A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms

We describe a genetic variation map for the chicken genome containing 2.8 million single-nucleotide polymorphisms ( SNPs). This map is based on a comparison of the sequences of three domestic chicken breeds ( a broiler, a layer and a Chinese silkie) with that of their wild ancestor, red jungle fowl. Subsequent experiments indicate that at least 90% of the variant sites are true SNPs, and at least 70% are common SNPs that segregate in many domestic breeds. Mean nucleotide diversity is about five SNPs per kilobase for almost every possible comparison between red jungle fowl and domestic lines, between two different domestic lines, and within domestic lines - in contrast to the notion that domestic animals are highly inbred relative to their wild ancestors. In fact, most of the SNPs originated before domestication, and there is little evidence of selective sweeps for adaptive alleles on length scales greater than 100 kilobases

Adaption of Seasonal H1N1 Influenza Virus in Mice

The experimental infection of a mouse lung with influenza A virus has proven to be an invaluable model for studying the mechanisms of viral adaptation and virulence. The mouse adaption of human influenza A virus can result in mutations in the HA and other proteins, which is associated with increased virulence in mouse lungs. In this study, a mouse-adapted seasonal H1N1 virus was obtained through serial lung-to-lung passages and had significantly increased virulence and pathogenicity in mice. Genetic analysis indicated that the increased virulence of the mouse-adapted virus was attributed to incremental acquisition of three mutations in the HA protein (T89I, N125T, and D221G). However, the mouse adaption of influenza A virus did not change the specificity and affinity of receptor binding and the pH-dependent membrane fusion of HA, as well as the in vitro replication in MDCK cells. Notably, infection with the mouse adapted virus induced severe lymphopenia and modulated cytokine and chemokine responses in mice. Apparently, mouse adaption of human influenza A virus may change the ability to replicate in mouse lungs, which induces strong immune responses and inflammation in mice. Therefore, our findings may provide new insights into understanding the mechanisms underlying the mouse adaption and pathogenicity of highly virulent influenza viruses

Genomic Polymorphism of the Pandemic A (H1N1) Influenza Viruses Correlates with Viral Replication, Virulence, and Pathogenicity In Vitro and In Vivo

The novel pandemic A (H1N1) virus was first identified in Mexico in April 2009 and quickly spread worldwide. Like all influenzas, the H1N1 strain-specific properties of replication, virulence, and pathogenicity are a result of the particular genomic sequence and concerted expression of multiple genes. Thus, specific mutations may support increased virulence and may be useful as biomarkers of potential threat to human health. We performed comparative genomic analysis of ten strains of the 2009 pandemic A (H1N1) influenza viruses to determine whether genotypes associated with clinical phenotypes, which ranged from mild to severe illness and up to lethal. Virus replication capacity was tested for each strain in vitro using cultured epithelial cells, while virulence and pathogenicity were investigated in vivo using the BALB/c mouse model. The results indicated that A/Sichuan/1/2009 strain had significantly higher replication ability and virulence than the other strains, and five unique non-synonymous mutations were identified in important gene-encoding sequences. These mutations led to amino acid substitutions in HA (L32I), PA (A343T), PB1 (K353R and T566A), and PB2 (T471M), and may be critical molecular determinants for replication, virulence, and pathogenicity. Our results suggested that the replication capacity in vitro and virulence in vivo of the 2009 pandemic A (H1N1) viruses were not associated with the clinical phenotypes. This study offers new insights into the transmission and evolution of the 2009 pandemic A (H1N1) virus

a defect typology to support software process verification and validation

Harvard University; University of California; University of Minnesota; University of Illinois at Urbana-Champaign; Georgia Institute of Technology and Emory UniversityApproaches to software process development that are based on the principles and practices of software engineering have been advocated by many researchers as a means to produce software processes that meet the needs of process users. Such approaches requi

software effort estimation model based on use case specification

Software effort estimation is essential for the project planning. Use case is widely used to capture and describe the requirements of customers and used as an index of software measurement and estimation. Based on the framework of traditional use case point estimation model, the paper presents UCSE, an effort estimation model based on use case specification. Firstly, the model abstracts factors influencing software effort from the use case specification and calculates the Use Case Weight, which is a kind of measurement of use cases size. Secondly, a function is constructed to translate the software size expressed by Use Case Weight to by software scale whose unit is kilo source line of code (KSLOC). Subsequently, effort estimation model COCOMO II is used to estimate the software effort according to the estimated software size measured by KSLOC. Compared with the traditional Use case point estimation model, UCSE model makes use of more relevant information and is more operable since it provides more concrete and objective references for the analysis and measurement of software effort factors in Use Case. What's more, the presented case study shows its results are more stable.Software effort estimation is essential for the project planning. Use case is widely used to capture and describe the requirements of customers and used as an index of software measurement and estimation. Based on the framework of traditional use case point estimation model, the paper presents UCSE, an effort estimation model based on use case specification. Firstly, the model abstracts factors influencing software effort from the use case specification and calculates the Use Case Weight, which is a kind of measurement of use cases size. Secondly, a function is constructed to translate the software size expressed by Use Case Weight to by software scale whose unit is kilo source line of code (KSLOC). Subsequently, effort estimation model COCOMO II is used to estimate the software effort according to the estimated software size measured by KSLOC. Compared with the traditional Use case point estimation model, UCSE model makes use of more relevant information and is more operable since it provides more concrete and objective references for the analysis and measurement of software effort factors in Use Case. What's more, the presented case study shows its results are more stable

an empirical study on classification of non-functional requirements

The classification of NKRs brings about the benefits that NKRs with respect to the same type In the system can be considered and Implemented aggregately by developers, and as a result be verified by quality assurers assigned for the type. This paper conducts an empirical study on using text mining techniques to classify NFRs automatically. Three kinds of Index terms, which are at different levels of llngulstlcal semantics, as Vgrams. Individual words, and multi-word expressions (MWE), are used In representation of NFRs. Then. SVM (Support Vector Machine) with linear kernel bt used as the classifier. We collected a data set from PROMISE web site for experimentation In this empirical study. The experiments show that Index term as Individual words with Boolean weighting outperforms the other two Index terms. When MWEs are used to enhance representation of Individual words, there Is no significant Improvement on classification performance. Automatic classification produces better performance on categories of large stees than that on categories of small sizes. It can be drawn from the experimental results that for automatic classification of NFRs. Individual words are the best Index terms In text representation of short NFRs' description and we should collect as many as possible NFRs of software system.Knowledge Systems Institute Graduate SchoolThe classification of NKRs brings about the benefits that NKRs with respect to the same type In the system can be considered and Implemented aggregately by developers, and as a result be verified by quality assurers assigned for the type. This paper conducts an empirical study on using text mining techniques to classify NFRs automatically. Three kinds of Index terms, which are at different levels of llngulstlcal semantics, as Vgrams. Individual words, and multi-word expressions (MWE), are used In representation of NFRs. Then. SVM (Support Vector Machine) with linear kernel bt used as the classifier. We collected a data set from PROMISE web site for experimentation In this empirical study. The experiments show that Index term as Individual words with Boolean weighting outperforms the other two Index terms. When MWEs are used to enhance representation of Individual words, there Is no significant Improvement on classification performance. Automatic classification produces better performance on categories of large stees than that on categories of small sizes. It can be drawn from the experimental results that for automatic classification of NFRs. Individual words are the best Index terms In text representation of short NFRs' description and we should collect as many as possible NFRs of software system

improving the roi of software quality assurance activities: an empirical study

University of Paderborn; Fraunhofer Inst. Exp. Softw. Eng. (IESE); Chinese Academy of Science (ISCAS)Review, process audit, and testing are three main Quality Assurance activities during the software development life cycle. They complement each other to examine work products for defects and improvement opportunities to the largest extent. Understanding the effort distribution and inter-correlation among them will facilitate software organization project planning, improve the software quality within the budget and schedule and make continuous process improvement. This paper reports some empirical findings of effort distribution pattern of the three types of QA activities from a series of incremental projects in China. The result of the study gives us some implications on how to identify which type of QA activity is insufficient while others might be overdone, how to balance the effort allocation and planning for future projects, how to improve the weak part of each QA activity and finally improve the Return On Investment (ROI) of QA activities and the whole process effectiveness under the specific organization context. © 2010 Springer-Verlag

measurement and analysis of process audit: a case study

University of Paderborn; Fraunhofer Inst. Exp. Softw. Eng. (IESE); Chinese Academy of Science (ISCAS)Process audit is one of the popular quality assurance activities. It helps individual projects to be in conformity with the process definition, standard, etc. and provide insights for process improvement. However, to the best of our knowledge, little quantitative analysis of process audit has been reported so far. The paper introduces a case study of quantitatively analyzing process audit based on the practice of a Chinese software research and development organization, CSRD. It presents a measurement schema for evaluating the effectiveness and efficiency of process audit from various facets. The study shows that the auditing process in CSRD has contributed to the process management and improvement and brought value to the organization. The presented measurement and analysis methods and empirical results can provide reference for other organizations within similar context. © 2010 Springer-Verlag