Genetic Insight Into Human Infertility from Mouse Models
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Non-Syndromic Monogenic Male Infertility
Acta Biomed 2019; Vol. 90, Supplement 10: 62-67 DOI: 10.23750/abm.v90i10-S.8762 © Mattioli 1885 Review Non-syndromic monogenic male infertility Giulia Guerri1, Tiziana Maniscalchi2, Shila Barati2, Gian Maria Busetto3, Francesco Del Giudice3, Ettore De Berardinis3, Rossella Cannarella4, Aldo Eugenio Calogero4, Matteo Bertelli2 1 MAGI’s Lab, Rovereto (TN), Italy; 2 MAGI Euregio, Bolzano, Italy; 3 Department of Urology, University of Rome La Sapien- za, Policlinico Umberto I, Rome, Italy; 4 Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy Summary. Infertility is a widespread clinical problem affecting 8-12% of couples worldwide. Of these, about 30% are diagnosed with idiopathic infertility since no causative factor is found. Overall 40-50% of cases are due to male reproductive defects. Numerical or structural chromosome abnormalities have long been associ- ated with male infertility. Monogenic mutations have only recently been addressed in the pathogenesis of this condition. Mutations of specific genes involved in meiosis, mitosis or spermiohistogenesis result in spermato- genic failure, leading to the following anomalies: insufficient (oligozoospermia) or no (azoospermia) sperm production, limited progressive and/or total sperm motility (asthenozoospermia), altered sperm morphology (teratozoospermia), or combinations thereof. Androgen insensitivity, causing hormonal and sexual impair- ment in males with normal karyotype, also affects male fertility. The genetic causes of non-syndromic mono- genic of male infertility are summarized in this article and a gene panel is proposed. (www.actabiomedica.it) Key words: male infertility, oligozoospermia, azoospermia, asthenozoospermia, teratozoospermia, spermato- genic failure, androgen insensitivity syndrome Introduction development. Genetic causes of male infertility are outlined in Table 1. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
The Role of Y Chromosome Deletions in Male Infertility
European Journal of Endocrinology (2000) 142 418–430 ISSN 0804-4643 INVITED REVIEW The role of Y chromosome deletions in male infertility Kun Ma, Con Mallidis and Shalender Bhasin Division of Endocrinology, Metabolism and Molecular Medicine, Department of Internal Medicine, Charles R Drew University of Medicine and Science, 1731 East 120th Street, Los Angeles, California 90050, USA (Correspondence should be addressed to K Ma; Email: [email protected]) Abstract Male infertility affects approximately 2–7% of couples around the world. Over one in ten men who seek help at infertility clinics are diagnosed as severely oligospermic or azoospermic. Recent extensive molecular studies have revealed that deletions in the azoospermia factor region of the long arm of the Y chromosome are associated with severe spermatogenic impairment (absent or severely reduced germ cell development). Genetic research into male infertility, in the last 7 years, has resulted in the isolation of a great number of genes or gene families on the Y chromosome, some of which are believed to influence spermatogenesis. European Journal of Endocrinology 142 418–430 Introduction of Infertility, with the objective of creating a standard protocol for the investigation of infertile couples. Normal Defective spermatogenesis is the result of a multitude of semen was classified as containing a sperm concentra- causes, such as diseases, malnutrition, endocrinological 6 tion of at least 20 × 10 /ml, of which more than 40% disorders, genetic defects or environmental hazards (1). are progressively motile, more than 60% are alive, and Genetic defects, such as mutations and chromosomal over 50% show normal morphology. In addition, the abnormalities, have been estimated to account for at 6 semen should contain no more than 1 × 10 /ml of white least 30% of male infertility (2). -
Detection of Genetic Variations of Five MMAF-Related Genes and Their
Detection of genetic variations of ve MMAF-related genes and their associations with litter size in goat Zhen Wang Northwest Agriculture and Forestry University Yun Pan Northwest Agriculture and Forestry University Libang He Northwest Agriculture and Forestry University Hong Chen Northwest Agriculture and Forestry University Chuanying Pan Northwest Agriculture and Forestry University Lei Qu Yulin University Xiaoyue Song Yulin University Xianyong Lan ( [email protected] ) https://orcid.org/0000-0003-2254-5805 Research article Keywords: goats; insertion/deletion (indel); MMAF; DNAH1; litter sizes; correlation analysis Posted Date: September 12th, 2019 DOI: https://doi.org/10.21203/rs.2.14419/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/13 Abstract Background: Multiple morphological abnormalities of the sperm agella (MMAF) makes an assignable contribution to male infertility, including QRICH2 , CFAP43 , CFAP44 , CFAP69 , CCDC39 , AKAP4 and DNAH1 gene. This work studied 28 putative indel mutations of MMAF related genes including QRICH2 , CFAP69 , CFAP43 , CCDC39 and DNAH1 gene and their correlation with the rst-born litter sizes of 769 Shaanbei white cashmere (SBWC) goats. Results: Electrophoresis and DNA sequencing analysis showed the 11-bp indel within QRICH2 ( QRICH2 -P4), the three indel variations in CFAP69 ( CFAP69 -P4, CFAP69 - P6 and CFAP69 -P7) and the 27-bp indel of DNAH1 ( DNAH1 -P1) were found to be polymorphic. The 27- bp indel variation within DNAH1 was not in consistent with HWE and the other four indel of QRICH2 and CFAP69 were in consistent with HWE. The linkage disequilibrium (LD) analysis showed the 8-bp indel ( CFAP69 -P4) and the 6-bp indel ( CFAP69- P6) within CFAP69 were in complete LD with each other (D'=0.99, r 2 =1.00). -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Fig1-13Tab1-5.Pdf
Supplementary Information Promoter hypomethylation of EpCAM-regulated bone morphogenetic protein genes in advanced endometrial cancer Ya-Ting Hsu, Fei Gu, Yi-Wen Huang, Joseph Liu, Jianhua Ruan, Rui-Lan Huang, Chiou-Miin Wang, Chun-Liang Chen, Rohit R. Jadhav, Hung-Cheng Lai, David G. Mutch, Paul J. Goodfellow, Ian M. Thompson, Nameer B. Kirma, and Tim Hui-Ming Huang Tables of contents Page Table of contents 2 Supplementary Methods 4 Supplementary Figure S1. Summarized sequencing reads and coverage of MBDCap-seq 8 Supplementary Figure S2. Reproducibility test of MBDCap-seq 10 Supplementary Figure S3. Validation of MBDCap-seq by MassARRAY analysis 11 Supplementary Figure S4. Distribution of differentially methylated regions (DMRs) in endometrial tumors relative to normal control 12 Supplementary Figure S5. Network analysis of differential methylation loci by using Steiner-tree analysis 13 Supplementary Figure S6. DNA methylation distribution in early and late stage of the TCGA endometrial cancer cohort 14 Supplementary Figure S7. Relative expression of BMP genes with EGF treatment in the presence or absence of PI3K/AKT and Raf (MAPK) inhibitors in endometrial cancer cells 15 Supplementary Figure S8. Induction of invasion by EGF in AN3CA and HEC1A cell lines 16 Supplementary Figure S9. Knockdown expression of BMP4 and BMP7 in RL95-2 cells 17 Supplementary Figure S10. Relative expression of BMPs and BMPRs in normal endometrial cell and endometrial cancer cell lines 18 Supplementary Figure S11. Microfluidics-based PCR analysis of EMT gene panel in RL95-2 cells with or without EGF treatment 19 Supplementary Figure S12. Knockdown expression of EpCAM by different shRNA sequences in RL95-2 cells 20 Supplementary Figure S13. -
Supplementary Table 1
Supplementary Table 1. 492 genes are unique to 0 h post-heat timepoint. The name, p-value, fold change, location and family of each gene are indicated. Genes were filtered for an absolute value log2 ration 1.5 and a significance value of p ≤ 0.05. Symbol p-value Log Gene Name Location Family Ratio ABCA13 1.87E-02 3.292 ATP-binding cassette, sub-family unknown transporter A (ABC1), member 13 ABCB1 1.93E-02 −1.819 ATP-binding cassette, sub-family Plasma transporter B (MDR/TAP), member 1 Membrane ABCC3 2.83E-02 2.016 ATP-binding cassette, sub-family Plasma transporter C (CFTR/MRP), member 3 Membrane ABHD6 7.79E-03 −2.717 abhydrolase domain containing 6 Cytoplasm enzyme ACAT1 4.10E-02 3.009 acetyl-CoA acetyltransferase 1 Cytoplasm enzyme ACBD4 2.66E-03 1.722 acyl-CoA binding domain unknown other containing 4 ACSL5 1.86E-02 −2.876 acyl-CoA synthetase long-chain Cytoplasm enzyme family member 5 ADAM23 3.33E-02 −3.008 ADAM metallopeptidase domain Plasma peptidase 23 Membrane ADAM29 5.58E-03 3.463 ADAM metallopeptidase domain Plasma peptidase 29 Membrane ADAMTS17 2.67E-04 3.051 ADAM metallopeptidase with Extracellular other thrombospondin type 1 motif, 17 Space ADCYAP1R1 1.20E-02 1.848 adenylate cyclase activating Plasma G-protein polypeptide 1 (pituitary) receptor Membrane coupled type I receptor ADH6 (includes 4.02E-02 −1.845 alcohol dehydrogenase 6 (class Cytoplasm enzyme EG:130) V) AHSA2 1.54E-04 −1.6 AHA1, activator of heat shock unknown other 90kDa protein ATPase homolog 2 (yeast) AK5 3.32E-02 1.658 adenylate kinase 5 Cytoplasm kinase AK7 -
Role of Genetic Testing in Male Infertility
eJKI Vol. 6, No. 1 April 2018 Role of Genetic Testing in Male Infertility REVIEW ARTICLE Role of Genetic Testing in Male Infertility Ponco Birowo Department of Urology, Faculty of Medicine, Universitas Indonesia/ Dr. Cipto Mangunkusumo Hospital, Jakarta, Indonesia Accepted 16 April 2018 Coressponding author: [email protected] DOI: 10.23886/ejki.6.9408 Abstract Male-factor infertility is responsible for 30-55% of all infertility cases. The causes of male infertility include varicocele, endocrine disorders, genital tract infections, genetic disorders and idiopathic. It is estimated that genetic abnormalities contribute to 50% of male infertility. In daily practice, the diagnosis of male infertility has been based on history taking, relevant physical examination, hormone tests and basic semen analysis with a strong emphasis on the assessment of sperm concentration, motility, and morphology. Although recent development in assisted-reproductive technologies such as in vitro fertilization and intrauterine insemination increases the chance of clinical pregnancy and live birth, genetic counseling and testing should always be performed whenever genetic risks are related to the cause of infertility for the identification of possible genetic abnormalities and to assess the risk of transmitting the genetic defects to future generations. Genetic defects affect male infertility by disrupting hormonal homeostasis, spermatogenesis, and sperm quality. These genetic defects include chromosomal abnormalities (e.g. Klinefelter Syndrome), Y chromosome deletions, and cystic fibrosis transmembrane conductance regulator gene mutations. The utilization of genetic counseling and testing is also important to predict the success of sperm retrieval in men with certain genetic abnormalities. To name a few, genetic analysis at the chromosomal level (karyotyping), androgen receptor gene mutations test, cystic fibrosis test, and Y chromosome microdeletions analysis should be considered in the diagnosis of male factor infertility where genetic risks are present. -
Pediatric and Adolescent Oncofertility in Male Patients—From Alpha to Omega
G C A T T A C G G C A T genes Review Pediatric and Adolescent Oncofertility in Male Patients—From Alpha to Omega Ovidiu Bîcă 1, Ioan Sârbu 2,3,* and Carmen Iulia Ciongradi 2,3 1 2nd Department of Morphofunctional Sciences—Cell and Molecular Biology, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Ias, i, Romania; [email protected] 2 2nd Department of Surgery—Pediatric Surgery and Orthopedics, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Ias, i, Romania; [email protected] 3 Department of Pediatric and Orthopaedic Surgery, “Sfânta Maria” Emergency Children Hospital, 700309 Ias, i, Romania * Correspondence: [email protected]; Tel.: +40-745-760-716 Abstract: This article reviews the latest information about preserving reproductive potential that can offer enhanced prospects for future conception in the pediatric male population with cancer, whose fertility is threatened because of the gonadotoxic effects of chemotherapy and radiation. An estimated 400,000 children and adolescents aged 0–19 years will be diagnosed with cancer each year. Fertility is compromised in one-third of adult male survivors of childhood cancer. We present the latest approaches and techniques for fertility preservation, starting with fertility preservation counselling, a clinical practice guideline used around the world and finishing with recent advances in basic science and translational research. Improving strategies for the maturation of germ cells in vitro combined with new molecular techniques for gene editing could be the next scientific keystone to eradicate genetic diseases such as cancer related mutations in the offspring of cancer survivors. Citation: Bîc˘a,O.; Sârbu, I.; Keywords: fertility preservation; prepubertal boys; cancer; oncofertility; pediatric; in vitro spermatogenesis Ciongradi, C.I. -
Genetic Evaluation of Patients with Non-Syndromic Male Infertility
Journal of Assisted Reproduction and Genetics https://doi.org/10.1007/s10815-018-1301-7 REVIEW Genetic evaluation of patients with non-syndromic male infertility Ozlem Okutman1,2 & Maroua Ben Rhouma1 & Moncef Benkhalifa3 & Jean Muller4,5 & Stéphane Viville1,2 Received: 24 July 2018 /Accepted: 28 August 2018 # Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Purpose This review provides an update on the genetics of male infertility with emphasis on the current state of research, the genetic disorders that can lead to non-syndromic male infertility, and the genetic tests available for patients. Methods A comprehensive review of the scientific literature referenced in PubMed was conducted using keywords related to male infertility and genetics. The search included articles with English abstracts appearing online after 2000. Results Mutations in 31 distinct genes have been identified as a cause of non-syndromic human male infertility, and the number is increasing constantly. Screening gene panels by high-throughput sequencing can be offered to patients in order to identify genes involved in various forms of human non-syndromic infertility. We propose a workflow for genetic tests which takes into account semen alterations. Conclusions The identification and characterization of the genetic basis of male infertility have broad implications not only for understanding the cause of infertility but also in determining the prognosis, selection of treatment options, and management of couples. Genetic diagnosis is essential for the success of ART techniques and for preserving future fertility as well as the prognosis for testicular sperm extraction (TESE) and adopted therapeutics. Keywords Male infertility . Non-syndromic .