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Marek's Disease (MD), which can result in neurological damage and tumour formation, has large effects on the economy and animal welfare of the poultry industry worldwide. Previously, we mapped autosomal MD QTL regions (QTLRs) by individual genotyping of an F 6 population from a full-sib advanced intercross line. We further mapped MD QTLRs on the chicken Z chromosome (GGZ) using the same F 6 population, and by selective DNA pooling (SDP) of 8 elite egg production lines. Here we used SDP of the same pools used on GGZ to map autosomal MD QTLRs. Thirty-seven QTLRs were found. Seven of the QTLRs were tested by all sires from the same 8 lines, individually genotyped for QTLR markers. Five of the tested QTLRs were confirmed. Linkage disequilibrium (LD) was calculated for all QTLR markers on the same chromosome, and complex LD blocks were found. Distribution of P and LD values were used to assess the QTLR causative elements. Allele substitution effects were calculated based on both pooled SNP microarray genotypes, and individual genotypes of QTLRs markers. Substantial allele effect and contribution to the phenotypic and genotypic variation were obtained. The results explain part of the MD response, and provide targets for mitigating MD., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics approval: Institutional Review Board Statement: The animal study protocol was approved by Hy-Line International Institutional Animal Care and Use Committee guidelines. Hy-Line do not have specific project identification codes. All of these samples had been collected in the past and stored frozen until use. At the termination of the study animals were humanely euthanized under the approval of the Hy-Line IACUC and supervision of licensed veterinarians., (© 2024. The Author(s).)

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 QTL regions (QTLR) influencing resistance to MDV, including an F 6 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, miRNAs, lncRNAs 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.

Bovine respiratory disease (BRD) is the leading cause of morbidity and mortality in feedlot cattle, caused by multiple pathogens that become more virulent in response to stress. As clinical signs often go undetected and various preventive strategies failed, identification of genes affecting BRD is essential for selection for resistance. Selective DNA pooling (SDP) was applied in a genome wide association study (GWAS) to map BRD QTLs in Israeli Holstein male calves. Kosher scoring of lung adhesions was used to allocate 122 and 62 animals to High (Glatt Kosher) and Low (Non-Kosher) resistant groups, respectively. Genotyping was performed using the Illumina BovineHD BeadChip according to the Infinium protocol. Moving average of -logP was used to map QTLs and Log drop was used to define their boundaries (QTLRs). The combined procedure was efficient for high resolution mapping. Nineteen QTLRs distributed over 13 autosomes were found, some overlapping previous studies. The QTLRs contain polymorphic functional and expression candidate genes to affect kosher status, with putative immunological and wound healing activities. Kosher phenotyping was shown to be a reliable means to map QTLs affecting BRD morbidity.

Background: Mastitis is a major disease of dairy cattle occurring in response to environmental exposure to infective agents with a great economic impact on dairy industry. Somatic cell count (SCC) and its log transformation in somatic cell score (SCS) are traits that have been used as indirect measures of resistance to mastitis for decades in selective breeding. A selective DNA pooling (SDP) approach was applied to identify Quantitative Trait Loci (QTL) for SCS in Valdostana Red Pied cattle using the Illumina Bovine HD BeadChip., Results: A total of 171 SNPs reached the genome-wide significance for association with SCS. Fifty-two SNPs were annotated within genes, some of those involved in the immune response to mastitis. On BTAs 1, 2, 3, 4, 9, 13, 15, 17, 21 and 22 the largest number of markers in association to the trait was found. These regions identified novel genomic regions related to mastitis (1-Mb SNP windows) and confirmed those already mapped. The largest number of significant SNPs exceeding the threshold for genome-wide significant signal was found on BTA 15, located at 50.43-51.63 Mb., Conclusions: The genomic regions identified in this study contribute to a better understanding of the genetic control of the mastitis immune response in cattle and may allow the inclusion of more detailed QTL information in selection programs.

We report on a complete genome scan for quantitative trait loci (QTL) affecting milk protein percentage (PP) in the Italian Holstein-Friesian cattle population, applying a selective DNA pooling strategy in a daughter design. Ten Holstein-Friesian sires were chosen, and for each sire, about 200 daughters, each from the high and low tails of estimated breeding value for PP, were used to construct milk DNA pools. Sires and pools were genotyped for 181 dinucleotide microsatellites covering all cattle autosomes. Sire marker allele frequencies in the pools were obtained by shadow correction of peak height in the electropherograms. After quality control, pool data from eight sires were used for all subsequent analyses. The QTL heterozygosity estimate was lower than that of similar studies in other cattle populations. Multiple marker mapping identified 19 QTL located on 14 chromosomes (BTA1, 2, 3, 4, 5, 6, 8, 9, 12, 14, 17, 20, 23 and 27). The sires were also genotyped for seven polymorphic sites in six candidate genes (ABCG2, SPP1, casein kappa, DGAT1, GHR and PRLR) located within QTL regions of BTA6, 14 and 20 found in this study. The results confirmed or excluded the involvement of some of the analysed markers as the causative polymorphic sites of the identified QTL. The QTL identified, combined with genotype data of these candidate genes, will help to identify other quantitative trait genes and clarify the complex QTL patterns observed for a few chromosomes. Overall, the results are consistent with the Italian Holstein population having been under long-term selection for high PP., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

Selective DNA pooling (SDP) is a cost-effective means for an initial scan for linkage between marker and quantitative trait loci (QTL) in suitable populations. The method is based on scoring marker allele frequencies in DNA pools from the tails of the population trait distribution. Various analytical approaches have been proposed for QTL detection using data on multiple families with SDP analysis. This article presents a new experimental procedure, fractioned-pool design (FPD), aimed to increase the reliability of SDP mapping results, by "fractioning" the tails of the population distribution into independent subpools. FPD is a conceptual and structural modification of SDP that allows for the first time the use of permutation tests for QTL detection rather than relying on presumed asymptotic distributions of the test statistics. For situations of family and cross mapping design we propose a spectrum of new tools for QTL mapping in FPD that were previously possible only with individual genotyping. These include: joint analysis of multiple families and multiple markers across a chromosome, even when the marker loci are only partly shared among families; detection of families segregating (heterozygous) for the QTL; estimation of confidence intervals for the QTL position; and analysis of multiple-linked QTL. These new advantages are of special importance for pooling analysis with SNP chips. Combining SNP microarray analysis with DNA pooling can dramatically reduce the cost of screening large numbers of SNPs on large samples, making chip technology readily applicable for genomewide association mapping in humans and farm animals. This extension, however, will require additional, nontrivial, development of FPD analytical tools.

Many large, half-sib sire families are an integral component of chicken genetic improvement programs. These family structures include a sufficient number of individuals for mapping quantitative trait loci (QTL) at high statistical power. However, realizing this statistical power through individual or selective genotyping is yet too costly to be feasible under current genotyping methodologies. Genotyping costs can be greatly reduced through selective DNA pooling, involving densitometric estimates of marker allele frequencies in pooled DNA samples. When using dinucleotide microsatellite markers, however, such estimates are often confounded by overlapping "shadow" bands and can be confounded further by differential amplification of alleles. In the present study a shadow correction procedure provided accurate densitometric estimates of allele frequency for dinucleotide microsatellite markers in pools made from chicken purified DNA samples, fresh blood samples, and frozen-thawed blood samples. In a retrospective study, selective DNA pooling with thawed blood samples successfully identified two QTL previously shown by selective genotyping to affect resistance in chickens to Marek's disease. It is proposed that use of selective DNA pooling can provide relatively low-cost mapping and use in marker-assisted selection of QTL that affect production traits in chickens.

"Selective DNA pooling" accomplishes quantitative trait locus (QTL) mapping through densitometric estimates of marker allele frequencies in pooled DNA samples of phenotypically extreme individuals. With poly(TG) microsatellites, such estimates are confounded by "shadow" ("stutter") bands. A correction procedure was developed on the basis of an observed linear regression between shadow band intensity and allele TG repeat number. Using this procedure, a selective DNA pooling study with respect to milk protein percentage was implemented in Israel-Holstein dairy cattle. Pools were prepared from milk samples of high and low daughters of each of seven sires and genotyped with respect to 11 markers. Highly significant associations with milk protein percentage were found for 5 of the markers; 4 of these markers confirmed previous reports. Selective DNA pooling accessed 80.6 and 48.3%, respectively, of the information that would have been available through individual selective genotyping or total population genotyping. In effect, the statistical power of 45,600 individual genotypings was obtained from 328 pool genotypings. This methodology can make genome-wide mapping of QTL accessible to moderately sized breeding organizations.