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      Uncovering the embryonic development-related proteome and metabolome signatures in breast muscle and intramuscular fat of fast-and slow-growing chickens

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          Abstract

          Background

          Skeletal muscle development is closely linked to meat production and its quality. This study is the first to quantify the proteomes and metabolomes of breast muscle in two distinct chicken breeds at embryonic day 12 (ED 12), ED 17, post-hatch D 1 and D 14 using mass spectrometry-based approaches.

          Results

          Results found that intramuscular fat (IMF) accumulation increased from ED 17 to D 1 and that was exactly the opposite of when most obvious growth of muscle occurred (ED 12 - ED 17 and D 1 - D 14). For slow-growing Beijing-You chickens, Ingenuity Pathway Analysis of 77–99 differential abundance (DA) proteins and 63–72 metabolites, indicated significant enrichment of molecules and pathways related to protein processing and PPAR signaling. For fast-growing Cobb chickens, analysis of 68–95 DA proteins and 56–59 metabolites demonstrated that molecules and pathways related to ATP production were significantly enriched after ED12. For IMF, several rate-limiting enzymes for beta-oxidation of fatty acid (ACADL, ACAD9, HADHA and HADHB) were identified as candidate biomarkers for IMF deposition in both breeds.

          Conclusions

          This study found that ED 17 - D 1 was the earliest period for IMF accumulation. Pathways related to protein processing and PPAR signaling were enriched to support high capacity of embryonic IMF accumulation in Beijing-You. Pathways related to ATP production were enriched to support the fast muscle growth in Cobb. The beta-oxidation of fatty acid is identified as the key pathway regulating chicken IMF deposition at early stages.

          Electronic supplementary material

          The online version of this article (10.1186/s12864-017-4150-3) contains supplementary material, which is available to authorized users.

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          Most cited references30

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          The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

          The Paragon Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2-5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space.
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            Nutrient Requirements of Poultry

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              Identification of differentially expressed genes and pathways for intramuscular fat deposition in pectoralis major tissues of fast-and slow-growing chickens

              Background Intramuscular fat (IMF) is one of the important factors influencing meat quality, however, for chickens, the molecular regulatory mechanisms underlying this trait have not yet been determined. In this study, a systematic identification of candidate genes and new pathways related to IMF deposition in chicken breast tissue has been made using gene expression profiles of two distinct breeds: Beijing-you (BJY), a slow-growing Chinese breed possessing high meat quality and Arbor Acres (AA), a commercial fast-growing broiler line. Results Agilent cDNA microarray analyses were conducted to determine gene expression profiles of breast muscle sampled at different developmental stages of BJY and AA chickens. Relative to d 1 when there is no detectable IMF, breast muscle at d 21, d 42, d 90 and d 120 (only for BJY) contained 1310 differentially expressed genes (DEGs) in BJY and 1080 DEGs in AA. Of these, 34–70 DEGs related to lipid metabolism or muscle development processes were examined further in each breed based on Gene Ontology (GO) analysis. The expression of several DEGs was correlated, positively or negatively, with the changing patterns of lipid content or breast weight across the ages sampled, indicating that those genes may play key roles in these developmental processes. In addition, based on KEGG pathway analysis of DEGs in both BJY and AA chickens, it was found that in addition to pathways affecting lipid metabolism (pathways for MAPK & PPAR signaling), cell junction-related pathways (tight junction, ECM-receptor interaction, focal adhesion, regulation of actin cytoskeleton), which play a prominent role in maintaining the integrity of tissues, could contribute to the IMF deposition. Conclusion The results of this study identified potential candidate genes associated with chicken IMF deposition and imply that IMF deposition in chicken breast muscle is regulated and mediated not only by genes and pathways related to lipid metabolism and muscle development, but also by others involved in cell junctions. These findings establish the groundwork and provide new clues for deciphering the molecular mechanisms underlying IMF deposition in poultry. Further studies at the translational and posttranslational level are now required to validate the genes and pathways identified here.
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                Author and article information

                Contributors
                liuranran112@126.com
                913870763@qq.com
                liujie84130@163.com
                wangjie4007@126.com
                zhengmaiqing@caas.cn
                710077657@qq.com
                tcsxingsy@126.com
                cuihuanxian78@126.com
                qli2014@126.com
                zhaoguiping@caas.cn
                wenjie@caas.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                23 October 2017
                23 October 2017
                2017
                : 18
                : 816
                Affiliations
                [1 ]GRID grid.464332.4, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, ; No. 2 Yuanmingyuan W Rd, Beijing, 100193 People’s Republic of China
                [2 ]State Key Laboratory of Animal Nutrition, Beijing, People’s Republic of China
                Article
                4150
                10.1186/s12864-017-4150-3
                5653991
                29061108
                ba6aca63-fa85-4492-aad1-765cce581108
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 May 2017
                : 2 October 2017
                Funding
                Funded by: 863 project
                Award ID: 2013AA102501
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31201797
                Award Recipient :
                Funded by: Agricultural Science and Technology Innovation Program
                Award ID: ASTIP-IAS04;ASTIP-IAS-TS-15
                Award Recipient :
                Funded by: National Nonprofit Institute Research Grant
                Award ID: 2017ywf-zd-2
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Genetics
                Genetics

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