Incorporating genomic annotation into single-step genomic prediction with imputed whole-genome sequence data

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 ssG_HBLUP, 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.     

Molecular and genomic data identify the closest living relative of primates

A full understanding of primate morphological and genomic evolution requires the identification of their closest living relative. In order to resolve the ancestral relationships among primates and their closest relatives, we searched multispecies genome alignments for phylogenetically informative rare genomic changes within the superordinal group Euarchonta, which includes the orders Primates, Dermoptera (colugos), and Scandentia (treeshrews). We also constructed phylogenetic trees from 14 kilobases of nuclear genes for representatives from most major primate lineages, both extant colugos, and multiple treeshrews, including the pentail treeshrew, Ptilocercus lowii, the only living member of the family Ptilocercidae. A relaxed molecular clock analysis including Ptilocercus suggests that treeshrews arose approximately 63 million years ago. Our data show that colugos are the closest living relatives of primates and indicate that their divergence occurred in the Cretaceous.     

Detection of genomic signatures for pig hairlessness using high-density SNP data

Hair provides thermal regulation for mammals and protects the skin from wounds, bites and ultraviolet (UV) radiation, and is important in adaptation to volatile environments. Pigs in nature are divided into hairy and hairless, which provide a good model for deciphering the molecular mechanisms of hairlessness. We conducted a genomic scan for genetically differentiated regions between hairy and hairless pigs using 60K SNP data, with the aim to better understand the genetic basis for the hairless phenotype in pigs. A total of 38405 SNPs in 498 animals from 36 diverse breeds were used to detect genomic signatures for pig hairlessness by estimating between-population (F_ST) values. Seven diversifying signatures between Yucatan hairless pig and hairy pigs were identified on pig chromosomes (SSC) 1, 3, 7, 8, 10, 11 and 16, and the biological functions of two notable genes, RGS17 and RB1, were revealed. When Mexican hairless pigs were contrasted with hairypigs, strong signatures were detected on SSC1 and SSC10, which harbor two functionally plausible genes, REV3L and BAMBI. KEGG pathway analysis showed a subset of overrepresented genes involved in the T cell receptor signaling pathway, MAPK signaling pathway and the tight junction pathways. All of these pathways may be important in local adaptability of hairless pigs. The potential mechanisms underlying the hairless phenotype in pigs are reported for the first time. RB1 and BAMBI are interesting candidate genes for the hairless phenotype in Yucatan hairless and Mexico hairless pigs, respectively. RGS17, REV3L, ICOS and RASGRP1 as well as other genes involved in the MAPK and T cell receptor signaling pathways may be important in environmental adaption by improved tolerance to UV damage in hairless pigs. These findings improve our understanding of the genetic basis for inherited hairlessness in pigs.     

A Bayesian networks approach for predicting protein-protein interactions from genomic data

We have developed an approach using Bayesian networks to predict protein-protein interactions genome-wide in yeast. Our method naturally weights and combines into reliable predictions genomic features only weakly associated with interaction (e.g., messenger RNAcoexpression, coessentiality, and colocalization). In addition to de novo predictions, it can integrate often noisy, experimental interaction data sets. We observe that at given levels of sensitivity, our predictions are more accurate than the existing high-throughput experimental data sets. We validate our predictions with TAP (tandem affinity purification) tagging experiments. Our analysis, which gives a comprehensive view of yeast interactions, is available at genecensus.org/intint.     

流式细胞术在测定竹类植物基因组大小中的应用

  目的  分析竹类植物不同组织部位及不同处理方法对其基因组大小的影响,可提高植物基因组大小测定精度。  方法  以竹类植物叶片和笋为材料,以水稻Oryza sativa为参照,设置细胞核染色时间为1、3、5、7、9、12、18、24和30 min共9个梯度,利用流式细胞仪对不同组织部位及处理的基因组大小进行分析。  结果  ①对同一竹种而言,其叶片和笋流式峰形图相似,基因组大小仅存在微小差异,差值为0.04~0.20 pg。②不同竹种对染色时间要求不同,其中,唐竹Sinobambusa tootsik、花叶唐竹Sinobambusa tootisik f. albo-striata、平安竹Pseudosasa japonica var. tsutsumiana、曙筋矢竹Pseudosasa japonica f. akebono、美丽箬竹Indocalamus decorus、花叶赤竹Sasaella glabra f. albo-striata及红秆寒竹Chimonobambusa mamorea f. variegata染色1 min即达到最大荧光峰值,孝顺竹Bambusa multiplex和黄皮绿筋竹Phyllostachys sulphurea染色3 min达到最大峰值,茶竿竹Pseudosasa amabilis var. amabilis和柳叶细竹Thyrsostachy ssiamensis染色5 min达到最大峰值,仅黄皮刚竹Phyllostachys sulphurea(叶片)7 min达到最大峰值。③12个竹种的荧光强度在1~30 min内存在较大变化,除茶竿竹、柳叶细竹、孝顺竹叶片及唐竹笋外,其他竹种的荧光强度变化值均在5%以上,特别是平安竹和花叶赤竹变化更大,分别为12.93%和12.88%。④热带木本竹种孝顺竹和柳叶细竹基因组大小为(1.64±0.54)~(2.69±1.01) pg,其他10个温带竹种基因组大小为(3.76±1.51)~(5.73±1.85) pg。10个温带竹种中,刚竹属Phyllostachys竹种基因组较小,大小为(3.76±1.51)~(3.91±0.95) pg,其他竹属的一些竹种基因组较大,大小为(4.82±0.54)~(5.73±1.85) pg。  结论  ①竹类植物叶片和笋均可作为基因组大小分析材料,细胞核染色时间对基因组大小测定结果存在一定影响,染色时间以3~5 min最佳。②热带木本竹种基因组大小明显小于温带木本竹种,温带木本竹种中,刚竹属竹种的基因组大小明显小于其他竹种。图1表5参29     

浅谈自动站数据的维护

本文通过作者在实践工作中总结了一点关于确保自动站数据资料安全的方法,可以最大限度的确保自动观测的程序、参数设置、数据资料的安全,可供台站维护人员及观测员参考。     

通过多基因组比较的方法在5种绿球蓝细菌中识别基因组岛(英文)

为探索水平基因转移在绿球蓝细菌基因组多样性中的作用,5个高光适应性绿球蓝细菌基因组被比较.先用BLASTP两两最佳匹配搜索和基因位置保守性的方法预测直系同源基因,并进一步计算每个基因组中所有基因在其他4种绿球蓝细菌基因组中直系同源基因的数量,从而达到识别外源基因的目的;而基因组岛是指由1个或几个连续外源基因组成的区域.结果表明:在5个绿球蓝细菌基因组中共识别出了16至52个不等的基因组岛,它们中的许多基因在病毒基因组或富含病毒的环境样本中都有同源基因.以上这些结果显示,在绿球蓝细菌中,病毒可能介导了基因的水平转移,从而导致了基因组的多样性.     

浅谈自动气象站月报表数据文件的预审

根据内蒙古呼和浩特市清水河县气象局近几年的报表预审情况,在制作月报表和运行中对预审员的各方面能力都提出了更高的要求。由于软件本身存在着一些不完善的地方,在数据文件的预审中难免会遇到一些问题。介绍了基本参数的设置、气薄—1与B文件的预审、A文件的预审、J文件的预审等,并指出了日常工作中应该注意的问题。     

Functional genomic analysis of the Wnt-wingless signaling pathway

The Wnt-Wingless (Wg) pathway is one of a core set of evolutionarily conserved signaling pathways that regulates many aspects of metazoan development. Aberrant Wnt signaling has been linked to human disease. In the present study, we used a genomewide RNA interference (RNAi) screen in Drosophila cells to screen for regulators of the Wnt pathway. We identified 238 potential regulators, which include known pathway components, genes with functions not previously linked to this pathway, and genes with no previously assigned functions. Reciprocal-Best-Blast analyses reveal that 50% of the genes identified in the screen have human orthologs, of which approximately 18% are associated with human disease. Functional assays of selected genes from the cell-based screen in Drosophila, mammalian cells, and zebrafish embryos demonstrated that these genes have evolutionarily conserved functions in Wnt signaling. High-throughput RNAi screens in cultured cells, followed by functional analyses in model organisms, prove to be a rapid means of identifying regulators of signaling pathways implicated in development and disease.     

A genomic view of the human-Bacteroides thetaiotaomicron symbiosis

The human gut is colonized with a vast community of indigenous microorganisms that help shape our biology. Here, we present the complete genome sequence of the Gram-negative anaerobe Bacteroides thetaiotaomicron, a dominant member of our normal distal intestinal microbiota. Its 4779-member proteome includes an elaborate apparatus for acquiring and hydrolyzing otherwise indigestible dietary polysaccharides and an associated environment-sensing system consisting of a large repertoire of extracytoplasmic function sigma factors and one- and two-component signal transduction systems. These and other expanded paralogous groups shed light on the molecular mechanisms underlying symbiotic host-bacterial relationships in our intestine.