Image_1_Genomic Prediction for 25 Agronomic and Quality Traits in Alfalfa (Medicago sativa).TIF

Agronomic and quality traits in alfalfa are very important to forage industry. Genomic prediction (GP) based on genotyping-by-sequencing (GBS) data could shorten the breeding cycles and accelerate the genetic gains of these complex traits, if they display moderate to high prediction accuracies. The aim of this study was to investigate the predictive potentials of these traits in alfalfa. A total of 322 genotypes from 75 alfalfa accessions were used for GP of the agronomic and quality traits, which were related to yield and nutrition value, respectively, using BayesA, BayesB, and BayesCπ methods. Ten-fold cross validation was used to evaluate the accuracy of GP represented by the correlation between genomic estimated breeding value (GEBV) and estimated breeding value (EBV). The accuracies ranged from 0.0021 to 0.6485 for different traits. For each trait, three GP methods displayed similar prediction accuracies. Among 15 quality traits, mineral element Ca had a moderate and the highest prediction accuracy (0.34). NDF digestibility after 48 h (NDFD 48 h) and 30 h (NDFD 30 h) and mineral element Mg had prediction accuracies varying from 0.20 to 0.25. Other traits, for example, fat and crude protein, showed low prediction accuracies (0.05 to 0.19). Among 10 agronomic traits, however, some displayed relatively high prediction accuracies. Plant height (PH) in fall (FH) had the highest prediction accuracy (0.65), followed by flowering date (FD) and plant regrowth (PR) with accuracies at 0.52 and 0.51, respectively. Leaf to stem ratio (LS), plant branch (PB), and biomass yield (BY) reached to moderate prediction accuracies ranging from 0.25 to 0.32. Our results revealed that a few agronomic traits, such as FH, FD, and PR, had relatively high prediction accuracies, therefore it is feasible to apply genomic selection (GS) for these traits in alfalfa breeding programs. Because of the limitations of population size and density of SNP markers, several traits displayed low accuracies which could be improved by a bigger reference population, higher density of SNP markers, and more powerful statistic tools.</p

DataSheet1_Transcriptome-wide m6A methylation profiling of Wuhua yellow-feathered chicken ovary revealed regulatory pathways underlying sexual maturation and low egg-laying performance.ZIP

RNA N6-melthyladenosine (m6A) can play an important role in regulation of various biological processes. Chicken ovary development is closely related to egg laying performance, which is a process primarily controlled by complex gene regulations. In this study, transcriptome-wide m6A methylation of the Wuhua yellow-feathered chicken ovaries before and after sexual maturation was profiled to identify the potential molecular mechanisms underlying chicken ovary development. The results indicated that m6A levels of mRNAs were altered dramatically during sexual maturity. A total of 1,476 differential m6A peaks were found between these two stages with 662 significantly upregulated methylation peaks and 814 downregulated methylation peaks after sexual maturation. A positive correlation was observed between the m6A peaks and gene expression levels, indicating that m6A may play an important role in regulation of chicken ovary development. Functional enrichment analysis indicated that apoptosis related pathways could be the key molecular regulatory pathway underlying the poor reproductive performance of Wuhua yellow-feathered chicken. Overall, the various pathways and corresponding candidate genes identified here could be useful to facilitate molecular design breeding for improving egg production performance in Chinese local chicken breed, and it might also contribute to the genetic resource protection of valuable avian species.</p

Additional file 9: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S9. Information about Ensembl genes found to be overlapped with yak-specific CNVRs identified in the present study. (XLSX 14 kb

Additional file 5: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S5. Significantly enriched GO terms and Reactome pathways of genes associated with the identified CNVRs. (XLSX 11 kb

Additional file 7: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S7. Information about QTLs found to be overlapped with CNVRs identified in the present study. (XLSX 104 kb

Additional file 10: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S10. Significantly enriched GO terms and PANTHER pathways of genes associated with the yak-specific CNVRs. (XLSX 9 kb

Additional file 12: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S12. Detail information about primers used for CNVRs validation. (XLSX 9 kb

Additional file 6: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S6. Hypoxia-related genes found to be overlapped with CNVRs identified in the present study. (XLSX 16 kb

Additional file 4: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S4. Information about Ensembl genes found to be overlapped with CNVR identified in the present study. (XLSX 134 kb

Additional file 8: of Genome-wide detection of copy number variations in polled yak using the Illumina BovineHD BeadChip

Table S8. Detail information of the yak-specific CNVRs. (XLSX 11 kb