Large-scale investigation of the parameters in response to Eimeria maxima challenge in broilers

Coccidiosis, a parasitic disease of the intestinal tract caused by members of the genera Eimeria and Isospora, is one of the most common and costly diseases in chicken. The aims of this study were to assess the effect of the challenge and level of variability of measured parameters in chickens during the challenge with Eimeria maxima. Furthermore, this study aimed to investigate which parameters are the most relevant indicators of the health status. Finally, the study also aimed to estimate accuracy of prediction for traits that cannot be measured on large scale (such as intestinal lesion score and fecal oocyst count) using parameters that can easily be measured on all animals. The study was performed in 2 parts: a pilot challenge on 240 animals followed by a large-scale challenge on 2,024 animals. In both experiments, animals were challenged with 50,000 Eimeria maxima oocysts at 16 d of age. In the pilot challenge, all animals were measured for BW gain, plasma coloration, hematocrit, and rectal temperature and, in addition, a subset of 48 animals was measured for oocyst count and the intestinal lesion score. All animals from the second challenge were measured for BW gain, plasma coloration, and hematocrit whereas a subset of 184 animals was measured for intestinal lesion score, fecal oocyst count, blood parameters, and plasma protein content and composition. Most of the parameters measured were significantly affected by the challenge. Lesion scores for duodenum and jejunum (P < 0.001), oocyst count (P < 0.05), plasma coloration for the optical density values between 450 and 490 nm (P < 0.001), albumin (P < 0.001), α1-globulin (P < 0.01), α2-globulin (P < 0.001), α3-globulin (P < 0.01), and β2-globulin (P < 0.001) were the most strongly affected parameters and expressed the greatest levels of variation. Plasma protein profiles proved to be a new, reliable parameter for measuring response to Eimeria maxima. Prediction of intestinal lesion score and fecal oocyst count using the other parameters measured was not very precise (R2 < 0.7). The study was successfully performed in real raising conditions on a large scale. Finally, we observed a high variability in response to the challenge, suggesting that broilers' response to Eimeria maxima has a strong genetic determinism, which may be improved by genetic selection.

Numerical analysis of intensity signals resulting from genotyping pooled DNA samples in beef cattle and broiler chicken

Pooled genomic DNA has been proposed as a cost-effective approach in genomewide association studies (GWAS). However, algorithms for genotype calling of biallelic SNP are not adequate with pooled DNA samples because they assume the presence of 2 fluorescent signals, 1 for each allele, and operate under the expectation that at most 2 copies of the variant allele can be found for any given SNP and DNA sample. We adapt analytical methodology from 2-channel gene expression microarray technology to SNP genotyping of pooled DNA samples. Using 5 datasets from beef cattle and broiler chicken of varying degrees of complexity in terms of design and phenotype, continuous and dichotomous, we show that both differential hybridization (M = green minus red intensity signal) and abundance (A = average of red and green intensities) provide useful information in the prediction of SNP allele frequencies. This is predominantly true when making inference about extreme SNP that are either nearly fixed or highly polymorphic. We propose the use of model-based clustering via mixtures of bivariate normal distributions as an optimal framework to capture the relationship between hybridization intensity and allele frequency from pooled DNA samples. The range of M and A values observed here are in agreement with those reported within the context of gene expression microarray and also with those from SNP array data within the context of analytical methodology for the identification of copy number variants. In particular, we confirm that highly polymorphic SNP yield a strong signal from both channels (red and green) while lowly or nonpolymorphic SNP yield a strong signal from 1 channel only. We further confirm that when the SNP allele frequencies are known, either because the individuals in the pools or from a closely related population are themselves genotyped, a multiple regression model with linear and quadratic components can be developed with high prediction accuracy. We conclude that when these approaches are applied to the estimation of allele frequencies, the resulting estimates allow for the development of cost-effective and reliable GWAS.

Genome-wide association studies for feedlot and growth traits in cattle

A genome wide-association study for production traits in cattle was carried out using genotype data from the 10K Affymetrix (Santa Clara, CA) and the 50K Illumina (San Diego, CA) SNP chips. The results for residual feed intake (RFI), BW, and hip height in 3 beef breed types (Bos indicus, Bos taurus, and B. indicus × B. taurus), and for stature in dairy cattle, are presented. The aims were to discover SNP associated with all traits studied, but especially RFI, and further to test the consistency of SNP effects across different cattle populations and breed types. The data were analyzed within data sets and within breed types by using a mixed model and fitting 1 SNP at a time. In each case, the number of significant SNP was more than expected by chance alone. A total of 75 SNP from the reference population with 50K chip data were significant (P < 0.001) for RFI, with a false discovery rate of 68%. These 75 SNP were mapped on 24 different BTA. Of the 75 SNP, the 9 most significant SNP were detected on BTA 3, 5, 7, and 8, with P ≤ 6.0 × 10(-5). In a population of Angus cattle divergently selected for high and low RFI and 10K chip data, 111 SNP were significantly (P < 0.001) associated with RFI, with a false discovery rate of 7%. Approximately 103 of these SNP were therefore likely to represent true positives. Because of the small number of SNP common to both the 10K and 50K SNP chips, only 27 SNP were significantly (P < 0.05) associated with RFI in the 2 populations. However, other chromosome regions were found that contained SNP significantly associated with RFI in both data sets, although no SNP within the region showed a consistent effect on RFI. The SNP effects were consistent between data sets only when estimated within the same breed type.

The combined effect of SNP-marker and phenotype attributes in genome-wide association studies

The last decade has seen rapid improvements in high-throughput single nucleotide polymorphism (SNP) genotyping technologies that have consequently made genome-wide association studies (GWAS) possible. With tens to hundreds of thousands of SNP markers being tested simultaneously in GWAS, it is imperative to appropriately pre-process, or filter out, those SNPs that may lead to false associations. This paper explores the relationships between various SNP genotype and phenotype attributes and their effects on false associations. We show that (i) uniformly distributed ordinal data as well as binary data are more easily influenced, though not necessarily negatively, by differences in various SNP attributes compared with normally distributed data; (ii) filtering SNPs on minor allele frequency (MAF) and extent of Hardy–Weinberg equilibrium (HWE) deviation has little effect on the overall false positive rate; (iii) in some cases, filtering on MAF only serves to exclude SNPs from the analysis without reduction of the overall proportion of false associations; and (iv) HWE, MAF and heterozygosity are all dependent on minor genotype frequency, a newly proposed measure for genotype integrity.

Assignment of transcription factor NFAT5 to human chromosome 16q22.1, murine chromosome 8D and porcine chromosome 6p1.4 and comparison of the polyglutamine domains

To date, transcription factors of the NFAT family (nuclear factors of activated T cells) have been described for mouse and man. Recently, we mapped the human NFAT5 gene to chromosome 16 by PCR using DNA from hybrid cell lines. Here we report the exact position of the human gene between D16S496 and WI5254 within the 16q22.1 subband, the localization of the murine gene at chromosome 8D, and the identification and mapping of the porcine counterpart to chromosome 6p1.4.

Construction of a whole-genome radiation hybrid panel for high-resolution gene mapping in pigs

We have developed a panel of 152 whole-genome radiation hybrids by fusing irradiated diploid pig lymphocytes or fibroblasts with recipient hamster permanent cells. The number and size of the porcine chromosome fragments retained in each hybrid clone were checked by fluorescence in situ hybridization with a SINE probe or by primed in situ labeling (PRINS) with SINE-specific primers. A strategy based on the interspersed repetitive sequence polymerase chain reaction (IRS-PCR) was developed for selected clones to determine if the large fragments painted by the SINE probe corresponded to one pig chromosome or to different fragments of several chromosomes. This strategy was buttressed by a double PRINS approach using primers specific for alpha-satellite sequences of two different groups of swine chromosomes. Genome retention frequency was estimated for each clone by PCR with 32 markers localized on different porcine chromosomes. Of the 152 hybrids produced, 126 were selected on the basis of cytogenetic content and chromosome retention frequency to construct a radiation hybrid map of swine chromosome 8. Our initial results for this chromosome indicate that the resolution of the radiation hybrid map is 18 times higher than that obtained by linkage analysis.

IMpRH server: an RH mapping server available on the Web

SUMMARY

The INRA-Minnesota Porcine Radiation Hybrid (IMpRH) Server provides both a mapping tool (IMpRH mapping tool) and a database (IMpRH database) of officially submitted results. The mapping tool permits the mapping of a new marker relatively to markers previously mapped on the IMpRH panel. The IMpRH database is the official database for submission of new results and queries. The database not only permits the sharing of public data but also semi-private and private data.