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he first ever geostationary satellite to provide 3D profiles for temperature and humidity for Europe launched yesterday [1 July], in the latest phase of a multi-year project to transform weather forecasting and climate monitoring.

The Meteosat Third Generation Sounder (MTG-S1) will be the first ever European sounding satellite in geostationary orbit, joining the imager satellite which launched in 2022 and is now the primary imaging satellite for Europe and providing data to European meteorological organisations, including the Met Office.

The launch, organised by EUMETSAT, will put MTG-S1 into orbit focused on Europe and will provide data to enhance the next generation of weather forecasts. It’s the second satellite as part of a series of six which will revolutionise and safeguard weather forecasting across Europe for the next 20 years.

Met Office, Managing Director of Products and Services Simon Brown is present at the launch and is part of the team that represents the Met Office within EUMETSAT. Speaking ahead of the launch, he yesterday said:

“Our vision is to be the most trusted for weather and climate intelligence and, once available, the more frequent and more detailed satellite data will be assimilated into calculations run on our new supercomputer, providing an extra layer of data to Met Office forecasts to further improve accuracy.

“The MTG mission is a hugely important project, not just for us at the Met Office, but also for forecasters and meteorologists across Europe. This international collaboration is vital in ensuring that recent improvements to forecast accuracy can be safeguarded and enhanced in the coming years.”

MTG-S1 includes an infrared sounder, which will provide the first ever regular 3D profiles for temperature and humidity, adding more data for meteorologists to work with, as well as to be embedded in numerical weather predictions.

Satellite data is the largest contributor to numerical weather prediction accuracy and the ongoing project will both safeguard existing performance, as well as accelerate improvements in the coming years. The space-to-ground profiles will enable more complex calculations and aid understanding of the competing factors at play in the Earth’s atmosphere.

The Infrared Sounder scans Europe every 30 minutes, providing near-real time observations for meteorologists in a marked shift from existing sounder observations, which come from low-earth orbit satellites typically only revisiting Europe a few times a day.

The enhanced detail and frequency of data is crucial to forecasters, according to Met Office Head of Space Applications and Nowcasting R&D Simon Keogh. He yesterday said:

“The infrared sounder represents a marked step-change in data availability for forecasters in Europe.

“The data will further enhance our nowcasting capabilities, which is the forecasting of impactful convective systems at short ranges. Coupled with the imaging satellite that is now providing data, the sounding satellite will allow meteorologists to make more detailed, timely and accurate assessments of the atmosphere prior to severe convective rainfall and thunderstorms, which can be responsible for impactful weather, including flash floods.”

The satellite also hosts the Copernicus Sentinel-4 mission, by carrying an Ultraviolet, Visible and Near-Infrared spectrometer which will be used for long-term climate monitoring, and which captures data every hour to monitor air quality and pollution over Europe and North Africa.

Harshbir Sangha, Director of Missions and Capabilities at the UK Space Agency, said:

“The data from Sentinel 4 will be pivotal for the UK’s Earth observation sector, particularly users of the Copernicus Atmosphere Monitoring Service, by allowing rapid, hourly forecasting on air quality and pollution.

“We are proud to acknowledge the UK’s critical role in the instrument’s development, with essential characterisation and calibration phases carried out at the RAL Space’s test facility, ensuring Sentinel‑4 meets the exacting standards necessary to support timely, policy-relevant air quality services.”

A live feed of the launch is available online. This link will close at the conclusion of the launch.

Phil Evans, Director-General of EUMETSAT, said:

“MTG-S1 will provide entirely new types of data products that will support specialists across EUMETSAT member states to detect signs of atmospheric instability even before clouds begin to form. Combined with data from the MTG imaging satellites it will, for the first time, offer a space-based view of the full lifecycle of convective storms. This will provide tremendous support to national meteorological services in carrying out their vital work, helping to save lives, reduce disruption, and strengthen resilience.

“The effects of the climate crisis are not distant threats: they are already being felt across Europe – through more frequent storms, longer heatwaves, and shifting climate patterns. MTG-S1 will support more timely warnings, safer travel decisions, more effective emergency response, and support informed action.

“My sincere thanks go to everyone who made MTG-S1 possible – our teams at EUMETSAT, our member states, the European Union, the European Space Agency, national meteorological services, and all our industrial and academic partners. This successful launch is a testament to the strength of European cooperation. We now move to the next phases and preparing the satellite for full operations.”

Post launch, it will take around a year for the first data to be available from the satellite, with further quality assurance tests needed before the new data can be routinely used by meteorologists in Europe.

The next launch in this series, led by EUMETSAT and ESA, is expected in 2026, with a further imaging satellite.

 

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Many medically relevant genes reside in “dark regions” of the genome that have long been elusive. To address this, we developed Paraphase – a computational tool that accurately resolves and analyzes paralogous genes. By unlocking the difficult-to-analyze regions of the genome where paralogous genes reside, Paraphase provides deeper insights into genetic variation, disease mechanisms and population diversity. This knowledge helps lay the groundwork for improved diagnostics, more inclusive reference genomes and future discoveries in genomic medicine. This multi-institutional study, led by PacBio, was published in Nature Communications.

Shedding light on the genome’s dark regions

We wanted to overcome a longstanding challenge in genomics: highly similar paralogous genes. These genes often reside within segmental duplications (SDs), which are large, repeated regions of DNA with nearly identical sequences. The repetitiveness of SDs complicates variant calling and copy number analysis, meaning traditional short-read sequencing technologies struggle to resolve these regions, leaving many genomic regions understudied and conditions undiagnosed.

To further our mission of accurately analyzing previously “dark” regions of the genome, we decided to design a tool for precise phasing and analysis of SDs with high accuracy and throughput. We also wanted to examine how copy number variations (CNVs) in certain paralogous genes differ across ancestries, and to show how this affects disease risk for different populations of people. We wanted to prove further how understanding genetic diversity such as copy numbers is key for building inclusive reference genomes and advancing equitable genomic medicine.

Paraphase uncovers genetic variations in segmental duplications in global populations

We developed a computational tool, Paraphase, to resolve segmental duplications (SDs) and allow us to accurately assess paralogs and copy numbers.

Before applying Paraphase to new data, we first validated the tool by applying it to known positive pathogenic samples and confirmed its accuracy. We then extended our analysis to 160 SD regions, spanning 316 genes. Samples came from 259 individuals across 5 ancestral groups: South Asian, European, African, Latin American and East Asian; the goal was to identify patterns of population-specific diversity and potential reference genome errors. Additionally, we examined 36 parent–offspring trios to detect de novo variants and gene conversion events.

The key findings of the study were:

• Paraphase enabled the analysis of medically important genes and associated diseases, such as those implicated in spinal muscular atrophy (SMN1/SMN2) and congenital adrenal hyperplasia (CYP21A2).
• We observed high copy number variability in many gene families within segmental duplications across people of different ancestries.
• We discovered a new approach for identifying false duplications in the reference genome.
• We identified 23 paralog groups with exceptionally low genetic diversity between genes and paralogs, indicating that frequent gene conversion and unequal crossing-over may contribute to similar gene copies.

Diverse genomic insights improve disease research and diagnosis

Our study demonstrates that using long-read HiFi sequencing in conjunction with our computational tool, Paraphase, provides a much richer and more detailed picture of genetic variation, specifically in complex SDs. By improving our ability to call disease-linked variants that are often missed by other technologies, Paraphase opens up new avenues for disease research.

For example, using Paraphase, we disentangled medically important gene families in a single test that have previously required specialized, multi-step assays. In the CYP21A2/CYP21A1P region – where mutations cause congenital adrenal hyperplasia – we characterized a previously overlooked duplication allele carrying both a functional CYP21A2 copy and a nonfunctional CYP21A2(Q319X) copy. Using standard tests, this duplication allele could easily have been misclassified.

Our study further highlights the power of long-read sequencing in detecting de novo variations, particularly in previously inaccessible parts of the genome. We uncovered seven previously undetected de novo single nucleotide variants (SNVs) and four de novo gene conversion events, two of which were non-allelic – a level of detail not possible with traditional sequencing approaches.

Additionally, our approach revealed high variation in copy number distributions across paralog groups in different ancestries. This finding reinforces the need for more genetically diverse reference genomes, as current references genomes are often biased toward European populations.

Paraphase provides a method for studying paralogous genes at scale, offering new opportunities for disease research, population-wide analysis and potentially even clinical testing. By broadening our understanding of genetic variation across ancestries, we can better understand how certain diseases impact specific populations, paving the way for more targeted diagnoses and treatment approaches.

By enabling more accurate identification of de novo variants and gene conversion events, our approach provides deeper insights into how genetic disorders arise and how traits are inherited. These discoveries offer a clearer view of genetic inheritance patterns and help reveal the underlying mechanisms of disease.

It should be noted that the current study focuses exclusively on gene families with fewer than 10 genes. Larger and more complex gene families were not included, meaning some medically important regions have yet to be studied. Additionally, the study is limited to assessing DNA-level variation in paralogs and does not explore transcriptomic or epigenetic factors, such as RNA expression or methylation differences between gene copies.

A broader lens: From genomics to multiomics

Looking ahead, we would like to extend Paraphase to study larger gene families, which were excluded from the current study. We’re also interested in applying Paraphase to investigate RNA-level differences and the transcriptional activity of paralogs that are very similar in sequence. It would be beneficial to explore epigenetic regulation with Paraphase, as it could provide further insights into how paralogous genes are controlled and expressed.

Reference: Chen X, Baker D, Dolzhenko E, et al. Genome-wide profiling of highly similar paralogous genes using HiFi sequencing. Nat Commun. 2025;16(1):2340. doi:10.1038/s41467-025-57505-2