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Comparative morphological study of skeletal muscle weight among the red jungle fowl (Gallus gallus) and various fowl breeds (Gallus domesticus).

Hideki EndoNaoki TsunekawaKohei KudoTatsuo OshidaMasaharu MotokawaMitsuru SonoeSawai WanghongsaChanin TirawattanawanichViengsavanh PhimphachanhvongsodTakeshi SasakiTakahiro YonezawaFumihito Akishinonomiya
Published in: Journal of experimental zoology. Part B, Molecular and developmental evolution (2021)
We examined the weight distribution of skeletal muscles of the red jungle fowl, then compared these values with those of domesticated populations to determine how muscle distribution has changed by selecting breeding. Sonia, Fayoumi, and Rhode Island Red were selected for comparison from livestock breeds, while Japanese Shamo and Thai fighting cocks were selected from cockfighting groups. Principal component analysis was applied using body size-free data. The mass distribution of muscles clearly differed between the wild, livestock, and cockfighting groups, demonstrating that muscle distribution has changed after selecting breeding, coupled with functional demands of each group. The red jungle fowl, which has the ability to fly, could be clearly distinguished from the flightless domesticated populations due to differences in flight pectoral muscle size. The cervical muscles in the wild population were smaller than in the domesticated groups; these do not contribute to flight. The gluteal muscles were larger in the fighting cock group, functionally coupled to their traditionally preferred upright posture. Wild bird populations typically exhibit reduced weight of their hind limbs, associated with flight, but as the red jungle fowl displays largely terrestrial behavior, these muscles are similar in arrangement and relative size to those of the livestock groups. We showed that the mass distribution pattern of skeletal muscles expresses selecting breeding strategy and clearly reflects the specific traits for each group.
Keyphrases
  • skeletal muscle
  • genetic diversity
  • body mass index
  • physical activity
  • weight gain
  • insulin resistance
  • type diabetes
  • gene expression
  • genome wide
  • metabolic syndrome
  • machine learning
  • electronic health record