcriptome analysis of the livers of ducklings hatched normally and with assistance
Yali Liu,Shishan He,Tao Zeng,Xue Du,Junda Shen,Ayong Zhao,Lizhi Lu 아세아·태평양축산학회 2017 Animal Bioscience Vol.30 No.6
Objective: “Hatchability” is an important economic trait in domestic poultry. Studies on poultry hatchability focus mainly on the genetic background, egg quality, and incubation conditions, whereas the molecular mechanisms behind the phenomenon that some ducklings failed to break their eggshells are poorly understood. Methods: In this study, the transcriptional differences between the livers of normally hatched and assisted ducklings were systematically analyzed. Results: The results showed that the clean reads were de novo assembled into 161,804 and 159,083 unigenes (≥200-bp long) by using Trinity, with an average length of 1,206 bp and 882 bp, respectively. The defined criteria of the absolute value of log2 fold-change ≥1 and false discovery rate≤0.05 were differentially expressed and were significant. As a result, 1,629 unigenes were identified, the assisted ducklings showed 510 significantly upregulated and 1,119 significantly down-regulated unigenes. In general, the metabolic rate in the livers of the assisted ducklings was lower than that in the normal ducklings; however, compared to normal ducklings, glucose- 6-phosphatase and ATP synthase subunit alpha 1 associated with energy metabolism were significantly upregulated in the assisted group. The genes involved in immune defense such as major histocompatibility complex (MHC) class I antigen alpha chain and MHC class II beta chain 1 were downregulated in the assisted ducklings. Conclusion: These data provide abundant sequence resources for studying the functional genome of the livers in ducks and other poultry. In addition, our study provided insight into the molecular mechanism by which the phenomenon of weak embryos is regulated.
Kaizhen Liu,Lizhi Wang,Tianhai Yan,Zhisheng Wang,Bai Xue,Quanhui Peng 아세아·태평양축산학회 2019 Animal Bioscience Vol.32 No.1
Objective: This experiment was conducted to compare the structure and composition of ruminal microorganisms in goats with high and low neutral detergent fibre (NDF) digestibility. Methods: Nineteen crossbred goats were used as experimental animals and fed the same total mixed rations during the 30-day pre-treatment and 6-day digestion trialperiods. All faeces were collected during the digestion period for measuring the NDF digestibility. Then, high and the low NDF digestibility individuals were chosen for the high NDF digestibility group (HFD) and low NDF digestibility group (LFD), respectively. Rumen contents were collected for total microbial DNA extraction. The V4 region of the bacterial 16S rRNA gene was amplified using universal primers of bacteria and sequenced using high-throughput sequencer. The sequences were mainly analysed by QIIME 1.8.0. Results: A total of 18,694 operational taxonomic units were obtained, within 81.98% belonged to bacteria, 6.64% belonged to archaea and 11.38% was unassigned microorganisms. Bacteroidetes, Firmicutes, and Proteobacteria were the predominant microbial phyla in both groups. At the genus level, the relative abundance of fifteen microorganisms were significantly higher (p<0.05) and six microorganisms were extremely significantly higher (p<0.01) in LFD than HFD. Overall, 176 core shared genera were identified in the two groups. The relative abundance of 2 phyla, 5 classes, 10 orders, 13 families and 15 genera had a negative correlation with NDF digestibility, but only the relative abundance of Pyramidobacter had a positive correlation with NDF digestibility. Conclusion: There were substantial differences in NDF digestibility among the individual goats, and the NDF digestibility had significant correlation with the relative abundance of some ruminal microorganisms.
Human Activities Recognition Based on Skeleton Information via Sparse Representation
Suolan Liu,Lizhi Kong,Hongyuan Wang 한국정보과학회 2018 Journal of Computing Science and Engineering Vol.12 No.1
Human activities recognition is a challenging task due to its complexity of human movements and the variety performed by different subjects for the same action. This paper presents a recognition algorithm by using skeleton information generated from depth maps. Concatenating motion features and temporal constraint feature produces feature vector. Reducing dictionary scale proposes an improved fast classifier based on sparse representation. The developed method is shown to be effective by recognizing different activities on the UTD-MHAD dataset. Comparison results indicate superior performance of our method over some existing methods.