To work out how old the grains were, the researchers measured how long they had been exposed to cosmic rays in space. These rays are high-energy particles that travel through our galaxy and penetrate solid matter.
Some of these rays interact with the matter they encounter and form new elements. The longer they are exposed, the more of these elements form. The researchers used a particular form (isotope) of the element neon - Ne-21 - to date the grains.
"I compare this with putting out a bucket in a rainstorm. Assuming the rainfall is constant, the amount of water that accumulates in the bucket tells you how long it was exposed," said Dr Heck.
Measuring how many of the new elements are present tells scientists how long the grain was exposed to cosmic rays. This in turn informs them how old it is.
Some of the pre-solar grains turned out to be the oldest ever discovered.
Based on how many cosmic rays had interacted with the grains, most had to be 4.6-4.9 billion years old. For comparison, the Sun is 4.6 billion years old and the Earth is 4.5 billion.
However, the oldest yielded a date of around 7.5 billion years old.
For many years, the National Human Genome Research Institute (NHGRI) has tracked the costs associated with DNA sequencing performed at the sequencing centers funded by the Institute. This information has served as an important benchmark for assessing improvements in DNA sequencing technologies and for establishing the DNA sequencing capacity of the NHGRI Genome Sequencing Program. Here, NHGRI provides an analysis of these data, which gives one view of the remarkable improvements in DNA sequencing technologies and data-production pipelines in recent years.
The cost-accounting data presented here are summarized relative to two metrics: (1) "Cost per Megabase of DNA Sequence" - the cost of determining one megabase (Mb; a million bases) of DNA sequence of a specified quality [see below]; (2) "Cost per Genome" - the cost of sequencing a human-sized genome. For each, a graph is provided showing the data since 2001; in addition, the actual numbers reflected by the graphs are provided in a summary table.
NHGRI welcomes people to download these graphs and use them in their presentations and teaching materials. NHGRI plans to update these data on a regular basis. You can view the data in in Excel by downloading the Sequencing Costs 2019.
Sequencing cost per megabase - 2019
Cost per genome data - 2019
To illustrate the nature of the reductions in DNA sequencing costs, each graph also shows hypothetical data reflecting Moore's Law, which describes a long-term trend in the computer hardware industry that involves the doubling of 'compute power' every two years (See: Moore's Law [wikipedia.org]). Technology improvements that 'keep up' with Moore's Law are widely regarded to be doing exceedingly well, making it useful for comparison.
How science has shifted our sense of identity Biological advances have repeatedly changed who we think we are, writes Nathaniel Comfort, in the third essay of a series marking Natureâs anniversary on how the past 150 years have shaped science today.