Background Ewe productivity is considered as the most important economic trait in sheep meat production. Due to very limited reports, the objective of this study was the application of alternative GWAS approaches followed by gene set enrichment analysis (GSEA) on the maternal genome to unravel the genomic architecture underlying ewe productivity in Iranian Baluchi sheep. Six maternal composite traits including progeny birth weight (PBW), litter mean weight at birth (LMWB), total litter weight at birth (TLWB), progeny weaning weight (PWW), litter mean weight at weaning (LMWW) and total litter weight at weaning (TLWW) were studied. Results Genes such as RDX , FDX1 , ARHGAP20 , ZC3H12C , THBS1 , and EPG5 on OAR6, OAR7, OAR15, and OAR23 were identified for composite traits at birth. The genes are involved in pregnancy, including autophagy in the placenta, progesterone production by the placenta, maternal immune response and placenta formation. Some maternal pathways, related to calcium ion transport, signal transduction, neurogenesis, and immune response were also identified for birth weight traits. Moreover, many genes including NR2C1 , VEZT , HSD17B4 , RSU1 , CUBN , VIM , PRLR , and FTH1 were located on OAR2, OAR3, OAR5, OAR7, OAR13, OAR16, and OAR25 identified as maternal genes affecting weaning weight traits. Most of the identified genes were involved in mammary glands development and milk components production. Also, many GO terms related to protein processing and transport, ion transport and homeostasis, proteins and lipid phosphorylation, and phospholipid translocation were identified in association with weaning weight traits. Conclusions The results of the present study revealed that calcium ion homeostasis and transport and the maternal immune system could have an important role in progeny’s birth weight. Also, the results showed that genes and pathways affecting mammary glands development during pregnancy and milk components production have the most impact on lambs weaning weight. These findings contribute to a better understanding of the genetic architecture of the studied traits and providing opportunities for improving ewe productivity via marker-assisted selection.