High resolution mapping and identification of new quantitative trait loci (QTL) affecting susceptibility to Marek's disease

Epigenetic Factor MicroRNAs Likely Mediate Vaccine Protection Efficacy against Lymphomas in Response to Tumor Virus Infection in Chickens through Target Gene Involved Signaling Pathways

Epigenetic factors, including microRNAs (miRNAs), play an important role in affecting gene expression and, therefore, are involved in various biological processes including immunity protection against tumors. Marek's disease (MD) is a highly contagious disease of chickens caused by the MD virus (MDV). MD has been primarily controlled by vaccinations. MD vaccine efficacy might, in part, be dependent on modulations of a complex set of factors including host epigenetic factors. This study was designed to identify differentially expressed miRNAs in the primary lymphoid organ, bursae of Fabricius, in response to MD vaccination followed by MDV challenge in two genetically divergent inbred lines of White Leghorns. Small RNA sequencing and bioinformatic analyses of the small RNA sequence reads identified hundreds of miRNAs among all the treatment groups. A small portion of the identified miRNAs was differentially expressed within each of the four treatment groups, which were HVT or CVI988/Rispens vaccinated line 63-resistant birds and line 72-susceptible birds. A direct comparison between the resistant line 63 and susceptible line 72 groups vaccinated with HVT followed by MDV challenge identified five differentially expressed miRNAs. Gene Ontology analysis of the target genes of those five miRNAs revealed that those target genes, in addition to various GO terms, are involved in multiple signaling pathways including MAPK, TGF-β, ErbB, and EGFR1 signaling pathways. The general functions of those pathways reportedly play important roles in oncogenesis, anti-cancer immunity, cancer cell migration, and metastatic progression. Therefore, it is highly likely that those miRNAs may, in part, influence vaccine protection through the pathways.

Transgenerational epigenetic inheritance and immunity in chickens that vary in Marek's disease resistance

Marek's disease virus (MDV), a naturally oncogenic, highly contagious alpha herpesvirus, induces a T cell lymphoma in chickens that causes severe economic loss. Marek's disease (MD) outcome in an individual is attributed to genetic and environmental factors. Further investigation of the host-virus interaction mechanisms that impact MD resistance is needed to achieve greater MD control. This study analyzed genome-wide DNA methylation patterns in 2 highly inbred parental lines 63 and 72 and 5 recombinant congenic strains (RCS) C, L, M, N, and X strains from those parents. Lines 63 and 72, are MD resistant and susceptible, respectively, whereas the RCS have different combinations of 87.5% Line 63 and 12.5% Line 72. Our DNA methylation cluster showed a strong association with MD incidence. Differentially methylated regions (DMRs) between the parental lines and the 5 RCS were captured. MD-resistant and MD-susceptible markers of DNA methylation were identified as transgenerational epigenetic inheritable. In addition, the growth of v-src DNA tumors and antibody response against sheep red blood cells differed among the 2 parental lines and the RCS. Overall, our results provide very solid evidence that DNA methylation patterns are transgenerational epigenetic inheritance (TEI) in chickens and also play a vital role in MD tumorigenesis and other immune responses; the specific methylated regions may be important modulators of general immunity.

The Diverse Major Histocompatibility Complex Haplotypes of a Common Commercial Chicken Line and Their Effect on Marek's Disease Virus Pathogenesis and Tumorigenesis

The major histocompatibility complex (MHC) is crucial for appropriate immune responses against invading pathogens. Chickens possess a single predominantly-expressed class I molecule with strong associations between disease resistance and MHC haplotype. For Marek's disease virus (MDV) infections of chickens, the MHC haplotype is one of the major determinants of genetic resistance and susceptibility. VALO specific pathogen free (SPF) chickens are widely used in biomedical research and vaccine production. While valuable findings originate from MDV infections of VALO SPF chickens, their MHC haplotypes and associated disease resistance remained elusive. In this study, we used several typing systems to show that VALO SPF chickens possess MHC haplotypes that include B9, B9:02, B15, B19 and B21 at various frequencies. Moreover, we associate the MHC haplotypes to MDV-induced disease and lymphoma formation and found that B15 homozygotes had the lowest tumor incidence while B21 homozygotes had the lowest number of organs with tumors. Finally, we found transmission at variable levels to all contact birds except B15/B21 heterozygotes. These data have immediate implications for the use of VALO SPF chickens and eggs in the life sciences and add another piece to the puzzle of the chicken MHC complex and its role in infections with this oncogenic herpesvirus.

Selection for Favorable Health Traits: A Potential Approach to Cope with Diseases in Farm Animals

Disease is a global problem for animal farming industries causing tremendous economic losses (>USD 220 billion over the last decade) and serious animal welfare issues. The limitations and deficiencies of current non-selection disease control methods (e.g., vaccination, treatment, eradication strategy, genome editing, and probiotics) make it difficult to effectively, economically, and permanently eliminate the adverse influences of disease in the farm animals. These limitations and deficiencies drive animal breeders to be more concerned and committed to dealing with health problems in farm animals by selecting animals with favorable health traits. Both genetic selection and genomic selection contribute to improving the health of farm animals by selecting certain health traits (e.g., disease tolerance, disease resistance, and immune response), although both of them face some challenges. The objective of this review was to comprehensively review the potential of selecting health traits in coping with issues caused by diseases in farm animals. Within this review, we highlighted that selecting health traits can be applied as a method of disease control to help animal agriculture industries to cope with the adverse influences caused by diseases in farm animals. Certainly, the genetic/genomic selection solution cannot solve all the disease problems in farm animals. Therefore, management, vaccination, culling, medical treatment, and other measures must accompany selection solution to reduce the adverse impact of farm animal diseases on profitability and animal welfare.

Mapping QTL Associated with Resistance to Avian Oncogenic Marek's Disease Virus (MDV) Reveals Major Candidate Genes and Variants

Marek’s disease (MD) represents a significant global economic and animal welfare issue. Marek’s disease virus (MDV) is a highly contagious oncogenic and highly immune-suppressive α-herpes virus, which infects chickens, causing neurological effects and tumour formation. Though partially controlled by vaccination, MD continues to have a profound impact on animal health and on the poultry industry. Genetic selection provides an alternative and complementary method to vaccination. However, even after years of study, the genetic mechanisms underlying resistance to MDV remain poorly understood. The Major Histocompatability Complex (MHC) is known to play a role in disease resistance, along with a handful of other non-MHC genes. In this study, one of the largest to date, we used a multi-facetted approach to identify quantitative trait locus regions (QTLR) influencing resistance to MDV, including an F₆ population from a full-sib advanced intercross line (FSIL) between two elite commercial layer lines differing in resistance to MDV, RNA-seq information from virus challenged chicks, and genome wide association study (GWAS) from multiple commercial lines. Candidate genomic elements residing in the QTLR were further tested for association with offspring mortality in the face of MDV challenge in eight pure lines of elite egg-layer birds. Thirty-eight QTLR were found on 19 chicken chromosomes. Candidate genes, microRNAs, long non-coding RNAs and potentially functional mutations were identified in these regions. Association tests were carried out in 26 of the QTLR, using eight pure lines of elite egg-layer birds. Numerous candidate genomic elements were strongly associated with MD resistance. Genomic regions significantly associated with resistance to MDV were mapped and candidate genes identified. Various QTLR elements were shown to have a strong genetic association with resistance. These results provide a large number of significant targets for mitigating the effects of MDV infection on both poultry health and the economy, whether by means of selective breeding, improved vaccine design, or gene-editing technologies.

Latency characteristics in specific pathogen-free chickens 21 and 35 days after intra-tracheal inoculation with vaccine or field strains of infectious laryngotracheitis virus

Latency is an important feature of infectious laryngotracheitis virus (ILTV) yet is poorly understood. This study aimed to compare latency characteristics of vaccine (SA2) and field (CL9) strains of ILTV, establish an in vitro reactivation system and examine ILTV infection in peripheral blood mononuclear cells (PBMC) in specific pathogen-free chickens. Birds were inoculated with SA2 or CL9 ILTV and then bled and culled at 21 or 35 days post-inoculation (dpi). Swabs (conjunctiva, palatine cleft, trachea) and trigeminal ganglia (TG) were examined for ILTV DNA using PCR. Half of the TG, trachea and PBMC were co-cultivated with cell monolayers to assess in vitro reactivation of ILTV infection. ILTV DNA was detected in the trachea of approximately 50% of ILTV-inoculated birds at both timepoints. At 21 dpi, ILTV was detected in the TG only in 29% and 17% of CL9- and SA2-infected birds, respectively. At 35 dpi, ILTV was detected in the TG only in 30% and 10% of CL9- and SA2-infected birds, respectively. Tracheal organ co-cultures from 30% and 70% of CL9- and SA2-infected birds, respectively, were negative for ILTV DNA at cull but yielded quantifiable DNA within 6 days post-explant (dpe). TG co-cultivation from 30% and 40% of CL9-and SA2-infected birds, respectively, had detectable ILTV DNA within 6 dpe. Latency characteristics did not substantially vary based on the strain of virus inoculated or between sampling timepoints. These results advance our understanding of ILTV latency and reactivation. RESEARCH HIGHLIGHTS Following inoculation, latent ILTV infection was detected in a large proportion of chickens, irrespective of whether a field or vaccine strain was inoculated. In vitro reactivation of latent ILTV was readily detected in tracheal and trigeminal ganglia co-cultures using PCR. ILTV latency observed in SPF chickens at 21 days post-infection was not substantially different to 35 days post-infection.

Mhc-B haplotypes in "Campero-Inta" chicken synthetic line

The major histocompatibility complex-B (MHC-B) in chickens is a cluster of genes located on chromosome 16. The chicken MHC-B is known to be highly associated with resistance to numerous diseases caused by viruses, bacteria, and parasitic pathogens. Since the level of resistance varies with MHC-B haplotypes, identification and classification of different haplotypes within lines is important for sustaining lines. The "Campero-INTA" chicken breed is a meat-type free-range poultry breed that was developed specifically for small producers in Argentina. Campero-INTA was started by selection in populations produced by crosses between a variety of established lines. MHC-B variation was examined in 65 samples obtained in 2002 using the VNTR marker LEI0258, a marker for MHC-B region. These samples plus and an additional 55 samples from 2018 were examined for variation using the MHC-B specific SNP panel that encompasses ∼230,000 bp of the MHC-B region. Eleven MHC-B SNP haplotypes with 6 LEI0258 alleles were identified in the 120 samples representing the Campero-INTA AH (male) line. Seven haplotypes originate from the breeds originally used in the development of Campero-INTA AH line. Two appear to be recombinant haplotypes. The origin of the remaining 2 is not known, but may be associated with genes introduced from crosses with the Fayoumi breed conducted more recently to sustain the line.

Macrophages from Susceptible and Resistant Chicken Lines have Different Transcriptomes following Marek's Disease Virus Infection

Despite successful control by vaccination, Marek’s disease (MD) has continued evolving to greater virulence over recent years. To control MD, selection and breeding of MD-resistant chickens might be a suitable option. MHC-congenic inbred chicken lines, 6₁ and 7₂, are highly resistant and susceptible to MD, respectively, but the cellular and genetic basis for these phenotypes is unknown. Marek’s disease virus (MDV) infects macrophages, B-cells, and activated T-cells in vivo. This study investigates the cellular basis of resistance to MD in vitro with the hypothesis that resistance is determined by cells active during the innate immune response. Chicken bone marrow-derived macrophages from lines 6₁ and 7₂ were infected with MDV in vitro. Flow cytometry showed that a higher percentage of macrophages were infected in line 7₂ than in line 6₁. A transcriptomic study followed by in silico functional analysis of differentially expressed genes was then carried out between the two lines pre- and post-infection. Analysis supports the hypothesis that macrophages from susceptible and resistant chicken lines display a marked difference in their transcriptome following MDV infection. Resistance to infection, differential activation of biological pathways, and suppression of oncogenic potential are among host defense strategies identified in macrophages from resistant chickens.

Genetic assessment of inbred chicken lines indicates genomic signatures of resistance to Marek's disease

Background

Marek’s disease (MD) is a highly contagious pathogenic and oncogenic disease primarily affecting chickens. However, the mechanisms of genetic resistance for MD are complex and not fully understood. MD-resistant line 6₃ and MD-susceptible line 7₂ are two highly inbred progenitor lines of White Leghorn. Recombinant Congenic Strains (RCS) were developed from these two lines, which show varied susceptibility to MD.

Results

We investigated genetic structure and genomic signatures across the genome, including the line 6₃ and line 7₂, six RCSs, and two reciprocally crossed flocks between the lines 6₃ and 7₂ (F1 6₃ × 7₂ and F1 7₂ × 6₃) using Affymetrix® Axiom® HD 600 K genotyping array. We observed 18 chickens from RCS lines were specifically clustered into resistance sub-groups distributed around line 6₃. Additionally, homozygosity analysis was employed to explore potential genetic components related to MD resistance, while runs of homozygosity (ROH) are regions of the genome where the identical haplotypes are inherited from each parent. We found several genes including SIK, SOX1, LIG4, SIK1 and TNFSF13B were contained in ROH region identified in resistant group (line 6₃ and RCS), and these genes have been reported that are contribute to immunology and survival. Based on F_ST based population differential analysis, we also identified important genes related to cell death and anti-apoptosis, including AKT1, API5, CDH13, CFDP and USP15, which could be involved in divergent selection during inbreeding process.

Conclusions

Our findings offer valuable insights for understanding the genetic mechanism of resistance to MD and the identified genes could be considered as candidate biomarkers in further evaluation.

Electronic supplementary material

The online version of this article (10.1186/s40104-018-0281-x) contains supplementary material, which is available to authorized users.

Comparative transcriptomics of genetically divergent lines of chickens in response to Marek's disease virus challenge at cytolytic phase

Marek's disease (MD), caused by Marek's disease virus (MDV), remains an economically significant threat to the poultry industry worldwide. Genetic resistance to MD is a promising alternative strategy to augment current control measures (vaccination and management). However, only a few functional genes reportedly conferring MD resistance have been identified. Here, we performed a comparative transcriptomics analysis of two highly inbred yet genetically divergent lines of chickens (line 63 and 72) that are resistant and susceptible to MD, respectively, in response to a very virulent plus strain of MDV (vv+MDV) challenge at cytolytic phase. A total of 203 DEGs in response to MDV challenge were identified in the two lines. Of these, 96 DEGs were in common for both lines, in addition to 36 and 71 DEGs that were specific for line 63 and 72, respectively. Functional enrichment analysis results showed the DEGs were significantly enriched in GO terms and pathways associated with immune response. Especially, the four DEGs, FGA, ALB, FN1, and F13A1 that reportedly facilitate virus invasion or immunosuppression, were found to be significantly up-regulated in the susceptible line 72 but down-regulated in the resistant line 63 birds. These results provide new resources for future studies to further elucidate the genetic mechanism conferring MD resistance.

Characterization of Copy Number Variation's Potential Role in Marek's Disease

Marek’s Disease (MD) is a highly contagious pathogenic and oncogenic disease primarily affecting chickens. Chicken Lines 63 and 72, as well as their recombinant congenic strains (RCS) with varied susceptibility to MD, are ideal models to study the complex mechanisms of genetic resistance to MD. In this study, we investigated copy number variation (CNV) in these inbred chicken lines using the Affymetrix Axiom HD 600 K SNP genotyping array. We detected 393 CNV segments across all ten chicken lines, of which 12 CNVs were specifically identified in Line 72. We then assessed genetic structure based on CNV and observed markedly different patterns. Finally, we validated two deletion events in Line 72 and correlated them with genes expression using qPCR and RNA-seq, respectively. Our combined results indicated that these two CNV deletions were likely to contribute to MD susceptibility.

Validation of Alternative Transcript Splicing in Chicken Lines that Differ in Genetic Resistance to Marek's Disease

Utilizing RNA-seq data, 1,574 candidate genes with alternative splicing were previously identified between two chicken lines that differ in Marek's disease (MD) genetic resistance under control and Marek's disease virus infection conditions. After filtering out 1,530 genes with splice variants in the first or last exon, 44 genes were screened for possible exon loss or gain using PCR and gel electrophoresis. Consequently, 7 genes exhibited visually detectable differential expression of splice variants between lines 6 (MD resistant) and 7 (MD susceptible), and the resultant PCR products verified by DNA sequencing. Birds from inbred line 6 have transcripts that preferentially retain an exon compared to line 7 chickens for ITGB2, SGPL1, and COMMD5. Birds from inbred line 7 have alleles that preferentially retain an exon compared to line 6 for MOCS2. CCBL2 exon 1a is absent and ATAD1 exon 2 is truncated by 87 nucleotides in transcripts expressed by line 7 compared to those from line 6. For CHTF18, line 6 transcripts have an indel mutation with 7 additional nucleotides in exon 21 compared to line 7. The current study validates 7 genes with alternatively spliced isomers between the two chicken lines, which helps provide potential underlying mechanisms for the phenotypic differences.

Virus and host genomic, molecular, and cellular interactions during Marek's disease pathogenesis and oncogenesis

Marek's Disease Virus (MDV) is a chicken alphaherpesvirus that causes paralysis, chronic wasting, blindness, and fatal lymphoma development in infected, susceptible host birds. This disease and its protective vaccines are highly relevant research targets, given their enormous impact within the poultry industry. Further, Marek's disease (MD) serves as a valuable model for the investigation of oncogenic viruses and herpesvirus patterns of viral latency and persistence--as pertinent to human health as to poultry health. The objectives of this article are to review MDV interactions with its host from a variety of genomic, molecular, and cellular perspectives. In particular, we focus on cytogenetic studies, which precisely assess the physical status of the MDV genome in the context of the chicken host genome. Combined, the cytogenetic and genomic research indicates that MDV-host genome interactions, specifically integration of the virus into the host telomeres, is a key feature of the virus life cycle, contributing to the viral achievement of latency, transformation, and reactivation of lytic replication. We present a model that outlines the variety of virus-host interactions, at the multiple levels, and with regard to the disease states.

Genome-wide identification of copy number variations between two chicken lines that differ in genetic resistance to Marek's disease

Background

Copy number variation (CNV) is a major source of genome polymorphism that directly contributes to phenotypic variation such as resistance to infectious diseases. Lines 6₃ and 7₂ are two highly inbred experimental chicken lines that differ greatly in susceptibility to Marek’s disease (MD), and have been used extensively in efforts to identify the genetic and molecular basis for genetic resistance to MD. Using next generation sequencing, we present a genome-wide assessment of CNVs that are potentially associated with genetic resistance to MD.

Methods

Three chickens randomly selected from each line were sequenced to an average depth of 20×. Two popular software, CNVnator and Pindel, were used to call genomic CNVs separately. The results were combined to obtain a union set of genomic CNVs in the two chicken lines.

Results

A total of 5,680 CNV regions (CNVRs) were identified after merging the two datasets, of which 1,546 and 1,866 were specific to the MD resistant or susceptible line, respectively. Over half of the line-specific CNVRs were shared by 2 or more chickens, reflecting the reduced diversity in both inbred lines. The CNVRs fixed in the susceptible lines were significantly enriched in genes involved in MAPK signaling pathway. We also found 67 CNVRs overlapping with 62 genes previously shown to be strong candidates of the underlying genes responsible for the susceptibility to MD.

Conclusions

Our findings provide new insights into the genetic architecture of the two chicken lines and additional evidence that MAPK signaling pathway may play an important role in host response to MD virus infection. The rich source of line-specific CNVs is valuable for future disease-related association studies in the two chicken lines.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2080-5) contains supplementary material, which is available to authorized users.

Genome-wide association study for Marek's disease mortality in layer chickens

A genome-wide association study (GWAS) using Bayesian variable selection was performed to determine genomic regions associated with mortality due to Marek's disease virus (MDV) infection in layers. Mortality (%) under experimental disease challenge (500 plaque-forming units of a very virulent plus MDV strain) was recorded for progeny groups (average 15.5 birds; range 3 to 30) of 253 genotyped sires from four generations of a brown-egg layer line. An additional generation of 43 sires with progeny data was used to validate results. Sires were genotyped with a 42K Illumina single-nucleotide polymorphism (SNP) chip. Methods BayesB (pi = 0.995) and BayesCpi, with or without weighting residuals by the size of progeny groups were applied. The proportion of genetic variance contributed by SNPs within each 1-megabase (Mb) genomic region was quantified. Average mortality was 33% but differed significantly between generations. Genetic markers explained about 11% of phenotypic variation in mortality. Correlations between genomic estimated breeding values and percentage of progeny mortality for the validation generation (sons of individuals in training) were 0.12, 0.17, 0.02, and 0.16 for BayesB, weighted BayesB, BayesCpi, and weighted BayesCpi, respectively, when using the whole genome, and 0.03, 0.20, -0.06, and 0.14, when using only SNP from the 10, 1-Mb regions, explaining the largest proportion of genetic variance according to each method. Results suggest that regions on chromosomes 2, 3, 4, 9, 15, 18, and 21 are associated with Marek's disease resistance and can be used for selection and that accounting for the size of progeny groups has a large impact on correct localization of such genomic regions.

Improving the outcome of a Marek's disease challenge in multiple lines of egg type chickens

A challenge test following inoculation with a standard amount of a vv+ strain of the Marek's disease (MD) virus in multiple lines and multiple generations of egg type chicken and the corresponding phenotypic trend are described. This program significantly reduced mortality of progeny from selected sires for three to 11 generations in eight of the nine elite lines studied herein. In brown egg lines, a retrospective analysis of DNA indicated an association between the blood type B (major histocompatibility complex) of the sire and the MD mortality in the challenge of its progeny. As a result of the multigeneration stock amplification and crossbreeding processes used in the commercial breeding industry, improvement in survival after challenge at the elite level will translate to improved welfare for millions of birds at the commercial production level.

Comparison and contrast of genes and biological pathways responding to Marek's disease virus infection using allele-specific expression and differential expression in broiler and layer chickens

BACKGROUND

Marek's disease (MD) is a commercially important neoplastic disease of chickens caused by the Marek's disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Enhancing MD genetic resistance is desirable to augment current vaccines and other MD control measures. High throughput sequencing was used to profile splenic transcriptomes from individual F1 progeny infected with MDV at 4 days of age from both outbred broilers (meat-type) and inbred layer (egg-type) chicken lines that differed in MD genetic resistance. The resulting information was used to identify SNPs, genes, and biological pathways exhibiting allele-specific expression (ASE) in response to MDV infection in each type of chicken. In addition, we compared and contrasted the results of pathway analyses (ASE and differential expression (DE)) between chicken types to help inform on the biological response to MDV infection.

RESULTS

With 7 individuals per line and treatment group providing high power, we identified 6,132 single nucleotide polymorphisms (SNPs) in 4,768 genes and 4,528 SNPs in 3,718 genes in broilers and layers, respectively, that exhibited ASE in response to MDV infection. Furthermore, 548 and 434 genes in broilers and layers, respectively, were found to show DE following MDV infection. Comparing the datasets, only 72 SNPs and 850 genes for ASE and 20 genes for DE were common between the two bird types. Although the chicken types used in this study were genetically different, at the pathway level, both TLR receptor and JAK/STAT signaling pathways were enriched as well as exhibiting a high proportion of ASE genes, especially at the beginning of both above mentioned regulatory pathways.

CONCLUSIONS

RNA sequencing with adequate biological replicates is a powerful approach to identify high confidence SNPs, genes, and pathways that are associated with transcriptional response to MDV infection. In addition, the SNPs exhibiting ASE in response to MDV infection provide a strong foundation for determining the extent to which variation in expression influences MD incidence plus yield genetic markers for genomic selection. However, given the paucity of overlap among ASE SNP sets (broilers vs. layers), it is likely that separate screens need to be incorporated for each population. Finally, comparison of gene lists obtained between these two diverse chicken types indicate the TLR and JAK/STAT signaling are conserved when responding to MDV infection and may be altered by selection of genes exhibiting ASE found at the start of each pathway.

An assessment of opportunities to dissect host genetic variation in resistance to infectious diseases in livestock

This paper reviews the evidence for host genetic variation in resistance to infectious diseases for a wide variety of diseases of economic importance in poultry, cattle, pig, sheep and Atlantic salmon. Further, it develops a method of ranking each disease in terms of its overall impact, and combines this ranking with published evidence for host genetic variation and information on the current state of genomic tools in each host species. The outcome is an overall ranking of the amenability of each disease to genomic studies that dissect host genetic variation in resistance. Six disease-based assessment criteria were defined: industry concern, economic impact, public concern, threat to food safety or zoonotic potential, impact on animal welfare and threat to international trade barriers. For each category, a subjective score was assigned to each disease according to the relative strength of evidence, impact, concern or threat posed by that particular disease, and the scores were summed across categories. Evidence for host genetic variation in resistance was determined from available published data, including breed comparison, heritability studies, quantitative trait loci (QTL) studies, evidence of candidate genes with significant effects, data on pathogen sequence and on host gene expression analyses. In total, 16 poultry diseases, 13 cattle diseases, nine pig diseases, 11 sheep diseases and three Atlantic salmon diseases were assessed. The top-ranking diseases or pathogens, i.e. those most amenable to studies dissecting host genetic variation, were Salmonella in poultry, bovine mastitis, Marek's disease and coccidiosis, both in poultry. The top-ranking diseases or pathogens in pigs, sheep and Atlantic salmon were Escherichia coli, mastitis and infectious pancreatic necrosis, respectively. These rankings summarise the current state of knowledge for each disease and broadly, although not entirely, reflect current international research efforts. They will alter as more information becomes available and as genome tools become more sophisticated for each species. It is suggested that this approach could be used to rank diseases from other perspectives as well, e.g. in terms of disease control strategies.

Whole-genome scan for signatures of recent selection reveals loci associated with important traits in White Leghorn chickens

Chicken is considered to be an excellent model for genetic studies of phenotypic and genomic evolution, with large effective population size, specialized commercial lines, and strong human-driven selection. High-density chicken SNP chips can help to achieve a better understanding of the selection mechanisms in artificially selected populations. We performed the genome-wide tests for the selection signature in 385 White Leghorn hens and mapped positively selected regions to the genome annotations. Ten QTL related to egg production, egg quality, growth, and disease resistance traits were selected for extended haplotype homozygosity tests to give a brief overview of recent selection signatures in chicken QTL. We also reported 185 candidate genes/CDSs showing top P-values and slower decay of haplotype homozygosities. Some of these genes seemed to have significant effects on important economical traits, and most of them have not been reported in chickens. The current study provides a genome-wide map of linkage disequilibrium extents and distributions and selection footprints in the chicken genome. A panel of genes, including PRL, NCKX1, NRF1, LHX2, and SFRP1 associated with egg production, metabolism traits, and response to illumination were identified. In addition, there were more genes identified that have not yet been reported in chickens, and our results provide new clues for further study.

Histone methylation analysis and pathway predictions in chickens after MDV infection

Marek's disease (MD) is a lymphoproliferative disease in chicken induced by Marek's disease virus (MDV). Although studies have focused on the genetic differences between the resistant and susceptible chicken, less is known about the role of epigenetic factors in MD. In this study, genome-wide histone modifications in the non-MHC-associated resistant and susceptible chicken lines were examined. We found that tri-methylation at histone H3 Lys4 (H3K4me3) enrichment is positively correlated with the expression of protein coding genes as well as microRNA (miRNA) genes, whereas tri-methylation at histone H3 Lys27 (H3K27me3) exhibits a negative correlation. By identifying line-specific histone modifications in MDV infection, we found unique H3K4me3 islands in the resistant chicken activated genes, which are related to immune response and cell adhesion. Interestingly, we also found some miRNAs from unique H3K27me3 patterns in the susceptible chickens that targeted genes involved in 5-hydroxytryptamine (5-HT)-receptor and adrenergic receptor pathways. In conclusion, dynamic line-specific histone modifications in response to MDV infection suggested that intrinsic epigenetic mechanisms may play a role in MD-resistance and -susceptibility.

A genome-wide SNP scan reveals two loci associated with the chicken resistance to Marek's disease

Marek's disease (MD) is a neoplastic disease in chickens, caused by the Marek's disease virus (MDV). To investigate host genetic resistance to MD, we conducted a genome-wide association study (GWAS) on 67 MDV-infected chickens based on a case and control design, including 57 susceptible chickens in the case group and 10 resistant chickens as controls. After searching 38 655 valid genomic markers, two SNPs were found to be associated with host resistance to MD. One SNP, rs14527240, reaching chromosome-wide significance level (P < 0.01) was located in the SPARC-related modular calcium-binding 1 (SMOC1) gene on GGA5. The other one, GGaluGA156129, reaching genome-wide significance (P < 0.05), was located in the protein tyrosine phosphatase, non-receptor type 3 (PTPN3) gene on GGA2. In addition, expression patterns of these two genes in spleens were detected by qPCR. The expression of SMOC1 was significantly up-regulated (P < 0.05), whereas the expression of PTNP3 did not show significance when the case group was compared with the control group. Up-regulation of SMOC1 in susceptible spleens suggests its important roles in MD tumorigenesis. This is the first study to investigate MD-resistant loci, and it demonstrates the power of GWASs for mapping genes associated with MD resistance.

Genome-Wide Identification and Quantification of cis- and trans-Regulated Genes Responding to Marek's Disease Virus Infection via Analysis of Allele-Specific Expression

Marek’s disease (MD) is a commercially important neoplastic disease of chickens caused by Marek’s disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Selecting for increased genetic resistance to MD is a control strategy that can augment vaccinal control measures. To identify high-confidence candidate MD resistance genes, we conducted a genome-wide screen for allele-specific expression (ASE) amongst F₁ progeny of two inbred chicken lines that differ substantially in MD resistance. High throughput sequencing was initially used to profile transcriptomes from pools of uninfected and infected individuals at 4 days post-infection to identify any genes showing ASE in response to MDV infection. RNA sequencing identified 22,655 single nucleotide polymorphisms (SNPs) of which 5,360 in 3,773 genes exhibited significant allelic imbalance. Illumina GoldenGate assays were subsequently used to quantify regulatory variation controlled at the gene (cis) and elsewhere in the genome (trans) by examining differences in expression between F₁ individuals and artificial F₁ RNA pools over six time periods in 1,536 of the most significant SNPs identified by RNA sequencing. Allelic imbalance as a result of cis-regulatory changes was confirmed in 861 of the 1,233 GoldenGate assays successfully examined. Furthermore we have identified seven genes that display trans-regulation only in infected animals and ∼500 SNP that show a complex interaction between cis- and trans-regulatory changes. Our results indicate ASE analyses are a powerful approach to identify regulatory variation responsible for differences in transcript abundance in genes underlying complex traits. And the genes with SNPs exhibiting ASE provide a strong foundation to further investigate the causative polymorphisms and genetic mechanisms for MD resistance. Finally, the methods used here for identifying specific genes and SNPs have practical implications for applying marker-assisted selection to complex traits that are difficult to measure in agricultural species, when expression differences are expected to control a portion of the phenotypic variance.

Systems analysis of immune responses in Marek's disease virus-infected chickens identifies a gene involved in susceptibility and highlights a possible novel pathogenicity mechanism

Marek's disease virus (MDV) is a highly contagious oncogenic alphaherpesvirus that causes disease that is both a cancer model and a continuing threat to the world's poultry industry. This comprehensive gene expression study analyzes the host response to infection in both resistant and susceptible lines of chickens and inherent expression differences between the two lines following the infection of the host. A novel pathogenicity mechanism, involving the downregulation of genes containing HIC1 transcription factor binding sites as early as 4 days postinfection, was suggested from this analysis. HIC1 drives antitumor mechanisms, suggesting that MDV infection switches off genes involved in antitumor regulation several days before the expression of the MDV oncogene meq. The comparison of the gene expression data to previous QTL data identified several genes as candidates for involvement in resistance to MD. One of these genes, IRG1, was confirmed by single nucleotide polymorphism analysis to be involved in susceptibility. Its precise mechanism remains to be elucidated, although the analysis of gene expression data suggests it has a role in apoptosis. Understanding which genes are involved in susceptibility/resistance to MD and defining the pathological mechanisms of the disease gives us a much greater ability to try to reduce the incidence of this virus, which is costly to the poultry industry in terms of both animal welfare and economics.

Quantitative trait loci associated with the humoral innate immune response in chickens were confirmed in a cross between Green-Legged Partridgelike and White Leghorn

Natural antibodies (NA) create a crucial barrier at the initial steps of the innate humoral immune response. The main role of NA in the defense system is to bind the pathogens at early stages of infection. Different pathogens are recognized by the presence of highly conserved antigen determinant [e.g., lipopolysaccharide (LPS) in gram-negative bacteria or lipoteichoic acid (LTA) in gram-positive bacteria]. In chickens, a different genetic background of NA binds LPS and LTA antigens, encoded by different QTL. The main objective of this work was to confirm known QTL associated with LPS and LTA NA. For this purpose a chicken reference population was created by crossing 2 breeds: a commercial layer, White Leghorn, and a Polish indigenous chicken, Green-Legged Partridgelike. The chromosomal regions analyzed harbored to GGA3, GGA5, GGA6, GGA8, GGA9, GGA10, GGA14, GGA15, GGA18, and GGAZ. The data collected consisted of the NA titers binding LPS and LTA (determined by ELISA at 12 wk of age) as well as the genotypes (30 short tandem repeat markers; average of 3 markers/chromosome, collected for generations F(0), F(1), and F(2)). The analyses were performed with 3 statistical models (paternal and maternal half-sib, line cross, and linkage analysis and linkage disequilibrium) implemented in GridQTL software (http://www.gridqtl.org.uk/). The QTL study of humoral innate immune response traits resulted in the confirmation of 3 QTL associated with NA titers binding LPS (located on GGA9, GGA18, and GGAZ) and 2 QTL associated with NA titers binding LTA (located on GGA5 and GGA14). A set of candidate genes within the regions of the validated QTL has been proposed.

Temporal transcriptome changes induced by MDV in Marek's disease-resistant and -susceptible inbred chickens

Background

Marek's disease (MD) is a lymphoproliferative disease in chickens caused by Marek's disease virus (MDV) and characterized by T cell lymphoma and infiltration of lymphoid cells into various organs such as liver, spleen, peripheral nerves and muscle. Resistance to MD and disease risk have long been thought to be influenced both by genetic and environmental factors, the combination of which contributes to the observed outcome in an individual. We hypothesize that after MDV infection, genes related to MD-resistance or -susceptibility may exhibit different trends in transcriptional activity in chicken lines having a varying degree of resistance to MD.

Results

In order to study the mechanisms of resistance and susceptibility to MD, we performed genome-wide temporal expression analysis in spleen tissues from MD-resistant line 6₃, susceptible line 7₂ and recombinant congenic strain M (RCS-M) that has a phenotype intermediate between lines 6₃ and 7₂ after MDV infection. Three time points of the MDV life cycle in chicken were selected for study: 5 days post infection (dpi), 10dpi and 21dpi, representing the early cytolytic, latent and late cytolytic stages, respectively. We observed similar gene expression profiles at the three time points in line 6₃ and RCS-M chickens that are both different from line 7₂. Pathway analysis using Ingenuity Pathway Analysis (IPA) showed that MDV can broadly influence the chickens irrespective of whether they are resistant or susceptible to MD. However, some pathways like cardiac arrhythmia and cardiovascular disease were found to be affected only in line 7₂; while some networks related to cell-mediated immune response and antigen presentation were enriched only in line 6₃ and RCS-M. We identified 78 and 30 candidate genes associated with MD resistance, at 10 and 21dpi respectively, by considering genes having the same trend of expression change after MDV infection in lines 6₃ and RCS-M. On the other hand, by considering genes with the same trend of expression change after MDV infection in lines 7₂ and RCS-M, we identified 78 and 43 genes at 10 and 21dpi, respectively, which may be associated with MD-susceptibility.

Conclusions

By testing temporal transcriptome changes using three representative chicken lines with different resistance to MD, we identified 108 candidate genes for MD-resistance and 121 candidate genes for MD-susceptibility over the three time points. Genes included in our resistance or susceptibility genes lists that are also involved in more than 5 biofunctions, such as CD8α, IL8, USP18, and CTLA4, are considered to be important genes involved in MD-resistance or -susceptibility. We were also able to identify several biofunctions related with immune response that we believe play an important role in MD-resistance.

Whole genome QTL mapping for growth, meat quality and breast meat yield traits in turkey

Background

The turkey (Meleagris gallopavo) is an important agricultural species and is the second largest contributor to the world's poultry meat production. Demand of turkey meat is increasing very rapidly. Genetic markers linked to genes affecting quantitative traits can increase the selection response of animal breeding programs. The use of these molecular markers for the identification of quantitative trait loci, and subsequently fine-mapping of quantitative trait loci regions, allows for pinpointing of genes that underlie such economically important traits.

Results

The quantitative trait loci analyses of the growth curve, body weight, breast yield and the meat quality traits showed putative quantitative trait loci on 21 of the 27 turkey chromosomes covered by the linkage map. Forty-five quantitative trait loci were detected across all traits and these were found in 29 different regions on 21 chromosomes. Out of the 45 quantitative trait loci, twelve showed significant (p < 0.01) evidence of linkage while the remaining 33 showed suggestive evidence (p < 0.05) of linkage with different growth, growth curve, meat quality and breast yield traits.

Conclusion

A large number of quantitative trait loci were detected across the turkey genome, which affected growth, breast yield and meat quality traits. Pleiotropic effects or close linkages between quantitative trait loci were suggested for several of the chromosomal regions. The comparative analysis regarding the location of quantitative trait loci on different turkey, and on the syntenic chicken chromosomes, along with their phenotypic associations, revealed signs of functional conservation between these species.

Mapping of quantitative trait loci affecting organ weights and blood variables in a broiler layer cross

1. A genome scan was performed to locate genomic regions associated with traits that are known to vary in birds (most commonly broilers) suffering from heart, lung or muscular dysfunction and for weight of the dressed carcass and some internal organs. 2. The F2 population studied was derived from a cross between a broiler and a layer line and consisted of over 460 birds that were genotyped for 101 markers. 3. There was strong support for segregation of quantitative trait loci (QTL) for carcass and organ weights and blood variables. We identified 11 genome-wide significant QTL (most of them for dressed carcass weight) and several genome-wide suggestive QTL. 4. The results point to some genome regions that may be associated with health-related traits and merit further study, with the final aim of identifying linked genetic markers that could be used in commercial breeding programmes to decrease the incidence of muscular and metabolic disorders in broiler populations.

Across-line SNP association study of innate and adaptive immune response in laying hens

The aim of the present study was to detect quantitative trait loci (QTL) for innate and adaptive immunity in laying hens. For this purpose, the associations between 1022 single nucleotide polymorphism (SNP) markers and immune traits were studied in 583 hens from nine different layer lines. Immune traits were natural antibodies for keyhole limpet haemocyanin (KLH) and lipopolysaccharide (LPS) at 20, 40 and 65 weeks, acquired antibodies to the vaccinal virus of Newcastle disease at 20 weeks, and complement activity measured on sheep and bovine red blood cells at 20, 40 and 65 weeks. We adopted a novel approach based on across-line analysis and testing of the SNP-by-line interaction. Among lines, linkage disequilibrium is conserved at shorter distances than in individual lines; therefore, SNPs significantly associated with immune traits across lines are expected to be near the functional mutations. In the analysis, the SNPs that had a significant across-line effect but did not show significant SNP-by-line interaction were identified to test whether the association was consistent in the individual lines. Ultimately, 59 significant associations between SNPs and immune traits were detected. Our results confirmed some previously identified QTL and identified new QTL potentially involved in the immune function. We found evidence for a role of IL17A (chromosome 3) in natural and acquired antibody titres and in the classical and alternative pathways of complement activation. The major histocompatibility genes on chromosome 16 showed significant association with natural and acquired antibody titres and classical complement activity. The IL12B gene on chromosome 13 was associated with natural antibody titres.

A review of the need and possible uses for genetically standardized Atlantic salmon (Salmo salar) in research

Large numbers of Atlantic salmon ( Salmo salar) are used as research animals in basic research and to solve challenges related to the fish-farming industry. Most of this research is performed on farmed animals provided by local breeders or national breeding companies. The genetic constitution of these animals is usually unknown and highly variable. As a result, large numbers of fish are often needed to produce significant results, and results from one study are often impossible to reproduce in another facility. The production of standardized salmon could in many cases reduce the number of animals used in research and at the same time provide more reproducible results. This paper provides an overview of the methods available for the production of standardized Atlantic salmon, and discusses the pros and cons of each technique. The use of zebrafish and other well-defined laboratory fish species as a model for salmon is also discussed. Access to genetically defined fish would greatly benefit the scientific community, in the same way as genetically defined lines of rodents have revolutionized mammalian research.

Microsatellite mapping of QTLs affecting resistance to coccidiosis (Eimeria tenella) in a Fayoumi x White Leghorn cross

Background

Avian coccidiosis is a major parasitic disease of poultry, causing severe economical loss to poultry production by affecting growth and feed efficiency of infected birds. Current control strategies using mainly drugs and more recently vaccination are showing drawbacks and alternative strategies are needed. Using genetic resistance that would limit the negative and very costly effects of the disease would be highly relevant. The purpose of this work was to detect for the first time QTL for disease resistance traits to Eimeria tenella in chicken by performing a genome scan in an F2 cross issued from a resistant Fayoumi line and a susceptible Leghorn line.

Results

The QTL analysis detected 21 chromosome-wide significant QTL for the different traits related to disease resistance (body weight growth, plasma coloration, hematocrit, rectal temperature and lesion) on 6 chromosomes. Out of these, a genome-wide very significant QTL for body weight growth was found on GGA1, five genome-wide significant QTL for body weight growth, plasma coloration and hematocrit and one for plasma coloration were found on GGA1 and GGA6, respectively. Two genome-wide suggestive QTL for plasma coloration and rectal temperature were found on GGA1 and GGA2, respectively. Other chromosme-wide significant QTL were identified on GGA2, GGA3, GGA6, GGA15 and GGA23. Parent-of-origin effects were found for QTL for body weight growth and plasma coloration on GGA1 and GGA3. Several QTL for different resistance phenotypes were identified as co-localized on the same location.

Conclusion

Using an F2 cross from resistant and susceptible chicken lines proved to be a successful strategy to identify QTL for different resistance traits to Eimeria tenella, opening the way for further gene identification and underlying mechanisms and hopefully possibilities for new breeding strategies for resistance to coccidiosis in the chicken. From the QTL regions identified, several candidate genes and relevant pathways linked to innate immune and inflammatory responses were suggested. These results will be combined with functional genomics approaches on the same lines to provide positional candidate genes for resistance loci for coccidiosis. Results suggested also for further analysis, models tackling the complexity of the genetic architecture of these correlated disease resistance traits including potential epistatic effects.

Mapping QTL affecting resistance to Marek's disease in an F6 advanced intercross population of commercial layer chickens

BACKGROUND

Marek's disease (MD) is a T-cell lymphoma of chickens caused by the Marek's disease virus (MDV), an oncogenic avian herpesvirus. MD is a major cause of economic loss to the poultry industry and the most serious and persistent infectious disease concern. A full-sib intercross population, consisting of five independent families was generated by crossing and repeated intercrossing of two partially inbred commercial White Leghorn layer lines known to differ in genetic resistance to MD. At the F6 generation, a total of 1615 chicks were produced (98 to 248 per family) and phenotyped for MD resistance measured as survival time in days after challenge with a very virulent plus (vv+) strain of MDV.

RESULTS

QTL affecting MD resistance were identified by selective DNA pooling using a panel of 15 SNPs and 217 microsatellite markers. Since MHC blood type (BT) is known to affect MD resistance, a total of 18 independent pool pairs were constructed according to family x BT combination, with some combinations represented twice for technical reasons. Twenty-one QTL regions (QTLR) affecting post-challenge survival time were identified, distributed among 11 chromosomes (GGA1, 2, 3, 4, 5, 8, 9, 15, 18, 26 and Z), with about two-thirds of the MD resistance alleles derived from the more MD resistant parental line. Eight of the QTLR associated with MD resistance, were previously identified in a backcross (BC) mapping study with the same parental lines. Of these, 7 originated from the more resistant line, and one from the less resistant line.

CONCLUSION

There was considerable evidence suggesting that MD resistance alleles tend to be recessive. The width of the QTLR for these QTL appeared to be reduced about two-fold in the F6 as compared to that found in the previous BC study. These results provide a firm basis for high-resolution linkage disequilibrium mapping and positional cloning of the resistance genes.

Detecting parent of origin and dominant QTL in a two-generation commercial poultry pedigree using variance component methodology

INTRODUCTION

Variance component QTL methodology was used to analyse three candidate regions on chicken chromosomes 1, 4 and 5 for dominant and parent-of-origin QTL effects. Data were available for bodyweight and conformation score measured at 40 days from a two-generation commercial broiler dam line. One hundred dams were nested in 46 sires with phenotypes and genotypes on 2708 offspring. Linear models were constructed to simultaneously estimate fixed, polygenic and QTL effects. Different genetic models were compared using likelihood ratio test statistics derived from the comparison of full with reduced or null models. Empirical thresholds were derived by permutation analysis.

RESULTS

Dominant QTL were found for bodyweight on chicken chromosome 4 and for bodyweight and conformation score on chicken chromosome 5. Suggestive evidence for a maternally expressed QTL for bodyweight and conformation score was found on chromosome 1 in a region corresponding to orthologous imprinted regions in the human and mouse.

CONCLUSION

Initial results suggest that variance component analysis can be applied within commercial populations for the direct detection of segregating dominant and parent of origin effects.

Avian NK activities, cells and receptors

Natural killer (NK) activity has been examined in birds for over 30 years, but evidence that avian NK activity plays crucial roles in disease is only suggestive. In chickens, NK activity is mediated by TCR0 cells in the intestinal epithelium, but elsewhere subsets of alphabeta and gammadelta T cells (NKT cells) may be more important. There are few lectin-like NK receptor genes, located in the genomic region syntenic with the natural killer complex (NKC) as well as the major histocompatibility complex (MHC). In contrast, a huge number of Ig-like receptor genes are located in a region syntenic with the leukocyte receptor complex (LRC).

Mapping quantitative trait loci affecting susceptibility to Marek's disease virus in a backcross population of layer chickens

Marek's disease (MD), caused by the oncogenic MD avian herpes virus (MDV), is a major source of economic losses to the poultry industry. A reciprocal backcross (BC) population (total 2052 individuals) was generated by crossing two partially inbred commercial Leghorn layer lines known to differ in MDV resistance, measured as survival time after challenge with a (vv+) MDV. QTL affecting resistance were identified by selective DNA pooling using a panel of 198 microsatellite markers covering two-thirds of the chicken genome. Data for each BC were analyzed separately, and as a combined data set. Markers showing significant association with resistance generally appeared in blocks of two or three, separated by blocks of nonsignificant markers. Defined this way, 15 chromosomal regions (QTLR) affecting MDV resistance, distributed among 10 chromosomes (GGA 1, 2, 3, 4, 5, 7, 8, 9, 15, and Z), were identified. The identified QTLR include one gene and three QTL associated with resistance in previous studies of other lines, and three additional QTL associated with resistance in previous studies of the present lines. These QTL could be used in marker-assisted selection (MAS) programs for MDV resistance and as a platform for high-resolution mapping and positional cloning of the resistance genes.

Functional genomics of the chicken--a model organism

Since the sequencing of the genome and the development of high-throughput tools for the exploration of functional elements of the genome, the chicken has reached model organism status. Functional genomics focuses on understanding the function and regulation of genes and gene products on a global or genome-wide scale. Systems biology attempts to integrate functional information derived from multiple high-content data sets into a holistic view of all biological processes within a cell or organism. Generation of a large collection ( approximately 600K) of chicken expressed sequence tags, representing most tissues and developmental stages, has enabled the construction of high-density microarrays for transcriptional profiling. Comprehensive analysis of this large expressed sequence tag collection and a set of approximately 20K full-length cDNA sequences indicate that the transcriptome of the chicken represents approximately 20,000 genes. Furthermore, comparative analyses of these sequences have facilitated functional annotation of the genome and the creation of several bioinformatic resources for the chicken. Recently, about 20 papers have been published on transcriptional profiling with DNA microarrays in chicken tissues under various conditions. Proteomics is another powerful high-throughput tool currently used for examining the dynamics of protein expression in chicken tissues and fluids. Computational analyses of the chicken genome are providing new insight into the evolution of gene families in birds and other organisms. Abundant functional genomic resources now support large-scale analyses in the chicken and will facilitate identification of transcriptional mechanisms, gene networks, and metabolic or regulatory pathways that will ultimately determine the phenotype of the bird. New technologies such as marker-assisted selection, transgenics, and RNA interference offer the opportunity to modify the phenotype of the chicken to fit defined production goals. This review focuses on functional genomics in the chicken and provides a road map for large-scale exploration of the chicken genome.

Genetical genomics: combining gene expression with marker genotypes in poultry

Microarrays have been widely implemented across the life sciences, although there is still debate on the most effective uses of such transcriptomics approaches. In genetical genomics, gene expression measurements are treated as quantitative traits, and genome regions affecting expression levels are denoted as expression QTL (eQTL). The detected eQTL can represent a locus that lies close to the gene that is being controlled (cis-acting) or one or more loci that are unlinked to the gene that is being controlled (trans-acting). One powerful outcome of genetical genomics is the reconstruction of genetic pathways underlying complex trait variation. Because of the modest size of experiments to date, genetical genomics may fall short of its promise to unravel genetic networks. We propose to combine expression studies with fine mapping of functional trait loci. This synergistic approach facilitates the implementation of genetical genomics for species without inbred resources but is equally applicable to model species. Among livestock species, poultry is well placed to embrace this technology with the availability of the chicken genome sequence, microarrays for various platforms, as well as experimental populations in which QTL have been mapped. In the buildup toward full-blown eQTL studies, we can study the effects of known candidate genes or marked QTL at the gene expression level in more focused studies. To demonstrate the potential of genetical genomics, we have identified the cis and trans effects for a functional BW QTL on chicken chromosome 4 in breast tissue samples from chickens with contrasting QTL genotypes.

Detection of agriculturally important QTLs in chickens and analysis of the factors affecting genotyping strategy

Three single cross populations were generated in order to analyze factors affecting the ability to detect true linkage with minimum false positive or false negative associations, and to detect associations between markers and quantitative traits. The three populations are: (1) a broiler x broiler cross of a single sire and 34 dams, resulting in 266 progeny; (2) a broiler x broiler cross of a single sire and 41 dams resulting in 360 progeny; and (3) a broiler x layer cross of a single sire with 56 dams resulting in 1180 progeny. Based on these three resource populations we show that: a) gradient selective genotyping was more effective than the random selective genotyping; b) selective genotyping was significant at a selected proportion less than 62% of the cumulative truncation point; c) as few as 10% of selected individuals (5% of each of the two tails) were sufficient to show significant association between markers and phenotypes; d) a gradient slices approach was more powerful than using replicates of the extreme groups; and e) in resource populations resulting from crosses between lines of different backgrounds, most of the microsatellite markers used are polymorphic. We also used simulation to test factors affecting power to detect true associations between markers and traits that are hard to detect in experimental resource populations. Using defined populations in the simulation, we concluded that the following guidelines provide reliable detection of linked QTLs: 1) the resource population size should be larger than 100; 2) a QTL effect larger than 0.4 SD is detectable with a reasonable number of markers (>100) and resource population size (>200 subjects); 3) the DNA pool from each tail of the trait distribution should contain at least 10% of the resource family; 4) each of the two DNA pools should include more than 35 individuals. Some of these guidelines that were deduced from the simulation analysis have been confirmed in the experimental part of this study.