A phenome database (NEAUHLFPD) designed and constructed for broiler lines divergently selected for abdominal fat content
Received date: 2017-02-08
Revised date: 2017-03-10
Online published: 2017-12-25
Supported by
the China Agriculture Research System(CARS-42);the National Natural Science Foundation of China(31472088)
Effective management and analysis of precisely recorded phenotypic traits are important components of the selection and breeding of superior livestocks. Over two decades, we divergently selected chicken lines for abdominal fat content at Northeast Agricultural University (Northeast Agricultural University High and Low Fat, NEAUHLF), and collected large volume of phenotypic data related to the investigation on molecular genetic basis of adipose tissue deposition in broilers. To effectively and systematically store, manage and analyze phenotypic data, we built the NEAUHLF Phenome Database (NEAUHLFPD). NEAUHLFPD included the following phenotypic records: pedigree (generations 1-19) and 29 phenotypes, such as body sizes and weights, carcass traits and their corresponding rates. The design and construction strategy of NEAUHLFPD were executed as follows: (1) Framework design. We used Apache as our web server, MySQL and Navicat as database management tools, and PHP as the HTML-embedded language to create dynamic interactive website. (2) Structural components. On the main interface, detailed introduction on the composition, function, and the index buttons of the basic structure of the database could be found. The functional modules of NEAUHLFPD had two main components: the first module referred to the physical storage space for phenotypic data, in which functional manipulation on data can be realized, such as data indexing, filtering, range-setting, searching, etc.; the second module related to the calculation of basic descriptive statistics, where data filtered from the database can be used for the computation of basic statistical parameters and the simultaneous conditional sorting. NEAUHLFPD could be used to effectively store and manage not only phenotypic, but also genotypic and genomics data, which can facilitate further investigation on the molecular genetic basis of chicken adipose tissue growth and development, and expedite the selection and breeding of broilers with low fat content.
Key words: broiler; abdominal fat rate; divergent selection; phenotype; database
Min Li,Xiangyu Dong,Hao Liang,Li Leng,Hui Zhang,Shouzhi Wang,Hui Li,Zhi-Qiang Du . A phenome database (NEAUHLFPD) designed and constructed for broiler lines divergently selected for abdominal fat content[J]. Hereditas(Beijing), 2017 , 39(5) : 430 -437 . DOI: 10.16288/j.yczz.17-034
| [1] | Wang JF.Advance in animal molecular breeding. J Mt Agric Biol, 2015, 34(3): 1-6. | |||
| [1] | 王嘉福. 畜禽分子育种技术研究进展及趋势. 山地农业生物学报, 2015, 34(3): 1-6. | |||
| [2] | Li D, Chen YQ, Zhao W, Xu M.New ideas and suggestions on the genetic breeding of poultry industry in China. Anim Sci Abroad-Pigs Poultry, 2013, 33(3): 67-70. | |||
| [2] | 李东, 陈印权, 赵薇, 徐敏.我国家禽产业化遗传育种新思路与策划建议. 国外畜牧学-猪与禽, 2013, 33(3): 67-70. | |||
| [3] | Shao C, Sun W.Influence of protein databases in proteomic identification. Chin J Biomed Eng, 2013, 32(2): 129-134. | |||
| [3] | 邵晨, 孙伟. 蛋白质数据库对蛋白质组鉴定的影响. 中国生物医学工程学报, 2013, 32(2): 129-134. | |||
| [4] | Fang G, Chen YJ, Gao G, Liu D, He K, Wu X, Gu XC, Luo JC.Introduction to genome databases. Hereditas (Beijing), 2003, 25(4): 440-444. | |||
| [4] | 方刚, 陈蕴佳, 高歌, 刘翟, 何坤, 吴昕, 顾孝诚, 罗静初. 基因组数据库简介. 遗传, 2003, 25(4): 440-444. | |||
| [5] | Hu DH, Fang P.The retrieval of GenBank by E-mail. Hereditas (Beijing), 1999, 21(6): 43-46. | |||
| [5] | 胡德华, 方平. 基因库(GenBank)的电子邮件检索. 遗传, 1999, 21(6): 43-46. | |||
| [6] | Zhuang YL, Zhou M, Li YD, Shen Y.The application of human mutation databases. Hereditas (Beijing), 2004, 26(4): 514-518. | |||
| [6] | 庄永龙, 周敏, 李衍达, 沈岩. 人类遗传突变数据库及其应用. 遗传, 2004, 26(4): 514-518. | |||
| [7] | Chen HF, Wang JK.The databases of transcription factors. Hereditas (Beijing), 2010, 32(10): 1009-1017. | |||
| [7] | 陈鸿飞, 王进科. 转录因子相关数据库. 遗传, 2010, 32(10): 1009-1017. | |||
| [8] | Li ZF, Li YJ, Zhao DS, Hang XY, Wang ZZ, Luo ZG, Zhang CG.Construction of standard human transcript dataset based on refseq and human genome sequence database. Hereditas (Beijing), 2006, 28(3): 329-333. | |||
| [8] | 李稚锋, 李玉鉴, 赵东升, 杭兴宜, 王正志, 骆志刚, 张成岗. 基于RefSeq数据库的人类标准转录数据集的构建. 遗传, 2006, 28(3): 329-333. | |||
| [9] | Robinson PN.Deep phenotyping for precision medicine. Hum Mutat, 2012, 33(5): 777-780. | |||
| [10] | Tang QM, Zhou Y, He BR, Mo QH, Li Z, Huang DH, Liang MX, Shen WD.Establishment of Rh blood group phenotype database and its application in clinical blood transfusion. J Clin Transfus Lab Med, 2009, 11(4): 328-330. | |||
| [10] | 唐秋民, 周燕, 何保仁, 莫秋红, 李忠, 黄东辉, 梁明霞, 申卫东. Rh血型表型库的建立及在临床输血中的应用. 临床输血与检验, 2009, 11(4): 328-330. | |||
| [11] | Chen WH, Wang Q, Pu JH.Applications of computers in modern poultry production. J Anim Sci Vet Med, 2006, 25(3): 29-
/
|