Single-step genomic best linear unbiased prediction (ssGBLUP) is now intensively investigated and widely used in livestock breeding due to its beneficial feature of combining information from both genotyped and ungenotyped individuals in the single model.  With the increasing accessibility of whole-genome sequence (WGS) data at the population level, more attention is being paid to the usage of WGS data in ssGBLUP.  The predictive ability of ssGBLUP using WGS data might be improved by incorporating biological knowledge from public databases.  Thus, we extended ssGBLUP, incorporated genomic annotation information into the model, and evaluated them using a yellow-feathered chicken population as the examples.  The chicken population consisted of 1 338 birds with 23 traits, where imputed WGS data including 5 127 612 single nucleotide polymorphisms (SNPs) are available for 895 birds.  Considering different combinations of annotation information and models, original ssGBLUP, haplotype-based ssGHBLUP, and four extended ssGBLUP incorporating genomic annotation models were evaluated.  Based on the genomic annotation (GRCg6a) of chickens, 3 155 524 and 94 837 SNPs were mapped to genic and exonic regions, respectively.  Extended ssGBLUP using genic/exonic SNPs outperformed other models with respect to predictive ability in 15 out of 23 traits, and their advantages ranged from 2.5 to 6.1% compared with original ssGBLUP.  In addition, to further enhance the performance of genomic prediction with imputed WGS data, we investigated the genotyping strategies of reference population on ssGBLUP in the chicken population.  Comparing two strategies of individual selection for genotyping in the reference population, the strategy of evenly selection by family (SBF) performed slightly better than random selection in most situations.  Overall, we extended genomic prediction models that can comprehensively utilize WGS data and genomic annotation information in the framework of ssGBLUP, and validated the idea that properly handling the genomic annotation information and WGS data increased the predictive ability of ssGBLUP.  Moreover, while using WGS data, the genotyping strategy of maximizing the expected genetic relationship between the reference and candidate population could further improve the predictive ability of ssGBLUP.  The results from this study shed light on the comprehensive usage of genomic annotation information in WGS-based single-step genomic prediction.

    High-throughput sequencing has identified a large number of sense-antisense transcriptional pairs, which indicates that these genes were transcribed from both directions. Recent reports have demonstrated that many antisense RNAs, especially lncRNA (long non-coding RNA), can interact with the sense RNA by forming an RNA duplex. Many methods, such as RNA-sequencing, Northern blotting, RNase protection assays and strand-specific PCR, can be used to detect the antisense transcript and gene transcriptional orientation. However, the applications of these methods have been constrained, to some extent, because of the high cost, difficult operation or inaccuracy, especially regarding the analysis of substantial amounts of data. Thus, we developed an easy method to detect and validate these complicated RNAs. We primarily took advantage of the strand specificity of RT-PCR and the single-strand specificity of S1 endonuclease to analyze sense and antisense transcripts. Four known genes, including mouse β-actin and Tsix (Xist antisense RNA), chicken LXN (latexin) and GFM1 (G elongation factor, mitochondrial 1), were used to establish the method. These four genes were well studied and transcribed from positive strand, negative strand or both strands of DNA, respectively, which represented all possible cases. The results indicated that the method can easily distinguish sense, antisense and sense-antisense transcriptional pairs. In addition, it can be used to verify the results of high-throughput sequencing, as well as to analyze the regulatory mechanisms between RNAs. This method can improve the accuracy of detection and can be mainly used in analyzing single gene and was low cost.

Heat stress is one of the main factors that influence poultry production. Heat shock proteins (HSPs) are known to affect heat tolerance. The formation of HSPs is regulated by heat shock transcription factor 3 (HSF3) in chicken. A DNA pool was established for identifying single nucleotide polymorphisms (SNPs) of the chicken HSF3, and 13 SNPs were detected. The bioinformatic analysis showed that 8 SNPs had the capacity to alter the transcription activity of HSF3. The dual luciferase report gene assay showed that there was a significant difference (P<0.01) in the Firefly luciferase/Renilla luciferase ratio (F/R) of C.–1 703 A>G (S1) and C.–1 388 A>G (S4) sites at the 5´-untranslated region (UTR) of chicken HSF3. The electrophoretic mobility shift assay showed that the S4 site was a transcription binding factor. The analysis of the association of the S1 and S4 sites with heat tolerance index revealed that the S4 site was significantly correlated with the CD3+ T cell, corticosterone, and T3 levels in Lingshan chickens and with the heterophil/lymphocyte value in White Recessive Rock. These results showed that the S4 site at the 5´ UTR of chicken HSF3 might have an impact on heat tolerance in summer and could be used as a potential marker for the selection of chicken with heat tolerance in the future.

Marker assisted selection (MAS) for residual feed intake (RFI) is considered to be one of the powerful means to improve feed conversion efficiency, and therefore reduce production costs. To test the inner relationship among body compositions, growth traits and RFI, four models were proposed to assess the extensively explanatory variables accounting for partial variables in feed intake besides metabolic body weight and growth rate. As a result, the original model (Koch’s model) had the lowest R2 (80.78%) and the highest Bayesian information criterion (1 323.3) value among the four models. Moreover, the effects on RFI caused by single nucleotide polymorphisms (SNPs) were assessed in this study. Twelve SNPs from 7 candidate genes were genotyped in 2 Chinese native strains. rs14743490 of RPLP2 gene showed suggestively significant association with initial body weight in both strains (P<0.10). rs15047274 of TAF15 was significantly associated with growth weight, final weight, and feed intake (P<0.05) in N301 strain, in contrast, it was only suggestively significant associated with feed intake (P<0.10) in N414 strain. rs15869967 was significantly associated with RFI in N414 strain but not in N301 strain. This study has identified potential genetic markers suitable for MAS in improving the above mentioned traits, but these associations need to be rectified in other larger populations in future.

A substantial fraction of miRNA* species are conserved in animals and can repress activities of target genes. This study aims to investigate the miRNA* species in duck skin by using Solexa sequencing. We obtained a total of 96 miRNA* species in two skin small RNA libraries and identified 56 miRNA/miRNA* (miR/miR*) pairs. Nucleotide bias of miRNA* indicated that the priority was C>A>U>G for the first nucleotide and U>C>A>G for the last nucleotide. Comparison analyses showed that 3´-U accounted for a higher proportion in the 56 miR/miR* pairs. Among the top 20 expressed miRNA* species, 17 were shared by two libraries and most of the miRNA* species were highly conservative, especially in the “seed region”. miR-199a* were expressed highly in our samples, which was also previously shown abundant in mouse hair follicle. Furthermore, four miRNA* species were predicted to target their genes in signal pathways of feather follicle development and feather morphogenesis despite very low levels.

Variants in chicken growth hormone receptor (GHR) gene lead to sex-linked dwarf (SLD) chickens, but effects of different variants are distinct. In this study, 11 SLD chicken breeds or strains including 3 Chinese native breeds and 8 breeding strains were studied in order to investigate the effects of different sex-linked dwarf variations on growth performance. The results showed that there were three reasons which could lead to dwarfism in the 11 breeds or strains. Firstly, an about 1.7 kb deletion of growth hormone receptor (GHR) gene leads to dwarfism in Jiangxi dwarf chicken, strains GF24, GF26, N308, N309, and N310. Secondly, a T354C mutation in exon 5 of the GHR gene leads to dwarfism in strains N301 and N305. Thirdly, an unknown variant leads to dwarfism in Guizhou Yellow Dwarf chicken and Yixing Bantam chicken. In addition, all individuals of N303 had the 1.7 kb deletion of the GHR gene, and additionally, some of them also carried the T354C mutation. As far as the performance of individuals were compared among T354C homozygote, deletion homozygote, and heterozygote carrying both T354C and deletion, it was found that the T354C’s impacts on body weight of Chinese chickens were maximum, the body weight of chickens with homozygote T354C was 92.12% of those with heterozygote, and the difference of the body weight between deletion homozygote and heterozygote was not significant. There was no significant difference of shank length among three genotypes.