COMPUTATIONAL ANALYSIS OF MOLECULAR SIGNATURES OF SELECTION AT PRODUCTION GENES FOR EGG AND MEAT IN LIVESTOCK AND WILD RELATIVES

Abstract

In Kenya, indigenous chicken form the majority of poultry. Their egg and meat production is low compared to commercial chicken. However there is variation among the indigenous chicken caused by evolutionary forces
such  as  Natural  Selection.  The  aim  of  this  study  was  to  model  evolution  and  subsequent  detection  positive selection on genes for egg and meat production. Genes for egg production were prolactin, vasoactive intestinal peptide  (vip)  and  intestinal  peptide  receptor  (vipr)  while  genes  for  meat  production  were  growth  hormone (gh), growth hormone receptor (ghr), insulin growth factor 1(igf1) and insulin growth factor 1 receptor (igf1r). This  was  achieved  by  data  mining  of  the  sequences  of  these  genes  from  databases  followed  by  performing reciprocal  BLASTp  and  BLOSUM62  substitution  matrix  using  chicken  sequence  for  each  gene  as  the  query. Homologues with an expectation value greater than 1e-10 were selected for each gene. Thereafter, Multiple
Sequence Alignment was done using MUSCLE which uses an iterative algorithm. The alignments were edited using  Seaview.  MEGA6  was  used  to  test  for  heterogeneity  in  substitution  rate  and  for  determining
evolutionary  model  using  lowest  Akaike  Information  Criterion.  Finally,  phylogenetic  trees  were  constructed using Nearest Neighbour Interchange with subtree pruning and regrafting of FastME followed by analysis for
signatures  of  selection  using  PAML4.  This  led  to  inferred  phylogenetic  trees  that  modeled  evolu tion  of  the genes in the different species and identification of positive selection on one amino acid site on igf1r. This is an advanced  genetic  technology  that  may  be  used  to  improve  egg  and  meat  production  through  artificial
selection.

Key words: poultry; growth hormone; natural selection; insulin growth factor1 receptor; codon-substitution models; prolactin; vipr1