Back

Molecular Phylogenetics of HIV-1 Subtypes in African Populations: A Case Study of Sub-Saharan African Countries

Obura, H. O.; Mlay, C. D.; Moyo, L.; Karumbo, B. M.; Omar, K. M.; Sinza, E. M.; Rotich, G. J.; Mudaki, W.; Kamau, B. M.; Awe, O. I.

2022-05-20 genomics
10.1101/2022.05.18.492401 bioRxiv
Show abstract

Despite advances in antiretroviral therapy that have revolutionized HIV-1 disease management, effective control of the HIV-1 infection pandemic remains elusive. Increased HIV-1 infection rates and genetic diversity in Sub-Saharan African countries pose a challenge in HIV-1 clinical management. This study provides a picture of HIV-1 genetic diversity and its implications for HIV-1 disease spread and the effectiveness of therapies in Africa. Whole-genome sequences of HIV-1 were obtained from Genbank using the accession numbers from 10 African countries with high HIV-1 prevalence. Alignment composed of the query and reference sequences retrieved from the Los Alamos database. The alignment file was viewed and curated in Aliview. Phylogenetic analysis was done by constructing a phylogenetic tree using the maximum likelihood method implemented in IQ-TREE. The clustering pattern of the studied countries showed both homogeneous clustering and heterogeneous clustering with all Zambia sequences clustering with HIV-1 subtype-C indicating local distribution of only subtype-C. Sequences from nine countries showed heterogeneous clustering along with different subtypes as well as individual clustering of the sequences away from references suggesting cross border genetic exchange. Sequences from Kenya and Nigeria clustered with almost all the HIV-1 subtypes suggesting high HIV-1 genetic diversity in Kenya and Nigeria as compared to other African countries. Our results indicate that there is the presence of subtype-specific HIV-1 polymorphisms and interactions during border movements.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.