Genomic probing of selection signature to detect chromosomal region related to Johne’s disease in Holstein cattle

Document Type : Research Paper

Authors

1 Department of Animal Sciences, College of Agriculture & Natural Resources, University of Tehran, Karaj, Alborz, Iran

2 Department of Animal Sciences, College of Agriculture & Natural Resources, University of Tehran, Karaj, Alborz, Iran.

3 Department for Sustainable Agricultural Systems University of Natural Resources and Life Sciences,

4 Department of Animal Science, Ares Campus, University of Tehran, Jolfa, Iran

Abstract

Selection as a factor increases the frequency of positive mutations in some subpopulations and creates selection signatures in the genome. Identifying the selection signatures in animals aimed at promoting economic traits and reducing diseases is one of the main and most challenging research areas in population genetics. This study aimed to conduct an extensive genome scan using single nucleotide polymorphisms (SNPs) to identify genomic regions under positive selection between diseased and healthy Holstein cattle populations. The data included 145 Holstein cows from Foka. These cows were genotyped using Illumina 30K chips. The cows were divided into diseased (45 cows) and healthy (100 cows) groups. FST and XP-EHH statistics were used in this study to identify genomic regions under selection. The genes identified by FST statistics in both diseased and healthy populations included RAB37, ZC3H10, ESR1, HSD17B6, KCNC4, and ERBB3. Genes identified by XP-EHH statistics in both diseased and healthy populations included AK1, ATP8A1, BTBD1, C1GALT1, CCDC6, CEP295, CLGN, CLSTN2, EHHADH, ERBB4, FRK, GRID2, GRIP1, and LRP6. Most of the genes identified in this study were related to immunity, diseases such as cancer, lactation, skeletal muscles, estrous cycle, feed consumption, sperm adhesion, and growth, which are among the important biological traits and characteristics of living organisms. Further research using an increased sample size in the population will provide a better understanding of candidate genes for ion disease in cattle. Moreover, the design of successful breeding programs will help reduce the costs associated with this disease.

Keywords

Main Subjects

Extended Abstract

Introduction

Ion's disease, pseudotuberculosis, or paratuberculosis is a chronic infectious disease of the digestive system and small intestines in domestic and wild ruminants caused by Mycobacterium ovium subspecies paratuberculosis [1]. The disease is common in cattle and, to some extent, in sheep and goats [2]. The characteristics of this disease include granulomatous enterocolitis and lymphadenitis [3]. Due to the slow spread of the disease, ion disease occurs in isolation [4]. In cattle, clinical symptoms do not appear until two years of age due to the long incubation period [5]. Ion disease is responsible for significant economic losses in dairy herds worldwide, leading to reduced milk production, increased management costs, and premature culling or death due to clinical disease [7]. The alteration of the pattern of genetic diversity and linkage disequilibrium of the connected loci with a beneficial mutation during selection is called a Selective Sweep. These regions are related to major effect genes and genes affecting production traits and reproduction, making them of special importance as valuable sources of information for further research [8]. Therefore, identifying susceptible and resistant animals to this disease can play a significant and important role in preventing or reducing contamination of cattle farms with this infection. This study aims to identify genomic regions under selection related to this disease in two populations of diseased and healthy Holstein cattle using single nucleotide markers (SNPs).

 

Materials and Methods

The present study was conducted at Foka cattle ranch in Isfahan. Initially, in the laboratory, the blood samples of the cows were tested for ion disease with ELISA. Subsequently, the cows were categorized into two groups: sick and healthy, comprising 45 sick cattle and 100 healthy cattle. Both groups were genotyped based on microarrays and SNPchip30k. To ensure the quality of the genotype data, various filtration steps were applied to the raw data using Plink software. To investigate the genomic pattern of positive selection in this disease, theta values for each SNP were calculated using the unbiased θ estimator method [10] in the R x64 4.0.4 software environment. Instead of the numerical theta value of each SNP, the average of 5 adjacent SNPs within a 300 kbp range was used to better identify the selection signals. Ancestral alleles were not required to identify the regions under selection [12]. In the XP-EHH test, haplotypes in two populations were compared to consider the variation in the recombination rate across different genomic regions. The R x64 4.0.4 software and rehh package were used to identify selection signals in two populations. After identifying the selected regions, Illumina's gene list was used in the Plink v1.9 software environment to identify the genes related to these regions. To identify important KEGG metabolic pathways, ClueGo version 2.5.6, a Cytoscape plugin that provides biological annotations of genes, was used [13].

 

Results

After quality control of the data, 28,749 SNP markers were selected for further analysis. The genomic distribution of FST was determined using the win5 method for all SNPs across the genome. The results showed that several genomic regions had high population differences among adjacent SNPs. In this research, 79 genomic regions on 6 chromosomes were identified between the two populations of diseased and healthy cattle. After analyzing the regions under selection, 34 genes were identified in two populations of sick and healthy Holstein cows using FST statistics. The XP-EHH statistic indicated the presence of selection in the patient population when it was negative and in the healthy population when it was positive. Regions of the genome with high XP-EHH values were indicative of population differentiation in those genomic regions due to the disease. The results showed that 170 regions on different chromosomes were identified in the healthy population, and 156 genomic regions were identified on different chromosomes in the patient population. After analyzing the selected regions, 50 genes were identified in the diseased population, and 62 genes were identified in the healthy population of Holstein cows using the XP-EHH statistic.

 

Conclusion

Most of the genes identified in this study were related to immunity, diseases such as cancer, lactation, skeletal muscles, estrous cycle, feed consumption, sperm adhesion, and growth. These traits are among the important biological characteristics of living organisms. The results of this research, by identifying potential candidate genes related to ion disease and changes in the genome due to the disease, can be used in breeding programs for Holstein cows in the given country.

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Iranian Journal of animal Science
Volume 55, Issue 3
September 2024
Pages 437-450

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  • Receive Date: 21 November 2023
  • Revise Date: 31 January 2024
  • Accept Date: 13 February 2024

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