RESULTS: The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods.
CONCLUSION: Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation.
METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation.
RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P
RESULTS: More than 15,000 partial sequences were generated from the 5' and 3' ends of clones randomly selected from an E. tenella second generation merozoite full-length cDNA library. Clustering of these sequences produced 1,529 unique transcripts (UTs). Based on the transcript assembly and subsequently primer walking, 433 full-length cDNA sequences were successfully generated. These sequences varied in length, ranging from 441 bp to 3,083 bp, with an average size of 1,647 bp. Simple sequence repeat (SSR) analysis identified CAG as the most abundant trinucleotide motif, while codon usage analysis revealed that the ten most infrequently used codons in E. tenella are UAU, UGU, GUA, CAU, AUA, CGA, UUA, CUA, CGU and AGU. Subsequent analysis of the E. tenella complete coding sequences identified 25 putative secretory and 60 putative surface proteins, all of which are now rational candidates for development as recombinant vaccines or drug targets in the effort to control avian coccidiosis.
CONCLUSIONS: This paper describes the generation and characterisation of full-length cDNA sequences from E. tenella second generation merozoites and provides new insights into the E. tenella transcriptome. The data generated will be useful for the development and validation of diagnostic and control strategies for coccidiosis and will be of value in annotation of the E. tenella genome sequence.