Challenges in assessing adaptive genetic diversity j 137 in .NET Implement Code 3/9 in .NET Challenges in assessing adaptive genetic diversity j 137

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Challenges in assessing adaptive genetic diversity j 137 using visual studio .net toreceive 3 of 9 on web,windows application .NET (1) RNA extract (2) RT-PCR cDNA (3) Labelling of amplified cDNA Pop1 Pop2 Gene over expressed in Pop 2 Cy3 signal (4) Hybridization on cDNA microarray containing spotted gene probes Gene over expressed in Pop 1 Cy5 signal Figure 6.5. Basic p rinciples of transcription profiling based on a cDNA microarray.

The basic principles of cDNA microarray analysis consist in quantifying differential levels of gene expression by means of a competitive hybridization between RNA (retro transcribed cDNA) from two experimental specimens. It involves four basic steps: (1) RNA is first extracted from each specimen to be analysed, (2) source RNA is retro transcribed into complementary DNA (cDNA) and amplified using PCR, (3) cDNAs of both experimental specimens are marked with different fluorescent labels, and (4) labelled cDNAs of both specimens are simultaneously hybridized on a cDNA microarray usually containing probes for thousands of genes. Hybridized microarrays are then image scanned and the differential intensity of both labels for each gene is translated into differential levels of expression between experimental specimens.

(See also colour plate.). at specific genes, Code 39 Extended for .NET but will also be manifested as changes in gene expression during development (Purugganan 1998; Streelman and Kocher 2000). Accordingly, technologies are being developed to characterize organismal transcriptomes that include the set of genes expressed in a particular tissue at a specific time.

The method that is now most commonly used to define transcriptomes is termed DNA microarray (Gibson 2002) (Fig. 6.5, and Plate 1, colour plate section).

By comparing patterns of gene expression between populations, this method offers the possibility to identify the most significant shifts in gene expression involved in the adaptive divergence of populations. In fact, several recent studies have demonstrated the potential of transcription profiling to reveal differential gene expression between populations, and thus offer a tremendous opportunity for investigating the. 138 j Aurelie Bonin and Louis Bernatchez genomic basis of ph .NET Code 39 Extended enotypic divergence under various environmental conditions (Oleksiak et al. 2002; Bochdanovits et al.

2003; Oleksiak et al. 2005; Whitehead and Crawford 2006). Even without prior information on which genes may be adaptive in a specific context, genome-wide expression employing natural populations permits the identification of specific genes potentially implicated in adaptive divergence and the direction of genetic divergence using a comparative approach.

Evidence that the same subset of genes presents parallel, directional changes in expression among independently evolving populations of similar phenotype can also provide strong empirical support for the role of natural selection in shaping differential gene transcription profiling. Moreover, traits under strong selection are expected to display lower variance than traits under weaker selection. Since gene expression is a quantitative trait, testing for a significantly reduced variance in expression among individuals may further support the role of natural selection acting on those genes.

One important constraint on the current use of this method in the context of conservation is that specific microarrays are currently available for only a handful of species, although the use of cross-specific arrays has proven feasible and useful (Renn et al. 2004). Also, it should be noted that microarrays only measure the steady state concentration of a gene s mRNA, and that mRNA translation, degradation, and protein turnover will also affect the active amount of a protein ultimately affecting a phenotypic change.

. Rapid evolutionary changes of gene expression in farmed Atlantic salmon (Salmo salar): relevance for the conservation of wild populations. Selective breeding Code 39 Full ASCII for .NET of Atlantic salmon (Salmo salar) was initiated in Norway some 35 years ago and is now intensively practised in Chile, the United Kingdom, the United States and Canada. At first, artificial selection was limited to the improvement of growth rate, but this practice now also targets traits such as age at sexual maturity, bacteria resistance, fat content and flesh colour.

Moreover, phenotypic changes in traits that were not the focus of artificial selection have also been observed in Norwegian farmed salmon, including increased fat content in flesh (Rye and Gjerde 1996), poorer performance in natural conditions (Fleming et al. 2000; McGinnity et al. 2003) and morphological and behavioural changes (Fleming and Einum 1997), as well as a higher feeding rate and food conversion efficiency (Thodesen et al.

1999). The last decade has seen the world-wide production of farmed Atlantic salmon outstrip that of fisheries (FAO 2004); in.
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