An international consortium has sequenced and compared 103 bat genomes spanning all 21 recognized bat families, then combined that genomic dataset with information from 44 bat fossils to reconstruct how bats evolved their extraordinary biology. The study, led by researchers at the University of St Andrews as part of the Bat1K consortium, was published in Nature.
Bats make up roughly one in five mammal species and are the only mammals capable of powered flight, but their evolutionary history has been difficult to pin down using fossils or genetics alone. By sequencing genomes from across the full breadth of living bat diversity and integrating that data with the fossil record, the consortium built a more complete picture of bat evolution than either approach could produce on its own.
The genomic sequencing effort allowed the team to computationally reconstruct the ancestral bat genome, tracing the genetic changes that gave rise to traits such as echolocation and flight across the bat family tree. Comparing genomes across all 21 families also let researchers identify the genes and genetic changes associated with these specialized adaptations, linking specific sequence differences to the biological features that distinguish bat lineages from one another.
Combining this genomic resource with the fossil dataset gave the researchers a new way to date bat origins. According to Prof. Liliana M Dávalos, “The approach we used to model the evolution of fossil and living species together can do what other methods cannot: identify the oldest group of fossil bats while taking the genomic data into account, and uncover when and where bats originated.”
The scale of the genomic resource itself reflects years of coordinated sequencing work across the consortium. Prof. Sonja Vernes, who leads the Bat1K initiative, said, “Bats constantly surprise us. They are one of evolution’s greatest experiments. This extraordinary genomic resource, the culmination of years of international cooperation of Bat1K, is finally allowing us to understand how their remarkable biology evolved.”
By pairing whole-genome sequencing across the entire bat order with fossil-informed modeling, the study offers a genomic framework other researchers can use to investigate the molecular basis of bat-specific traits, and demonstrates how integrating large-scale comparative genomics with paleontological data can resolve evolutionary questions that neither dataset could answer alone.
Bats make up roughly one in five mammal species and are the only mammals capable of powered flight, but their evolutionary history has been difficult to pin down using fossils or genetics alone. By sequencing genomes from across the full breadth of living bat diversity and integrating that data with the fossil record, the consortium built a more complete picture of bat evolution than either approach could produce on its own.
The genomic sequencing effort allowed the team to computationally reconstruct the ancestral bat genome, tracing the genetic changes that gave rise to traits such as echolocation and flight across the bat family tree. Comparing genomes across all 21 families also let researchers identify the genes and genetic changes associated with these specialized adaptations, linking specific sequence differences to the biological features that distinguish bat lineages from one another.
Combining this genomic resource with the fossil dataset gave the researchers a new way to date bat origins. According to Prof. Liliana M Dávalos, “The approach we used to model the evolution of fossil and living species together can do what other methods cannot: identify the oldest group of fossil bats while taking the genomic data into account, and uncover when and where bats originated.”
The scale of the genomic resource itself reflects years of coordinated sequencing work across the consortium. Prof. Sonja Vernes, who leads the Bat1K initiative, said, “Bats constantly surprise us. They are one of evolution’s greatest experiments. This extraordinary genomic resource, the culmination of years of international cooperation of Bat1K, is finally allowing us to understand how their remarkable biology evolved.”
By pairing whole-genome sequencing across the entire bat order with fossil-informed modeling, the study offers a genomic framework other researchers can use to investigate the molecular basis of bat-specific traits, and demonstrates how integrating large-scale comparative genomics with paleontological data can resolve evolutionary questions that neither dataset could answer alone.