Accuracy of genomic prediction using imputed whole‐genome sequence data in white layers

There is an increasing interest in using whole‐genome sequence data in genomic selection breeding programmes. Prediction of breeding values is expected to be more accurate when whole‐genome sequence is used, because the causal mutations are assumed to be in the data. We performed genomic prediction for the number of eggs in white layers using imputed whole‐genome resequence data including ~4.6 million SNPs. The prediction accuracies based on sequence data were compared with the accuracies from the 60 K SNP panel. Predictions were based on genomic best linear unbiased prediction (GBLUP) as well as a Bayesian variable selection model (BayesC). Moreover, the prediction accuracy from using different types of variants (synonymous, non‐synonymous and non‐coding SNPs) was evaluated. Genomic prediction using the 60 K SNP panel resulted in a prediction accuracy of 0.74 when GBLUP was applied. With sequence data, there was a small increase (~1%) in prediction accuracy over the 60 K genotypes. With both 60 K SNP panel and sequence data, GBLUP slightly outperformed BayesC in predicting the breeding values. Selection of SNPs more likely to affect the phenotype (i.e. non‐synonymous SNPs) did not improve the accuracy of genomic prediction. The fact that sequence data were based on imputation from a small number of sequenced animals may have limited the potential to improve the prediction accuracy. A small reference population (n = 1004) and possible exclusion of many causal SNPs during quality control can be other possible reasons for limited benefit of sequence data. We expect, however, that the limited improvement is because the 60 K SNP panel was already sufficiently dense to accurately determine the relationships between animals in our data.     

新城疫病毒La Sota株HN基因的克隆与序列分析

旨在从分子生物学角度进一步研究新城疫病毒La Sota株HN基因,探究NDV La Sota HN基因的遗传变异情况。研究以试验室冻存的p NDV-HN为模版,根据Gen Bank中登录的NDV La Sota株序列设计引物扩增HN基因,将其克隆到pMD18-T载体后进行鉴定,对鉴定正确的重组质粒p MD-NDV-HN进行测序分析。应用生物信息学软件对新城疫病毒Lasota株HN基因进行系统进化树分析、氨基酸序列同源性分析、糖基化位点、蛋白结构跨膜区分析及磷酸化位点预测分析。核苷酸序列测定结果表明:HN基因的序列长度为1743bp,该基因的开放阅读框(Open Reading Frame,ORF)总长为1716 bp,编码571个氨基酸。生物信息学表明:试验获得的HN基因具有6个潜在糖基化位点及12个半胱氨酸残基,第5个潜在糖基化位点(508-510 aa)发生缺失及第123位半胱氨酸残基被色氨酸残基取代。La Sota株HN基因编码的蛋白质中有29个丝氨酸、10个酪氨酸和16个苏氨酸可能成为蛋白激酶磷酸化位点。将试验获得的La Sota株HN基因序列和推导的氨基酸序列与新城疫毒株的HN基因相应序列比较后发现,它们的核苷酸序列同源性和氨基酸序列同源性最高均可达到99%,表明HN基因在种属间具有较高的保守性。研究为新城疫病毒的分子病毒学研究奠定了基础。     

Antioxidant,anti-amylase and anti-glycation potential of brans of some Sri Lankan traditional and improved rice (Oryza sativa L.) varieties

Brans of 23 traditional and 12 improved (both red and white) rice varieties in Sri Lanka were screened for anti-amylase and anti-glycation activities in vitro. Varieties which showed the highest inhibitory activities at screening were further investigated for anti-glucosidase and glycation reversing as anti-diabetic properties. The same varieties were studied for selected antioxidant properties. Significantly high anti-amylase and anti-glycation activities were observed for bran extracts of red varieties compared to white varieties at screening. Traditional red rice varieties, Masuran, Sudu Heeneti, Dik Wee and Goda Heeneti, exhibited significant and dose dependent anti-amylase, anti-glycation and glycation reversing activities. These varieties also showed marked antioxidant properties. It is concluded that brans of Sri Lankan traditional red rice varieties Masuran, Sudu Heeneti, Dik Wee and Goda Heeneti may be potential food supplements for diabetes.     

基于框架理论的变电站操作票自动生成系统

介绍了一种基于框架理论的变电站操作票自动生成系统。该系统用框架知识表示法来描述电力系统的设备参数，建构了一个直观的、层次分明的数据结构。通过融合框架理论于面向对象的语言VC 中，开发出了一个集通用、实用、智能于一体的操作票专家系统。     

带优先加工约束2×n型异序排序的简便解法

为解决异序排序问题,提出了新的表上作业法。该方法不仅可以解决2×n型异序排序问题,还可以有效地解决带优先加工约束2×n型异序排序问题。该方法简便易行,便于掌握,可获得比较满意的近似最优加工顺序。