Characterization and Genetic Diversity of Taif Chicken Ecotype Using Dense Microsatellites Panel

The current study is the first comprehensive investigation to address the native chicken ecotypes of the Taif region to unravel the genetic diversity using a dense panel of 40 microsatellites (SSR). Blood samples were collected from 25 hens randomly sampled from a village farm at Taif governorate. A total of 147 alleles were detected, with an average of 3.7 alleles per locus. The overall mean of polymorphic information content (PIC) was 0.43. The average observed heterozygosity (Hobs) of 0.28 was lower than the expected heterozygosity (Hexp) of 0.48. Out of 40l ocionly11 loci showed insignificant deviation from Hardy Weinberg expectation. The ecotypes showed low genetic diversity (HS = 0.65) and a high level of inbreeding (FIS= 0.75). The high FIS is indicative of the endangerment potentiality of this ecotype. Nine SSR showed an inbreeding coefficient of one. The significant estimate of the inbreeding coefficient of the present study calls for an immediate breeding plan to preserve such endangered ecotypes. Results of the present study will provide an initial guide to design further investigations for the development of sustainable genetic improvement and conservation programs for the Taif ecotype genetic resources.

329 Mendelian sampling, QTL similarity, and accuracy of genomic selection

Superiority of genomic selection (GS) is argued to be due to better modeling of the Mendelian sampling (MS) and tracking of QTL similarities between individuals. It is not clear that a better genome-wide modeling of MS contributes to the increased accuracy. In fact, it might be that modeling of MS outside areas of the genome under selection pressure is detrimental to the accuracy of GS. If true, this hypothesis will provide a better framework to understand the complex relationships between MS, QTL similarity and accuracy. Increases in marker density and the need for marker prioritization makes this hypothesis even more practically important. Answering this question could have a significant impact on accuracy and the computational costs of GS implementation. A 30-chromosome genome with 50K SNPs was simulated. 200 QTL were simulated on two chromosomes for a trait with heritability of 0.4. Genomic relationships were calculated based on all 50K SNPs (G30), 3,333 SNPs on the two chromosomes carrying QTL (G2), and 46,667 SNPs on chromosomes without QTL (G28). Table 1 shows accuracies after 3 and 10 generations of (G)EBV-based selection (M1) and random selection (M2). BLUP accuracies are consistently higher (11.5 to 43.8%) than G28, showing that expected relationships better model QTL similarities than a dense panel of markers that lie outside QTL regions. Inclusion of markers that lie outside QTL regions with markers inside QTL regions reduces accuracies, as shown by the inferior (20.2 to 22.8%) performance of G30 compared to G2. Coefficients of variation were higher for low than high additive relationships suggesting that errors made in estimating QTL similarities for lowly related animals may have the most detrimental impact. Furthermore, while G28 markers capture more variation than pedigree, the superiority of BLUP indicates that variation captured by G28 is not consistent with true variation in QTL inheritance.

QTL mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici

SummaryWe conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using QTL mapping. High throughput phenotyping based on automated image analysis allowed measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540,710 pycnidia were counted and their sizes and grey values were measured, yielding over 1.6 million phenotypes associated with pathogen reproduction. Large pycnidia were shown to produce more numerous and larger spores than small pycnidia. Precise measures of percent leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotype datasets with a dense panel of RADseq genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and components related to pathogen reproduction. We show that different components of virulence can be under separate genetic control. Large-and small-effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence or absence of accessory chromosomes with several virulence traits, providing the first evidence for an important function associated with accessory chromosomes in this organism. A large-effect QTL involved in host specialization was identified on chromosome 7, leading to identification of candidate genes having a large effect on virulence.