Abstract Study question Can genome-wide genotyping data be analysed in a hypothesis-driven fashion to better understand the genetic component of male infertility due to severe spermatogenic failure (SPGF)? Summary answer We revealed that both common and rare genetic variants in genomic regions involved in spermatogenesis contribute to the development of idiopathic SPGF. What is known already Spermatogenesis is a tightly regulated process involving the controlled expression of over 2,000 genes. Mutations in spermatogenesis-related genes have been associated with SPGF development. Next-generation sequencing methods are useful for identifying rare mutations that explain monogenic forms of this condition. Additionally, genome-wide association studies (GWAS) have provided valuable insights into the role of common polymorphisms in complex forms of SPGF. Interestingly, novel methods have shown that GWAS datasets can be used to infer rare coding variants that are causal for male infertility phenotypes, but this approach has never been applied to characterise the genetic component of a whole case-control cohort. Study design, size, duration We conducted a thorough examination of both common (minor allele frequency, MAF > 0.01) and rare (MAF < 0.01) genetic variation within a set of 1,797 spermatogenesis genes. This gene panel was meticulously curated through an exhaustive search in the literature and in different databases of male infertility genetics. The genotype data were obtained from a previously published GWAS in Europeans, encompassing over 6 million polymorphisms. Participants/materials, setting, methods We analysed a cohort that included 1,274 SPGF patients and 1,951 unaffected controls with European ancestry. Three independent approaches were follow: (1) variant-wise analysis using logistic regression models followed by a meta-analysis of the study cohorts; (2) gene-wise analysis using a Combined Multivariate and Collapsing (CMC) burden test; and (3) identification and characterisation of highly damaging rare coding variants in homozygosity. Multiple testing correction was applied to determine statistical significance Main results and the role of chance Our results suggested a potential association between SPGF and the rs12347237*T variant of the SHOC1 gene in the GWAS population (P = 3.17E-05, OR = 2.94). This association was subsequently validated in an independent Iberian cohort (Pcombined = 6.992E-06, OR = 2.61). Furthermore, our gene-wise analysis showed putative associations through the cumulative effect of some rare and low-frequency variants in SHOC1 (P = 4.9E-03), PCSK4 (P = 1E-04), AP3B1 (P = 5E-04), and DLK1 (P = 5E-04). Remarkably, the rare and common variants identified in SHOC1 are part of the same haplotype block, impacting both coding and non-coding regions. Additionally, we identified 35 individuals carrying 32 very rare and potentially pathogenic variants in homozygosity within the coding regions of the selected genes. Limitations, reasons for caution The analysis of low-frequency variants presents challenges in achieving sufficient statistical power to detect genetic associations. Consequently, independent studies involving large sample sets are essential to replicate our findings. In addition, the specific role of the identified variants in the pathogenic mechanisms of SPGF should be assessed using functional experiments. Wider implications of the findings The discovery of novel genetic risk factors for SPGF and the elucidation of the genetic causes underlying both monogenic and complex forms of SPGF provide new perspectives for personalized medicine and reproductive counselling. Trial registration number not applicable