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Multilevel SNP Analysis for Salmonella Response in Young Chicks Jason Robert Hasenstein Iowa State University

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Multilevel SNP Analysis for Salmonella Response in Young Chicks Jason Robert Hasenstein Iowa State University Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 2007 Single, several, saturated: multilevel SNP analysis for Salmonella response in young chicks Jason Robert Hasenstein Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Genetics and Genomics Commons Recommended Citation Hasenstein, Jason Robert, "Single, several, saturated: multilevel SNP analysis for Salmonella response in young chicks" (2007). Retrospective Theses and Dissertations. 15994. https://lib.dr.iastate.edu/rtd/15994 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. i Single, several, saturated: Multilevel SNP a nalysis for Salmonella response in young chicks by Jason Robert Hasenstein A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Genetics Program of Study Committee: Susan J. Lamont, Major Professor Jack C. M. Dekkers Max F. Rothschild D. L. ( Hank ) Harris Jean -Luc Jannink Iowa State University Ames, Iowa 2007 Copyright © Jason Robert Hasenstein, 2007. All Rights Reserv ed. UMI Number: 3274823 UMI Microform 3274823 Copyright 2007 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, MI 48106-1346 ii TABLE OF CONTENTS LIST OF FIGURES iii LIST OF TABLES iv ABSTRACT vi CHAPTER 1 GENERAL INTRODUCTION 1 CHAPTER 2 ANALYSIS OF FIVE GALLINACIN GENES AND SALMONELLA SEROVAR ENTERITIDIS RESPONSE IN POULTRY 40 CHAPTER 3 CHICKEN GALLINACIN GENE CLUSTER ASSOCIATED WITHSALMONELLA RESPONSE IN ADVANCED INTERCROSS LINE 57 CHAPTER 4 LINKAGE DISEQUILIBRIUM LEVELS IN TWO F2 AND TWO ADVANCED INTERCROSS POPULATIONS 76 CHAPTER 5 HIGH DENSITY SNP ANALYSIS OF GENOME -WIDE ASSOC IATIONS WITH POST -CHALLENGE BURDEN LEVELS OF SALMONELLA IN TWO ADVANCED INTERCROSS POPULATIONS OF CHICKENS 99 CHAPTER 6 GENERAL CONCLUSIONS AND DISCUSSION 120 CHAPTER 7 ACKNOWLEDGEMENTS 138 APPENDIX 1 ANALYSIS OF CHICKEN TLR4, CD28, MIF, MD -2, AND LITAF GENES IN A SALMONELLA ENTERITIDIS RESOURCE POPULATION 139 APPENDIX 2 FOUR GALLINACIN GENES AND SALMONELLA RESPONSE IN CHICKENS 155 iii LIST OF FIGURES CHAPTER 1 Figure 1 Invasion of intestinal mucosa by Salmonella 7 CHAPTER 2 Figur e 1 Vaccine antibody level by sire gallinacin allele 56 CHAPTER 3 Figure 1 Gallinacin genome organization and SE bacterial burden associations 75 CHAPTER 4 Figure 1 Distribution of r2 values for marker pairs as a function of distance. 94 Figure 2 Comparison of D’ and r2 values using the combined F 8 AIL 97 Figure 3 Theoretical reduction in LD confidence interval between markers in advanced intercross lines 98 CHAPTER 5 Figure 1 Position of immune function genes along signaling pathways. 118 Figure 2 Histog ram of Chi -Square P -Values 119 iv LIST OF TABLES CHAPTER 1 Table 1 Technical req uirements and characteristics of molecular markers 11 CHAPTER 2 Table 1 Primer sequence and PCR -RFLP assay conditi ons for genotyping SNPs of Gal2 - HpyCH4IV, Gal3 -Ava1, Gal4 -AluI, Gal5 - HinfI, and Gal7 -MlyI 54 Table 2 Associations between sire Gal2, Gal3, Gal4, Gal5, and Gal7 gene polymorphisms and progeny Salmonella serovar enteritidis response 55 CHAPTER 3 Table 1 Primer sequence, PCR conditions, and SNaPshot primer sequences for genotyping SNPs of Gal1 -13 72 Table 2 Gallinacin gene polymorphism association with postchallenge bacterial burden in chickens 73 Table 3 Genotype e ffect of GAL13, 12, and 11 combined on bacterial burden in cecal content of Br x Leg AIL 74 CHAPTER 4 Table 1 Mean D’ and r2 and their standard deviations (for markers < 12.5 Mb apart), and Student Pairwise t -tests of mean LD values between populations 91 v Table 2 Correlations and regression coefficients of D’ and r2 according to distance between marker pairs 92 Table 3 Least square means of r2 by population and chromosome for given distances between marker pairs 93 CHA PTER 5 Table 1 Summary of SNPs and genes identified through whole genome association with high -density SNP array in two chicken AILs 115 Table 2 Additive and Dominance effects for significant SNPs by line 117 APPENDIX 1 Table 1 Primer de signs for polymorphism identification of TLR4, CD28, MD -2, LITAF, and MIF genes 152 Table 2 PCR -RFLP assay for genotyping single nucleotide polymorphisms (SNP) of TLR4 - Sau96I, CD28 -RsaI, and MD2 -AseI 153 Table 3 Associations (P -value) among TLR4, CD28, and MD -2 gene polymorphisms and SE response 154 APPENDIX 2 Table 1 Primer sequence and PCR conditions for SNPs of Gal 6, Gal 11, Gal 12, and Gal 13 161 Table 2 Associations (P -value) between Gal 6, Gal 11, Gal 1 2, and Gal 13 polymorphisms and post challenge bacterial load in two advanced intercross lines 162 vi ABSTRACT Detection of genomic regions containing genes that affect economic traits is a primary step for potential improvements of livestock throug h marker -assisted selection. Salmonella enteritidis (SE) bacterial burden and SE vaccine antibody production are examples of important traits in commercial chickens. A main objective of the research presented herein was to identify single nucleotide poly morphisms ( SNPs ) associated with SE bacterial burden in either the spleen or cecum and vaccine antibody levels of young chickens through the use of multiple levels of genotyping platforms. Another objective was to compare linkage disequilibrium levels pre sent prior to and after implementation of an advanced intercrossing mating scheme . SNPs within the Gallinacin gene cluster were genotyped on an F 1 cross between four broiler sires and two inbred dam lines (Fayoumi and Leghorn), and were analyzed for assoc iation with SE bacterial burden in the spleen and cecal content and vaccine antibody response. The use of individual candidate gene studies identified two potential markers (SNPs in Gal3 and Gal7 ) for marker -assisted selection for SE vaccine antibody resp onse. A subsequent study was performed on the Gallinacin genes through the use of the SNaPshot genotyping platform and utilizing two separate F 8 advanced intercross lines (AIL) to examine SE bacterial burden response . Five SNPs showed association at P<0. 05, with three clustering between Gal11 -13 (3 -SNP haplotype P<0.008). The haplotype indicates the Gal11 -13 region is a strong candidate for SE response. Using a high -density SNP array to genotype 27 33 SNPs, a linkage disequilibrium (LD) fine mapping stud y was conducted to examine the change in LD between an F 2 and two F 8 AIL populations. LD levels were reduced 1.5 -fold from the F 2 to F 8 AIL populations. The reduction illustrates the potential gain of utilizing the advanced intercross mating scheme for f uture association studies. Using 3000 SNPS, associations with SE bacterial burden were examined. Twenty -one markers in nineteen genes were identified at P<0.02 with SE burden . These genes confirmed previously identified biological pathways important in response to bacterial infections in livestock. The molecular markers and reduction in LD identified provides an integral step in improvement of SE resistance in commercial birds th rough marker -assisted selection programs. 1 CHAPTER 1 GENERAL INTRODUCTION 1.1 INTRODUCTION The livestock industry has become increasingly interested in genetic improvement of disease resistance traits, especially for Salmonella as all commercial livestock are susceptible to infection. Salmonella enteritidis has incrementally inc reased in prevalence since the early 1970s and now presents a unique food biosafety concern (CDC 2005; Rodrigue et al. 1990) . While there are multiple strains of Salmonella , only Salmonella enteritidis is known to dire ctly infect chicken eggs (Girard -Santosuosso et al. 1998; Herikstad et al. 2002) . As many Salmonella serovars, including S. enteritidis , have developed resistance to antimicrobials commonly used to treat infection, concerns have been raised o n how to treat and prevent outbreaks (Di as de Oliveira et al. 2005; Johnson et al. 2005) . Through identification of genes associated with decreased levels of bacterial burden, it may be possible to naturally enhance the chicken’s immune response to Salmonella enteritidis bacterial challenge an d enhance antibody formation due to vaccination . Genetic variation of the trait, intensity and accuracy of selection, and the animal’s generation interval all factor into the amount of genetic gain in a trait per unit of time (Falconer and Mackay 1996) . Low heritability presents a substantial problem when improv ement is attempted by phenotypic selection (Dekkers and Hospital 2002) since it is difficult to accurately determine the animals with the best genetic background based upon their phenotype. Disease -resistance traits typically show a low level of heritability, thereby making genetic improvements difficult by phenotypic selection practices (Cheng et al. 1991; Dekkers 2004) . Marker assisted selection (MAS) has been shown to increase genetic response, especially when a trait has low heritability (Lande and Thompson 1990; Villanueva et al. 2002) . Advancements in animal genetics, such as the completed chicken and dog genomes and sequencing of the bovine and swine underway, has allowed for identification of molecular markers for marker assisted selection programs (Hillier et al. 2004; Lindblad -Toh et al. 2005) . The candidate gene approach is a useful method that has been widely implemented to identify genes that influence disease response. These candidate genes regulate a significan t proportion of the quantitative trait loci affecting trait variation within the population 2 (Rothschild and Soller 1997) . The genes analyzed through the candidate gene approach can be either structural, positional, or biological candidates.
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