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IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility
Infertility is a complex multifactorial disease that affects up to 10% of couples across the world. However, many mechanisms of infertility remain unclear due to the lack of studies based on systematic knowledge, leading to ineffective treatment and/or transmission of genetic defects to offspring. H...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779019/ https://www.ncbi.nlm.nih.gov/pubmed/32941628 http://dx.doi.org/10.1093/nar/gkaa753 |
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author | Wu, Jing Li, Danjun Liu, Xinyi Li, Qian He, Xinheng Wei, Jiale Li, Xinyi Li, Mingyu Rehman, Ashfaq Ur Xia, Yujia Wu, Chengwei Zhang, Jian Lu, Xuefeng |
author_facet | Wu, Jing Li, Danjun Liu, Xinyi Li, Qian He, Xinheng Wei, Jiale Li, Xinyi Li, Mingyu Rehman, Ashfaq Ur Xia, Yujia Wu, Chengwei Zhang, Jian Lu, Xuefeng |
author_sort | Wu, Jing |
collection | PubMed |
description | Infertility is a complex multifactorial disease that affects up to 10% of couples across the world. However, many mechanisms of infertility remain unclear due to the lack of studies based on systematic knowledge, leading to ineffective treatment and/or transmission of genetic defects to offspring. Here, we developed an infertility disease database to provide a comprehensive resource featuring various factors involved in infertility. Features in the current IDDB version were manually curated as follows: (i) a total of 307 infertility-associated genes in human and 1348 genes associated with reproductive disorder in 9 model organisms; (ii) a total of 202 chromosomal abnormalities leading to human infertility, including aneuploidies and structural variants; and (iii) a total of 2078 pathogenic variants from infertility patients’ samples across 60 different diseases causing infertility. Additionally, the characteristics of clinically diagnosed infertility patients (i.e. causative variants, laboratory indexes and clinical manifestations) were collected. To the best of our knowledge, the IDDB is the first infertility database serving as a systematic resource for biologists to decipher infertility mechanisms and for clinicians to achieve better diagnosis/treatment of patients from disease phenotype to genetic factors. The IDDB is freely available at http://mdl.shsmu.edu.cn/IDDB/. |
format | Online Article Text |
id | pubmed-7779019 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77790192021-01-07 IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility Wu, Jing Li, Danjun Liu, Xinyi Li, Qian He, Xinheng Wei, Jiale Li, Xinyi Li, Mingyu Rehman, Ashfaq Ur Xia, Yujia Wu, Chengwei Zhang, Jian Lu, Xuefeng Nucleic Acids Res Database Issue Infertility is a complex multifactorial disease that affects up to 10% of couples across the world. However, many mechanisms of infertility remain unclear due to the lack of studies based on systematic knowledge, leading to ineffective treatment and/or transmission of genetic defects to offspring. Here, we developed an infertility disease database to provide a comprehensive resource featuring various factors involved in infertility. Features in the current IDDB version were manually curated as follows: (i) a total of 307 infertility-associated genes in human and 1348 genes associated with reproductive disorder in 9 model organisms; (ii) a total of 202 chromosomal abnormalities leading to human infertility, including aneuploidies and structural variants; and (iii) a total of 2078 pathogenic variants from infertility patients’ samples across 60 different diseases causing infertility. Additionally, the characteristics of clinically diagnosed infertility patients (i.e. causative variants, laboratory indexes and clinical manifestations) were collected. To the best of our knowledge, the IDDB is the first infertility database serving as a systematic resource for biologists to decipher infertility mechanisms and for clinicians to achieve better diagnosis/treatment of patients from disease phenotype to genetic factors. The IDDB is freely available at http://mdl.shsmu.edu.cn/IDDB/. Oxford University Press 2020-09-17 /pmc/articles/PMC7779019/ /pubmed/32941628 http://dx.doi.org/10.1093/nar/gkaa753 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Wu, Jing Li, Danjun Liu, Xinyi Li, Qian He, Xinheng Wei, Jiale Li, Xinyi Li, Mingyu Rehman, Ashfaq Ur Xia, Yujia Wu, Chengwei Zhang, Jian Lu, Xuefeng IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
title | IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
title_full | IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
title_fullStr | IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
title_full_unstemmed | IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
title_short | IDDB: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
title_sort | iddb: a comprehensive resource featuring genes, variants and characteristics associated with infertility |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779019/ https://www.ncbi.nlm.nih.gov/pubmed/32941628 http://dx.doi.org/10.1093/nar/gkaa753 |
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