{
    "created": "2022-01-11 11:45:05",
    "updated": "2026-04-15 02:07:31",
    "id": "44eda276-e011-45de-9afd-c463e16bebb7",
    "version": 8,
    "ds_topic": null,
    "title_cn": "沙米环境适应性相关SNP（2020年）",
    "title_en": "SNPs associated with environmental adaptation in sago (2020)",
    "ds_abstract": "<p>&emsp;&emsp;通过RAD群体测序进行沙米沙区环境的遗传适应性分析，对所得数据进行SNP calling和质量控制后，最终得到6124个SNP，结合WorldClim database version 1.4 (1950–2000, 下载的生态因子数据，利用Samβada软件进行SNP多样性与环境因子的关联分析，通过G-scores>0.0001来确定相关性，得到沙米环境适应性相关SNP。",
    "ds_source": "<p>&emsp;&emsp;通过RAD群体测序进行沙米沙区环境的遗传适应性分析，对所得数据进行SNP calling和质量控制后，最终得到6124个SNP，结合WorldClim database version 1.4 (1950–2000, 下载的生态因子数据，利用Samβada软件进行SNP多样性与环境因子的关联分析，通过G-scores>0.0001来确定相关性，得到沙米环境适应性相关SNP。",
    "ds_process_way": "<p>&emsp;&emsp;通过RAD群体测序进行沙米沙区环境的遗传适应性分析，对所得数据进行SNP calling和质量控制后，最终得到6124个SNP，结合WorldClim database version 1.4 (1950–2000, 下载的生态因子数据，利用Samβada软件进行SNP多样性与环境因子的关联分析，通过G-scores>0.0001来确定相关性，得到沙米环境适应性相关SNP。",
    "ds_quality": "<p>&emsp;&emsp;数据质量良好。",
    "ds_acq_start_time": "2020-01-01 00:00:00",
    "ds_acq_end_time": "2020-12-31 00:00:00",
    "ds_acq_place": "北方半干旱区",
    "ds_acq_lon_east": null,
    "ds_acq_lat_south": null,
    "ds_acq_lon_west": null,
    "ds_acq_lat_north": null,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "login-access",
    "ds_total_size": 149412,
    "ds_files_count": 2,
    "ds_format": "excel",
    "ds_space_res": null,
    "ds_time_res": "",
    "ds_coordinate": "无",
    "ds_projection": "",
    "ds_thumbnail": "44eda276-e011-45de-9afd-c463e16bebb7.png",
    "ds_thumb_from": 2,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "8534e8f7-cbd5-4771-81d6-d524ffde0065",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "10.12072/ncdc.ZDYF.db1669.2022",
    "subject_codes": [
        "170.4510"
    ],
    "quality_level": 3,
    "publish_time": "2022-02-18 14:34:13",
    "last_updated": "2025-06-30 11:29:10",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.ZDYF.db1669.2022",
    "i18n": {
        "en": {
            "title": "SNPs associated with environmental adaptation in sago (2020)",
            "ds_format": "excel",
            "ds_source": "<p>&emsp; Genetic adaptation analysis of the environment in the sandy sandy area of Shami was carried out by RAD population sequencing, and 6124 SNPs were finally obtained after SNP calling and quality control of the obtained data, which were combined with the WorldClim database version 1.4 (1950-2000,). Combined with the ecological factor data downloaded from WorldClim database version 1.4 (1950-2000,), the correlation analysis between SNP diversity and environmental factors was carried out by using Samβada software, and the correlation was determined by G-scores>0.0001 to obtain the SNPs related to environmental adaptation in sago.",
            "ds_quality": "<p>&emsp; Data quality is good.",
            "ds_ref_way": "",
            "ds_abstract": "<p>  Genetic adaptation analysis of the environment in the sandy sandy area of Shami was carried out by RAD population sequencing, and 6124 SNPs were finally obtained after SNP calling and quality control of the obtained data, which were combined with the WorldClim database version 1.4 (1950-2000,). Combined with the ecological factor data downloaded from WorldClim database version 1.4 (1950-2000,), the correlation analysis between SNP diversity and environmental factors was carried out using Samβada software, and the correlation was determined by G-scores&gt;0.0001 to obtain the SNPs related to the environmental adaptation of sago.</p>",
            "ds_time_res": "",
            "ds_acq_place": "Northern semi-arid region",
            "ds_space_res": "",
            "ds_projection": "",
            "ds_process_way": "<p>&emsp; Genetic adaptation analysis of the environment in the sandy sandy area of Shami was carried out by RAD population sequencing, and 6124 SNPs were finally obtained after SNP calling and quality control of the obtained data, which were combined with the WorldClim database version 1.4 (1950-2000,). Combined with the ecological factor data downloaded from WorldClim database version 1.4 (1950-2000,), the correlation analysis between SNP diversity and environmental factors was carried out by using Samβada software, and the correlation was determined by G-scores>0.0001 to obtain the SNPs related to environmental adaptation in sago.",
            "ds_ref_instruction": ""
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "license_type": "CC BY 4.0",
    "ds_topic_tags": [
        "沙米",
        "RAD群体测序",
        "SNP"
    ],
    "ds_subject_tags": [
        "自然地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "北方半干旱区"
    ],
    "ds_time_tags": [
        2020
    ],
    "ds_contributors": [
        {
            "true_name": "马小飞",
            "email": "maxiaofei@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": "尹晓月",
            "email": "yxyjing@126.com",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        },
        {
            "true_name": "钱朝菊",
            "email": "chaojuqian@lzb.ac.cn",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "马小飞",
            "email": "maxiaofei@lzb.ac.cn",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "敏玉芳",
            "email": "myf@lzb.ac.cn",
            "work_for": "中国科学院西北生态环境资源研究院",
            "country": "中国"
        }
    ],
    "category": "沙漠与荒漠化"
}