Do twins have the same DNA?
That depends whether they are fraternal twins or identical twins.
Fraternal twins are produced when two eggs are present and both are fertilized. Each of these fertilized eggs develop into a baby, and they are born at the same time. But, even if they have been nurtured in the same womb at the same time, these twins don’t have the same DNA since they come from separate eggs and sperms.
Meanwhile, identical twins come from just one egg that’s been fertilized by one sperm. It would turn into twins when the egg divides and each half develops into a baby. Since they come from one egg, these babies are called identical twins given the fact they do have identical DNA.
However, identical twins have different fingerprints.
And we know that twins do grow up with different personalities. Their talents and skills may vary. Even their intelligence.
So, it goes without saying that the study of human DNA or genome is really a very complex pursuit.
However, there’s a new controversy that’s rocking the world of genomics!
Lead author Christoph Lippert, Ph.D. and senior author J. Craig Venter, Ph.D., along with other researchers have recently published a paper on the Proceedings of National Academy of Sciences which claims that they have formulated algorithms that can come up with computer-generated images of people based on their genome data.
This has caused an alarm since there are many people who have been providing their genome data to various research centers albeit anonymously.
According to the authors, “much of the promise of genome sequencing relies on our ability to associate genotypes to physical and disease traits. However, phenotype prediction may allow the identification of individuals through genomics—an issue that implicates the privacy of genomic data. Today, where online services with personal images coexist with large genetic databases, such as 23andMe, associating genomic data to physical traits (e.g., eye and skin color) obtains particular relevance. In fact, genome data may be linked to metadata through online social networks and services, thus complicating the protection of genome privacy. Revealing the identity of genome data may not only affect the contributor, but may also compromise the privacy of family members.”
The study involved 1,061 ethnically diverse people with ages from 18 to 82 whose genomes were sequenced to an average depth of at least 30 times. Phenotype data in the form of 3D facial images, color of eye and skin, voice samples, age, height, and weight were also collected.
The team was able to predict eye and skin color including sex with high accuracy. However, they encountered difficulty with the other more complex genetic characteristics.
Meanwhile, the researchers have also developed a machine learning algorithm called a “maximum entropy algorithm”. Based on their press release, this algorithm also proved successful since it “found an optimal combination of all predictive models to match whole-genome sequencing data with phenotypic and demographic data and enabled the correct identification of, on average, 8 out of 10 participants of diverse ethnicity, and 5 out of 10 African American or European participants.”
The number of participants to their study may be small, but the team believes that their predictive models are reliable.
Venter, who co-founded Human Longevity Inc. remarked, “We set out to do this study to prove that your genome codes for everything that makes you, you. This is clearly a proof of concept with a limited cohort but we believe that as we increase the numbers of people in this study and in the HLI database to hundreds of thousands we will be able to accurately predict all that can be predicted from individuals’ genomes.”
Venter did also explain that they were concerned that the public and the research community at large were not seeing the need for stricter policies and better safeguards for those who have been providing their genomic data to various agencies. The researchers want everyone to realize that continued discussion, more analytical studies, and better technical solutions are of great importance.
Christoph Lippert, a data scientist at Human Longevity, Inc, also stated that the study “shows the potential of imaging technologies to screen the traits of large numbers of individuals. Machine learning enables fully automated data interpretation and plays a crucial role in scientific discovery.”
How will the world react to this?
Some experts disagree with the study while other people are alarmed, especially after learning that their genomic data could be exploited by insurance companies or unscrupulous entities.
So, what’s the best thing to do?
Weight the risks, basically. Consider the welfare of your family whose lives may also be impacted as more and more genomes are generated and placed in public databases. Determine your priorities in life, whether it’s a necessity to provide your genomic data to the government or private institution. Will it make a difference to the world?
In this world of so many scientific advances, you can get blinded by all the new knowledge getting acquired every day from every corner and spoken by every expert.
In the end, it may be best to listen to your conscience. It tells what’s best, for you and everyone you care about.
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