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Transcript
Mammalian Evolution Using
IRBP Gene
Goal:
To provide a problem space wherein students
can use sequence data using a slowly
evolving genes to resolve deep-level
divergences within and among mammalian
groups.
To illustrate the explanatory powers of
(molecular) phylogenetics for biology.
Problems with deep-level
divergences
Mitochondrial markers are too fast evolving to
resolve divergences of more than >50
millions years.
- Data sets often beset by saturation
(homoplasy) and trees often suffer from
long branch attractions.
Some Potential Questions:
Does the major grouping of mammals reflect
biogeographic history?
Does molecular phylogeny reflect present (worldwide or local) distribution?
Are marsupials monophyletic relative to eutherian
mammals?
Are rodents monophyletic?
To what groups of mammals whales and dolphins are
most related to?
Opportunities for students
Provides students to pose many other questions and generate
many hypotheses.
Investigate the concept of HOMOLOGY in both molecular
and morphological (or behavioral, ecological ) data sets
Test geographic events with character evolution.
Allow students to view biodiversity (and conservation) in the
context of evolution.
IRBP exon 1(Interphotoreceptor
Binding Protein)
• Single copy nuclear gene (currently the most
widely used marker for mammalian
phylogeny)
• Widely used to infer mammalian phylogeny
• Relative rate of mutation is slower than
mitochondrial genes, thus, ideal marker to
resolve deep-level divergences
Phylogeny of placental mammals
Murphy et al. 2001. Nature.294: 2348-2351
Cetartiodactyla
Perissodactyla
Carnivora
Pholidota
Chiroptera
Eulipotyphla
Rodentia
Glires
Lagomorpha
Dermoptera
Scandentia
Primates
Pilosa
Cingulata
Afrosoricida
Macroscelidea
Tubulidentata
Sirenia
Hyracoidea
Proboscidea
Marsupialia
Laurasiatheria
Euarchonta
Xenarthra
Afrotheria
Other Possibilities
Using other genes, such as vonWillebrand and
rag-1 genes to further illustrate the virtues
of the scientific concept:
Testability,
Repeatability,
Congruence among independent
data sets