Porcine sperm binding to oviduct cells and glycans as supplements to traditional laboratory semen analysis.

Accurate semen evaluation is necessary to maintain high reproductive efficiency but difficult to accomplish. The objective was to determine if the ability to bind oviduct cells or oviduct glycans are useful supplements to traditional semen analyses. Measuring binding to specific soluble glycans is less laborious than assessing binding to oviduct cell aggregates and more suitable for routine use. Previous work has shown that sperm binding to oviduct cells improves fertility prediction, possibly by estimating the ability of sperm to form an oviduct reservoir. The two oviduct glycan motifs, biantennary 6-sialylated N-acetyllactosamine (bi-SiaLN) and LewisX trisaccharide (LeX), that bind boar spermatozoa with high affinity and specificity were tested. Semen from 30 boars was shipped overnight for laboratory analysis and for inseminations to determine fertility (n = 3 replicates). Oviduct cell binding and traditional sperm analyses including motility and morphology were completed. Additionally, binding to soluble fluoresceinated glycans bi-SiaLN, sulfated LeX (suLeX), and the control lactosamine disaccharide (LacNAc) was measured. Inseminations were at 15 farms (>50 matings per boar) in the Midwest and farrowing data from all matings were used. Pregnancy rate (PR) and litter size (LS) were adjusted to account for different farms, number of services, number of doses inseminated, and sow parity, using the MIXED procedure in SAS 9.4. A fertility index (FI) was generated, consisting of PR × LS, to estimate boar overall fertility. Finally, the GLMSELECT procedure was used to select variables having a significant impact on PR, LS, and FI. The predictive models constructed were further analyzed using the REG procedure and accounted for 58% or more of the variation in PR, LS, and FI [PR (P < 0.001, r2 = 0.60), LS (P < 0.001, r2 = 0.58), and FI (P < 0.001, r2 = 0.63)]. The final model for PR includes oviduct cell binding as well as boar age, % distal droplets, head morphology, tail morphology, beat/cross frequency, and curvilinear velocity. The final model for LS includes boar age, % distal droplets, tail morphology, and overall morphology. Finally, the FI model included boar age, % distal droplets, head morphology, tail morphology, curvilinear velocity, and semen volume per ejaculate. Although binding to intact oviduct cells was impactful as a means to predict PR, binding to specific soluble oviduct glycans was not a useful supplement to traditional semen analysis.

Whole-genome sequence, SNP chips and pedigree structure: building demographic profiles in domestic dog breeds to optimize genetic-trait mapping.

In the decade following publication of the draft genome sequence of the domestic dog, extraordinary advances with application to several fields have been credited to the canine genetic system. Taking advantage of closed breeding populations and the subsequent selection for aesthetic and behavioral characteristics, researchers have leveraged the dog as an effective natural model for the study of complex traits, such as disease susceptibility, behavior and morphology, generating unique contributions to human health and biology. When designing genetic studies using purebred dogs, it is essential to consider the unique demography of each population, including estimation of effective population size and timing of population bottlenecks. The analytical design approach for genome-wide association studies (GWAS) and analysis of whole-genome sequence (WGS) experiments are inextricable from demographic data. We have performed a comprehensive study of genomic homozygosity, using high-depth WGS data for 90 individuals, and Illumina HD SNP data from 800 individuals representing 80 breeds. These data were coupled with extensive pedigree data analyses for 11 breeds that, together, allowed us to compute breed structure, demography, and molecular measures of genome diversity. Our comparative analyses characterize the extent, formation and implication of breed-specific diversity as it relates to population structure. These data demonstrate the relationship between breed-specific genome dynamics and population architecture, and provide important considerations influencing the technological and cohort design of association and other genomic studies.