Faculty Opinions recommendation of A cross-genomic approach for systematic mapping of phenotypic traits to genes.

Author(s):  
Christos Ouzounis
2005 ◽  
Vol 11 ◽  
pp. 16
Author(s):  
Sandeep Kumar Mathur ◽  
Piyush Chandra ◽  
Sandhya Mishra ◽  
Piyush Ajmera ◽  
Praveen Sharma

10.28945/4505 ◽  
2020 ◽  
Vol 15 ◽  
pp. 039-064
Author(s):  
Rogerio Ferreira da Silva ◽  
Itana Maria de Souza Gimenes ◽  
José Carlos Maldonado

Aim/Purpose: This paper presents a study of Virtual Communities of Practice (VCoP) evaluation methods that aims to identify their current status and impact on knowledge sharing. The purposes of the study are as follows: (i) to identify trends and research gaps in VCoP evaluation methods; and, (ii) to assist researchers to position new research activities in this domain. Background: VCoP have become a popular knowledge sharing mechanism for both individuals and organizations. Their evaluation process is complex; however, it is recognized as an essential means to provide evidences of community effectiveness. Moreover, VCoP have introduced additional features to face to face Communities of Practice (CoP) that need to be taken into account in evaluation processes, such as geographical dispersion. The fact that VCoP rely on Information and Communication Technologies (ICT) to execute their practices as well as storing artifacts virtually makes more consistent data analysis possible; thus, the evaluation process can apply automatic data gathering and analysis. Methodology: A systematic mapping study, based on five research questions, was carried out in order to analyze existing studies about VCoP evaluation methods and frameworks. The mapping included searching five research databases resulting in the selection of 1,417 papers over which a formal analysis process was applied. This process led to the preliminary selection of 39 primary studies for complete reading. After reading them, we select 28 relevant primary studies from which data was extracted and synthesized to answer the proposed research questions. Contribution: The authors of the primary studies analyzed along this systematic mapping propose a set of methods and strategies for evaluating VCoP, such as frameworks, processes and maturity models. Our main contribution is the identification of some research gaps present in the body of studies, in order to stimulate projects that can improve VCoP evaluation methods and support its important role in social learning. Findings: The systematic mapping led to the conclusion that most of the approaches for VCoP evaluation do not consider the combination of data structured and unstructured metrics. In addition, there is a lack of guidelines to support community operators’ actions based on evaluation metrics.


Author(s):  
Maren N. Vitousek ◽  
Laura A. Schoenle

Hormones mediate the expression of life history traits—phenotypic traits that contribute to lifetime fitness (i.e., reproductive timing, growth rate, number and size of offspring). The endocrine system shapes phenotype by organizing tissues during developmental periods and by activating changes in behavior, physiology, and morphology in response to varying physical and social environments. Because hormones can simultaneously regulate many traits (hormonal pleiotropy), they are important mediators of life history trade-offs among growth, reproduction, and survival. This chapter reviews the role of hormones in shaping life histories with an emphasis on developmental plasticity and reversible flexibility in endocrine and life history traits. It also discusses the advantages of studying hormone–behavior interactions from an evolutionary perspective. Recent research in evolutionary endocrinology has provided insight into the heritability of endocrine traits, how selection on hormone systems may influence the evolution of life histories, and the role of hormonal pleiotropy in driving or constraining evolution.


2014 ◽  
Vol 56 (10) ◽  
pp. 1167-1182 ◽  
Author(s):  
Marc Oriol ◽  
Jordi Marco ◽  
Xavier Franch

Author(s):  
Runze Li ◽  
Rebecca C Deed

Abstract It is standard practice to ferment white wines at low temperatures (10-18 °C). However, low temperatures increase fermentation duration and risk of problem ferments, leading to significant costs. The lag duration at fermentation initiation is heavily impacted by temperature; therefore, identification of Saccharomyces cerevisiae genes influencing fermentation kinetics is of interest for winemaking. We selected 28 S. cerevisiae BY4743 single deletants, from a prior list of open reading frames (ORFs) mapped to quantitative trait loci (QTLs) on chromosomes VII and XIII, influencing the duration of fermentative lag time. Five BY4743 deletants, Δapt1, Δcgi121, Δclb6, Δrps17a, and Δvma21, differed significantly in their fermentative lag duration compared to BY4743 in synthetic grape must (SGM) at 15 °C, over 72 h. Fermentation at 12.5 °C for 528 h confirmed the longer lag times of BY4743 Δcgi121, Δrps17a, and Δvma21. These three candidate ORFs were deleted in S. cerevisiae RM11-1a and S288C to perform single reciprocal hemizygosity analysis (RHA). RHA hybrids and single deletants of RM11-1a and S288C were fermented at 12.5 °C in SGM and lag time measurements confirmed that the S288C allele of CGI121 on chromosome XIII, encoding a component of the EKC/KEOPS complex, increased fermentative lag phase duration. Nucleotide sequences of RM11-1a and S288C CGI121 alleles differed by only one synonymous nucleotide, suggesting that intron splicing, codon bias, or positional effects might be responsible for the impact on lag phase duration. This research demonstrates a new role of CGI121 and highlights the applicability of QTL analysis for investigating complex phenotypic traits in yeast.


2021 ◽  
Vol 53 (1) ◽  
pp. 162-188
Author(s):  
Krzysztof Bartoszek ◽  
Torkel Erhardsson

AbstractExplicit bounds are given for the Kolmogorov and Wasserstein distances between a mixture of normal distributions, by which we mean that the conditional distribution given some $\sigma$ -algebra is normal, and a normal distribution with properly chosen parameter values. The bounds depend only on the first two moments of the first two conditional moments given the $\sigma$ -algebra. The proof is based on Stein’s method. As an application, we consider the Yule–Ornstein–Uhlenbeck model, used in the field of phylogenetic comparative methods. We obtain bounds for both distances between the distribution of the average value of a phenotypic trait over n related species, and a normal distribution. The bounds imply and extend earlier limit theorems by Bartoszek and Sagitov.


Author(s):  
Ricardo Wilches ◽  
William H Beluch ◽  
Ellen McConnell ◽  
Diethard Tautz ◽  
Yingguang Frank Chan

Abstract Most phenotypic traits in nature involve the collective action of many genes. Traits that evolve repeatedly are particularly useful for understanding how selection may act on changing trait values. In mice, large body size has evolved repeatedly on islands and under artificial selection in the laboratory. Identifying the loci and genes involved in this process may shed light on the evolution of complex, polygenic traits. Here, we have mapped the genetic basis of body size variation by making a genetic cross between mice from the Faroe Islands, which are among the largest and most distinctive natural populations of mice in the world, and a laboratory mouse strain selected for small body size, SM/J. Using this F2 intercross of 841 animals, we have identified 111 loci controlling various aspects of body size, weight and growth hormone levels. By comparing against other studies, including the use of a joint meta-analysis, we found that the loci involved in the evolution of large size in the Faroese mice were largely independent from those of a different island population or other laboratory strains. We hypothesize that colonization bottleneck, historical hybridization, or the redundancy between multiple loci have resulted in the Faroese mice achieving an outwardly similar phenotype through a distinct evolutionary path.


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