Category Archives: Transhuman News

Are itch and pain related? In both cases, the nervous system is involved and deciphering the molecular basis of itch has tremendous contribution to pain management. In diseases like cancer, sickle cell anaemia and others, the excruciating pain and managing it to tolerable limits is one of the challenges faced by clinicians, said paediatrician-turned-geneticist Geoff Woods from Cambridge Institute for Medical Research, UK, on Sunday.

In his talk on With Extreme Phenotypes, think of Genetics, even with Itch, organised by the city-based Genome Foundation, in collaboration with Indian Association of Dermatologists, Venereologists and Leprologists (IDVL) Telangana branch, he said administering opioids was being intensely debated in medical practice.

Opioids, a substance found in certain prescription pain medications and illegal drugs such as heroin, are prescribed to treat pain. With prolonged use, pain-relieving effects may lessen and pain can become worse. In addition, opioid-dependency causes withdrawal symptoms, which makes it difficult to stop taking them, he explained.

Mr.Woods presented case studies of ultra-rare diseases like the Congenital Itch inherited in families with autosomal dominant transmission of mutations in two genes, SCN10A and COL6A5. Most important finding related to this disorder is that small addition of nucleotides (small DNA changes) differentiates onset of pain.

Second is congenital insensitivity for pain caused by dominant hyper-activity mutations in the gene SCN11A and third is the Mid-facial Toddler Excoriation syndrome (MiTES) - a congenital insensitivity to pain, an autosomal recessive disorder caused by mutations in PRDM12 gene.

The webinar began with remarks by chairman of Genome Foundation K.P.C. Gandhi while dean-research V.R.Rao convened the programme. Consulting dermatologist V. Anand Kumar introduced the speaker and Genome Foundation director Aparna Kaja delivered the vote of thanks, said a press release.

Link:
Scratching the itch behind pain management - The Hindu

NEW YORK A recently completed draft human pangenome reference aims to be the first step toward a reference genome that not only is more complete but also better reflects human diversity.

The current human reference genome, GRCh38, is a mishmash of sequences from different individuals, though about 70 percent of the sequence comes from just one person. "Obviously one human can't represent all the variation in humans," said Benedict Paten, an associate professor at the University of California, Santa Cruz, and a member of the Human Pangenome Reference Consortium.

Instead, the consortium plans to generate 700 reference-quality haplotypes from 350 individuals, maximizing genomic and geographical diversity.

The idea of a pangenome reference that encompasses a wider range of human diversity is appealing, according to Fritz Sedlazeck, an associate professor at Baylor College of Medicine, who was part of the Telomere-to-Telomere Consortium that recently generated a continuous haploid human genome sequence, T2T-CHM13. He adds that a diverse pangenome reference could uncover genomic regions or even genes that are not represented in GRCh38.

So far, the Human Pangenome Reference Consortium has generated a draft reference of 94 de novo haplotype assemblies from 47 individuals. As the researchers reported in a preprint in BioRxiv in July, they generated these assemblies using a combination of Pacific Biosciences high-fidelity and Oxford Nanopore long-read sequencing, Bionano Genomics optical maps, and high-coverage Hi-C Illumina short-read sequencing. These assemblies, they reported, cover more than 99 percent of the expected sequence and are more than 99 percent accurate at the structural and base-pair levels.

But the 47 individuals represented in this draft human pangenome reference all hail from the 1,000 Genomes Project.

By first focusing on individuals from that project which represents 26 global populations the consortium aimed to both improve their sequencing and assembly approaches and enrich the genetic diversity represented by the reference, said Eimear Kenny, a professor at the Icahn School of Medicine at Mount Sinai and a consortium member.

"A lot of work was happening on not only assessing [and] comparing technology and figuring out how different technologies could be knit together for a better representation of a genome, but also how that [technology] moves through pipelines in a production way that meets standards of quality," she added.

This work was enabled by the 1,000 Genomes Project individuals, who had provided consent allowing open access to their genomes. The researchers also had access to their parental genomes, which helped for phasing the assemblies.

Going forward, the consortium plans on bringing in sequencing data from other biobanks, as well as from additional populations and participants. For instance, the researchers have been contacting individuals from the Icahn School of Medicine at Mount Sinai's BioMe BioBank program about participating in the pangenome effort. BioMe participants, Kenny noted, are unselected from the Mount Sinai health system and reflect the diversity of New York City.

At the same time, the consortium is also partnering with other researchers and reaching out to populations around the world to participate. "We really, really, really want this to be a reference for all humanity. We want this to be representative, as far as possible, of as much of the population as we can," Paten said.

But the field is not always trusted by underrepresented groups. "We also recognize that genetics doesn't have a great history [with respect] to marginalized populations," he noted.

To address those issues, the consortium has an ethical, legal, and social implications working group embedded. During the first phase of the pangenome project, that group has been reaching out to other consortia and partners for ideas on the best frameworks for recruiting participants and the best models for consent. As the project is asking participants to openly share their data, Paten said, the consent needs to be ethical and respect participants.

"What we're trying to do in phase one is assess the types of models that are out there," Kenny said. "In phase two, we really want to have a principled way to generate evidence for what works [and] what doesn't work."

She noted, though, that some groups may opt not to participate, or to participate on their own terms.

Meanwhile, with the 1,000 Genomes Project participant data, the researchers tested different graph assembly approaches to present their draft pangenome reference. Paten pointed out that despite the millions of variations they contain, human genomes are actually quite similar, and a graph approach is a way of describing the relationships between them.

The group used three different graph assembly approaches: Minigraph, Minigraph-Cactus, and the Pangenome Graph Builder. Each of these has different nuances to them, Sedlazeck noted, with one being comprehensive, the other focusing on SNVs, and the third on structural variants in pangenomes.

"Structural variants are rather complex and often hard to identify," Sedlazeck said. "Encompassing this kind of ethnicity-unique or just unique regions is really helping us to understand the diversity of these regions that are not represented in GCh38."

For instance, the pangenome researchers were able to annotate and visualize the structure of five multiallelic CNV loci including the variable HLA-A region. Further, around HLA-A, they noted two previously reported deletion alleles but also homed in on a previously unreported insertion allele carrying an HLA-Y pseudogene. This insertion, they noted, occurred at high frequency, 28 percent, but was not seen in GRCh38.

"If it's not represented in GRCh38, obviously this hinders the research on this," Sedlazeck noted.

The consortium also mapped the annotated gene list from GRCh38 to the pangenome assemblies to find that all the genes contained in GRCh38 are also well represented there. Sedlazeck said, though, that it would have also been interesting to know what new genes or isoforms are in the assemblies, for example in large insertions.

Paten added that there is ongoing work to fill in the gaps in the assemblies with an eye toward generating telomere-to-telomere assemblies, as well as to improve the alignments and tools. Still, he noted there is already plenty of interesting genome biology to explore in the current assemblies.

"This is such a foundational resource for the entire field," Kenny added, noting that there are likely many unanticipated benefits from having a modern and diverse pangenome.

See the article here:
Draft Human Pangenome Reference Shows the Way to Capturing More Human Diversity - GenomeWeb

image:Wingless expression (red) in regenerating (left), developing (center) and tumorigenic (right) wing primordia of Drosophila. view more

Credit: IRB Barcelona

Barcelona, 22 August, 2021 The first mutation of the wingless gene was found by accident in Drosophila in the 1970s, following the observation of flies that did not possess wings, hence its name. Fifteen years after its discovery, the gene was found to be conserved in mammals, an event that gave rise to foundation of the wnt gene family. Mutations in wnt genes lead to various types of cancer.

The wnt gene family, including its founding member, the wingless gene, regulates several processes during the embryonic development of both insects and mammals. However, if this is true, then why did the first mutation of the wingless gene discovered only affect the wings of Drosophila flies? This was the question put forward by the IRB Barcelona Development and Growth Control lab.

Using gene editing techniques, such as CRISPR/Cas9, the researchers discovered an evolutionarily-conserved genomic region that regulates the expression of the Wingless protein only during the formation of the wing. Using functional assays, the scientists discovered that this regulatory region not only acts to exclusively promote wing formation but it also regenerates the wings when damaged.

Ensuring wing formation in different ways

The researchers showed that this regulatory region is exclusively involved in the regulation of Wingless expression during the formation of the wing. Their functional assays also discovered the presence of two highly redundant modules in this regulatory region that are activated by independent signalling pathways.

"What we have discovered in this study is a highly robust genetic regulation mechanism that ensures proper wing development, and this mechanism is consistent with the crucial importance that these structures have for insects in general", stated Dr. Marco Milan, an ICREA researcher and the Head of the Development and Growth Control Laboratory, who led this study. "Wing development was an enormous evolutionary advantage for insects and it is what permitted their expansion and diversification," Dr. Miln added.

Regeneration and tumours

When organ damage occurs, the injured cells send signals to their surrounding cells so that these then divide in order to restore the organ. The authors of this investigation have shown that Wingless is also the molecule responsible for signalling healthy cells to divide and regenerate tissue, and that the regulatory region involved in wing formation is also activated in situations of damage in order to induce the expression of Wingless.

The research team demonstrated in functional assays that the JNK stress signalling pathway acts in a redundant manner on the two existing modules. "Once again, a very robust genetic regulatory mechanism ensures not only the correct development of the wing but also its ability to regenerate", stated Elena Gracia-Latorre and Lidia Prez, the initial research authors.

As a final note, the researchers performed experiments in which they blocked the damaged-cell removal process, to find that the Wingless regulatory zone remained continually activated. Due to the constant presence of Wingless, the cells proliferated uncontrollably, and this eventually gave rise to the formation of tumorous and malignant growths. "This allows us to propose that regeneration and tumour development are two sides of the same coin: if Wingless is induced for a short period of time, it forms the wing normally or allows it to regenerate, but if it is maintained chronically, then it causes overgrowth and a tumour, concludes Dr. Milan.

Nature Communications

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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A genomic region that is exclusively dedicated to the formation and regeneration of a single organ - EurekAlert

CRISPR is a family of DNA sequences found in the genomes of prokaryotic organisms such as bacteria and archaea. These sequences are derived from DNA fragments of viruses called bacteriophages that had previously infected the prokaryote. They are used to detect and destroy DNA from similar bacteriophages during subsequent infections, providing the prokaryote with a sort of immunity.

The following is an interview with CRISPR co-discoverer and Nobel Prize-winner Dr. Jennifer Doudna.

Describe the eureka moment around CRISPR the moment when you realized that this technology was not only possible but actually worked. How did you feel? Has your feeling changed since that eureka moment? If so, how?

Theres one moment that stands out in my mind, right at the time we realized what CRISPR could do and that we could reprogram it to edit specific sequences of DNA. I was cooking dinner and thinking about it, and I burst out laughing. My son was in the kitchen and he asked why I was laughing. So I explained it to him with a little drawing of a car zooming around, grabbing onto viruses, and chopping them up. I think my drawing did the trick, because he started laughing too.

The implications of this finding were too big to understand all at once. Its been ten years since that time now, and everything that has happened since surpassed any expectations I had back then. With multiple therapies in clinical trials, plants in fields that help farmers adapt to a changing climate, and countless uses of CRISPR in life science research, the scope of what has been achieved in just ten years continues to surprise me.

What excites and inspires you most about the possibilities of CRISPR technologies?

I recently spoke with Victoria Gray, one of the first people to receive a CRISPR-based therapy for sickle cell disease. Hearing from her about how her life has changed for the better, how shes no longer in constant pain and able to go back to work and spend more time with her family theres nothing more inspiring than real human impact. Thats what drives the work we do at the institute that I started at UC-Berkeley, the Innovative Genomics Institute (IGI), where the focus is not just developing new therapies and agricultural products, but making sure they reach the people who need them most.

Subscribe for a weekly email with ideas that inspire a life well-lived.

What is the most interesting, or counterintuitive, use of CRISPR technology that youve encountered thus far?

We talk a lot about the ability of CRISPR to cut DNA, but its ability to find a specific sequence of DNA is just as interesting. Thats not an easy thing to do, and it turns out that it can be really useful in other ways. For example, at the IGI, were developing CRISPR-based diagnostics for infectious disease. Instead of editing DNA, these tests quickly find a specific sequence of DNA from a pathogen, like the SARS-CoV-2 virus or HIV, and then release a fluorescent marker. The great thing about these tests is that theyre fast, can be performed anywhere, and should be quite cheap to produce. After everything weve all experienced during the pandemic, its clear that rapid point-of-need tests are going to be increasingly important.

Are there any parallels in history of a technology that fundamentally changed human life?

In many ways CRISPR genome editing builds on groundbreaking technologies and innovations that came before it, and each one was a watershed moment for science. We needed X-ray crystallography to understand the structure of DNA, Sanger sequencing to be able to read it, PCR to make copies of it, and the Human Genome Project and other large bioinformatics projects to start to understand the bigger picture of how genomes function. Being able to edit the genome is the next chapter in this story, but it couldnt exist without the others that came before it.

How can we most responsibly use the power this technology has unlocked? Where should we put the guardrails?

With any powerful technology, there is always potential for its misuse. And we have already seen this, even though the vast majority of scientists are using it responsibly. Determining what constitutes misuse, what is unethical, what is medically necessary that is where a lot of the discussion is focused at the moment. There is broad agreement on certain topics, particularly around human germline editing, but when it comes to questions of ethics, there will always be gray areas.

One risk that is often overlooked is the real possibility that some of the advances we make in genome editing will benefit a small fraction of society. With new technologies this is often the case at first, so we have to consciously work from the start to make new cures and agricultural tools that are accessible and affordable.

In your mind, what does it mean for humanity to have the ability to directly alter genetic material so precisely?

Its a powerful tool, and one that can be used to do a lot of good. Sickle cell disease affects millions of people worldwide, and its caused by a single-letter mutation in just one gene. This has been understood for a long time, but we didnt have the means to fix that mutation. There are several thousand other genetic diseases, including very rare diseases that are often neglected, that we can now look to address. It goes beyond medicine: Climate change is impacting agriculture, and agriculture itself is contributing to climate change. With genome editing, we can mitigate both of those impacts.

How do you think CRISPR will affect our understanding and definition of what it means to be human?

Understanding even just a little bit about genetic disorders what causes them, how many people are affected by them increases your compassion for what people are going through of no fault of their own. You also start to understand that there are people who have genetic mutations that affect their lives, but dont necessarily view them as diseases or problems to fix. CRISPR itself may not change what it means to be human, but perhaps having a tool that can rewrite our DNA helps to shine a light on all of the diversity that humanity already encompasses.

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10 years on, a spin-off use for CRISPR: Infectious disease testing - Big Think

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Evolution of longitudinal division in multicellular bacteria of the Neisseriaceae family - Nature.com

Published 13 hours ago

Submitted by Illumina

Originally published on Illumina News Center

SAN DIEGO, August 22, 2022/CSRwire/ -- Illumina, Inc. (NASDAQ: ILMN), a global leader in DNA sequencing and array-based technologies, announced that on September 30, its Illumina Genomics Forum (IGF) will feature Bill Gates, co-chair of the Bill & Melinda Gates Foundation, who will deliver a keynote address on the remarkable potential of genomics to change the trajectory of global health. In addition, IGF will host a panel session titled "Making 'Genomics for All' More than a Mantra," on the requirements needed to ensure broader access to genomic health.

"Genomics should be available to the many, not the few, and even though the genomic health era has already led to breakthrough discoveries that are advancing medical care, the benefits have not yet had a true globalimpact," said Kathryne Reeves, chief marketing officer for Illumina. "Through sessions led by Bill Gates and expert panelists, Illumina Genomics Forum will help attendees see and understand the path toward global health equity."

The "Genomics for All" panel includes representatives driving increased access to genomic health, including:

Illumina previously announced that former U.S. President Barack Obama will headline the inaugural forum in a fireside chat on the evening of Wednesday, September 28. Twelve years after the passage of the Affordable Care Act, Obama will discuss the continued need for equity, accessibility, and smarter healthcare to improve the human condition. Additional speakers, panels, and details about the event agenda will continue to be released in the coming weeks.

Other IGF key themes include:

IGF will take place in San Diego from September 28 through October 1. For more information and to register for the conference, go to illuminagenomicsforum.com.

About Illumina

Illumina is improving human health by unlocking the power of the genome. Our focus on innovation has established us as a global leader in DNA sequencing and array-based technologies, serving customers in the research, clinical and applied markets. Our products are used for applications in the life sciences, oncology, reproductive health, agriculture and other emerging segments. To learn more, visit illumina.com and connect with us on Twitter, Facebook, LinkedIn, Instagram, and YouTube.

Investors:Salli Schwartz858-291-6421IR@illumina.com

Media:Adi RavalUS: 202-629-8172PR@illumina.com

SOURCE Illumina, Inc.

Illumina is improving human health by unlocking the power of the genome. Our focus on innovation has established us as the global leader in DNA sequencing and array-based technologies, serving customers in the research, clinical, and applied markets. Our products are used for applications in the life sciences, oncology, reproductive health, agriculture, and other emerging segments.

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RNA-seq read mapping in wheat and Pst reflects the susceptibility of the interaction

We selected three bread wheat varieties (Oakley, Solstice and Santiago) previously demonstrated to display different susceptibility levels to our two selected Pst isolates (F22 and 13/14)14. We quantified visible phenotypes of pathogen infection and infection types (ITs) at 12 days post-inoculation (dpi) following the 04 scale16 (Supplementary TableS1). Oakley was fully susceptible to both Pst isolates, while Solstice was moderately susceptible to Pst isolate F22 and almost fully susceptible to Pst isolate 13/14; Santiago was resistant to Pst isolate F22 and showed moderate resistance to Pst isolate 13/14. These results confirmed the range of susceptibility/resistance exhibited by the selected wheat varieties for this study. We infected each of the three wheat varieties with each of the two Pst isolates individually (Fig.1a) and collected samples at 1, 3, 7 and 11 dpi for RNA-seq analysis, alongside mock-inoculated samples from each variety collected at 12h post-inoculation (hpi). Following quality filtering, we aligned clean reads from each of the 81 generated samples to the wheat reference genome (Refseq v1.1)17 and Pst reference genome (isolate Pst-104E18).

a Diagram of the stages of Pst development during plant infection. The time points selected for RNA-seq analyses (1, 3, 7 and 11 days post-inoculation [dpi]) are highlighted. S uredinospore, SV substomatal vesicle, IH invasive hyphae, HM haustorial mother cell, H haustorium, P pustule, G guard cell. Inspired by a schematic illustration from61. b Percentage of reads mapping to the wheat or Pst reference genomes across wheat varieties and pathogen isolates. Following quality filtering, RNA-seq reads were mapped to the Pst reference genome (isolate Pst-104E18) and wheat reference genome Refseq v1.117. Values represent an average of three independent biological replicates (independent infected plants) for each Pstvariety pair. c Principal component analysis (PCA) of wheat gene expression profiles shows that samples from all Pstvariety pairs cluster into two well-defined groups: 1) 1 dpi; and 2) all remaining time points. d Independent PCA on 1 dpi samples only (left) or remaining time points (right) illustrating the clustering of 1 dpi samples by host variety, for infection by Pst isolate F22. e Differentially expressed genes (DEGs) are more numerous at 1 dpi, with samples infected with Pst isolate 13/14 showing more isolate-specific DEGs than those infected with Pst isolate F22. The number of DEGs was defined at each time point by comparing normalised transcript abundance for each Pst-wheat interaction against the corresponding mock-inoculated control using a negative binomial regression (Wald test) in DESeq2. Genes were considered differentially expressed when q-value<0.05.

We detected similar proportions of reads mapping to the wheat and Pst reference genomes across samples collected at 1 and 3 dpi (average of 85.51.5% for wheat and<1% for Pst, Fig.1b). By 7 dpi, the percentage of reads mapping to the wheat and Pst genomes varied and reflected the degree of susceptibility between the respective varietypathogen pairs. We observed the largest differences between varieties at 11 dpi upon infection with Pst isolate F22. Indeed, while we obtained an average of 45.724.0% reads mapping to wheat and 18.711.5% to Pst for the most susceptible interaction (Pst isolate F22Oakley), the fraction of reads mapping to Pst decreased with higher host resistance. The moderately susceptible interaction (Pst isolate F22Solstice) returned 73.620% of reads mapping to wheat and 5.768.02% to Pst, compared to 87.00.92% of reads mapping to the wheat genome and 0.050.02% to Pst in the context of the most resistant interaction (Pst isolate F22Santiago). Notably, the percentages of reads mapping to the wheat genome were comparable for the SantiagoPst isolate F22 pair between early and later time points, as well as with mock-inoculated samples (87.31.8%), in agreement with the high resistance of the host to the pathogen (Fig.1b). By contrast, infection of all three varieties with Pst isolate 13/14 resulted in similar percentages of reads mapping to each reference genome (host and pathogen) at 7 and 11 dpi, although samples collected from the highly susceptible variety Solstice showed the largest percentage of reads mapping to Pst at 11 dpi relative to the other two varieties (Fig.1b). This analysis illustrates that the percentage of reads mapping to the wheat and Pst genomes at later time points reflect the degree of susceptibility of each Pstvariety interaction.

To assess the host response to Pst infection under different levels of susceptibility, we determined wheat transcript abundances at each time point for each Pstvariety interaction. We normalised our data to account for library size and samples with low read counts before conducting a principal component analysis (PCA). We generated scatterplots of the first two principal components for each Pst isolate, which identified two well-defined groups across all Pst-infected samples: (1) samples collected at 1 dpi and (2) samples collected at all remaining time points (Fig.1c). As samples collected at 1 dpi clustered separately from all others and might obscure later transcriptome patterns, we repeated the PCA by separating the 1 dpi samples from the others (Fig.1d and Supplementary Fig.S1). The scatterplot of the first two principal components for all 1 dpi samples demonstrated a clear separation by Pst isolate and wheat variety. We also noticed that separation between wheat varieties tends to follow their genetic relatedness, with Santiago grouping closely with its parent variety Oakley, whereas the unrelated Solstice variety clustered separately (Fig.1d and Supplementary Fig.S1). Analyses of the remaining time points showed a similar distribution for both Pst isolates, with mock-inoculated control samples clustering together and away from the remaining time points (3, 7 and 11 dpi). These results suggest that host transcript abundance is largely similar at 3 dpi onward irrespective of the Pst isolate or the level of susceptibility of the wheat variety used for infection.

We identified differentially expressed genes (DEGs) at the different time points by comparing normalised transcript abundance for each Pstvariety interaction against their respective mock-inoculated controls. Overall, we observed substantial overlap between DEGs from different Pstvariety pairs, ranging from 68.713.0% (standard deviation) to 59.514.2% shared between Pst F22- and Pst 13/14-infected samples. In agreement with the PCA, we detected far more DEGs at 1 dpi (q-value<0.05), with an average number of 27,9735453 DEGs across all Pstvariety interactions (Fig.1e), compared to 91251193 at 3 dpi, 13,3573305 at 7 dpi, and 13,9285222 at 11 dpi. Looking at Pst isolate-specific transcriptional responses, we determined that all wheat varieties exhibit more DEGs specific for Pst 13/14 infection than with Pst F22 (Fig.1e and Supplementary Data1 and 2). This pattern was particularly evident at 1 dpi, with 30,7331886 DEGs across the three varieties infected with Pst 13/14, of which 10,0355825 were unique to Pst 13/14. Conversely, across the three varieties infected with Pst F22 a total of 25,2136923 DEGs were identified, of which 4516 (range 9339987) were specific to Pst F22 at 1 dpi. Notably, 96.6% of all DEGs at 1 dpi in Santiago plants infected with Pst F22 were also differentially expressed in Santiago infected with Pst 13/14, despite the difference in susceptibility (resistance for Pst F22, moderately resistant for Pst 13/14).

To identify biological processes associated with variety-specific expression profiles in response to Pst infection, we generated functional enrichment networks for each Pstvariety pair (Fig.2a and Supplementary Figs.S2 and S3). Accordingly, we assigned gene ontology (GO) terms to all DEGs where possible and identified those significantly enriched in each condition (q-value>0.0005). We detected enrichment for second-level GO terms across all conditions and time points that reflected general responses to Pst infection and included GO:0009536 (plastid), GO:0009507 (chloroplast) and GO:0003824 (catalytic activity) (Fig.2a and Figs.S2 and S3). Focusing on DEGs at 1 dpi, all Pstvariety pairs showed enrichment in functions related to response to biotic stimulus, chloroplast and photosynthesis, metal binding (ironsulfur cluster binding), cell redox homoeostasis and cell metabolism, including transferase activity, hydrolase activity and phosphatase activity (Fig.2a). Looking across all wheat varieties, we identified 1494 DEGs specifically in response to infection with Pst F22 and another 8627 DEGs specific to inoculation with Pst 13/14 (Fig.2b). Functional annotation of each set of DEGs highlighted functions related to protein transport and protein localisation for those specific to Pst F22 infection (Fig. S4), while those specific to Pst 13/14 infection were related to part of the chloroplast, the chloroplast membrane and photosystems (Fig.2c).

a Functional enrichment network for each Pstvariety pair identified in samples taken at 1 dpi. Gene ontology (GO) terms were assigned to all DEGs where possible and those identified as significantly enriched (q-value<0.0005) in at least one Pst-varietal pair are represented by a node, with node sizes proportional to the number of genes annotated with the GO term. Edges indicate overlapping member genes and conservation of GO term enrichment is highlighted by node border colour. Highly similar gene sets formed clusters, which were annotated and labelled with appropriate summarising terms. b Venn diagram illustrating the extent of overlap between the number of DEGs conserved for the three wheat varieties at 1 dpi upon inoculation with Pst isolate 13/14 or Pst isolate F22. c Functional GO term enrichment analysis results for the 8627 Pst 13/14-specific DEGs. GO terms were annotated when Log(q-value)>20 (first panel) or Log(q-value)>15 (second panel). Circle size represents the number of genes annotated within the particular enriched function; circle colour represents the GO term classification: molecular function (MF, blue), biological process (BP, pink) and cellular component (CC, green).

We hypothesised that the greater number of DEGs shared across wheat varieties infected with Pst 13/14 reflects either the more homogeneous susceptible phenotypes or the stronger transcriptional reprogramming induced by this isolate. To explore this question in more detail, we built co-expression clusters for each Pstvariety pair by using the 8,627 DEGs identified at 1 dpi (Figs. S5S10). We classified the clusters into two classes based on expression profiles: (1) early upregulated clusters whose constituent genes were highly expressed at 1 dpi but returned to mock-inoculated levels by 3 dpi and (2) early downregulated clusters whose genes were expressed at lower levels than the controls at 1 dpi but returned to mock-inoculated levels by 3 dpi. For example, during the fully susceptible interaction between Santiago and Pst 13/14, we classified 2127 genes across two co-expression clusters as early upregulated and 2318 genes from two co-expression clusters as early downregulated. Using the same method in the context of the resistant interaction between Santiago and Pst F22, we identified 1826 genes across three co-expression clusters as early upregulated and 2069 genes from one co-expression cluster as early downregulated (Fig.3a).

a Example of co-expression clusters classified as containing early upregulated (red) or early downregulated (blue) genes following infection of Santiago with Pst isolates 13/14 and F22. Co-expression clusters were generated using the 8627 Pst 13/14-specific DEGs. The coloured line represents the average normalised expression of all genes in a given co-expression cluster. b, c GO terms for functionally enriched biological processes across the co-expression clusters from 8627 Pst 13/14-specific DEGs, assessed for each Pstvariety pair, and classified as early upregulated (b) or early downregulated (c) genes. Significant Log(q-value) values are represented using a 0100 scale and GO terms with Log(q-value)>5 are shown.

GO term enrichment analysis indicated that early upregulated DEGs are associated with a diverse array of cellular processes (Figs.3b and S11). All co-expression clusters for each of the three varieties infected with Pst 13/14 contained genes mainly involved in the myosin complex and peroxisomes. The resistant interaction (Pst isolate F22Santiago) was the only one associated with the NatA acetyltransferase complex, which also contained genes involved in protein deubiquitination. In terms of biological processes, early upregulated genes in the context of resistant and moderately susceptible interactions included mRNA metabolism and protein modification by small protein conjugation or removal. Susceptible interactions comprised genes involved in organelle organisation, protein transport, RNA processing, protein modification and pyridine nucleotide salvage. By contrast, we observed shared functions across all conditions for genes classified as early downregulated (Figs.3c and S12). In terms of cellular components, these co-expression clusters included genes annotated as part of the chloroplast. In agreement with this observation, photosynthesis was the main biological process enriched in all clusters, with other enriched processes such as organonitrogen compound biosynthesis, peptide metabolism and translation. Notably, the specific early downregulated genes associated with the chloroplast and involved in photosynthesis differed between each Pstvariety pair.

Among the DEGs at 1 dpi, we observed an enrichment for functions associated with defence-related responses. We selected genes participating in programmed cell death (48 genes), response to salicylic acid (SA; 59 genes), the innate immune response (179 genes), defence response to fungi (151 genes) and those predicted to encode nucleotide-binding site leucine-rich repeat (NLR)-type R proteins (9078 genes) for further analysis. We normalised their expression and determined the median value (Fig.4a, b). Most varieties exhibited a consistent upregulation of transcript levels across all categories at 1 dpi, followed by a drop in expression at 3 dpi and a later increase at 7 and 11 dpi. Importantly, the expression of genes belonging to all four defence-related response processes reaches a higher peak at later stages of infection (711 dpi) in the resistant interaction (Pst isolate F22Santiago) relative to its susceptible counterpart (Pst isolate 13/14Santiago) (Fig.4a). Turning to genes annotated as encoding potential NLRs, we detected most DEGs from this class at 1 dpi. At this time point, we identified the greatest numbers of NLR DEGs for Oakley infected with Pst 13/14 (most susceptible interaction), followed by Solstice infected with Pst 13/14 (fully susceptible) and Pst F22 (moderate susceptibility). The lowest numbers of NLR DEGs were for Santiago infected with Pst F22 (resistant interaction) and Oakley infected with Pst F22 (fully susceptible) (Fig.4b). However, we noted that at 1 dpi in Oakley infected with Pst F22, many genes involved in defence-related responses lacked the expression peak seen in other Pstvariety pairs, likely due to the peak occurring outside of the sampling timepoint in this case. Overall, our results suggest that the outcome of the hostpathogen interaction may be decided early during initial fungal colonisation.

a Median expression of normalised transcripts per million (tpm) values obtained for genes annotated as being involved in response to salicylic acid (GO:0009751), defence response to fungus (GO:0050832), innate immune response (GO:0045087) and cell death (GO:0012501). The peak in gene expression at later stages of infection (711 dpi) is more pronounced in resistant interactions (Pst isolate F22Santiago) when compared to its susceptible counterpart (Pst isolate 13/14Santiago). b The number of DEGs encoding proteins with typical NLR domains is greatest at 1 dpi, with the most DEGs at this time point identified in samples from Oakley infected with Pst 13/14 (most susceptible interaction). Typical NLR domains were defined as IPR001611:Leu-rich_rpt, IPR032675:LRR_dom_sf, IPR002182:NB-ARC, IPR027417:P-loop_NTPase. Genes were considered differentially expressed compared to the control when q-value<0.05.

Among the early downregulated genes, we noticed the presence of many genes encoding proteins with GO terms associated with the chloroplast (Fig.3c). We identified components of photosystem I (Psah2) and II (PsbQ proteins and PsbO2), enzymes from the CalvinBensonBassham cycle (pyruvate kinase [PRK], Ribose-5-phosphate isomerase [RPI], Rubisco, Fructose-bisphosphate aldolase [FBA1]), chloroplast calcium signalling components (CAS), proteins involved in chloroplast RNA metabolism (CSP41a and CSP41b) and isochorismate synthase 1 (ICS1) that synthesises SA in the chloroplasts from chorismic acid (Fig.5a). In each case, their gene expression was downregulated at 1 dpi, followed by a sharp peak in expression at 3 dpi and a second rapid decline by 7 dpi. The most resistant interaction (Pst isolate F22Santiago) was the notable sole exception across Pstvariety pairs, as the expression of many of these genes, failed to decline or declined to a lesser extent after 3 dpi than with more susceptible interactions (Supplementary Fig.S13).

a Schematic illustration of the chloroplast. The genes encoding the proteins marked with a star were identified as differentially expressed at 1 dpi across wheat varieties upon infection with Pst isolate 13/14. b Many genes are annotated with chloroplast-related functions among the 8627 Pst 13/14-specific DEGs, as 1038 DEGs belong to eight second-level GO terms with chloroplast-related functions. c Chloroplast-related DEGs show a conserved, temporally regulated expression profile during Pst infection. Normalised transcripts per million (tpm) values were used to determine the median expression levels for genes assigned to each of the eight chloroplast-related GO terms.

We explored the expression patterns of these nuclear genes encoding chloroplast-localised proteins (NGCPs) during a susceptible Pst-wheat interaction by re-examining the enriched GO terms among the 8627 Pst 13/14-specific DEGs. We obtained 1038 DEGs that belong to eight second-level GO terms with chloroplast-related functions. For each of the eight categories, we determined the genome-wide number of genes associated with each GO term, which illustrated the high proportion of chloroplast-related genes among the 8627 DEGs (26.685.7% for each GO term) (Fig.5b and Supplementary Data3). In addition, all chloroplast-related genes followed the same pattern of expression observed above, with a sharp increase in expression at 3 dpi, followed by a rapid decline by 7 dpi, except in the highly resistant interaction (Pst isolate F22Santiago; Fig.5c). This conserved gene expression profile likely reflects a well-coordinated transcriptional modulation of genes encoding chloroplast-targeted proteins upon pathogen recognition.

We selected the putative chloroplast-localised stem-loop RNA binding protein TaCSP41a among NGCPs for detailed analyses. TaCSP41a was selected due to the availability of tetraploid Kronos TILLING mutants and as CSP41 abundance has previously been linked to abiotic stress in Arabidopsis and tomato (Solanum lycopersicum)19,20. To investigate the expression pattern of CSP41 in more detail in response to biotic stress, we performed an RT-qPCR analysis of TaCSP41a transcript levels at 12 hpi, 2, 5, 9 and 11 dpi following infection of the wheat varieties Oakley, Santiago and Solstice with Pst F22. We designed primers to amplify all three TaCSP41a homoeologues simultaneously and compared expression levels between infected and mock-inoculated plants (Fig.6a). TaCSP41a was substantially more highly expressed at 12 hpi in the highly susceptible variety Oakley and expressed significantly lower levels in the highly resistant variety Santiago upon infection (Fig.6a). In all susceptible interactions, TaCSP41a was initially more highly expressed before decreasing substantially, reaching its lowest levels by 5 dpi for infected Oakley and 2 dpi for infected Solstice. These observations confirmed a link between TaCSP41a expression early during infection and the extent of susceptibility to Pst infection as shown in the RNA-seq analyses.

a TaCSP41a expression during a controlled infection time course of the wheat varieties Oakley, Solstice and Santiago with Pst isolate F22. Relative TaCSP41a expression was measured by RT-qPCR from all three homoeologous copies simultaneously and compared to mock-inoculated control plants, with the UBC4 gene used as a reference53. Two independent leaves from the same plant were pooled and three independent plants were analysed for TaCSP41a expression at each time point. Asterisks denote statistically significant differences (***p<0.005, **p<0.01, *p<0.05; 2-tailed t-test). b TaCSP41a-A co-localises with chlorophyll autofluorescence. TaCSP41a-A-GFP was transiently expressed in N. benthamiana and images were captured after 2 days. Images are representative of >10 images captured, all displaying co-localisation of TaCSP41a-A-GFP and chlorophyll autofluorescence. Left, individual TaCSP41a-A-GFP (top) and chlorophyll autofluorescence (bottom) patterns; right, merged image of TaCSP41a-A-GFP and chlorophyll autofluorescence illustrating co-localisation. Scale bars, 10m.

To test the subcellular location of TaCSP41a, we scanned the predicted protein sequence of the three homoeologues TaCSP41a-A, TaCSP41a-B, TaCSP41a-D for potential targeting signals. We detected a chloroplast targeting peptide with a high probability (>99%) in all three homoeologues (Supplementary TableS2). Encouraged by this result, we generated a fusion construct by cloning the TaCSP41a-A coding sequence in-frame and upstream of that of the green fluorescent protein (GFP) and transiently infiltrated the resulting TaCSP41a-A-GFP construct in Nicotiana benthamiana leaves. We observed GFP fluorescence in foci that co-localise with chlorophyll autofluorescence, as determined by confocal microscopy, supporting the notion that TaCSP41a is a chloroplast-resident protein (Fig.6b).

To assess the contribution of TaCSP41a to Pst-induced disease progression, we looked for tetraploid Kronos TILLING mutants21. We identified two mutant lines (Kronos3238 and Kronos3239) introducing early stop codons in the TaCSP41a-A sequence at amino acids 218 and 174 (Supplementary Fig.S14). We obtained homozygous TILLING mutant lines by self-pollination. We infected F2 homozygous progeny (TaCSP41a-AF218* and TaCSP41a-AQ174*) with Pst 13/14 and compared their disease phenotypes to the wild type (WT, cv. Kronos) and a Kronos3238 sibling carrying the wild-type allele at TaCSP41a-A (Fig.7a). Both mutant lines displayed limited sporulation and higher Pst resistance at 20 dpi, with a substantial reduction in the extent of leaf area infected by Pst, compared to both the Kronos WT and the wild-type Kronos3238 sibling (Fig.7b). Leaves of the TaCSP41a-AF218* and TaCSP41a-AQ174* mutant lines remained largely green outside of a few necrotic spots consistent with localised programmed cell death. By contrast, both WT lines were uniformly chlorotic, with low or no necrotic lesions (Fig.7a). The TaCSP41a-AQ174* mutant line displayed a stronger phenotype, with no chlorosis and only small necrotic regions in all plants tested. Together, these results demonstrate that disrupting TaCSP41a-A function promotes tolerance to Pst 13/14, indicating a role for TaCSP41a in supporting Pst disease progression.

a TaCSP41a-AF218* and TaCSP41a-AQ174* disruption mutants are more resistant to infection by Pst isolate 13/14 compared to the Kronos wild type (WT) or the Kronos ethyl methanesulfonate (EMS) mutant Kronos3238 carrying a WT allele at TaCSP41a. Images were captured at 20 dpi. b Lower rates of leaf infection in the TaCSP41a-A disruption mutants at 20 dpi, represented as box and whiskers plots. Lowercase letters denote statistically significant differences by Duncans multi-range test (p<0.05). Horizontal bars, median values; boxes, upper (Q3) and lower (Q1) quartiles; whiskers, 1.5the inter-quartile range.

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Temporally coordinated expression of nuclear genes encoding chloroplast proteins in wheat promotes Puccinia striiformis f. sp. tritici infection |...