New worlds: Big data and the social character of genes

The new study used “big-data” analytical methods to reveal the “social character” of genes – a phenomenon in certain diseases whereby genes operate jointly rather than independently.

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October 18, 2015 10:19
4 minute read.
DNA

DNA structure [Illustrative]. (photo credit: INIMAGE)

 
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University of Haifa researchers have managed to narrow down from 900 million to just 340,000 the possibilities requiring examination of the connection between genetic markers and genetic expression. In the process, they have identified “social” genes that play a cooperative role. The study was just published in the journal PLOS ONE.

The new study used “big-data” analytical methods to reveal the “social character” of genes – a phenomenon in certain diseases whereby genes operate jointly rather than independently.

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“The problem is that the possible number of combinations of different genes is enormous, and it is almost impossible to examine them all effectively and reliably,” the researchers explained. “Our study offers a solution to this problem.” The study, which was undertaken as part of a master’s thesis by Pavel Goldstein from the university’s department of statistics, was headed by Dr. Anat Reiner-Benaim. It proposed a new method for discovering complex and rare genetic effects that form part of the mechanism of creation of complex disorders such as autoimmune diseases.

The study focuses on the connection between genetic markers – DNA segments situated along the genome that effectively represent genes – and the expression (the creation of the proteins they encode) of different genes. Various studies over recent years have shown that in complex biological mechanisms, such as those in most diseases, the genetic expression is not the product of the action of a single marker, but rather of a combination of several markers, some close to the location of the gene on the DNA chain and others more distant.

In the Human Genome Project, for example, the researchers initially found that some 98 percent of the human genome contains genes that do not “do” anything. However, it later emerged that some of these genes are in fact active – not independently, but as part of a network of genes. Thus the influence of a given genetic marker may be dependent on the influence of other markers – a phenomenon known as epistasis.

The problem is that the theoretical number of combinations in which different genes could cooperate is almost infinite – equivalent to the product of the enormous number of potential connections between markers and the potential list of genetic expression.

Thus it is difficult to decide where to look for these connections.

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The Haifa researchers propose a new method of calculation that significantly reduces the number of possibilities, causing the identification of the interactions between genes to become feasible. The method shrinks the number of markers by applying a hierarchical filter to DNA areas containing at least one epistatic phenomenon, enabling research to focus solely on genetic markers within these areas. The method reduces the number of genetic expressions by clustering together similar expressions. The proposed method was applied for the purpose of analyzing the genome of the thale cress plant (Arabidopsis thaliana).

CANDIDATE VOICE PITCH INFLUENCES VOTERS

As Israelis suspected during the Bibi vs.Buji vote in the last Knesset elections, US political scientists have found that the tone of a candidate’s voice can influence whether he or she wins office.

“Our analyses of both real-life elections and data from experiments show that candidates with lower-pitched voices are generally more successful at the polls,” explained Prof. Casey Klofstad of the University of Miami College of Arts and Sciences, who is corresponding author on two separate studies on the issue.

The first study, published in Political Psychology, showed that candidates who ran in the 2012 US House of Representatives elections and had lower voices were more likely to win their elections. These findings are more complex, however, once the sex of the candidate and his or her challenger is accounted for. When facing male opponents, candidates with lower voices won a larger vote share. But, when facing female opponents, candidates with higher voices were more successful and particularly so in the case of male candidates. “As individuals with lower voices have higher levels of testosterone, and as testosterone correlates with physical and social aggressiveness, it could be that male candidates with lower voices are perceived as too aggressive when paired against a female opponent,” Klofstad said.

The second study, published online in the open-access journal PLOS ONE, used an experiment to examine why voters prefer leaders with lower voices. In the experiment, Klofstad and his colleagues asked study participants to listen to pairs of recorded voices that had been manipulated to vary only in pitch. The participants were then asked which voice of each pair was stronger, more competent and older and for whom they would vote. The findings were that the preference for leaders with lower-pitched voices correlates with the perception that speakers with lower voices are stronger, more competent and older, but the influence of perception of age on vote choice is the weakest of the three. “While these findings add to our understanding of why voters prefer leaders with lower voices, future studies are needed to test whether people with lower voices are actually stronger and more competent leaders,” Klofstad said.

These new studies show that while voters consciously consider their own political preferences and those of the candidates when casting their ballots, voters also make thin impressionistic judgments based on far more subtle factors of which they may not be aware, the authors wrote. Ironically, these factors may not be relevant to a candidate’s leadership ability, which calls into question whether voters are actually capable of making reasoned choices at the polls.

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