Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits

In identifying mutations occurring in distinct cow breeds, genetic elements must be taken into consideration. More recently, these hereditary features have gained attention throughout the world. As in many underdeveloped nations, to bridge the deficit in molecular genetics, multiple solutions are re...

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Main Authors: Javed Ahmed Ujjan, Sapna Waheed Memon, Majeeda Ruk, Zuneera Akram, Allahwadhayo Ghoto, Betty Nokobi Dugbakie
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Food Quality
Online Access:http://dx.doi.org/10.1155/2022/6017374
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author Javed Ahmed Ujjan
Sapna Waheed Memon
Majeeda Ruk
Zuneera Akram
Allahwadhayo Ghoto
Betty Nokobi Dugbakie
author_facet Javed Ahmed Ujjan
Sapna Waheed Memon
Majeeda Ruk
Zuneera Akram
Allahwadhayo Ghoto
Betty Nokobi Dugbakie
author_sort Javed Ahmed Ujjan
collection DOAJ
description In identifying mutations occurring in distinct cow breeds, genetic elements must be taken into consideration. More recently, these hereditary features have gained attention throughout the world. As in many underdeveloped nations, to bridge the deficit in molecular genetics, multiple solutions are required. The inner membrane anion carrier superfamily contains the uncoupling proteins (UCPs), vital to energy regulation. Research on heredity has shown that variations in the UCP2 and UCP3 genes are connected to obesity and metabolic syndrome. This research aimed to investigate if any mutation in the UCP 2 and UCP 3 genes are related to many characteristics in Pakistan’s three indigenous cattle breeds using artificial neural network (ANN). For better analysis, the output of the ANN model is loaded into the Primer Premier 3 software. Using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and sequencing, the results of this study indicated 07 variations in the exon 4 region of the UCP2 gene and 03 variants in the exon 3 area of the UCP3 gene among 215 indigenous cow breeds. The association study revealed that the g.C35G mutation in the UCP3 gene is strongly related to meat quantity characteristics such as carcass weight and drip percentage (P0.05) but not with body height or hip width (P>0.05). Sequence analysis showed five distinct diplotypes: AA, BC, AC, CC, and CD. Cattle with the novel heterozygous diplotype BC perform better in carcass trait and drip percentage than animals with other genotypes. The study’s findings suggest that the UCP3 gene may be utilized for marker-assisted selection (MAS) and breed mixing in Pakistan cattle breeds to aid in the country’s economic growth.
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spelling doaj-art-037eaa57a7954d62a6e603147fcc07e52025-02-03T06:05:51ZengWileyJournal of Food Quality1745-45572022-01-01202210.1155/2022/6017374Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity TraitsJaved Ahmed Ujjan0Sapna Waheed Memon1Majeeda Ruk2Zuneera Akram3Allahwadhayo Ghoto4Betty Nokobi Dugbakie5Department of ZoologyDepartment of ZoologyDepartment of ZoologyBaqai Institute of Pharmaceutical SciencesDepartment of ZoologyDepartment of Chemical EngineeringIn identifying mutations occurring in distinct cow breeds, genetic elements must be taken into consideration. More recently, these hereditary features have gained attention throughout the world. As in many underdeveloped nations, to bridge the deficit in molecular genetics, multiple solutions are required. The inner membrane anion carrier superfamily contains the uncoupling proteins (UCPs), vital to energy regulation. Research on heredity has shown that variations in the UCP2 and UCP3 genes are connected to obesity and metabolic syndrome. This research aimed to investigate if any mutation in the UCP 2 and UCP 3 genes are related to many characteristics in Pakistan’s three indigenous cattle breeds using artificial neural network (ANN). For better analysis, the output of the ANN model is loaded into the Primer Premier 3 software. Using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and sequencing, the results of this study indicated 07 variations in the exon 4 region of the UCP2 gene and 03 variants in the exon 3 area of the UCP3 gene among 215 indigenous cow breeds. The association study revealed that the g.C35G mutation in the UCP3 gene is strongly related to meat quantity characteristics such as carcass weight and drip percentage (P0.05) but not with body height or hip width (P>0.05). Sequence analysis showed five distinct diplotypes: AA, BC, AC, CC, and CD. Cattle with the novel heterozygous diplotype BC perform better in carcass trait and drip percentage than animals with other genotypes. The study’s findings suggest that the UCP3 gene may be utilized for marker-assisted selection (MAS) and breed mixing in Pakistan cattle breeds to aid in the country’s economic growth.http://dx.doi.org/10.1155/2022/6017374
spellingShingle Javed Ahmed Ujjan
Sapna Waheed Memon
Majeeda Ruk
Zuneera Akram
Allahwadhayo Ghoto
Betty Nokobi Dugbakie
Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
Journal of Food Quality
title Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
title_full Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
title_fullStr Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
title_full_unstemmed Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
title_short Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
title_sort artificial neural network based identification of associations between ucp2 and ucp3 gene polymorphisms and meat quantity traits
url http://dx.doi.org/10.1155/2022/6017374
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