Prospecting for pig single nucleotide polymorphisms in the human genome: have we struck gold?

Gene-to-gene variation in the frequency of single nucleotide polymorphisms (SNPs) has been observed in humans, mice, rats, primates and pigs, but a relationship across species in this variation has not been described. Here, the frequency of porcine coding SNPs (cSNPs) identified by in silico methods, and the frequency of murine cSNPs, were compared with the frequency of human cSNPs across homologous genes. From 150,000 porcine expressed sequence tag (EST) sequences, a total of 452 SNP-containing sequence clusters were found, totalling 1394 putative SNPs. All the clustered porcine EST annotations and SNP data have been made publicly available at http://sputnik.btk.fi/project?name=swine. Human and murine cSNPs were identified from dbSNP and were characterized as either validated or total number of cSNPs (validated plus non-validated) for comparison purposes. The correlation between in silico pig cSNP and validated human cSNP densities was found to be 0.77 (p < 0.00001) for a set of 25 homologous genes, while a correlation of 0.48 (p < 0.0005) was found for a primarily random sample of 50 homologous human and mouse genes. This is the first evidence of conserved gene-to-gene variability in cSNP frequency across species and indicates that site-directed screening of porcine genes that are homologous to cSNP-rich human genes may rapidly advance cSNP discovery in pigs.

Optimal haplotype structure for linkage disequilibrium-based fine mapping of quantitative trait loci using identity by descent.

A linkage disequilibrium-based method for fine mapping quantitative trait loci (QTL) has been described that uses similarity between individuals' marker haplotypes to determine if QTL alleles are identical by descent (IBD) to model covariances among individuals' QTL alleles for a mixed linear model. Mapping accuracy with this method was found to be sensitive to the number of linked markers that was included in the haplotype when fitting the model at a putative position of the QTL. The objective of this study was to determine the optimal haplotype structure for this IBD-based method for fine mapping a QTL in a previously identified QTL region. Haplotypes consisting of 1, 2, 4, 6, or all 10 available markers were fit as a "sliding window" across the QTL region under ideal and nonideal simulated population conditions. It was found that using haplotypes of 4 or 6 markers as a sliding "window" resulted in the greatest mapping accuracy under nearly all conditions, although the true IBD state at a putative QTL position was most accurately predicted by IBD probabilities obtained using all markers. Using 4 or 6 markers resulted in greater discrimination of IBD probabilities between positions while maintaining sufficient accuracy of IBD probabilities to detect the QTL. Fitting IBD probabilities on the basis of a single marker resulted in the worst mapping accuracy under all conditions because it resulted in poor accuracy of IBD probabilities. In conclusion, for fine mapping using IBD methods, marker information must be used in a manner that results in sensitivity of IBD probabilities to the putative position of the QTL while maintaining sufficient accuracy of IBD probabilities to detect the QTL. Contrary to expectation, use of haplotypes of 4-6 markers to derive IBD probabilities, rather than all available markers, best fits these criteria. Thus for populations similar to those simulated here, optimal mapping accuracy for this IBD-based fine-mapping method is obtained with a haplotype structure including a subset of all available markers.

SNP analysis of AMY2 and CTSL genes in Litopenaeus vannamei and Penaeus monodon shrimp.

Genetic studies in shrimp have focused on disease, with production traits such as growth left unexamined. Two shrimp species, Litopenaeus vannamei and Penaeus monodon, which represent the majority of US shrimp imports, were selected for single nucleotide polymorphism (SNP) discovery in alpha-amylase (AMY2) and cathepsin-l (CTSL), both candidate genes for growth. In L. vannamei, four SNPs were found in AMY2 and one SNP was found in CTSL. In P. monodon, one SNP was identified in CTSL. The CTSL gene was mapped to linkage group 28 of P. monodon using the female map developed with the Australian P. monodon mapping population. Association analyses for the AMY2 and CTSL genes with body weight (BW) were performed in two L. vannamei populations. While neither gene was found to be significantly associated with BW in these populations, there was a trend in one population towards higher BW for allele G of CTSL SNP C681G.

Characterization of an X-chromosome PCR-RFLP marker associated with fat deposition and growth in the pig.

The X-chromosome, highly conserved within mammals, has been shown to contain major quantitative trait loci (QTL) for growth and fat deposition in the pig. We have discovered a BamHI polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) marker that was assigned to the porcine X-chromosome by two-point and multi-point linkage analysis following genotyping of a three-generation Berkshire by Yorkshire reference family. The marker was positioned 9 cM telomeric to SW2126 and 15.6 cM centromeric to SW1943. Sequence flanking the marker was found to have high similarity to existing database porcine DNA repeat elements. Association analyses of the BamHI marker for growth and meat quality traits in the reference family revealed significant association with marbling (P < 0.03), 10th rib back fat (P < 0.09) and total lipid percentage (P < 0.05), as well as with loin eye area (P < 0.04), average glycolytic potential (P < 0.03) and average lactate content (P < 0.04). Further studies are required to determine the X-chromosome functional gene affecting fat deposition and growth in the pig.

Comparing linkage disequilibrium-based methods for fine mapping quantitative trait loci.

Recently, a method for fine mapping quantitative trait loci (QTL) using linkage disequilibrium was proposed to map QTL by modeling covariance between individuals, due to identical-by-descent (IBD) QTL alleles, on the basis of the similarity of their marker haplotypes under an assumed population history. In the work presented here, the advantage of using marker haplotype information for fine mapping QTL was studied by comparing the IBD-based method with 10 markers to regression on a single marker, a pair of markers, or a two-locus haplotype under alternative population histories. When 10 markers were genotyped, the IBD-based method estimated the position of the QTL more accurately than did single-marker regression in all populations. When 20 markers were genotyped for regression, as single-marker methods do not require knowledge of haplotypes, the mapping accuracy of regression in all populations was similar to or greater than that of the IBD-based method using 10 markers. Thus for populations similar to those simulated here, the IBD-based method is comparable to single-marker regression analysis for fine mapping QTL.