#genetic sequencing

To better understand the outbreak, The Times worked with prominent geneticists to determine the genetic sequence of viruses that infected two Times journalists believed to have been exposed to the coronavirus as part of their work covering the White House.

The study reveals, for the first time, the genetic sequence of the virus that may have infected President Trump and dozens of others, researchers said. That genome is a crucial clue that may allow researchers to identify where the outbreak originated and whether it went on to infect others across the country.

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The viral genomes of the two journalists shared the same distinct pattern of mutations, the research found. Along with their exposure history, the findings suggest that they were infected as part of the broader White House outbreak, said Trevor Bedford, a geneticist at the Fred Hutchinson Cancer Research Center and the University of Washington who led the research team.

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Viruses constantly mutate, picking up tiny, accidental alterations to their genetic material as they reproduce. Few mutations alter how a virus functions. But by comparing patterns of mutations across many genetic sequences, scientists can construct family trees of a virus, illuminating how it spreads.

The genomes believed by these researchers to be connected to the White House outbreak do not identify a recent geographic source, in part because they are unusual. The ancestors of those viruses spread to the United States from Europe and were circulating widely across the country in April and May, but the trail goes cold after that, according to Dr. Bedford.

If you could learn every disease your child could possibly develop in life, would you?

DNA has moved beyond esoteric science and into the center of everyday conversations about identity, culture and politics. It’s also reshaping stories about the past as advances allow scientists to extract ancient DNA (aDNA) from skeletons found at archaeological sites.

With each ancient genetic sequence, scientists learn new information about how people moved around and interacted in the ancient world. In some cases, this has helped overturn theories and resolve age-old debates.

But the aDNA “revolution” has also caused friction among geneticists, archaeologists and others over how this research is done. As archaeologists who collaborate on aDNA projects, we’ve witnessed these tensions firsthand. What lies at the heart of this rift, and how can these disciplines work together to better research humanity’s past?

The Animal Genetics Market is witnessing steady long-term growth as global livestock systems modernize. The market reached USD 1,783 million in 2024 and is expected to grow to USD 2,309 million by 2030, expanding at a 4.4% CAGR.

Population growth and rising protein consumption are increasing pressure on livestock productivity. Animal genetics solutions help address this demand by improving breeding efficiency and disease resistance.

Primary growth drivers include:

Increasing demand for efficient livestock production

Technological advancements in genetic sequencing

Expansion of commercial dairy and meat operations

Supportive government and research initiatives

The Animal Genetics Market forecast indicates sustained demand for genetic testing services and breeding technologies, particularly in developed markets such as the US.

Challenges such as high initial investment and data complexity are being addressed through automation and user-friendly platforms. These innovations are lowering entry barriers for producers.

The market is also benefiting from cross-sector collaboration between agriculture, biotechnology, and data science industries.

Businesses focusing on innovation, education, and scalable solutions are likely to capture long-term market share.

Mitochondrial targeted sequencing, also known as mitochondrial target region sequencing, is a technical means to capture and enrich the regions of the mitochondrial genome of interest by PCR or probe hybridization and achieve high-throughput sequencing. It can detect the genetic variation sites in the target genome region and obtain the variation information of the specified target region.