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BackgroundMany studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination.ResultsWe hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas.ConclusionThis work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ.

Recent studies have revealed that the major genes of the mammalian sex determination pathway are also involved in sex determination of fish. Several studies have reported QTL in various species and strains of tilapia, regions contributing to sex determination have been identified on linkage groups 1, 3, and 23. Genes contributing to sex-specific mortality have been detected on linkage groups 2, 6, and 23. To test whether the same genes might control sex determination in mammals and fishes, we mapped 11 genes that are considered putative master key regulators of sex determination: Amh, Cyp19, Dax1, Dmrt2, Dmrta2, Fhl3l, Foxl2, Ixl, Lhx9, Sf1, and Sox8. We identified polymorphisms in noncoding regions of these genes and genotyped these sites for 90 individuals of an [F.sub.2] mapping family. Mapping of Dax1 joined LG16 and LG21 into a single linkage group. The Amh and Dmrta2 genes were mapped to two distinct regions of LG23. The Amh gene was mapped 5 cM from UNH879 within a QTL region for sex determination and 2 cM from UNH216 within a QTL region for sex-specific mortality. Dmrta2 was mapped 4 cM from UNH848 within another QTL region for sex determination. Cyp19 was mapped to LG1 far from a previously reported QTL region for sex determination on this chromosome. Seven other candidate genes mapped to LG4, -11, -12, -14, and -17.

We present a simple algorithm for reconstruction of haplotypes from a sample of multilocus genotypes. The algorithm is aimed specifically for analysis of very large pedigrees for small chromosomal segments, where recombination frequency within the chromosomal segment can be assumed to be zero. The algorithm was tested both on simulated pedigrees of 155 individuals in a family structure of three generations and on real data of 1149 animals from the Israeli Holstein dairy cattle population, including 406 bulls with genotypes, but no females with genotypes. The rate of haplotype resolution for the simulated data was >91% with a standard deviation of 2%. With 20% missing data, the rate of haplotype resolution was 67.5% with a standard deviation of 1.3%. In both cases all recovered haplotypes were correct. In the real data, allele origin was resolved for 22% of the heterozygous genotypes, even though 70% of the genotypes were missing. Haplotypes were resolved for 36% of the males. Computing time was insignificant for both data sets. Despite the intricacy of large-scale real pedigree genotypes, the proposed algorithm provides a practical rule-based solution for resolving haplotypes for small chromosomal segments in commercial animal populations.

Nine Israeli Holstein sire families with 2978 daughters were analyzed for quantitative trait loci effects on chromosome 6 for five milk production traits by a daughter design. All animals were genotyped for 2 markers. The three families with significant effects were genotyped for up to 10 additional markers spanning positions 0-122 cM of BTA6. Two sires were segregating for a locus affecting protein and fat percentage near position 55 cM with an estimated substitution effect of 0.18% protein, which is equivalent to one phenotypic standard deviation. This locus was localized to a confidence interval of 4 cM. One of these sires was also heterozygous for a locus affecting milk, fat, and protein production near the centromere. The hypothesis of two segregating loci was verified by multiple regression analysis. A third sire was heterozygous for a locus affecting milk and protein percentage near the telomeric end of the chromosome. Possible candidates for the major quantitative gene near position 55 cM were determined by comparative mapping. IBSP and SSP1 were used as anchors for the orthologous region on human chromosome 4. Twelve genes were detected within a 2-Mbp sequence. None of these genes have been previously associated with lactogenesis.

Abstract Background Beef traceability has become mandatory in many regions of the world and is typically achieved through the use of unique numerical codes on ear tags and animal passports. DNA-based traceability uses the animal's own DNA code to identify it and the products derived from it. Using SNaPshot, a primer-extension-based method, a multiplex of 25 SNPs in a single reaction has been practiced for reducing the expense of genotyping a panel of SNPs useful for identity control. Findings To further decrease SNaPshot's cost, we introduced the Perl script SNPmplexViewer, which facilitates the analysis of trace files for reactions performed without the use of fluorescent size standards. SNPmplexViewer automatically aligns reference and target trace electropherograms, run with and without fluorescent size standards, respectively. SNPmplexViewer produces a modified target trace file containing a normalised trace in which the reference size standards are embedded. SNPmplexViewer also outputs aligned images of the two electropherograms together with a difference profile. Conclusions Modified trace files generated by SNPmplexViewer enable genotyping of SnaPshot reactions performed without fluorescent size standards, using common fragment-sizing software packages. SNPmplexViewer's normalised output may also improve the genotyping software's performance. Thus, SNPmplexViewer is a general free tool enabling the reduction of SNaPshot's cost as well as the fast viewing and comparing of trace electropherograms for fragment analysis. SNPmplexViewer is available at http://cowry.agri.huji.ac.il/cgi-bin/SNPmplexViewer.cgi.

Abstract Background Copy number variation (CNV) has been recently identified in human and other mammalian genomes, and there is a growing awareness of CNV's potential as a major source for heritable variation in complex traits. Genomic selection is a newly developed tool based on the estimation of breeding values for quantitative traits through the use of genome-wide genotyping of SNPs. Over 30,000 Holstein bulls have been genotyped with the Illumina BovineSNP50 BeadChip, which includes 54,001 SNPs (~SNP/50,000 bp), some of which fall within CNV regions. Results We used the BeadChip data obtained for 912 Israeli bulls to investigate the effects of CNV on SNP calls. For each of the SNPs, we estimated the frequencies of occurrence of loss of heterozygosity (LOH) and of gain, based either on deviation from the expected Hardy-Weinberg equilibrium (HWE) or on signal intensity (SI) using the PennCNV "detect" option. Correlations between LOH/CNV frequencies predicted by the two methods were low (up to r = 0.08). Nevertheless, 418 locations displayed significantly high frequencies by both methods. Efficiency of designating large genomic clusters of olfactory receptors as CNVs was 29%. Frequency values for copy loss were distinguishable in non-autosomal regions, indicating misplacement of a region in the current BTA7 map. Analysis of BTA18 placed major quantitative trait loci affecting net merit in the US Holstein population in regions rich in segmental duplications and CNVs. Enrichment of transporters in CNV loci suggested their potential effect on milk-production traits. Conclusions Expansion of HWE and PennCNV analyses allowed estimating LOH/CNV frequencies, and combining the two methods yielded more sensitive detection of inherited CNVs and better estimation of their possible effects on cattle genetics. Although this approach was more effective than methodologies previously applied in cattle, it has severe limitations. Thus the number of CNVs reported here for the Holstein breed may represent as little as one-tenth of inherited common structural variation.

Abstract Background Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Results We hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas. Conclusion This work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ.