一步法基因组预测方法广泛应用于畜禽育种中，它可以在一个模型中同时考虑有基因分型和无基因分型的个体信息。目前，基于群体水平的全基因组序列数据快速增长，如何在一步法基因组预测中更好地利用序列数据提高基因组预测准确性备受关注。研究表明，通过整合来自公共数据库的生物学先验信息可提高基因组预测的准确性。因此，本研究中对一步法基因组预测模型进行扩展，以探究如何在模型中有效地整合基因组注释信息提高基因组预测的性能。本研究以黄羽肉鸡群体为实验对象，群体共有1338个个体及23个性状，其中895个个体具有填充的全基因组序列数据，包含5127612个单核苷酸多态性（SNP）标记。研究考虑了不同注释信息与模型的组合，提出四种扩展的一步法模型，并与原始的一步法及基于单倍型的一步法模型进行比较。对于整合基因组注释信息的扩展一步法模型，我们根据鸡的基因组注释信息对SNP标记进行映射，在基因区域和外显子区域分别共映射到3155524和94837个SNP标记。随后采用这些映射到的SNP标记依据不同模型的规则构建基因组亲缘关系矩阵并用于基因组预测。研究结果发现，扩展的一步法模型在其中15个性状中优于其它基准模型。相比于原始的一步法模型，扩展的一步法模型预测能力可提升约2.5%~6.1%。此外，为了进一步提升一步法模型利用序列数据时的基因组预测准确性，我们在该群体中研究了参考群基因分型策略。结果显示在大部分情况下按家系均匀选择的策略来对个体进行基因分型优于随机选择的方式。综上，本研究在一步法框架下，扩展了基因组预测模型，使其整合序列数据以及基因组注释信息。验证了合理利用基因组注释信息和填充的序列数据可提高一步法基因组预测模型的预测能力。而且，在利用序列数据的同时，通过最大化参考群体和候选群体之间的期望亲缘关系来进行基因分型可进一步提高一步法模型的预测能力。本研究的创新在于通过序列数据将基因组注释信息整合至一步法模型中，为在一步法基因组预测方法中有效利用序列数据提供了有益参考。

    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.