Collective effects of common SNPs in foraging decisions in Caenorhabditis elegans and an integrative method of identification of candidate genes

A new paper of ours just published, demonstrating the power of the MGD theory in solving great puzzles of contemporary biology.

http://www.nature.com/articles/srep16904

Collective effects of common SNPs in foraging decisions in Caenorhabditis elegans and an integrative method of identification of candidate genes.

Sci Rep. 2015 Nov 19;5:16904. doi: 10.1038/srep16904.

Zhu Z, Lu Q, Wang J, Huang S

Abstract

Optimal foraging decision is a quantitative flexible behavior, which describes the time at which animals choose to abandon a depleting food supply. The total minor allele content (MAC) in an individual has been shown to correlate with quantitative variations in complex traits. We have studied the role of MAC in the decision to leave a food lawn in recombinant inbred advanced intercross lines (RIAILs) of Caenorhabditis elegans. We found a strong link between MAC and the food lawn leaving rates (Spearman r = 0.4, P = 0.005). We identified 28 genes of unknown functions whose expression levels correlated with both MAC and leaving rates. When examined by RNAi experiments, 8 of 10 tested among the 28 affected leaving rates, whereas only 2 of 9 did among genes that were only associated with leaving rates but not MAC (8/10 vs 2/9, P < 0.05). The results establish a link between MAC and the foraging behavior and identify 8 genes that may play a role in linking MAC with the quantitative nature of the trait. The method of correlations with both MAC and traits may find broad applications in high efficiency identification of target genes for other complex traits in model organisms and humans.

Some quotations from our Parkinson's disease paper just published in PLoS One

Some quotations from our Parkinson's disease paper just published in PLoS One:

Recent studies have begun to show that a much larger than expected portion of the human genome may be functional [24–29].

An organism can certainly accommodate some limited amounts of random variations within its building parts or DNAs, but too much random errors or mutations may exceed an organism’s maximum level of tolerable disorder or entropy. Thus overall level of randomness or minor allele amounts may be expected to be higher in complex diseases relative to controls.

In fact, while most bench biologists have thought otherwise, nearly all in the population genetics field still believe that most SNPs are neutral or that most minor alleles are minor because of random drift rather than because of disease-association.

The findings of higher MAC in PD cases is consistent with our intuitive hypothesis that a highly complex and ordered system such as the human brain must have an optimum limit on the level of randomness or entropy in its building parts or DNAs. Too much randomness over a critical threshold may trigger complex diseases. There may be only one unique and optimum way to build a complex system but there could be numerous ways to break it.While it may only take one single major effect error in a major pathway to cause diseases, it would require the collective effects of a large number of minor effect errors in many different pathways to achieve a similar outcome.

Application of the MGD theory on complex diseases, first success Parkinson's disease

We have a new research paper on Parkinson's disease in press in PLoS One

It is merely the first success of the MGD theory in solving complex dieseases problems.

Enrichment of Minor Alleles of Common SNPs and Improved Risk Prediction for Parkinson's Disease

Zuobin Zhu, Dejian Yuan, Denghui Luo，Xitong Lu and Shi Huang*

State Key Laboratory of Medical Genetics, Central South University, Changsha, Hunan, China

Abstract

Parkinson disease (PD) is the second most common neurodegenerative disorder in the aged population and thought to involve many genetic loci. While a number of individual single nucleotide polymorphisms (SNPs) have been linked with PD, many remain to be found and no known markers or combinations of them have a useful predictive value for sporadic PD cases. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have recently been shown to be linked with quantitative variations of numerous complex traits in model organisms with higher MAC more likely linked with lower fitness. Here we found that PD cases had higher MAC than matched controls. A set of 37564 SNPs with MA (MAF < 0.4) more common in cases (P < 0.05) was found to have the best predictive accuracy. A weighted risk score calculated by using this set can predict 2% of PD cases (100% specificity), which is comparable to using familial PD genes to identify familial PD cases. These results suggest a novel genetic component in PD and provide a useful genetic method to identify a small fraction of PD cases.