Human normal
thyroid database

  Thyroid gland is an endocrine gland, found at the front of the neck, below the laryngeal prominence in human body. The thyroid gland secretes thyroid hormones, which influence the metabolic rate, protein synthesis, development and have a wide range of other effects. The thyroid hormones T3 and T4 are created from iodine and tyrosine. The thyroid also produces calcitonin, which plays a role in calcium homeostasis.Thyroid diseases are the general popular malignancy of the endocrine system. And proteomics is a useful strategy to dissect the complex pathological situation of disease. Enhanced knowledge of the normal tissue proteome would facilitate studies of related diseases and give the molecular insight into health thyroid function.

  The recent rapid development of LC-MS/MS technologies has provided a powerful discovery platform that allows for the global proteomic coverage of thyroid. High pH reverse-phase liquid chromatography (hp-RPLC) is well established as a first-dimension peptide fractionation method that can be coupled with routine nano-RPLC-MS/MS. The TripleTOF 5600 system combines high resolution and mass accuracy with high rates of MS/MS acquisition, and provides a desirable discovery platform for the in-depth profiling of complex biological mixtures. Herein, based on the combination of hp-RPLC and TripleTOF 5600, resulting proteomics data from low samples (with 14 high-abundance proteins depletion) and raw samples (without immunoaffinity depletion) were used to produce a comprehensive map of the human thyroid proteome. A dataset of Chinese human normal thyroid proteome, including 5602 non-redundant proteins (more than 2 unique peptides), 71,157 peptides and 282,667 MS/MS spectra were presented and available for freely downloaded. This dataset will offer a useful baseline reference for thyroid biomarker discovery and provide insight into the further understanding of thyroid physiology.

Address:5 Dong Dan San Tiao BeiJing, 100005, China
Institute of Basic Medical Sciences Chinese Academy of Medical Sciences
Copyright by National Scientific Data Sharing Platform for Population and Health Biolicine Information Center
Beijing ICP filing:  09030020       Beijing public security preparation:  110402450025