Infertility is a major worldwide health problem and is estimated to affect 8–12% of couples in the reproductive-age population. Successful reproduction requires gamete maturation, fertilization, and early embryo development. One of the most common causes of male infertility is abnormal sperm, such as globozoospermia, acephalic spermatozoa, macrozoospermia, and multiple morphological abnormalities of sperm flagella. For example, DPY19L2 gene variation is the main cause of globozoospermia, SUN5, PMFBP1, and HOOK1 genes variation can lead to acephalic spermatozoa, and AURKC gene variation can cause macrozoospermia. For women, ovarian hypoplasia (OD) and premature ovarian insufficiency (POI) are related to genetic factors. Mutations in TUBB8, PATL2, WEE2, and ZP genes can lead to oocyte maturation disorders. Early embryonic arrest and recurrent abortion may also be related to genetic abnormalities.
Reproductive diseases associated with physical and mental health greatly affect families. The fertility assessment of patients with abnormal sperm should be considered in combination with the proportion of abnormal sperm and the type of malformation. Genetic screening can help patients and their families avoid the financial and psychological stress caused by repeated IVF failure. This Research Topic focuses on the latest advances in the genetics of reproductive system diseases such as infertility, looking forward to finding potential disease genes, and mechanisms through advanced technologies such as high-throughput sequencing, which is beneficial to the search for therapeutic methods.
The topics of interest will consist of (but will not be limited to) the following:
1. Newly identified potential disease genes that can cause male/female infertility
2. Genomics and mechanisms of abnormal sperm generation and function
3. Pathogenic genes and mechanisms of oocyte maturation disorders
4. Recent advances in diagnosis and treatment related to reproductive diseases
5. Application of bioinformatics and other big data analysis methods in reproductive diseases such as artificial intelligence and machine learning
6. Genomics of recurrent abortion
Infertility is a major worldwide health problem and is estimated to affect 8–12% of couples in the reproductive-age population. Successful reproduction requires gamete maturation, fertilization, and early embryo development. One of the most common causes of male infertility is abnormal sperm, such as globozoospermia, acephalic spermatozoa, macrozoospermia, and multiple morphological abnormalities of sperm flagella. For example, DPY19L2 gene variation is the main cause of globozoospermia, SUN5, PMFBP1, and HOOK1 genes variation can lead to acephalic spermatozoa, and AURKC gene variation can cause macrozoospermia. For women, ovarian hypoplasia (OD) and premature ovarian insufficiency (POI) are related to genetic factors. Mutations in TUBB8, PATL2, WEE2, and ZP genes can lead to oocyte maturation disorders. Early embryonic arrest and recurrent abortion may also be related to genetic abnormalities.
Reproductive diseases associated with physical and mental health greatly affect families. The fertility assessment of patients with abnormal sperm should be considered in combination with the proportion of abnormal sperm and the type of malformation. Genetic screening can help patients and their families avoid the financial and psychological stress caused by repeated IVF failure. This Research Topic focuses on the latest advances in the genetics of reproductive system diseases such as infertility, looking forward to finding potential disease genes, and mechanisms through advanced technologies such as high-throughput sequencing, which is beneficial to the search for therapeutic methods.
The topics of interest will consist of (but will not be limited to) the following:
1. Newly identified potential disease genes that can cause male/female infertility
2. Genomics and mechanisms of abnormal sperm generation and function
3. Pathogenic genes and mechanisms of oocyte maturation disorders
4. Recent advances in diagnosis and treatment related to reproductive diseases
5. Application of bioinformatics and other big data analysis methods in reproductive diseases such as artificial intelligence and machine learning
6. Genomics of recurrent abortion
