该数据集以原始序列数据为基础，经过与GenBank及本地数据库的双重比对，并进一步采用遗传距离分析（如Barcoding gap与序列相似性比较）及系统发育树分析等方法，系统剔除了其中的低质量与冗余序列。这一处理流程显著提升了数据的物种鉴定准确性与数据库整体可靠性，最终构建成高质量的中国干旱区种子植物DNA条形码参考数据库。我们同时更新了该数据库的v2版本，其包含的序列数据已同步公开于GenBank，以期为区域生物多样性监测与保护提供更坚实、持续更新并可公开获取的数据基础\n
本数据以我国青藏高原柴达木盆地为调查核心区，兼顾青藏高原阿里高原谷地等区域，于2017-2021年调查了这些区域的主要荒漠植物，并采集了标本及DNA分子材料。依据项目要求，对每份植物材料的5个DNA条形码片段（ITS，matK, rbcL, trnL-F, psbA-trnH）进行测序。本数据集包含DNA条形码781份3327条，其中柴达木盆地植物DNA条形码696份2951条，阿里地区DNA条形码85份376条。
", "ds_source": "自主产生。
", "ds_process_way": "野外采集、实验试验和数字化加工。
", "ds_quality": "1.植物标本的采集制作及DNA材料的获取\n
\n植物标本在野外采集，并栓挂采集号牌，野外记录采集地点坐标及生境。为了保证凭证标本与DNA材料的一致性，在压制标本过程中，直接从凭证标本上采集无明显病害或虫害的健康叶片，放在纸张很薄的小纸袋内，纸袋上的编号与标本采集号一致。经筛选、剔除腐烂标本，共获得1300份完整标本，标本经压干后上台纸。DNA材料在-80℃冰箱永久保存。\n
\n2.植物标本图像数据获取\n
\n标本图像采用高分辨相机拍摄，进行图像亮度调整和锐化处理，形成植物标本图像数据。\n
\n3.DNA条形码产生\n
\n采用磁珠法或CTAB法提取植物DNA。提取完成后，取少量样品利用琼脂糖凝胶电泳检测DNA的质量和完整性。采用PCR扩增项目要求的5个DNA条形码。扩增产物交由专业测序公司进行测序，为保证获得正确的序列，分别从两端测通。测序使用ABI系列自动测序仪（Applied Biosystems, Foster City, California, USA）。测序引物使用PCR扩增引物。\n
\n得到测序公司返回的峰图后，使用Geneious或Chromas软件进行人工校对，去除两端低质量的碱基序列，将正反序列进行拼接编辑，得到DNA序列并存为FASTA格式文件。为了验证测序的准确性或材料是否受到污染，通过NCBI网站的BLASTn功能检查每个样本已拼接好的DNA条形码序列。若某样本的条形码序列（query sequence）匹配的score值最高者（subject sequence）为同科、同属或同种的序列时，判定此样本在材料采集和实验过程中未出现错误，其条形码序列可初步确定为正确。\n
\n4.DNA条形码信息表生成\n
\n对采样地点、地理坐标、海拔及生境等信息进行整编，同时通过样本编号与植物标本图像数据相衔接，通过样本采集号与实物标本相衔接，最终形成DNA条形码描述信息表。
", "ds_acq_start_time": "2017-01-01 00:00:00", "ds_acq_end_time": "2021-12-31 00:00:00", "ds_acq_place": "青藏高原高寒荒漠", "ds_acq_lon_east": 99.25, "ds_acq_lat_south": 29.666666666666668, "ds_acq_lon_west": 78.4, "ds_acq_lat_north": 39.31666666666667, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 137609, "ds_files_count": 3, "ds_format": "Excel", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "aab68722-5300-48f6-9c90-3aac16e217bf.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "引用方式建议采用如下方式：刘占林，杜岩功，魏兴琥，岳广阳，曹广民，雷云静. 西北大学，中国科学院西北高原生物研究所，中国科学院西北生态环境资源研究院，佛山科学技术学院. 青藏高原高寒荒漠植物DNA条形码数据库（2017-2021）. 2021。", "ds_from_station": null, "organization_id": "7f392ba9-d3f1-4714-b1bc-52ac6d5b09fc", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2025-12-24 18:06:18", "last_updated": "2026-01-09 16:11:31", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.I-VEG.DB7040.2025", "i18n": { "en": { "title": "DNA barcode dataset of alpine desert plants on the Qinghai Tibet Plateau (2017-2021)", "ds_format": "Excel", "ds_source": "Autonomously generated
", "ds_quality": "1. Collection and production of plant specimens and acquisition of DNA material\n
\nPlant specimens were collected in the field with collection number plates bolted on, and the coordinates of the collection site and habitat were recorded in the field. In order to ensure the consistency between the voucher specimens and DNA materials, healthy leaves without obvious diseases or insect pests were collected directly from the voucher specimens in the process of pressing the specimens, and placed in small paper bags with very thin paper, and the numbers on the paper bags were consistent with the specimen collection numbers. After screening and removing decayed specimens, a total of 1,300 complete specimens were obtained, which were pressed dry and then put on the counterpane. the DNA material was permanently preserved in the refrigerator at -80℃.\n
\n2. Image data acquisition of plant specimens\n
\nThe specimen images were captured with a high-resolution camera, and the image brightness was adjusted and sharpened to form the image data of the plant specimens.\n
\n3. DNA barcode generation\n
\nPlant DNA is extracted by magnetic bead method or CTAB method, and after extraction, a small amount of sample is taken to detect the quality and integrity of DNA by agarose gel electrophoresis. PCR was used to amplify the 5 DNA barcodes required by the project. The amplified products were handed over to a professional sequencing company for sequencing, and in order to ensure that the correct sequence was obtained, they were sequenced through from both ends respectively. Sequencing was performed using an ABI series automated sequencer (Applied Biosystems, Foster City, California, USA). Sequencing primers used PCR amplification primers.\n
\nAfter obtaining the peak maps returned by the sequencing company, the DNA sequences were manually aligned using Geneious or Chromas software to remove low-quality base sequences at both ends, and the forward and reverse sequences were spliced and edited to obtain the DNA sequences and saved as FASTA format files. To verify the accuracy of sequencing or whether the material was contaminated, the spliced DNA barcode sequences of each sample were checked through the BLASTn function on the NCBI website. If a sample's barcode sequence (query sequence) matches the highest score value (subject sequence) for the same family, genus or species, it is determined that the sample in the material collection and experimental process did not make mistakes, its barcode sequence can be initially determined as correct.\n
\n4. Generation of DNA barcode information table\n
\nSampling location, geographic coordinates, elevation and habitat information is compiled, and at the same time, the sample number is connected with the image data of the plant specimen, and the sample collection number is connected with the physical specimen, which ultimately forms the DNA barcode description information table.
", "ds_ref_way": "", "ds_abstract": "This dataset is based on raw sequence data, which has been double compared with GenBank and local databases, and further analyzed using genetic distance analysis (such as Barcoding Gap and sequence similarity comparison) and phylogenetic tree analysis to systematically eliminate low-quality and redundant sequences. This processing flow significantly improves the accuracy of species identification and the overall reliability of the database, ultimately constructing a high-quality DNA barcode reference database for seed plants in arid regions of China. We have also updated the v2 version of the database, which contains sequence data that has been synchronized and made public in GenBank, in order to provide a more solid, continuously updated, and publicly available data foundation for regional biodiversity monitoring and protection\n
This data takes the Qaidam Basin on the Qinghai Tibet Plateau in China as the core area of the survey, taking into account regions such as the Ali Plateau valley on the Qinghai Tibet Plateau. From 2017 to 2021, the main desert plants in these areas were surveyed, and specimens and DNA molecular materials were collected. According to project requirements, sequence 5 DNA barcode fragments (ITS, matK, rbcL, trnL-F, psbA trnH) from each plant material. This dataset contains 781 DNA barcodes with 3327 entries, including 696 plant DNA barcodes with 2951 entries in the Qaidam Basin and 85 DNA barcodes with 376 entries in the Ali region.
", "ds_time_res": "", "ds_acq_place": "Qinghai Tibet Plateau Alpine Desert", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Field collection, experimental testing, and digital processing.
", "ds_ref_instruction": "Suggested citation methods include Liu Zhanlin, Du Yangong, Wei Xinghu, Yue Guangyang, Cao Guangmin, and Lei Yunjing Northwest University, Institute of Northwest Plateau Biology, Chinese Academy of Sciences, Northwest Institute of Ecological Environment and Resources, Chinese Academy of Sciences, Foshan Institute of Science and Technology DNA barcode database of alpine desert plants on the Qinghai Tibet Plateau (2017-2021) 2021." } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "DNA条形码", "ITS", "matK", "rbcL", "trnL-F", "trnH-psbA" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原高寒荒漠" ], "ds_time_tags": [ 2017, 2018, 2019, 2020, 2021 ], "ds_contributors": [ { "true_name": "刘占林", "email": "liuzl@nwu.edu.cn", "work_for": "西北大学", "country": "中国" }, { "true_name": "杜岩功", "email": "ygdu@nwipb.cas.cn", "work_for": "中国科学院西北高原生物研究所", "country": "中国" }, { "true_name": "魏兴琥", "email": "weixinghu1964@163.com", "work_for": "佛山科学技术学院", "country": "中国" }, { "true_name": "岳广阳", "email": "yuegy@lzb.ac.cn", "work_for": " 中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "曹广民", "email": "caogm@nwipb.cas.cn", "work_for": "中国科学院西北高原生物研究所", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "刘占林", "email": "liuzl@nwu.edu.cn", "work_for": "西北大学", "country": "中国" } ], "ds_managers": [ { "true_name": "刘占林", "email": "liuzl@nwu.edu.cn", "work_for": "西北大学", "country": "中国" } ], "category": "生态" }