A polymorphism within the equine CRISP3 gene is associated with stallion fertility in Hanoverian warmblood horses

Fertility of stallions is of high economic importance, especially for large breeding organisations and studs. Breeding schemes with respect to fertility traits and selection of stallions at an early stage may be improved by including molecular genetic markers associated with traits. The genes coding for equine cysteine-rich secretory proteins (CRISPs) are promising candidate genes because previous studies have shown that CRISPs play a role in the fertilising ability of male animals. We have previously characterised the three equine CRISP genes and identified a non-synonymous polymorphism in the CRISP1 gene. In this study, we report one non-synonymous polymorphism in the CRISP2 gene and four non-synonymous polymorphisms in the CRISP3 gene. All six CRISP polymorphisms were genotyped in 107 Hanoverian breeding stallions. Insemination records of stallions were used to analyse the association between CRISP polymorphisms and fertility traits. Three statistical models were used to evaluate the influence of single mutations, genotypes and haplotypes of the polymorphisms. The CRISP3 AJ459965:c.+622G>A SNP leading to the amino acid substitution E208K was significantly associated with the fertility of stallions. Stallions heterozygous for the CRISP3 c.+622G>A SNP had lower fertility than homozygous stallions (P = 0.0234). The pregnancy rate per cycle in these stallions was estimated to be approximately 7% lower than in stallions homozygous at this position.

Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.