Genetic Basis of Fitness Differences in Natural Populations

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

Table of Contents

Introduction
Research problem and research questions
Research background, research questions justification, and main hypothesis
Further review on quantitative genetics and approaches
Approaches to fitness genes’ studies in natural populations
Results
Conclusion
References

Introduction

Genomics is studying genes and their functions. It considers the genes’ molecular mechanisms and genetic and environmental factors interaction causing a disease. The genotype is the genetic structure of an organism, while a phenotype is the organism’s characteristics conformed to by the genetic structure. The study of gene relationships in various species is comparative genomics (Gerstein et al 2007).

Research problem and research questions

A research problem statement should identify theory, models, framework and variables (Creswell, 2003). Research questions aim to narrow the research topic from the broader research problem statement to what the researcher (s) will attempt to answer (Tashakkori and Creswell, 2007). In the article to summarize, the authors recognized that one way genomics affect biology is the possibility of identifying and studying how the characteristics affecting fitness, a key issue in natural selection, are genetically based.

Further, they identified how the various genomic approaches highlighted that genetic build up of quantitative variation can result in an up-and-coming understanding of quantitative genetics of fitness variation. This meant to the authors that biologists expect to see a synthesis of environmental and molecular approaches in evolutionary biology. The authors stated the following research questions: what is the genetic build up of fitness characteristics in wild populations. Second, how new genomic methodologies for non-model organisms can identify the genetic locus of evolution.

Research background, research questions justification, and main hypothesis

Although Ellegren and Sheldon (2008) did not provide an introduction section with a background literature review, yet, they reviewed fitness variations in the wild and their quantitative genetics. They identified that laboratory model organisms’ studies provide control, replication, uniformity, and stability; however, this does not mimic the operating conditions of natural selection in the wild. Therefore, they considered field studies advantageous to laboratory animal models studies.

Even in laboratory studies (like those on Dorsophila) where populations can be maintained for many generations with enough competition and adaptation to the environment, they considered there is little invariance of the environment. They thought this implies poor models results compared to those of natural populations. Ellegren and Sheldon (2008) identified long term dedicated effort and current marking methods, which may need a change to genetic marking techniques as major difficulty of field research.

Ellegren and Sheldon (2008) reviewed the available mathematical models for measuring the relationship between natural selection and evolution stating that price equation is conditional on the transmission of variation. A second method of measuring quantitative genetics is perceptive multiple regression method, which hypothesizes that selection inclinations describe the link between fitness and trait variation. However, they recognized how environmental factors (as a variable) interact to induce genetically determined fitness traits is a key challenge to studies in the wild. Based on the fitness measure they accepted (a measure that combines individual and population aspects of fitness, designed to deal with unstable population dynamics and to take account of the continuous nature of evolution), they suggested applying this and other methods to take account of population demography. This would help to produce insights about the operation of selection and evolution in natural populations.

The authors stated that fitness traits analysis at phenotype level may produce an incomplete image of the degree of genetic change across time, and as recent studies of wild populations show, the expressed genetic variation is conditional to environment, the life stage of the organism and its sex. Thus they hypothesized wild population studies especially the long term ones are more convenient than animal model laboratory studies.

Further review on quantitative genetics and approaches

Ellegren and Sheldon (2008) identified two main points need fulfillment to proceed for quantitative genetics; first, there are huge numbers of loci of small effect trigger traits besides the environmental influence.

Second, there is a need to have enough gene (DNA) sequence information to link potential loci to fitness. The authors responded to their first research question about the genetic build up of fitness characteristics in wild populations by stating there are two schools of thought, either change in regulation of gene expression or change in gene structure. They underlined that working on animal models provides little information on naturally occurring population variants. They emphasized that genetic variation at different loci may result in similar phenotypes in different populations because of gene-environment interaction; thus, quantitative trait locus (QTL) mapping can be helpful to decode genetic build-up of traits.

Ellegren and Sheldon (2008) explained the basic principle of QTL mapping methods as genetic markers of an organism’s genome are typed within a mapping population of individual organisms of available phenotype data. If a marker is in close correlation with a QTL, both the marker and QTL will be in linkage instability (disequilibrium) within the mapping population. This results in statistically significant correlation between the marker genotype and trait variation. The authors responded to their second research question clarifying techniques of QTL. First is using inbred line crosses, which they considered the most effective method of QTL since it expands linkage disequilibrium between markers and trait loci, despite laboratory conditions do not mimic the environment effect.

Second, QTL studies on out-bred natural populations need large lineage (pedigrees) to sample and measure the components of fitness. Alternatively, they suggested searching for linkage between markers and trait loci by genomes scanning instead of pedigree analysis as an alternative option having the advantage of drawing out the statistical association between markers and trait loci (linkage disequilibrium). In case genetic markers spreading over the genome are available, the authors suggested selective sweep sampling method taking benefit from the fact that strong positive selection leaves a print form of reduced genetic diversity around the selected locus.

Approaches to fitness genes’ studies in natural populations

Combining information from model studies to studies on the genetic basis of fitness differences in natural population provide the benefit of suggesting the gene candidates for trait loci based on the knowledge gained from comparable phenotype model species. Ellegren and Sheldon (2008) explained three approaches for these studies; first, they suggested a candidate gene approach focusing on allelic variation, second they suggested strengthening the candidate gene approach by parallel genetic mapping. Finally, they proposed examining the genes encoding proteins included in glucose metabolism (energy production).

Ellegren and Sheldon (2008) viewed transcriptome analysis, which is analyzing the universal gene expression of an organism or a cell by identifying the entire messenger RNA (Wang et al 2009) superior to other techniques as it allays the need to construct a species-specific microarray. They reviewed studies where transcriptome profiling showed marked differences in gene expression among different natural populations. They looked at improvement in array technology a hope for large-scale studies of gene expression in natural populations.

Results

Ellegren and Sheldon (2008) conducted a systematic literature review study; however, they did not provide information about their search strategy or methodology, inclusion criteria, data extraction or data synthesis methods (Ridley 2008).

Therefore, there is no results part in this article. However; based on their literature review, Ellegren and Sheldon (2008) highlighted three potential directions for future research. First, identification of specific genetic loci affecting phenotyping, which will lead to accurate insight of what makes a trait that can be the target of selection. Second, increased convergence to the evolution loci would solve many current problems and leads to a genomic perspective that allows identifying and characterizing sex-antagonistic genes and testing evolutionary theories. Finally, the authors suggested future research would aim at determining the processes that can maintain genetic variation in natural populations limiting the problem of environmental and temporal variations.

Conclusion

In the conclusion section, Ellegren and Sheldon (2008) spotted that the understanding of evolutionary genomics is expanding because of organisms’ models for laboratory genetics; however, it should be clear that a continuum exists between experimental models genomics and environmental realism. The species that are intermediate in this continuum like mice may provide the most productive grounds.

References

Creswell, J. W (2003). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (first edition). Thousand Oaks, Ca: Sage.

Ellegren, H., and Sheldon, B. C (2008). Genetic basis of fitness differences in natural populations. Nature, 452, 169-175.

Gerstein, M. B., Bruce, C., Roaowsky, J. S., Zheng, D. et al (2007). What is a gene, post-ENCODE? History and updated definition. Genome Res, 17, 669-681.

Ridley, D (2008). The Literature Review: A step-by Step Guide for Students. Thousand Oaks, Ca: Sage Publications Ltd.

Tashakkori, A., and Creswell, J. W (2007). Exploring the nature of research questions in mixed methods research. J Mixed Methods Research, 1(13), 207-211.

Wang, Z., Gerstein, M., and Snyder, M (2009). RNA-Seq: a revolutionary tool for transcriptomics. Nature Rev. Genetics, 10(1), 57-63.

Click Here To Order Now!