Ask about this productRelated genes to: GALNTL5 antibody
- Gene:
- GALNTL5 NIH gene
- Name:
- polypeptide N-acetylgalactosaminyltransferase like 5
- Previous symbol:
- GALNT15
- Synonyms:
- GalNAc-T5L
- Chromosome:
- 7q36.1
- Locus Type:
- gene with protein product
- Date approved:
- 2003-07-14
- Date modifiied:
- 2017-06-13
Related products to: GALNTL5 antibody
Related articles to: GALNTL5 antibody
- More than 20 genes expressed in the male reproductive tract have been identified as essential factors for sperm migration to and through the utero-tubal junction (UTJ), and they are divided into ADAM3-dependent and ADAM3-independent pathways. In parallel, sperm having UTJ migration defects also show impaired binding to the zona pellucida (ZP). Herein, we demonstrate that knockout of Galntl5, encoding a sperm surface protein, causes impaired sperm binding with the UTJ and ZP, and null males have severe infertility. GALNTL5 appreciably disappears in sperm lacking Adam3 or Lypd4, required for ADAM3-dependent and ADAM3-independent pathways, and GALNTL5 binds to N-acetylgalactosamine (GalNAc) distributed on the UTJ and ZP. Blockage of GalNAc decreases the number of sperm binding to the UTJ and ZP. Thus, we unveil that GALNTL5 is a responsible factor for UTJ migration and sperm-ZP binding, and that sperm bind to the UTJ and ZP through interaction of GALNTL5 and GalNAc. - Source: PubMed
Publication date: 2025/09/17
Noda TaichiUriu ReikaMashiko DaisukeShinohara HinaQu YongcunTaira AyumuMatzuk Ryan MTahala DuriNakano MotochikaAraki KimiYu ZhifengZhang YingMatzuk Martin MIkawa Masahito - Polypeptide N-acetylgalactosaminyltransferase-like protein 5 (GALNTL5) was identified as a pp-GalNAc-T family gene. Nevertheless, GALNTL5 has no glycosyltransferase activity. In mice, Galntl5 expression is restricted to differentiating spermatids, and haploinsufficiency leads to immotile spermatozoa with an aberrant protein composition. Moreover, heterozygotic deletions of human GALNTL5 have been detected in patients diagnosed with asthenozoospermia (low sperm motility). Although these findings indicate that GALNTL5 is a functional molecule essential for mature sperm formation in mammals, the exact function of GALNTL5 in spermiogenesis remains unknown. To clarify this role, we established the mouse spermatocyte cell line GC-2spd(ts), which exhibits drug-inducible GALNTL5 expression. Interestingly, continuous GALNTL5 expression in the resultant cell lines caused apoptosis with cell shrinkage, and GALNTL5 was localized in the endoplasmic reticulum (ER) and was associated with two ER-resident chaperone proteins, calnexin and BiP (GRP78). Calnexin recognized and strongly bound to the N-glycans on GALNTL5 molecules modified in the ER. In contrast, ER-resident BiP likely attached to GALNL5 regardless of its glycosylation. GALNTL5 expression abolished the binding between calnexin and misfolded substrate proteins, indicating that GALNTL5 directly blocks calnexin function. Furthermore, the interaction between GALNTL5 and calnexin decreased the level of BiP protein, and consequently also the expression levels of proteins that are resident in the ER, Golgi apparatus, and cytoplasm. These reduced protein levels were confirmed by loss of calnexin or BiP function in the GC-2spd(ts) cell line using siRNA knockdown. Further, sustained expression of GALNTL5 resulted in cell structure changes, including the position of the cis-Golgi apparatus and alterations in the ER network. These results strongly suggest that GALNTL5 contributes to alteration of the cell structure specific to differentiating spermatids by blocking ER function. - Source: PubMed
Publication date: 2024/12/18
Takasaki NobuyoshiKoya YoshihiroYamashita MamoruNawa Akihiro - In recent years, an increasing number of genes associated with male and female infertility have been identified. The genetics of infertility is no longer limited to the analysis of karyotypes or specific genes, and it is now possible to analyse several dozen infertility genes simultaneously. Here, we present the diagnostic activity over the past two years including 140 patients (63 women and 77 men). Targeted sequencing revealed causative variants in 17 patients, representing an overall diagnostic rate of 12.1%, with prevalence rates in females and males of 11% and 13%, respectively. The gene-disease relationship (GDR) was re-evaluated for genes due to the addition of new patients and/or variants in the actual study. Five genes changed categories: two female genes (MEIOB and TBPL2) moved from limited to moderate; two male genes (SOHLH1 and GALNTL5) moved from no evidence to strong and from limited to moderate; and SEPTIN12, which was unable to classify male infertility, was reclassified as limited. Many infertility genes have yet to be identified. With the increasing integration of genetics in reproductive medicine, the scope of intervention extends to include other family members, in addition to individual patients or couples. Genetic counselling consultations and appropriate staffing will need to be established in fertility centres. Trial registration number: Not applicable. - Source: PubMed
Publication date: 2024/04/25
Okutman ÖzlemGürbüz Ali SamiSalvarci AhmetBüyük UmutRuso HalilGürgan TimurTarabeux JulienLeuvrey Anne-SophieNourisson ElsaLang CécileMuller JeanViville Stephane - Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics. - Source: PubMed
Publication date: 2022/06/16
Gorski MathiasRasheed HumairaTeumer AlexanderThomas Laurent FGraham Sarah ESveinbjornsson GardarWinkler Thomas WGünther FelixStark Klaus JChai Jin-FangTayo Bamidele OWuttke MatthiasLi YongTin AdrienneAhluwalia Tarunveer SÄrnlöv JohanÅsvold Bjørn OlavBakker Stephan J LBanas BernhardBansal NishaBiggs Mary LBiino GinevraBöhnke MichaelBoerwinkle EricBottinger Erwin PBrenner HermannBrumpton BenCarroll Robert JChaker LayalChalmers JohnChee Miao-LiChee Miao-LingCheng Ching-YuChu Audrey YCiullo MarinaCocca MassimilianoCook James PCoresh JosefCusi Danielede Borst Martin HDegenhardt FraukeEckardt Kai-UweEndlich KarlhansEvans Michele KFeitosa Mary FFranke AndreFreitag-Wolf SandraFuchsberger ChristianGampawar PiyushGansevoort Ron TGhanbari MohsenGhasemi SaharGiedraitis VilmantasGieger ChristianGudbjartsson Daniel FHallan SteinHamet PavelHishida AsahiHo KevinHofer EdithHolleczek BerndHolm HilmaHoppmann AnselmHorn KatrinHutri-Kähönen NinaHveem KristianHwang Shih-JenIkram M ArfanJosyula Navya ShilpaJung BettinaKähönen MikaKarabegović IrmaKhor Chiea-ChuenKoenig WolfgangKramer HollyKrämer Bernhard KKühnel BrigitteKuusisto JohannaLaakso MarkkuLange Leslie ALehtimäki TerhoLi ManLieb Wolfgang Lind LarsLindgren Cecilia MLoos Ruth J FLukas Mary AnnLyytikäinen Leo-PekkaMahajan AnubhaMatias-Garcia Pamela RMeisinger ChristaMeitinger ThomasMelander OlleMilaneschi YuriMishra Pashupati PMononen NinaMorris Andrew PMychaleckyj Josyf CNadkarni Girish NNaito MarikoNakatochi MasahiroNalls Mike ANauck MatthiasNikus KjellNing BotingNolte Ilja MNutile TeresaO'Donoghue Michelle LO'Connell JeffreyOlafsson IsleifurOrho-Melander MarjuParsa AfshinPendergrass Sarah APenninx Brenda W J HPirastu MarioPreuss Michael HPsaty Bruce MRaffield Laura MRaitakari Olli TRheinberger MyriamRice Kenneth MRizzi FedericaRosenkranz Alexander RRossing PeterRotter Jerome IRuggiero DanielaRyan Kathleen ASabanayagam CharumathiSalvi ErikaSchmidt HelenaSchmidt ReinholdScholz MarkusSchöttker BenSchulz Christina-AlexandraSedaghat SanazShaffer Christian MSieber Karsten BSim XuelingSims MarioSnieder HaroldStanzick Kira JThorsteinsdottir UnnurStocker HannahStrauch KonstantinStringham Heather MSulem PatrickSzymczak SilkeTaylor Kent DThio Chris H LTremblay JohanneVaccargiu Simonavan der Harst Pimvan der Most Peter JVerweij NiekVölker UweWakai KenjiWaldenberger MelanieWallentin LarsWallner StefanWang JudyWaterworth Dawn MWhite Harvey DWiller Cristen JWong Tien-YinWoodward MarkYang QiongYerges-Armstrong Laura MZimmermann MartinaZonderman Alan BBergler TobiasStefansson KariBöger Carsten APattaro CristianKöttgen AnnaKronenberg FlorianHeid Iris M - Male infertility is a multifaceted disorder affecting approximately 50% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the "omics" perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes () were commonly differentially expressed between all disease groups. Likewise, 56 genes were common between NOA versus NOA and OA (). These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes. Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility. Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases. - Source: PubMed
Publication date: 2022/02/14
Omolaoye Temidayo SOmolaoye Victor AKandasamy Richard KHachim Mahmood YaseenDu Plessis Stefan S