Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

agricultural and biological sciences

Multi-locus Analyses Reveal Four Giraffe Species Instead of One

Current Biology, Volume 26, No. 18, Year 2016

Traditionally, one giraffe species and up to eleven subspecies have been recognized [1]; however, nine subspecies are commonly accepted [2]. Even after a century of research, the distinctness of each giraffe subspecies remains unclear, and the genetic variation across their distribution range has been incompletely explored. Recent genetic studies on mtDNA have shown reciprocal monophyly of the matrilines among seven of the nine assumed subspecies [3, 4]. Moreover, until now, genetic analyses have not been applied to biparentally inherited sequence data and did not include data from all nine giraffe subspecies. We sampled natural giraffe populations from across their range in Africa, and for the first time individuals from the nominate subspecies, the Nubian giraffe, Giraffa camelopardalis camelopardalis Linnaeus 1758 [5], were included in a genetic analysis. Coalescence-based multi-locus and population genetic analyses identify at least four separate and monophyletic clades, which should be recognized as four distinct giraffe species under the genetic isolation criterion. Analyses of 190 individuals from maternal and biparental markers support these findings and further suggest subsuming Rothschild's giraffe into the Nubian giraffe, as well as Thornicroft's giraffe into the Masai giraffe [6]. A giraffe survey genome produced valuable data from microsatellites, mobile genetic elements, and accurate divergence time estimates. Our findings provide the most inclusive analysis of giraffe relationships to date and show that their genetic complexity has been underestimated, highlighting the need for greater conservation efforts for the world's tallest mammal.
Statistics
Citations: 194
Authors: 9
Affiliations: 5
Identifiers
Research Areas
Genetics And Genomics
Maternal And Child Health
Study Design
Cross Sectional Study
Study Approach
Quantitative