Development of a 200 single nucleotide polymorphism panel for parentage assessment for 14 Italian goat breeds

The recent availability of a medium density SNPs chip in goat offers the possibility to develop a useful and less expensive tool for parentage assessment. However, standard approaches of SNP selection for parentage assignment are still ineffective due to a lack of information about markers position. In this study, we describe the identification of a 200 SNPs panel for parentage testing in goat. Data on 350 goats of 14 different Italian breeds genotyped with the Illumina 50K SNP array were provided by the Italian Goat Consortium (IGC). The 200 SNPs panel was identified by a three-step procedure, as follows: 1) parentage assessment by mendelian errors and genomic parentage to identify true parent-offspring pairs; 2) identification of informative SNPs by canonical discriminant analysis and 3) reduction by mendelian errors and stepwise regression. The 200 SNPs panel was tested on pairwise comparison of all animals at each locus. Sensitivity, specificity and accuracy of the panel were assessed. The probability of exclusion (Pe) and the probability of a random coincidental match inclusion (Pi) for each breed were estimated. The panel showed good assessment power, with high sensitivity (0.9429), specificity (1.0) and accuracy (0.99997). Pe values ranged from a minimum of 0.99999981 for Maltese from Sardinia to a maximum of 0.999999999996 for Nicastrese. We further reduced panel size by stepwise regression to 174 SNPs showing the same performance of the 200 SNP panel. The development of tools for parentage assessment could improve breeding management also in species with low genetic information, as goat

Genomic retrospective evaluation of 20 years of selection in Italian Holstein bulls for feet and legs trait

Under strong directional selection,allelefrequencies rapidly change,allowing the identificationof genomic regions carrying genes and variantsthat control selected traits, as production, functional and morphologicaltraits. Here we searched selection sweeps by birth date regression on EBVs and the analysis of changes in allele frequencies. Genomic retrospective evaluation of recent selection wasperformed in 2918 Italian Holstein bulls born between 1979 and 2011. Genotypedata from SELMOL, PROZOO and INNOVAGEN projects were used.Estimated Breeding Value (EBVs) for 32 traitswereprovided by the Italian Holstein association (ANAFI). Bulls were genotyped with BovineSNP50 v.1 and BovineHD SNPchips. SNPs positions were updated to UMD3.1 using SNPchiMp v.3. Genotypes were imputed using BEAGLE (v.3.3.4) to obtain HD genotypes for all individuals. After quality control, a total of 2918 animals and 613,956 SNPs were included in the working dataset. Birth date regressed on Feet and LegsEBVshowsa strong positive trend in the birth date interval analyzed. To detect genomic regions involved, we first identifiedPLUS- and MINUS-variantanimalsfor the target EBV over the total year range (134 bulls, group OVERALL)and within each birth year (130 bulls, group BY_YEAR). Then,SNP allelic frequencies, within each group,wereobtainedfor PLUS and MINUS variantspools and the absolute allele frequency difference (delta)was calculated. Mean delta valueswere estimated in overlapping sliding windows of 50 SNPs.Only windows with the mean delta above the 75th percentile + 1.5*Interquartile rangewere retained. Only overlapping regions between OVERALL and BY_YEAR group were retained. These regions cover the 0.84% of the total windows analyzed.Among these, two regions seem particularly interesting. The ~686Kb region on BTA10 (from position 62,578 to 63,264 Kb) had the highest mean delta on BY_YEAR. The~417Kb region onBTA20(from position 40,738 to 41,155 Kb)had thehighest mean delta on OVERALL.Bioinformatic analysis is underway to identify candidate genes, QTLsand metabolic pathways under selection for this trait

Birth date regression to identify genomic signatures of recent selection in Italian Holstein

Genomic signatures of recent selection were identified in 2918 Italian Holstein bulls born between 1987 and 2007 using a birth date regression on EBVs, and the analysis of changes in allele frequencies. Under strong directional selection, allele frequencies rapidly change and permit the identification of genomic regions that carry genes controlling production, functional or type traits. Genotype data from SELMOL, PROZOO and INNOVAGEN projects were used along with EBVs (Estimated Breeding Value) for 32 production and morphological traits of the genotyped animals, provided by the Italian Holstein association (ANAFI). Bulls were genotyped with BovineSNP50 and BovineHD SNPchips. Imputation using SNPchiMp v.1 and BEAGLE (v.3) was used to obtain HD genotypes for all individuals. A total of 2918 animals and 613,956 SNPs were included in the working dataset, after quality control. Birth date regressed Protein Yield EBVs, show a strong positive trend in the birth date interval analyzed. To detect genomic regions involved, we first identified animals with outlier PLUS- and MINUS-variant EBVs, over the total range of birth years (164 bulls, group 1) and in each birth year (159 bulls, group 2). Then, allele frequencies were obtained for each SNP, in PLUS and MINUS variants pools. Finally, we calculated the absolute allele frequency difference between PLUS and MINUS pools within each group and identified genomic regions with high values by overlapping sliding windows of 50 SNPs. Comparing the information from the plus and minus pool identified 0.53% shared windows in genomic regions under recent selection. A ~1.2 Mb region on BTA13 (from position 23.2 to 24.4Mb) had the highest absolute mean difference across datasets. This birth date based analysis is a novel and potentially powerful approach to identify regions under recent selection associated with production, type and functional traits

Parentage assessment with 200 single nucleotide polymorphisms on 15 Italian goat breeds

In this study we describe a panel of 200 SNPs for parentage testing in goat, optimized on 15 Italian breeds. Data on 350 goats genotyped with the Illumina 50K SNP array were provided by the Italian Goat Consortium (IGC). Animals belong to 15 breeds/populations farmed in North (Saanen, Alpine, Valdostana, Orobica, Bionda dell\u2019Adamello and Valpassiria), Center (Teramana and Grigia Ciociara), South Italy and Islands (Aspromontana, Nicastrese, Girgentana, Argentata dell\u2019Etna, Maltese, Maltese Sarda e Sarda). Quality editing excluded 2,211 SNPs with minor allele frequency <1%, genotype call rate <95% and individual call rate <90%. Genomic Parentage (GP) and Mendelian Errors (ME) were assessed on the 350 goats using the remaining 51,136 markers. Pairs of individuals were classified as Parent-Offspring (PO) when ME<1000 and GP 650.4. A total of 34 PO were identified out of 61,075 pairwise comparisons. We developed a novel method based on multivariate discriminant analysis and stepwise regression for choosing the best SNPs for parentage testing. Following ISAG standards for parentage testing in cattle, we identified a 200 SNP subset suitable to parentage testing in goat based on pairwise ME calculation. We considered PO all pairs of animals sharing 641 ME, doubtful all pairs sharing 2-3 ME and unrelated all pairs sharing >3 ME. The sensibility, specificity and accuracy (false negative, false positive and true assignment ratio, respectively) of the panel were assessed. In addition, we estimated the probability of single parental exclusion (Pe) and the probability of a random coincidental match inclusion (Pi) for each breed. The parentage panel showed good assessment power, with high specificity (0.9705882), sensibility (1.0) and accuracy (0.9999836). Pe values ranged from a minimum of 0.9999995 for Teramana to a maximum of 1.0 for Alpine. Pi values ranged from 8.49 X 10-78 for Alpine to 1.21 X 10-61 for Teramana. Pe for single SNP ranged from 0.0677\ub10.0592 to 0.1085\ub10.0506 (mean\ub1SD) for Teramana and Alpine, respectively. This is the first SNP panel available for parentage testing in goat. Our results suggest that genomic research can help solve practical problems in breeding, such as pedigree registration errors. In this context, cost-effective parentage testing would help goat breeders in the management of consanguinity

Use of different statistical approaches to study genetic variability of OAR6 in sheep breeds farmed in Italy.

Dense marker maps allow for the investigation of genomic regions that differentiate between breeds. In this work, 496 sheep belonging to 20 Italian sheep breeds were genotyped with the Illumina OvineSNP50 BeadChip. After data editing, 2,180 SNP located on chromosome 6 were analyzed with 4 different approaches. I) Fst Outlier Detection (FOD), implemented in the LOSITAN software, based on the comparison between Fst calculated on actual data and expected heterozygosity (He) and Fst under an island model. II) Composite Log-likelihood (CLL), based on calculation of CLL of the observed allelic frequencies across overlapping windows of 9 markers. III) Correspondence analysis (CA). VI) Canonical Discriminant Analysis (CDA). The different approaches were able to identify regions at OAR6 that expressed variation between breeds. Highest values for all statistics were found for a region spanning between 35 and 41 Mb known to harbour BMPR1b and ABCG2 loci. SNPs with a relevant discriminating power between breeds were also found at 76, 96 and 107 Mb, near to KIT, IL8 and SCD5 genes respectively. FOD detected 227 not neutral markers (17 under positive and 210 under balanced selection) using a confidence interval of 0.95. A total of 62 windows out of 242 were significant for CLL (P < 0.01). Several 85 and 135 SNPs exceeded empirical threshold for CA and CDA, respectively. The discriminating power was high for all methods and in general, they revealed a geographical pattern of variation between breeds. Moreover, each method provided specific information. FOD supplied a relatively low number of markers in divergent selection but it was able to identify loci under balanced selection. CA and CDA allowed a decomposition of total variability in different and uncorrelated variables that could be useful for the identification of genes influencing complex traits. The use of different statistical methods to study genetic variability between ethnic groups could provide indications about the adaptation to local conditions as well as the effect of selection

Mesophase configurations and optical properties of mesoporous TiO 2 thin films

10.1007/s10832-006-9905-1Journal of Electroceramics164499-502JOEL

Drawing up worldwide goat diversity and post-domestication history: update from ADAPTmap project

The study of goat adaptation to different environments is a major aim of the international ADAPTmap project, which joins the genotyping and re-sequencing efforts of the International Goat Genome Consortium (IGGC), the African Goat Improvement Network (AGIN), Feed the Future program of United States Agency for International Development and NEXTGEN EU project. Having a worldwide distribution, and thriving across a variety of contrasting habitats, goats offer an attractive opportunity to address the genetics of adaptation. This has to start with extensive analyses of the patterns of diversity, thus, a set of 144 breeds, representing 36 countries from 5 continents, has been genotyped with the Illumina GoatSNP50 BeadChip. Several analytical approaches have been adopted to describe the patterns of molecular variation across Africa, Europe and western Asia. The results obtained so far reveal a strong partitioning among continents. Three major gene pools correspond to goats from Europe, Africa and western Asia, while further sub-structuring reflects the main post-domestication migration routes. The reconstruction of past migration events highlighted several exchanges mainly between African populations, which often involve admixed and cosmopolitan breeds. In addition, extensive gene flow was revealed within specific areas (e.g., southern Europe, Morocco and Mali-Burkina FasoNigeria), while isolation due to geographical causes (e.g. insularity) or human management has brought a decrease in local gene flow. Taken together, these results confirm that after domestication in the Fertile Crescent in the early Neolithic era (approx. 15,000 BP), domestic goats spread to Europe, Africa and Asia through divergent migration routes, which determined the major genomic background of the continental populations. During the following centuries, due to geographical and reproductive isolation, further sub-structuring of diversity occurred at the local level. This has been accompanied by additional migrations and/or importations, the traces of which are still detectable, such as the clear African signatures in the goat populations of the Canary Islands and Southern America