Casein haplotypes and their association with milk production traits in Norwegian Red cattle

A high resolution SNP map was constructed for the bovine casein region to identify haplotype structures and study associations with milk traits in Norwegian Red cattle. Our analyses suggest separation of the casein cluster into two haplotype blocks, one consisting of the CSN1S1, CSN2 and CSN1S2 genes and another one consisting of the CSN3 gene. Highly significant associations with both protein and milk yield were found for both single SNPs and haplotypes within the CSN1S1-CSN2-CSN1S2 haplotype block. In contrast, no significant association was found for single SNPs or haplotypes within the CSN3 block. Our results point towards CSN2 and CSN1S2 as the most likely loci harbouring the underlying causative DNA variation. In our study, the most significant results were found for the SNP CSN2_67 with the C allele consistently associated with both higher protein and milk yields. CSN2_67 calls a C to an A substitution at codon 67 in β-casein gene resulting in histidine replacing proline in the amino acid sequence. This polymorphism determines the protein variants A1/B (CSN2_67 A allele) versus A2/A3 (CSN2_67 C allele). Other studies have suggested that a high consumption of A1/B milk may affect human health by increasing the risk of diabetes and heart diseases. Altogether these results argue for an increase in the frequency of the CSN2_67 C allele or haplotypes containing this allele in the Norwegian Red cattle population by selective breeding

Quantifying superspreading for COVID-19 using Poisson mixture distributions.

The number of secondary cases, i.e. the number of new infections generated by an infectious individual, is an important parameter for the control of infectious diseases. When individual variation in disease transmission is present, like for COVID-19, the distribution of the number of secondary cases is skewed and often modeled using a negative binomial distribution. However, this may not always be the best distribution to describe the underlying transmission process. We propose the use of three other offspring distributions to quantify heterogeneity in transmission, and we assess the possible bias in estimates of the mean and variance of this distribution when the data generating distribution is different from the one used for inference. We also analyze COVID-19 data from Hong Kong, India, and Rwanda, and quantify the proportion of cases responsible for 80% of transmission, [Formula: see text], while acknowledging the variation arising from the assumed offspring distribution. In a simulation study, we find that variance estimates may be biased when there is a substantial amount of heterogeneity, and that selection of the most accurate distribution from a set of distributions is important. In addition we find that the number of secondary cases for two of the three COVID-19 datasets is better described by a Poisson-lognormal distribution

Genetic support for a quantitative trait nucleotide in the ABCG2 gene affecting milk composition of dairy cattle

<p>Abstract</p> <p>Background</p> <p>Our group has previously identified a quantitative trait locus (QTL) affecting fat and protein percentages on bovine chromosome 6, and refined the QTL position to a 420-kb interval containing six genes. Studies performed in other cattle populations have proposed polymorphisms in two different genes (<it>ABCG2 </it>and <it>OPN</it>) as the underlying functional QTL nucleotide. Due to these conflicting results, we have included these QTNs, together with a large collection of new SNPs produced from PCR sequencing, in a dense marker map spanning the QTL region, and reanalyzed the data using a combined linkage and linkage disequilibrium approach.</p> <p>Results</p> <p>Our results clearly exclude the <it>OPN </it>SNP (<it>OPN_3907</it>) as causal site for the QTL. Among 91 SNPs included in the study, the <it>ABCG2 </it>SNP (<it>ABCG2_49</it>) is clearly the best QTN candidate. The analyses revealed the presence of only one QTL for the percentage traits in the tested region. This QTL was completely removed by correcting the analysis for <it>ABCG2_49</it>. Concordance between the sires' marker genotypes and segregation status for the QTL was found for <it>ABCG2_49 </it>only. The C allele of <it>ABCG2_49 </it>is found in a marker haplotype that has an extremely negative effect on fat and protein percentages and positive effect on milk yield. Of the 91 SNPs, <it>ABCG2_49 </it>was the only marker in perfect linkage disequilibrium with the QTL.</p> <p>Conclusion</p> <p>Based on our results, OPN_3907 can be excluded as the polymorphism underlying the QTL. The results of this and other papers strongly suggest the [A/C] mutation in <it>ABCG2_49 </it>as the causal mutation, although the possibility that <it>ABCG2_49 </it>is only a marker in perfect LD with the true mutation can not be completely ruled out.</p

Large scale genome-wide association and LDLA mapping study identifies QTLs for boar taint and related sex steroids

<p>Abstract</p> <p>Background</p> <p>Boar taint is observed in a high proportion of uncastrated male pigs and is characterized by an unpleasant odor/flavor in cooked meat, primarily caused by elevated levels of androstenone and skatole. Androstenone is a steroid produced in the testis in parallel with biosynthesis of other sex steroids like testosterone and estrogens. This represents a challenge when performing selection against androstenone in breeding programs, without simultaneously decreasing levels of other steroids. The aim of this study was to use high-density genome wide association (GWA) in combination with linkage disequilibrium-linkage analysis (LDLA) to identify quantitative trait loci (QTL) associated with boar taint compounds and related sex steroids in commercial Landrace (n = 1,251) and Duroc (n = 918) breeds.</p> <p>Results</p> <p>Altogether, 14 genome wide significant (GWS) QTL regions for androstenone in subcutaneous fat were obtained from the LDLA study in Landrace and 14 GWS QTL regions in Duroc. LDLA analysis revealed that 7 of these QTL regions, located on SSC 1, 2, 3, 7 and 15, were obtained in both breeds. All 14 GWS androstenone QTLs in Landrace are also affecting the estrogens at chromosome wise significance (CWS) or GWS levels, while in Duroc, 3 of the 14 QTLs affect androstenone without affecting any of the estrogens. For skatole, 10 and 4 QTLs were GWS in the LDLA analysis for Landrace and Duroc respectively, with 4 of these detected in both breeds. The GWS QTLs for skatole obtained by LDLA are located at SSC 1, 5, 6, 7, 10, 11, 13 and 14.</p> <p>Conclusion</p> <p>This is the first report applying the Porcine 60 K SNP array for simultaneous analysis of boar taint compounds and related sex hormones, using both GWA and LDLA approaches. Several QTLs are involved in regulation of androstenone and skatole, and most of the QTLs for androstenone are also affecting the levels of estrogens. Seven QTLs for androstenone were detected in one breed and confirmed in the other, i.e. in an independent sample, although the majority of QTLs are breed specific. Most QTLs for skatole do not negatively affect other sex hormones and should be easier to implement into the breeding scheme.</p

Mapping of a Milk Production Quantitative Trait Locus to a 420-kb Region on Bovine Chromosome 6

A QTL affecting milk production traits was previously mapped to an interval of 7.5 cM on chromosome 6 in Norwegian dairy cattle. This article aimed to refine this position by increasing the map density in the region by a set of single-nucleotide polymorphisms and analyzing the data with a combined linkage and linkage disequilibrium approach. Through a series of single- and multitrait and single- and multipoint analyses, the QTL was positioned to an interval surrounded by the genes ABCG2 and LAP3. As no recombinations were detected in this interval, physical mapping was required for further refining. By using radiation hybrid mapping as well as BAC clones, the bovine and human comparative maps in the region are resolved, and the QTL is mapped within a distance of 420 kb