TY - JOUR
T1 - VAPPER
T2 - high-throughput variant antigen profiling in African trypanosomes of livestock
AU - Pereira, Sara Silva
AU - Heap, John
AU - Jones, Andrew R.
AU - Jackson, Andrew P.
N1 - Funding Information:
This work was supported by a Grand Challenges (Round 11) award fromthe Bill and Melinda Gates Foundation, a BBSRC New investigator Award (BB/M022811/1), and the Technology Directorate of the University of Liverpool to A.P.J.
Funding Information:
This work was supported by a Grand Challenges (Round 11) award from the Bill and Melinda Gates Foundation, a BBSRC New investigator Award (BB/M022811/1), and the Technology Directorate of the University of Liverpool to A.P.J.
Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press.
PY - 2019/9/18
Y1 - 2019/9/18
N2 - Background: Analysing variant antigen gene families on a population scale is a difficult challenge for conventional methods of read mapping and variant calling due to the great variability in sequence, copy number, and genomic loci. In African trypanosomes, hemoparasites of humans and animals, this is complicated by variant antigen repertoires containing hundreds of genes subject to various degrees of sequence recombination. Findings: We introduce Variant Antigen Profiler (VAPPER), a tool that allows automated analysis of the variant surface glycoprotein repertoires of the most prevalent livestock African trypanosomes. VAPPER produces variant antigen profiles for any isolate of the veterinary pathogens Trypanosoma congolense and Trypanosoma vivax from genomic and transcriptomic sequencing data and delivers publication-ready figures that show how the queried isolate compares with a database of existing strains. VAPPER is implemented in Python. It can be installed to a local Galaxy instance from the ToolShed (https://toolshed.g2.bx.psu.edu/) or locally on a Linux platform via the command line (https://github.com/PGB-LIV/VAPPER). The documentation, requirements, examples, and test data are provided in the Github repository. Conclusion: By establishing two different, yet comparable methodologies, our approach is the first to allow large-scale analysis of African trypanosome variant antigens, large multi-copy gene families that are otherwise refractory to high-throughput analysis.
AB - Background: Analysing variant antigen gene families on a population scale is a difficult challenge for conventional methods of read mapping and variant calling due to the great variability in sequence, copy number, and genomic loci. In African trypanosomes, hemoparasites of humans and animals, this is complicated by variant antigen repertoires containing hundreds of genes subject to various degrees of sequence recombination. Findings: We introduce Variant Antigen Profiler (VAPPER), a tool that allows automated analysis of the variant surface glycoprotein repertoires of the most prevalent livestock African trypanosomes. VAPPER produces variant antigen profiles for any isolate of the veterinary pathogens Trypanosoma congolense and Trypanosoma vivax from genomic and transcriptomic sequencing data and delivers publication-ready figures that show how the queried isolate compares with a database of existing strains. VAPPER is implemented in Python. It can be installed to a local Galaxy instance from the ToolShed (https://toolshed.g2.bx.psu.edu/) or locally on a Linux platform via the command line (https://github.com/PGB-LIV/VAPPER). The documentation, requirements, examples, and test data are provided in the Github repository. Conclusion: By establishing two different, yet comparable methodologies, our approach is the first to allow large-scale analysis of African trypanosome variant antigens, large multi-copy gene families that are otherwise refractory to high-throughput analysis.
KW - African trypanosomes
KW - VAPPER
KW - Variant antigen profiling
KW - Variant surface glycoproteins
UR - http://www.scopus.com/inward/record.url?scp=85071896314&partnerID=8YFLogxK
U2 - 10.1093/gigascience/giz091
DO - 10.1093/gigascience/giz091
M3 - Article
C2 - 31494667
SN - 2047-217X
VL - 8
JO - GigaScience
JF - GigaScience
IS - 9
M1 - giz091
ER -