What have we 'Ear'?

An AOP publication in Nature Genetics claims to have identified a gene involved in the secretion of wet earwax (Yoshiura et al). Quite why they chose to investigate this trait is beyond my understanding (after all I feel that auto-immune and cardio-vascular diseases and cancers have a far larger impact on human health world-wide than the need for the occasional ear syringe), particularly given that it is mendelian and not polygenic in nature, despite the contentious nature of the association with breast-cancer (which is likely to only be pure co-incedence).

The claim that this is "...the first example of DNA polymorphism determining a visible genetic trait" is I feel somewhat grandiose and misled as there are innumerable polmorphims which have a direct effect on the phenotype of individuals who carry them, for example the ΔF508 mutation in Cystic Fibrosis, or the Huntington's Disease gene.

More interstingly the current issue of Nature Genetics has an article on a sex-xpecific QTL (Quantitative-Trait Locus). In this article they review 17 quantitative traits (including systolic and diastolic blood pressure, triglycerides, serontin levels, LDL and HDL levels) in the Hutterite's to see if there are any sex-specific effects. They found that 11 of these showed differences between the sexes at a significance level of p < 0.05 (although really they should have applied a Bonferroni correction and set the significance level to 0.0029 at a bare minimum assuming all the traits were independent). Heritability differed between sexes in some cases as well.

This obviously has important implications when analysing genetic data for QTL's and sex should therefore always be included in the early stages of the analysis to determine whether it has a significant effect.

Links

Complex Trait Mapping in the Hutterites

DNA databases...

Back in April 2005 (21st to be precise), I attended a public debate entitled DNA Profiling and You: Do genetic databases threaten or benefit society? at the Nowgen Centre in Manchester.

I heard that when the databases were initiated in 1999 it was only admisable to take DNA samples from individuals who had been convicted of a crime, but was astounded that since then the laws have been relaxed to such an extent that samples are routinely taken by people who are arrested even if they are acquited of the crime for which they were arrested. This was verified by a friend of mine who was arrested but never charged, yet was obliged (under the threat of force) to provide a DNA sample.

Recent articles in the news are highlighted in this months Nature Reviews Genetics, and highlights not only the racial bias that exists within the UK database, but the rapid expansion that it has undergone (see the article here if you can access it).

I was astounded to read that only ten microsatellites are used for typing individuals as this seems exceptionally small (in the future I may do some simulations to investigate the statistical probabilites of finding matches by chance alone with such a small sample size if time permits).

I do not wish to comment on the moral or ethical implications of collecting such databases, but find it amazing that such databases exist and continue to expand relatively unchecked. It is heinous that samples can be taken and retained freely, particularly in light of the extensive legal and ethical standards that organised medical research projects have to adhere to when applying for and executing medical research.

Links

DNA database continues to swelll (BBC News, 04/01/2006)

Statalist Blog...

I use the statistical package Stata and today I came across the blogger feed of the mailing list and thought I'd menion it here.

To view posts to this mailing list simply go here.

Festa(r) & Festa(r) tagging SNPs

Yet another SNP tagging algorithm and program has been released, this time from the University of Michigan Center of Statistical Genetics.

Qin et al (2006) Bioinformatics 22:220-225 propose tagging on the basis of the pairwise LD measure r² and have developed a fast and efficent algortihm which breaks genomic regions down into sections, allowing for faster computation of tagging SNPs has been developed to carry this out.

It avoids the potential drawback of multimarker approaches which may not perform well when genotyping fails.

This is a nice simple approach to increasing efficency, since there is little point in attempting to tag SNPs over long distances.