AbstractRwanda was the first low-income African country to introduce RotaTeq vaccine into its Expanded Programme on Immunization in May 2012. To gain insights into the overall genetic make-up and evolution of Rwandan G1P[8] strains pre- and post-vaccine introduction, rotavirus positive fecal samples collected between 2011 and 2016 from children under the age of 5 years as part of ongoing surveillance were genotyped with conventional RT-PCR based methods and whole genome sequenced using the Illumina MiSeq platform. From a pool of samples sequenced (n = 158), 36 were identified as G1P[8] strains (10 pre-vaccine and 26 post-vaccine), of which 35 exhibited a typical Wa-like genome constellation. However, one post vaccine strain, RVA/Human-wt/RWA/UFS-NGS:MRC-DPRU442/2012/G1P[8], exhibited a RotaTeq vaccine strain constellation of G1-P[8]-I2-R2-C2-M2-A3-N2-T6-E2-H3, with most of the gene segments having a close relationship with a vaccine derived reassortant strain, previously reported in USA in 2010 and Australia in 2012. The study strains segregated into two lineages, each containing a paraphyletic pre- and post-vaccine introduction sub-lineages. In addition, the study strains demonstrated close relationship amongst each other when compared with globally selected group A rotavirus (RVA) G1P[8] reference strains. For VP7 neutralization epitopes, amino acid substitutions observed at positions T91A/V, S195D and M217T in relation to the RotaTeq vaccine were radical in nature and resulted in a change in polarity from a polar to non-polar molecule, while for the VP4, amino acid differences at position D195G was radical in nature and resulted in a change in polarity from a polar to non-polar molecule. The polarity change at position T91A/V of the neutralizing antigens might play a role in generating vaccine-escape mutants, while substitutions at positions S195D and M217T may be due to natural fluctuation of the RVA. Surveillance of RVA at whole genome level will enhance further assessment of vaccine impact on circulating strains, the frequency of reassortment events under natural conditions and epidemiological fitness generated by such events.