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Disciplines that are now using nucleic acid measurement technologies range from basic biology to medicine to environmental science to biotechnology.  Each of these will use the basic data to answer different questions.  Below are some of the fundamental questions.

Questions about DNA:

• What is the sequence? (This is basic).
• How is the sequence organized on the chromosome? What is adjacent to what along the strand of DNA? Are there adjacency issues because of the coiling involved, i.e. spatial adjacency of features due to 3-D coiling that are not adjacent on the chromosome.

• What are the molecules that bind to the DNA and where do they bind? How does this vary with genomic variations?

• We want to know about individual sequence variations in a population such as changes at single loci (SNPs), larger mutations such as deletions, insertions, duplication, etc. and whether they are associated with phenotypes such as disease susceptibility, growth and other traits of interest

• We want to know how species vary and evolve.  This is of interest not only to evolutionary biologists, but also for understanding phenotypic variation.

• We want to know about communities of microorganisms (microbiomes) which may be important for reasons such as human health (e.g. the gut and skin microbiomes), environmental health (e.g. healthy and unhealthy mixes of soil micro-organisms), industrial processes (e.g. clean-up of contaminated sites, biofuel production.)     We would like to associate the community composition with measures of health (of the organism or of the environment). 

Some very popular analyses include looking at genetic markers, which are readily detected genomic variants. These include single nucleotide polymorphisms (SNPs) and microsatellites. A SNP is a change in a single base in the sequence. A microsatellite is sometimes called a small repeat -  a sequence of two or three or four nucleotides which repeat several times in adjacent locations. SNPs are very easy to measure and vary over time scales of thousands of years.  Microsatellites are very popular for marking disease associations because they are easy to measure and the number of repeats can vary quite a bit over populations in short time periods compared to other kinds of mutations.

Genome Wide Association Studies (GWAS) involve associating these markers on a genome-wide (or at least single chromosome) scale with phenotypes or traits of interest such as disease stage, tendency to become overweight, having resistance to a pathogen, and so on.

 In looking at how organisms of the same species differ, and also organisms the same evolutionary branch differ biologists may also look at genomic duplications and rearrangements. Copy number variation occurs when duplicate copies of the gene (or segment of DNA) gets added to the chromosome. Alternatively,  a copy gets deleted and then the individual won't have that gene or express that protein.  Studies of copy number variation are quite common when looking at cancer, which often seems to involve large numbers of chromosome defects.  Duplications of genes, segments of DNA or even the entire genome are thought to be involved in evolutionary processes.

gene duplication or deletion

Another type of genomic rearrangement is an inversion.  The chromosome is cut and segment of DNA is inserted backwards.

A number of molecules bind to the DNA and regulate transcription in various ways.  Transcription factors are proteins that bind to promoter regions and regulate gene expression.  Small RNAs may also bind to regions of the chromosome and have a role in gene regulation.   Methylation involves changes in the DNA molecule but can be measured in a very similar way.  Molecular markers are used to bind to the molecules of interest or the methylated sites.  The DNA is fragmented.  The fragments bound to the markers are retrieved and the other fragments are washed away, enriching the sample of nucleotides for the bound fragments.   The binding is reversed and the markers are washed away.  What remains are fragments of DNA which can be measured using microarrays or sequencing tools.

Questions about RNA:

• What RNAs are in the sample (particularly for studies of small RNAs)
• What isoforms are in the sample?
• How much of each transcript is in the sample?
• Are certain alleles (or maternally or paternally derived alleles) more likely to create transcripts?

Typically questions about RNA involve quantification, as well as identification.  We discuss this more in the next section on gene expression.