Category Archives: Genome

79.99, two-notes.com

Two Notes has recently brought its hardware amp sim more in line with the rest of the pedal world its recent Opus was a much more direct competitor to things like the Iridium and UAFX amp pedals than the previous C.A.B. products and , of course, the logical extension of this is a dedicated full-signal chain VST plugin in the vein of IK Multimedias ToneX, or Neural DSPs suites. Enter, then, Genome.

Genome is a VST plugin that offers pedal, amps, cabinets and studio effects with a wide (and expandable) library of virtual gear to run your guitar through. It has just recently been updated to version 1.2, after 1.0 was officially released earlier this year (a beta was unveiled at NAMM 2022). Theres no standalone app, so youll need a DAW to host it in, but there are free options for this on every platform and realistically, if youre considering Genome, youre already making music within your DAW of choice.

Genomes UI is fairly self-explanatory, and if youve used basically any other guitar plugin before, youll get your head around whats going on pretty quickly. At the very top youve got some basic input/output monitoring and level control, and buttons for the tuner and noise gate. Above the view of whatever virtual gear youre focusing on, theres a left-to-right signal chain of 10 blocks.

Interacting with this UI is intuitive: blocks can be reordered by dragging them around, and switched out with a drop-down menu, and the virtual gears virtual controls are all clearly laid out and easily adjustable. You can split the signal chain into two parallel chains and then choose where it merges, and also pan and mix the two streams. Its very easy to get your head around, and it all happens quickly and responsively.

Using Genome I never feel lost at all not even in the preset loading menu, which lets you select from a veritable shedload of premade signal chains or save your own. Automation is relatively simple too, with controls easily assignable to various parameters.

The tuner and gate are both perfectly functional, behaving exactly as youd expect. However right now theres no pre-chain pitch-shifter that can be a handy feature for changing tunings on the fly, so its absence here is a little bit of a shame. In fact, across the entire effects range, theres nothing of any pitch variety at all (for now future updates may change this). But hows everything else?

The default starting preset is, as seems to be tradition, a super-clean Fender-inspired amp with a little compression and reverb on the end. Not the most exciting sound on the planet. However, like ordering a margherita to gauge the quality of a pizza place, the execution of the brass-tacks basics can be very telling.

Here, I find the Fendery clean thing very well-executed indeed theres a liveliness that indicates some attention to detail has been paid to what makes a clean tone not totally boring to play. Two Notes has past experience with this particular sound: its long-time flagship hardware cab sim unit, the C.A.B. M+ unit came loaded with just a single Fender-inspired preamp model, so its success here is unsurprising.

The clean tone would go great with a spring reverb, but if you do want a portion of that surf-flavoured dipping sauce, the two available spring emulations are part of the paid extra side of Genome. Its $20 for the basic spring emulation, $50 for the more complex one. Though its worth noting that compared to other similar guitar plugins, Genome is fairly affordable off the bat and so while some paid extras in the form of some of the cabinets, amps and effects might initially seem like a sting in the tail, it allows the plugin to function as a more affordable bare-bones platform, with a more focused approach to expandability.

In some ways this makes it more enticing than a pricey yet complete sandbox of infinite options with the base option being cheaper, youre likely saving money as long as you know what you want to expand out into. To help in this regard, paid-for effects can be demoed within the software.

Moving onto some higher-gain sounds, things remain realistic-sounding and familiar-feeling. Virtual fuzz and overdrive pedals interact with virtual tube amps as you would expect their real counterparts to do a RAT before an Orange gives woolly midrange saturation, and a Tube Screamer before a 5150 gives tight modern metal. Across the board, the amps are just, well, good and thats before we smack into the cresting iceberg that is CODEX. More on that in a second.

The cabinet, er, cabinet is well stocked, and of course has room for your own IRs of choice. But Two Notes DynIR captures are another one of its strengths, and its with these that I find the most instant tweakability. Various mic models and positions provide the sort of continuous tone-twiddling that, when Im building a preset from the ground up, makes it easy to achieve a natural sound.

Splitting the signal chain is very useful here, too we all know parallel drive sounds can be fun, but mixing, matching and panning different DynIR captures led to some almost completely mix-ready tones out of a single guitar track.

Its worth noting that the effects and amps selection arent as overwhelmingly huge as some plugins libraries however, in practice I often found that beyond a certain point all that really does is increase option paralysis without actually making the thing more versatile.

So, onto the CODEX amp block. This is perhaps the unsung hero of Genome, as it has the potential to glue various bits of a digital setup together in a very seamless and cool way. Compatible with Neural Amp Modeller (NAM), AIDA-X and Proteus formats , it allows you to load these amp/pedal captures, shape them with some extensive EQ, level and gain controls, and treat them as you would any other block within Genome.

While Two Notes is indeed offering paid extras to expand Genome, AIDA-X, NAM and Proteus are free and open-source processes its pleasing to see standards based on so much flexibility and free sharing of captures integrated seamlessly into a more expansive and considered plugin. If youre already using any of these capture formats, the CODEX aspect of Genome should make it a very appealing prospect indeed, as it allows for an efficient and controllable way of integrating them into a live or recorded workflow.

As mentioned, the sounds from Genome are pretty damn good, and it seems Two Notes plans to add more free and paid gear with updates. But, right now, its still very comprehensive as a plugin really, if you were looking at something like ToneX but the price tag was putting you off, you might find Genome offers a more affordable and focused alternative. The seamless compatibility with third-party amp captures is great to see, too and there is a free trial, so, if youre curious, why not have a try yourself?

Pros:

Cons:

As mentioned, ToneX (199.99) is perhaps the most obvious competitor, and its tiered pricing might or might not work better for you than Genomes approach to expandability. Theres also Guitar Rig, Positive Grids BIAS AMP 2, and if you want a very focused set of virtual gear Neural DSPs various suites.

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Two Notes Genome review could this no-nonsense guitar plugin be all you need? - Guitar.com

WEST PALM BEACH, Fla., May 21, 2024 (Newswire.com) - Next Gen Diagnostics (NGD) and a team at Vanderbilt University Medical Center (VUMC) today announced the results of a study reporting that comparison of the whole genome sequence (WGS) of bacterial pathogens obtained from surveillance of infants in a neonatal intensive care unit (NICU) revealed substantial transmission of infection not detected by conventional infection control procedures. The findings demonstrate that even in highly resourced medical centers and in wards like the NICU with high levels of constant vigilance, WGS enables the detection of transmission not achievable with methods in current practice. The abstract reporting the results of the study will be presented for publication at the American Society for Microbiology Conference in Atlanta on June 15.

We found that WGS of S. aureus isolates obtained from surveillance swabs and clinical samples revealed a significant amount of likely transmission, which provided guidance enabling our infection control team to take a series of actions with beneficial effect, said Dr. Romney Humphries, Professor of Pathology, Microbiology and Immunology and Director of Laboratory Medicine at VUMC and senior author on the study. The findings were notable in the apparent transmission discovered when WGS was utilized, noted first author Dr. David Gaston, Assistant Professor and Medical Director of Molecular Infectious Disease Laboratory of VUMC. Moreover, we were struck by the observation that transmission was more likely to occur with MRSA versus MSSA infection, and occurred in multiple networks rather than a single outbreak.

In the study, 171 S. aureus samples from 132 distinct patients, obtained from surveillance sampling conducted in April, June and July supplemented with clinical samples, were short-read sequenced and bioinformatically analyzed for relatedness of core genomes at the SNP level by the NGD automated system1, with a strict (6 SNP) cutoff used to identify putative transmission for assessment and action by the VUMC infection prevention team. 42/132 (31.8%) of patients with S. aureus infections were found to be putatively connected by transmission, with the percentage of patients with MRSA infections connected by transmission (46.8%) over twice the frequency in patients with MSSA infection (21.2%). 13 distinct strains were involved in transmission, suggesting localized undetected causes of spread rather than a ward-level outbreak.

NGD was privileged to have the opportunity to work with the very distinguished team at VUMC to employ NGDs automated bioinformatic systems to facilitate the use of WGS to detection of transmission in a setting such as a NICU, noted Dr. Paul A. Rhodes, founder and CEO of NGD. The demonstration that comparison of WGS so readily enabled detection of transmission that was not otherwise observed even in a state-of-the-art medical setting and in a vigilantly monitored ward was striking.

This result, along with those emerging from other medical centers2, of the use of WGS to detect rather than simply verify transmission may signal a sea-change in best practice, noted Tom Talbot, Professor of Medicine and Medical Director of Infection Prevention at VUMC. With a sufficiently low cost for sequencing and bioinformatic analysis, use of WGS to detect transmission, at least in those wards where patients are at the greatest risk, may become a more routine infection prevention practice.

1Brown et al 2019, J Clinical Microbiology 2Sundermann et al 2022, Antibiotic Stewardship and Healthcare Epidemiology

About Next Gen Diagnostics NGD offers integrated high-volume turn-key sequencing and bioinformatic services to enable detection of transmission in hospitals, and is working with leading collaborators in the U.S., Europe and Israel to be among the first to bring WGS-based regulated diagnostics to patient care. NGD is based in the U.S., with subsidiaries in Cambridge, UK and in Israel.

Source: Next Gen Diagnostics

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Next Gen Diagnostics and Vanderbilt Report the Use of Whole Genome Sequencing to Detect Transmission of Infection ... - Newswire

The rectangular-shaped petri dish used to collect air, water, and surface samples on the International Space Station. Credit: Georgia Tech

The Genomic Enumeration of Antibiotic Resistance in Space (GEARS) project successfully completed on-orbit genomic sequencing of microbes isolated from the ISS on April 29.

Georgia Tech Ph.D. student, Jordan McKaig, demonstrates how NASA astronauts onboard the International Space Station used the MinION sequencing device to identify bacteria genomes. Credit: Georgia Tech

All experiment slides were safely returned to Earth on SpaceX-30. The slides with the microbial samples from the GEARS spaceflight experiment were retrieved from the cold stow team and successfully transferred to the Johnson Space Center (JSC) Microbiology Laboratory on May 4.

The JSC team will work to subculture and identify all microorganisms present. The isolates will also be archived. Additionally, comparison of the returned plates to the photos obtained in-flight is in work (prior to crew manipulation of the colonies). The Co-Investigator team is conducting the preliminary screening of retrieval of bacteria.

GEARS is a series of four experiments that will survey the space station for antibiotic resistant organisms. On-board sequencing of isolates aims to show how these bacteria adapt to the space environment, providing knowledge that informs measures to protect astronauts on future long-duration missions.

Image: On-orbit sequencing of microbes isolated from the ISS for the GEARS mission.

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Explorers Club Fellow, ex-NASA Space Station Payload manager/space biologist, Away Teams, Journalist, Lapsed climber, Synaesthete, NaVi-Jedi-Freman-Buddhist-mix, ASL, Devon Island and Everest Base Camp veteran, (he/him)

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Genomic Enumeration of Antibiotic Resistance in Space (GEARS) Completes Mission Operations - Astrobiology - Astrobiology News

NEW YORK, May 22, 2024 /PRNewswire/ -- The globalgenome editing marketsize is estimated to grow by USD 7.23 billionfrom 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of almost15.88% during the forecast period.

For more insights on the forecast market size and historic data (2018 - 2022)-Request asample report!

Genome Editing Market Scope

Report Coverage

Details

Base year

2023

Historic period

2018 - 2022

Forecast period

2024-2028

Growth momentum & CAGR

Accelerate at a CAGR of 15.88%

Market growth 2024-2028

USD 7.23 billion

Market structure

Fragmented

YoY growth 2022-2023 (%)

14.56

Regional analysis

North America, Europe, Asia, and Rest of World (ROW)

Performing market contribution

North America at 40%

Key countries

US, Canada, UK, Germany, and China

Key companies profiled

AstraZeneca PLC, Caribou Biosciences Inc., Cellectis SA, Cibus, Danaher Corp., Editas Medicine Inc., Egenesis, GenScript Biotech Corp., Horizon Discovery Ltd., Intellia Therapeutics Inc., Lonza Group Ltd., Merck KGaA, New England Biolabs Inc., OriGene Technologies Inc., PerkinElmer Inc, Precision BioSciences Inc., Sangamo Therapeutics Inc., Takara Bio Inc., Tecan Trading AG, and Thermo Fisher Scientific Inc.

Market Driver

Advancements in genome editing technologies like CRISPR-Cas9 and base editing offer precise modifications to DNA, expanding research and therapy applications. High-throughput screening methods accelerate discovery of gene functions and drug targets.

Automation streamlines workflows, reducing errors and increasing efficiency in large-scale experiments. Bioinformatics tools optimize editing protocols and assess outcomes, enhancing reliability and safety. These advancements drive growth in the global genome editing market.

MarketChallenges

Research report provides comprehensive data on impact of trend, driver and challenges-Request asample report!

Segment Overview

1.1Pharmaceutical and biotechnology companies-During the forecast period, the pharmaceutical and biotechnology companies segment is expected to experience significant market share growth. Genome exploration enables researchers to study gene function and disease mechanisms, aiding drug discovery and personalized medicine. By inducing genetic mutations in target genes, scientists gain insights into disease biology and drug responses.

The segment, valued at USD 1.86 billion in 2018, benefits from genome-edited models for preclinical drug screening and personalized therapy development, improving treatment outcomes. CRISPR/Cas9 technology drives genetic engineering advancements, offering versatile applications in therapy development and research. Pharmaceutical and biotech firms increasingly adopt gene editing tools for drug discovery and viral vector production, fueling market expansion.

For more information on market segmentation with geographical analysis including forecast (2024-2028) and historic data (2017-2021) - Download a Sample Report

Research Analysis

The genome editing market encompasses the development and application of advanced tools and technologies for modifying single genes within an organism's genome. These innovations hold significant promise in addressing various genetic abnormalities, including sickle cell disease, Parkinson's disease, hearing loss, and others. Gene-editing technologies, such as CRISPR-Cas9, SMR, Pro-code, and others, are revolutionizing molecular biology by enabling precise alterations to DNA strands.

Clinical trials are underway for numerous conditions, including AIDS, cancer, cystic fibrosis (CF), hemophilia, sickle cell disease, multiple myeloma, and breast cancer. Gene therapy and gene editing are expected to bring transformative treatments for tumors and other diseases. Key applications include agriculture, particularly in white button mushrooms, and industrial biotechnology.

Market Research Overview

The Genome Editing Market refers to the industry focused on developing and implementing technologies that enable the precise modification of an organism's DNA. This innovative field combines the use of tools like CRISPR-Cas9, zinc finger nucleases, and TALENs to target specific genes and make desired changes. Genome editing holds significant potential in various sectors, including agriculture, medicine, and research.

Its applications range from creating disease-resistant crops to treating genetic disorders and enhancing protein production. The technology's versatility and potential to revolutionize numerous industries continue to drive its growth and global interest.

Table of Contents:

1 Executive Summary 2 Market Landscape 3 Market Sizing 4 Historic Market Size 5 Five Forces Analysis 6 Market Segmentation

7Customer Landscape 8 Geographic Landscape 9 Drivers, Challenges, and Trends 10 Company Landscape 11 Company Analysis 12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research Jesse Maida Media & Marketing Executive US: +1 844 364 1100 UK: +44 203 893 3200 Email:[emailprotected] Website:www.technavio.com/

SOURCE Technavio

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Genome Editing Market size is set to grow by USD 7.23 billion from 2024-2028, Rapid technological advancements in ... - PR Newswire

Funk, V.A., Anderberg, A.A., Baldwin, B.G., Bayer, R.J., Bonifacino, J.M., Breitwieser, I., Brouillet, L., Carbajal, R., Chan, R. & Coutinho, A.X. Compositae Metatrees: The Next Generation, Systematics, Evolution, and Biogeography of Compositae (2009).

Pascual-Daz, J. P., Garcia, S. & Vitales, D. Plastome diversity and phylogenomic relationships in Asteraceae. Plants 10(12), 2699 (2021).

Article PubMed PubMed Central Google Scholar

Adkins, S. & Shabbir, A. Biology, ecology and management of the invasive parthenium weed (Parthenium hysterophorus L.). Pest Manag. Sci. 70(7), 10231029 (2014).

Article CAS PubMed Google Scholar

Navie, S., Panetta, F., McFadyen, R. & Adkins, S. Behaviour of buried and surface-sown seeds of Parthenium hysterophorus. Weed Res. (Oxford) 38(5), 335341 (1998).

Article Google Scholar

Tamado, T., Ohlander, L. & Milberg, P. Interference by the weed Parthenium hysterophorus L. with grain sorghum: Influence of weed density and duration of competition. Int. J. Pest Manag. 48(3), 183188 (2002).

Article Google Scholar

Bajwa, A. A., Chauhan, B. S. & Adkins, S. W. Germination ecology of two Australian biotypes of ragweed parthenium (Parthenium hysterophorus) relates to their invasiveness. Weed Sci. 66(1), 6270 (2018).

Article Google Scholar

Kaur, M., Aggarwal, N.K., Kumar, V. & Dhiman, R. Effects and management of Parthenium hysterophorus: A weed of global significance. In International Scholarly Research Notices 2014 (2014).

Singh, S., Khanna, S., Moholkar, V. S. & Goyal, A. Screening and optimization of pretreatments for Parthenium hysterophorus as feedstock for alcoholic biofuels. Appl. Energy 129, 195206 (2014).

Article ADS CAS Google Scholar

Reddy, K. N., Bryson, C. T. & Burke, I. C. Ragweed parthenium (Parthenium hysterophorus) control with preemergence and postemergence herbicides. Weed Technol. 21(4), 982986 (2007).

Article CAS Google Scholar

Javaid, A. & Adrees, H. Parthenium management by cultural filtrates of phytopathogenic fungi. Nat. Prod. Res. 23(16), 15411551 (2009).

Article CAS PubMed Google Scholar

Khan, H., Marwat, K. B., Hassan, G. & Khan, M. A. Socio-economic impacts of parthenium (Parthenium hysterophorus L.) in Peshawar valley, Pakistan. Pak. J. Weed Sci. Res. 19(3), 2013 (2013).

Google Scholar

Shabbir, A., Dhileepan, K., ODonnell, C. & Adkins, S. W. Complementing biological control with plant suppression: Implications for improved management of parthenium weed (Parthenium hysterophorus L.). Biol. Control 64(3), 270275 (2013).

Article Google Scholar

Gaudeul, M., Giraud, T., Kiss, L. & Shykoff, J. A. Nuclear and chloroplast microsatellites show multiple introductions in the worldwide invasion history of common ragweed, Ambrosia artemisiifolia. PloS one 6(3), e17658 (2011).

Article ADS CAS PubMed PubMed Central Google Scholar

Ueno, S., Rodrigues, J. F., Alves-Pereira, A., Pansarin, E. R. & Veasey, E. A. Genetic variability within and among populations of an invasive, exotic orchid. AoB Plants 7, plv077 (2015).

Article PubMed PubMed Central Google Scholar

Dar, T. H., Raina, S. N. & Goel, S. Cytogenetic and molecular evidences revealing genomic changes after autopolyploidization: A case study of synthetic autotetraploid Phlox drummondii hook. Physiol. Mol. Biol. Plants 23, 641650 (2017).

Article CAS PubMed PubMed Central Google Scholar

Te Beest, M. et al. The more the better? The role of polyploidy in facilitating plant invasions. Ann. Bot. 109(1), 1945 (2012).

Article Google Scholar

Gray, M. W. The evolutionary origins of organelles. Trends Genet. 5, 294299 (1989).

Article CAS PubMed Google Scholar

Howe, C. J. et al. Evolution of the chloroplast genome. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 358(1429), 99107 (2003).

Article CAS Google Scholar

Henry, R. J. Plant Diversity and Evolution: Genotypic and Phenotypic Variation in Higher Plants (Cabi Publishing, 2005).

Book Google Scholar

Loeuille, B. et al. Extremely low nucleotide diversity among thirty-six new chloroplast genome sequences from Aldama (Heliantheae, Asteraceae) and comparative chloroplast genomics analyses with closely related genera. PeerJ 9, e10886 (2021).

Article PubMed PubMed Central Google Scholar

Timme, R. E., Kuehl, J. V., Boore, J. L. & Jansen, R. K. A comparative analysis of the Lactuca and Helianthus (Asteraceae) plastid genomes: identification of divergent regions and categorization of shared repeats. Am. J. Bot. 94(3), 302312 (2007).

Article CAS PubMed Google Scholar

Mardanov, A. V. et al. Complete sequence of the duckweed (Lemna minor) chloroplast genome: Structural organization and phylogenetic relationships to other angiosperms. J. Mol. Evolut. 66, 555564 (2008).

Article ADS CAS Google Scholar

Kumar, S., Hahn, F. M., McMahan, C. M., Cornish, K. & Whalen, M. C. Comparative analysis of the complete sequence of the plastid genome of Parthenium argentatum and identification of DNA barcodes to differentiate Parthenium species and lines. BMC Plant Biol. 9(1), 112 (2009).

Article Google Scholar

Hollingsworth, P. M., Graham, S. W. & Little, D. P. Choosing and using a plant DNA barcode. PloS one 6(5), e19254 (2011).

Article ADS CAS PubMed PubMed Central Google Scholar

Yin, P., Kang, J., He, F., Qu, L.-J. & Gu, H. The origin of populations of Arabidopsis thalianain China, based on the chloroplast DNA sequences. BMC Plant Biol. 10(1), 116 (2010).

Article Google Scholar

Bock, R. & Khan, M. S. Taming plastids for a green future. Trends Biotechnol. 22(6), 311318 (2004).

Article CAS PubMed Google Scholar

Dierckxsens, N., Mardulyn, P. & Smits, G. NOVOPlasty: De novo assembly of organelle genomes from whole genome data. Nucleic Acids Res. 45(4), e18e18 (2017).

PubMed Google Scholar

Luo, R. et al. SOAPdenovo2: An empirically improved memory-efficient short-read de novo assembler. Gigascience 1(1), 2047-217X-118 (2012).

Article Google Scholar

Sugiura, M., Shinozaki, K., Zaita, N., Kusuda, M. & Kumano, M. Clone bank of the tobacco (Nicotiana tabacum) chloroplast genome as a set of overlapping restriction endonuclease fragments: Mapping of eleven ribosomal protein genes. Plant Sci. 44(3), 211217 (1986).

Article CAS Google Scholar

Yang, T. et al. Comparative analyses of 3,654 plastid genomes unravel insights into evolutionary dynamics and phylogenetic discordance of green plants. Front. Plant Sci. 13, 808156 (2022).

Article PubMed PubMed Central Google Scholar

Dempewolf, H. et al. Establishing genomic tools and resources for Guizotia abyssinica (Lf) Cass.The development of a library of expressed sequence tags, microsatellite loci, and the sequencing of its chloroplast genome. Mol. Ecol. Resour. 10(6), 10481058 (2010).

Article CAS PubMed Google Scholar

Ma, J. Analysis of genome characteristics of Helianthus annuus J-01 chloroplast. In IOP Conference Series: Earth and Environmental Science. 012046 (IOP Publishing, 2021).

Azarin, K., Usatov, A., Makarenko, M., Khachumov, V. & Gavrilova, V. Comparative analysis of chloroplast genomes of seven perennial Helianthus species. Gene 774, 145418 (2021).

Article CAS PubMed Google Scholar

Curci, P. L., De Paola, D., Danzi, D., Vendramin, G. G. & Sonnante, G. Complete chloroplast genome of the multifunctional crop globe artichoke and comparison with other Asteraceae. PloS one 10(3), e0120589 (2015).

Article PubMed PubMed Central Google Scholar

Asaf, S. et al. Chloroplast genomes of Arabidopsis halleri ssp. gemmifera and Arabidopsis lyrata ssp. petraea: Structures and comparative analysis. Sci. Rep. 7(1), 7556 (2017).

Article ADS PubMed PubMed Central Google Scholar

Xu, J. et al. The first intron of rice EPSP synthase enhances expression of foreign gene. Sci. China Ser. C Life Sci. 46, 561569 (2003).

Article CAS Google Scholar

Wolf, P. G. et al. The evolution of chloroplast genes and genomes in ferns. Plant Mol. Biol. 76, 251261 (2011).

Article CAS PubMed Google Scholar

Oliver, M. J. et al. Chloroplast genome sequence of the moss Tortula ruralis: Gene content, polymorphism, and structural arrangement relative to other green plant chloroplast genomes. BMC Genomics 11, 18 (2010).

Article Google Scholar

Wicke, S., Schneeweiss, G. M., Depamphilis, C. W., Mller, K. F. & Quandt, D. The evolution of the plastid chromosome in land plants: Gene content, gene order, gene function. Plant Mol. Biol. 76, 273297 (2011).

Article CAS PubMed PubMed Central Google Scholar

Jansen, R. K. et al. Analysis of 81 genes from 64 plastid genomes resolves relationships in angiosperms and identifies genome-scale evolutionary patterns. Proc. Natl. Acad. Sci. 104(49), 1936919374 (2007).

Article ADS CAS PubMed PubMed Central Google Scholar

Nakkaew, A., Chotigeat, W., Eksomtramage, T. & Phongdara, A. Cloning and expression of a plastid-encoded subunit, beta-carboxyltransferase gene (accD) and a nuclear-encoded subunit, biotin carboxylase of acetyl-CoA carboxylase from oil palm (Elaeis guineensis Jacq.). Plant Sci. 175(4), 497504 (2008).

Article CAS Google Scholar

Nie, X. et al. Comparative analysis of codon usage patterns in chloroplast genomes of the Asteraceae family. Plant Mol. Biol. Rep. 32, 828840 (2014).

Article CAS Google Scholar

Cavalier-Smith, T. Chloroplast evolution: Secondary symbiogenesis and multiple losses. Curr. Biol. 12(2), R62R64 (2002).

Article CAS PubMed Google Scholar

Nie, X. et al. Complete chloroplast genome sequence of a major invasive species, crofton weed (Ageratina adenophora). PloS one 7(5), e36869 (2012).

Article ADS CAS PubMed PubMed Central Google Scholar

Asaf, S. et al. The complete chloroplast genome of wild rice (Oryza minuta) and its comparison to related species. Front. Plant Sci. 8, 304 (2017).

Article PubMed PubMed Central Google Scholar

Saski, C. et al. Complete chloroplast genome sequences of Hordeum vulgare, Sorghum bicolor and Agrostis stolonifera, and comparative analyses with other grass genomes. Theor. Appl. Genet. 115, 571590 (2007).

Article CAS PubMed PubMed Central Google Scholar

Tangphatsornruang, S. et al. The chloroplast genome sequence of mungbean (Vigna radiata) determined by high-throughput pyrosequencing: Structural organization and phylogenetic relationships. DNA Res. 17(1), 1122 (2010).

Article CAS PubMed Google Scholar

Gao, L., Yi, X., Yang, Y.-X., Su, Y.-J. & Wang, T. Complete chloroplast genome sequence of a tree fern Alsophila spinulosa: Insights into evolutionary changes in fern chloroplast genomes. BMC Evolut. Biol. 9(1), 114 (2009).

Article Google Scholar

Zhao, Y. et al. The complete chloroplast genome provides insight into the evolution and polymorphism of Panax ginseng. Front. Plant Sci. 5, 696 (2015).

Article PubMed PubMed Central Google Scholar

Rose, O. & Falush, D. A threshold size for microsatellite expansion. Mol. Biol. Evolut. 15(5), 613615 (1998).

Article CAS Google Scholar

Huotari, T. & Korpelainen, H. Complete chloroplast genome sequence of Elodea canadensis and comparative analyses with other monocot plastid genomes. Gene 508(1), 96105 (2012).

Article CAS PubMed Google Scholar

Qian, J. et al. The complete chloroplast genome sequence of the medicinal plant Salvia miltiorrhiza. PloS one 8(2), e57607 (2013).

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The complete plastome sequences of invasive weed Parthenium hysterophorus: genome organization, evolutionary ... - Nature.com

Identification of a set of gut microbes associated with CRC

Most colorectal cancers arise from adenoma to carcinoma as verified by diet, inflammatory processes, gut microbiota, and genetic alterations. Nonetheless, the mechanism by which the microbiota interacts with these etiologic factors to promote CRC is not clear. Therefore, we collected stool samples, tumor and matched normal tissues from 41 CRC individuals, and carried out multi-omics sequencing analyses to evaluate the interplay between cancer cells and gut microbiome (Fig.1 and Additional file 1: Table S1). As shown in Additional file 1: Fig. S1a, the stool samples were subjected to metagenomic sequencing, achieving an average of 7Gb clean data. Additionally, we conducted whole exome sequencing, ensuring a minimum of more than 100X coverage and 20Gb data, respectively (Additional file 1: Table S2).

Metagenomics sequencing of the stool sample and exome and transcriptome sequencing of mucosa tissue in colorectal cancer. We collected stool specimens and matched tumor and normal mucosa tissue from 41 colorectal cancer patients. The former samples were metagenomically shotgun sequenced to yield taxonomic and functional profiles; the latter were processed using exome and transcriptome sequencing technology respectively. Features of the microbiome were correlated with clinic elements somatic mutations, and differentially expressed genes, respectively

We first examined the microbiome dysbiosis by integrating our metagenomic sequencing data with a public Chinese colorectal cancer cohort3 (CRC cohort2 and CON) (Fig.2A). Compared with healthy controls, the CRC patients in our cohort exhibited a significantly decreased alpha diversity (Additional file 1: Fig. S1b), but no obvious difference in the beta diversities (Additional file 1: Fig. S1c). To investigate the alterations in microbiota structure, we conducted the linear discriminant analysis effect size (LEfSe) analysis to compare healthy controls and combined tumor samples. Totally, there were 2 taxa (Viruses_noname and Fusobacteria) at the phylum level and 10 at the genus level significantly altered respectively (Fig.2B and Additional file 1: Table S3). Notably, we figured out 22 species associated with disease status, of which 14 were elevated in CRC group (Fig.2C). Of them, Bacteroides fragilis (LDA=3.897), Parabacteroides spp. (LDA=3.499) and Prevotella intermedia (LDA=3.452) exhibited the highest abundances in CRC patients. In contrast, eight species were enriched in healthy controls, including Faecalibacterium prausnitzii (LDA=4.299), Eubacterium rectale (LDA score=4.255), Eubacterium eligens (LDA=4.002), and so on.

A Microbiome alteration between healthy and CRC subjects. PCoA plot showed the two cohorts used in our project. B Taxonomic profile difference detected with LEfSe. C Differentially abundant species between healthy controls and CRC patients. D Differentially abundant KEGG pathways between healthy controls and CRC patients. E Unsupervised clustering uncovered associations between differentially abundant species and clinic covariates

To further investigate the functions of 22 tumor-associated bacteria, we used HUManN2 to estimate the relative abundance of KEGG ontology (KO) categories. Disease associated KEGG pathway changes were further identified using the method described in Feng Q. et al.4 We observed that bacteria related metabolic pathways were enriched in CRC groups. Especially, one carbon pool by folate metabolic pathway of microbiota was significantly (Reporter score=3.471) higher in CRC patients (Fig.2D). The one carbon pool by folate is a universal cell metabolic process supporting tumorigenesis, obtaining folate (vitamin B9) and cobalamin (vitamin B12) from diet. Furthermore, the cancer enriched species showed positive correlations with the metabolic pathways such as carbon metabolism and oxidative phosphorylation, whereas some well-known beneficial bacteria (including Faecalibacterium prausnitzii), displayed negative correlations (Additional file 1: Fig. S2).

Next, we investigated associations between overall microbiome configuration with CRC clinical covariates. Clinically, of the cohorts 41 individuals (63% male; ages 4679), 26 subjects (63%) belong to COAD and 15 subjects (37%) had carcinomas at rectum. Additionally, 10 subjects were diagnosed at early stage and 31 subjects (76%) at later stage. Among all 41 individuals, we observed that several paraprevotella.ssp were elevated in patients with age<65 (for example, paraprevotella clara, LDA score=3.051; paraprevotella xylaniphila, LDA score=2.478) (Additional file 1: Fig. S3a). Furthermore, Clostridium clostridioforme was predominated found in females (Additional file 1: Fig. S3b, LDA score=3.182). As to Bacteroides genus, the abundance of Bacteroides eggerthii was significantly increased in COAD (LDA score=3.625) whereas Bacteroides massiliensis was enriched in READ (LDA score=4.985) (Additional file 1: Fig. S3c). Bifidobacterium, one of the major probiotics, exhibited a significant increase in the early stage and individuals with age<65 (Bifidobacterium longum, LDA score=3.698; Bifidobacterium dentium, LDA score=2.102) (Additional file 1: Fig. S3a and d).

We also assessed the connections between clinical characteristics and 22 cancer associated bacteria in our subjects through unsupervised clustering (Fig.2E and Additional file 1: Table S4). Of note, we observed significant gender differences (p=0.01) among the C3 community type (Additional file 1: Fig. S4a). Tumor locations (colon or rectum; p=0.01) were linked to the C4 community type, which primarily consisting of the beneficial species (Additional file 1: Fig. S4b).

Previous studies indicated that gut microbes may induce DNA damage, thereby accelerating cancer development [29]. Consequently, we detected somatic mutations using exome sequencing technology from 41 CRC tumors and idntified 4 significantly mutated genes with MutSigCV, including TP53 (Q value=0), APC (Q value=1.26E-11), KRAS (Q value=1.11E-10) and SMAD4 (Q value=7.37E-04) (Fig.3A and Additional file 1: Table S6).

An overview of the associations between cancer genome and microbiome genomes. A Bar plots illustrate the frequently mutated genes in 41 tumor tissues. B The interaction between gut microbial taxa and somatic altered genes

To explore their associations with microbiota composition, we conducted the LEfSe analysis to compare tumors with or without mutated genes (Fig.3B). TP53 is the most prevalent somatic altered genes in our cohort. In TP53 mutated subjects, an enrichment of several disease-associated species, including Alistipes putredinis (LDA score=4.402), Porphyromonas asaccharolytica (LDA score=3.816), and Prevotella intermedia (LDA score=3.795) (Fig.4A). Previous observations uncovered that butyrate treatment could activate the TP53 pathway [30]. Consistently, the abundance of butyrate-producing bacteria, Butyricicoccus pullicaecorum, exhibited a significant reduction in TP53 mutation carriers (LDA score=2.395). Interestingly, Roseburia inulinivorans (LDA score=3.96) and Ruminococcus gnavus (LDA score=3.426), two other butyrate producers, were also significantly depleted in APC mutation carriers (Fig.4B). Besides, the relative abundance of Enterococcus genus was enriched in subjects with KRAS and SMAD4 mutations (Enterococcus faecalis, LDA=2.217; Enterococcus avium, LDA score=3.075) (Fig.4C, D). We also performed similar analysis between gut microbiota and other frequently mutated genes (Additional file 1: Fig. S5). In stool samples, probiotics, including Ruminococcus lactaris(LDA score=3.405), Bifidobacterium bifidum (LDA score=2.425), were dramatically elevated in MUC5B or MUC16 mutated individuals (Additional file 1: Fig. S5e, f). Barnesiella intestinihominis, acting as an enhancer for anticancer therapy, was proven enriched in TNN mutation carriers (LDA score=3.156) (Additional file 1: Fig. S5m).

AD Significantly mutated genes related taxonomic difference. Differentially abundant species between tumors with and without TP53 (A), APC (B), KRAS (C), SMAD4 (D) alterations, respectively

We further characterized the differences of microbial pathways between subjects with specific mutations and control group. Interestingly, the most abundant pathways were generally housekeeping processes encoded by microbes, such as one carbon metabolism, aromatic amino acids, branched chain amino acid and so on (Additional file 1: Fig. S6). One-carbon (1C) metabolism, consistently overexpressed in cancer, supports multiple biological processes, including nucleotides synthesis, methionine recycling pathway and redox defense [31]. An increased level of bacterial purine (reporter score=2.909) and pyrimidine (reporter score=3.188) metabolism were found in TP53 mutation carriers (Additional file 1: Fig. S6a). Similarly, bacterial cysteine-methionine metabolism (reporter score=3.246) and folate biosynthesis (reporter score=1.949) exhibited significant alterations in individuals with APC mutations (Additional file 1: Fig. S6b). Bacteria can synthesize different amino acids. Compared to control group, we found APC (Additional file 1: Fig. S6c) and SMAD4 mutation carriers (Additional file 1: Fig. S6d) were significantly associated with high levels of bacterial tryptophan (Trp) metabolism pathway (reporter score=3.045 and 2.732, respectively). Moreover, we observed an elevated abundance of bacterial phenylalanine metabolism correlated with KRAS mutations (reporter score=4.345) (Additional file 1: Fig. S6c).

We also investigated the relationship between the microbiome composition and the gene expression patterns in CRC. We observed that certain bacterial species were significantly correlated with the gene expression pattern (Additional file 1: Fig. S7 and Table S6). The differentially expressed functional genes were clustered according to their correlation with differentially abundant species, following by annotation with DAVID (Fig.5). We observed that Fusobacterium nucleatum, along with some Clostridium spp. exhibited positive associations nitrogen metabolism and bile secretion pathways, but negatively with cytokine-cytokine receptor interaction pathway.

Correlation of differentially abundant species and deregulated genes. Tumor associated deregulated genes were clustered and annotated with DAVID. The X axis illustrated the DAVID functional annotation and Y axis showed differentially abundant species. Red color represents positive association while green color means negative association

Subsequently, the interaction between 22 bacterial species and up-regulated oncogene expression was explored. As shown in Fig.6A, Fusobacterium nucleatum was positively correlated with PKM (p=0.03), SCD (p=0.0186), FASN (p=0.014), which are key enzymes in glycolysis and fatty acid metabolism. Consistent with the findings, we categorized patients into high and low Fusobacterium nucleatum groups, and found that various metabolism related pathways were significantly enriched in the high groups (pentose and glucuronate interconversions, p=0.026; starch and sucrose metabolism, p=0.007; porphyrin and chlorophyll metabolism, p=0.023; oxidative phosphorylation, p<0.00001) (Fig.6B). Taken together, the intestinal microbiota promotes CRC progression by shaping the expression of host gene expression, especially metabolic pathways.

Gene expression signature and metabolic pathways reprogramming associated with microbial shifts. A The association between up regulated oncogene expression and cancer related species. The X axis represents up regulated cancer genes. Significant associations were highlighted below the heatmap. B Pathway difference between high and low Fusobacterium nucleatum groups

The composition of immune and stromal cell types was identified by XCELL, a gene signature-based method that integrates the advantages of gene set enrichment with deconvolution approaches. Compared with adjacent normal tissues, the overall immune score was significantly lower in tumor tissue (Fig.7A). Especially, the abundance of most B cells and CD8+T cells elevated in tumors while regulatory T cells and T helper cells exhibited a decreasing trend (Additional file 1: Fig. S8), indicating the important role of the immune microenvironment in the progression of CRC. The associations between different microbial species and immune cell types in the CRC were shown in Fig.7B. Fusobacterium nucleatum was negatively associated with dendritic cells and CD8 T cells (Fig.7C). While Faecalibatcerium prausnitzii were significantly positively correlated with dendritic cells and Macrophages M1 (Additional file 1: Fig. S9a).

Fusobacterium nucleatum promoted CRC by modifying the tumor immune environment and TNFSF9 expression. A Comparison of immune cell scores between tumor and adjacent normal tissues. B The heatmap illustrates the correlations between differential abundant species and immune cells. The stars indicate the level of statistical significance. C Significant association of F. nucleatum and aDC and CD8 T cells. D Pathway alteration between normal and tumor tissue. E Significant association between Fusobacterium nucleatum and TNFSF9 gene expression

Interestingly, Gene set enrichment analysis of revealed that the cytokine-cytokine receptor interaction (p<0.001) was significantly altered in CRC (Fig.7D). Correlation analysis of genes related to cytokine-cytokine receptor interaction pathway related genes and 22 species uncovered several significant associations (Additional file 1: Fig. S9b). Among them, Fusobacterium nucleatum exhibited a positive association with TNFSF9, a member of TNF (tumor necrosis factor) family members (r=0.443, p=0.0037) (Fig.7E). Previous study showed that Fusobacterium nucleatum autoinducer-2 (AI-2) enhanced the mobility and M1 polarization of macrophages, possibly through TNFSF9/TRAF1/p-AKT/IL-1 signaling. Our results further suggested that pathogenic bacteria, like Fusobacterium nucleatum, may interact with CRC cells and modify the tumor immune environment by TNFSF9, finally facilitating the tumor development.

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Multi-omic profiling reveals associations between the gut microbiome, host genome and transcriptome in patients with ... - Journal of Translational...

Researchers at EPFL, led by Didier Trono, have developed a novel method to detect previously undetectable transposable elements (TEs) in the human genome, significantly expanding our knowledge of DNA composition. This discovery has profound implications for understanding genetic diseases and the genomes response to various stresses.

The human genome, a complex mosaic of genetic data essential for life, has proven to be a treasure trove of strange features. Among them are segments of DNA that can jump around and move within the genome, known as transposable elements (TEs).

As they change their position within the genome, TEs can potentially cause mutations and alter the cells genetic profile but also are master orchestrators of our genomes organization and expression. For example, TEs contribute to regulatory elements, transcription factor binding sites, and the creation of chimeric transcripts genetic sequences created when segments from two different genes or parts of the genome join together to form a new, hybrid RNA molecule.

Matching their functional importance, TEs have been recognized to account for half of the human DNA. However, as they move and age, TEs pick up changes that mask their original form. Over time, TEs degenerate and become less recognizable, making it difficult for scientists to identify and track them in our genetic blueprint.

In a new study, researchers in the group of Didier Trono at EPFL have found a way to improve the detection of TEs in the human genome by using reconstructed ancestral genomes from various species, which allowed them to identify previously undetectable degenerate TEs in the human genome. The study is published in Cell Genomics.

The scientists used a database of reconstructed ancestral genomes from different kinds of species, like a genomic time machine. By comparing the human genome with the reconstructed ancestral genomes, they could identify TEs in the latter that, over millions of years, have become degenerate (worn out) in humans.

This comparison allowed them to detect (annotate) TEs that might have been missed in previous studies that used data only from the human genome.

Using this approach, the scientists uncovered a larger number of TEs than previously known, adding significantly to the share of our DNA that is contributed by TEs. Furthermore, they could demonstrate that these newly unearthed TE sequences played all the same regulatory roles as their more recent, already-identified relatives.

The potential applications are vast: Better understanding TEs and their regulators could lead to insights into human diseases, many of which are believed to be influenced by genetic factors, says Didier Trono. First and foremost, cancer, but also auto-immune and metabolic disorders, and more generally our bodys response to environmental stresses and aging.

Reference: Ancestral genome reconstruction enhances transposable element annotation by identifying degenerate integrants by Wayo Matsushima, Evarist Planet and Didier Trono, 30 January 2024, Cell Genomics. DOI: 10.1016/j.xgen.2024.100497

The study was funded by the European Research Council, the Swiss National Science Foundation, the EMBO Postdoctoral Fellowship, and the JSPS Overseas Research Fellowship.

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Genomic Time Machine Reveals Secrets of Human DNA - SciTechDaily

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Over two decades after the first human genome was sequenced, a team of researchers has discovered ~1 million new exons in the human genome.

The research group, from the University of Torontos (U of T) Donnelly Centre for Cellular and Biomolecular Research, said that none of the newly discovered exons are consistently found in the genomes of other species. They seem to appear in the human genome mainly due to random mutation and are unlikely to play a significant role in our biology, explained Dr. Timothy Hughes, principal investigator on the study and professor and chair of molecular genetics at U of Ts Temerty Faculty of Medicine. This is evidence that evolution in humans involves a lot of trial and error most likely enabled by the vast size of our genome.

The study is published in Genome Research.

The human genome comprises ~20,000 genes. Genes consist of exons, DNA bases that encode protein, which are separated by introns non-coding DNA sequences. When a gene is transcribed, a process called splicing removes introns, so that only exons are included in the final mRNA product, which is then translated into protein. Exons are regarded as autonomous if they do not require any external help to splice into a mature RNA transcript.

Hughes and colleagues assayed large fragments (100500 base pairs) of the human genome using a method known as exon trapping. They wanted to test the exon definition model, a molecular biology concept that describes how splicing machinery is able to recognize exons during pre-mRNA processing. An assumption of this model is that the accurate removal of introns is achieved because there are clear and consistent indicators of where exons start, and where exons end. Sometimes, though, exon splicing doesnt go as planned and mature RNA transcripts containing nonfunctional components are produced.

Exon trapping is a traditional molecular biology technique that is used to find and isolate exons. A fragment of DNA is inserted into a vector that carries the DNA for introduction into a host cell. The RNA produced by the host cell is then analyzed, and exons that are expressed and trapped in the RNA can be detected using sequencing methods.

We used a classical exon trapping assay to survey the human genome for autonomous exons whereby genomic fragments are assayed outside of their normal contextual setting, for example, flanking exons, promoter, transcription level and distal intronic sequences, the authors described.

We reasoned that this survey would allow us to query whether protein-coding exons are generally autonomous, whether exons exist elsewhere in the genome, what sequence features they possess and whether exons arise at random, which would partly explain the existence of long non-coding RNAs (lncRNAs).

Hughes and colleagues defined any trapped exons as autonomous, of which there were ~1.25 million, including most known mRNAs and annotated lncRNAs.

Almost 1 million of the trapped exons are not annotated, Hughes and colleagues said: These exons are not conserved, suggesting they are nonfunctional and arose from random mutations. They are nonetheless highly enriched with known splicing promoting sequence features that delineate known exons.

The translation of randomly mutated exons could have consequences for human health. lncRNAs are autonomous but lack a known function though they have been associated with the development of cancer.

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This is an interesting study that broadens our knowledge of sequences across the human genome that have the potential to be recognized as exons in transcribed RNA, Dr. Benjamin Blencowe, professor of molecular genetics at U of T, who was not involved in the study, said. While the significance of the majority of the newly detected exons is unclear, some of them may be activated in certain contexts for example, by disease mutations and therefore cataloging them is important. This study will further serve as a valuable resource facilitating ongoing efforts directed at deciphering the splicing code.

The researchers are confident that their exon trapping data will also be helpful when fed into programs such as SpliceAI, a tool that is used widely to determine splice sites. SpliceAI often doesnt provide details on the characteristics of exons and has a poor ability to predict splicing in exons that arent already cataloged, said Hughes. Our exon trapping data contains biologically meaningful information that can be fed into SpliceAI and other splicing predictors to open up new paths for exploring the dark genome.

Reference: Stepankiw N, Yang AWH, Hughes TR. The human genome contains over a million autonomous exons.Genome Res. 2023. doi: 10.1101/gr.277792.123

This article is a rework of a press release issued by [name of institute]. Material has been edited for length and content.

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1 Million Unannotated Exons Discovered in the Human Genome - Technology Networks

The mysterious night parrot has long perplexed ecologists and birders from its presumed extinction in the 20th century, to the triumphant discovery of live birds in Queensland and Western Australia during the 2010s.

Its still one of the worlds most rarely seen birds, with only a handful of photographs and specimens surfacing over the last 20 years.

But now, Australian scientists have another feather in their nocturnal cap: theyve sequenced and annotated the night parrots genome.

This library of genetic information can now be used to learn more about, and conserve, the night parrot.

We never thought wed say those three words together in one sentence: night parrot genome, Dr Leo Joseph, director of the Australian National Wildlife Collection at the CSIRO, tells Cosmos.

It says a lot about hope for how we can learn more about our biodiversity, including really interesting, quirky species like this.

The opportunity to sequence the birds full genome arose last year, when Traditional Owners in the Pilbara found an injured night parrot caught on a fence.

The bird died from its injuries, so the Traditional Owners delivered it to the West Australian Museum, where the specimen was preserved and put on display last week.

Curator Dr Kenny Travouillon gave a small tissue sample from the bird to the CSIRO, so that researchers could run it through ANUs genetic sequencing technology under their Applied Genomics Initiative.

Dr Gunjan Pandey, a research scientist who led the sequencing project for the CSIRO, tells Cosmos that they were able to sequence the whole genome in 3-4 months, and take another month to annotate it a fast turnaround.

We have optimised workflows and pipelines to do high throughput genome assemblies, says Pandey.

In the last couple of years, we have done over 100 genomes.

The researchers finished annotating the genome yesterday, and have released it publicly on the Genbank database.

The idea here is to make the genome available to everybody so all of us can look at it together, rather than keeping it as our property, says Pandey.

The Australian community is paying for a lot of this work, and its only fair then that publicly supported science be publicly available, says Joseph.

But the researchers have their own plans to study the genome too.

We are going to compare it with genomes from other parrots and nocturnal birds and see what is happening, says Pandey.

The team is also interested in using the genome to learn about the night parrots camouflage, beak morphology, genetic diversity and population structure.

There are many dimensions to understanding a bird like this. One is to understand its habitat. One is to understand its vocalisations, says Joseph.

But if we start to think about genetics, and how genetics can contribute its own dimension to conservation, we can start to think about understanding the longer-term evolutionary history of the night parrot.

Joseph likens sequencing a creatures full genome to making a roadmap.

If you imagine a roadmap of Australia, with no place names, thats a bit like just saying we sequenced a genome.

[] But annotating the genome means you can put all the place names on the map, you can put all the genes on it.

So we start to get that genetic blueprint for an organism. We start to have a way of understanding what it is that makes up a night parrot. We can look into genes that we know from other birds are related to nocturnality, and we can understand its biology down to that level.

And we can use it in conjunction with other pieces of genetic data to understand the genetic structure, of the night parrot today, across its range which genes might be varying and which genes might not varying.

The researchers can also now compare the parrots DNA to DNA from other night parrot samples, like from feathers some of which are a century old.

With DNA from feathers, you dont get very good quality. But whatever fragmented DNA we get, now, we can use that information to get into the genetic diversity and the population structure, says Pandey.

Ecologists can also get a better sense of where night parrots have been without observing them in person through environmental DNA, or eDNA.

A bird watcher colleague of mine once said to me: the night parrot was the only bird in the world that no person living had shown to another person, which was a really good way to sum up the mystery, says Joseph.

The researchers are hoping that both they, and other scientists, will use the genetic information to help save the critically endangered species.

I think another level of interest in the night parrot is what it holds symbolically, says Joseph.

It says a lot about environmental change in Australia. It says a lot about how weve nearly lost bits of our biodiversity heritage, that we have lost bits.

And it says a lot about hope.

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Hope for the night parrot: bird's full genome has been sequenced - Cosmos

Lewin, H. A. et al. Earth BioGenome Project: Sequencing life for the future of life. Proc. Natl. Acad. Sci. 115(17), 43254333 (2018).

Article ADS CAS PubMed PubMed Central Google Scholar

Lewin, H. A. et al. The Earth BioGenome Project 2020: Starting the clock. Proc. Natl. Acad. Sci. U S A 119(4), e2115635118 (2022).

Article CAS PubMed PubMed Central Google Scholar

Hotaling, S., Kelley, J. & Frandsen, P. Toward a genome sequence for every animal: Where are we now?. Proc. Natl. Acad. Sci. 118, e2109019118 (2021).

Article CAS PubMed PubMed Central Google Scholar

Horgan, R. & Kenny, L. Omic technologies: Genomics, transcriptomics, proteomics and metabolomics. Obstet. Gynaecol. 13, 189 (2011).

Article Google Scholar

Formenti, G. et al. The era of reference genomes in conservation genomics. Trends Ecol. Evol. 37, 197 (2022).

Article CAS PubMed Google Scholar

Paez, S. et al. Reference genomes for conservation. Science 377(6604), 364366 (2022).

Article ADS CAS PubMed Google Scholar

Wong, A. K. et al. Decoding disease: From genomes to networks to phenotypes. Nat. Rev. Genet. 22(12), 774790 (2021).

Article CAS PubMed Google Scholar

Sayers, E. W. et al. Database resources of the national center for biotechnology information. Nucleic Acids Res. 50(D1), D20-d26 (2022).

Article CAS PubMed Google Scholar

AmphibiaWeb. Amphibian Species by the Numbers (University of California, 2022).

Google Scholar

Lamichhaney, S. et al. A bird-like genome from a frog: Mechanisms of genome size reduction in the ornate burrowing frog, Platyplectrum ornatum. Proc. Natl. Acad. Sci. USA 118(11), e2011649118 (2021).

Article CAS PubMed PubMed Central Google Scholar

Li, Q. et al. A draft genome assembly of the eastern banjo frog Limnodynastes dumerilii dumerilii (Anura: Limnodynastidae). Gigabyte 2020, 113 (2020).

Article Google Scholar

Rhie, A. et al. Towards complete and error-free genome assemblies of all vertebrate species. Nature 592(7856), 737746 (2021).

Article ADS CAS PubMed PubMed Central Google Scholar

Farquharson, K. et al. The genome sequence of the critically endangered Kroombit tinkerfrog (Taudactylus pleione) [version 1; peer review: 2 approved]. F1000Research 12, 845 (2023).

Article PubMed PubMed Central Google Scholar

Bredeson, J. V. et al. Conserved chromatin and repetitive patterns reveal slow genome evolution in frogs. Nat. Commun. 15(1), 579 (2024).

Article ADS CAS PubMed PubMed Central Google Scholar

Liedtke, H. C. et al. Macroevolutionary shift in the size of amphibian genomes and the role of life history and climate. Nat. Ecol. Evol. 2(11), 17921799 (2018).

Article PubMed Google Scholar

Sun, Y.-B., Zhang, Y. & Wang, K. Perspectives on studying molecular adaptations of amphibians in the genomic era. Zool. Res. 41(4), 351 (2020).

Article CAS PubMed PubMed Central Google Scholar

Seidl, F. et al. Genome of Spea multiplicata, a rapidly developing, phenotypically plastic, and desert-adapted spadefoot toad. G3 Genes Genomes Genetics 9(12), 39093919 (2019).

Article CAS PubMed PubMed Central Google Scholar

Novikova, P. Y. et al. Polyploidy breaks speciation barriers in Australian burrowing frogs Neobatrachus. PLoS Genet. 16(5), e1008769 (2020).

Article CAS PubMed PubMed Central Google Scholar

Session, A. M. et al. Genome evolution in the allotetraploid frog Xenopus laevis. Nature 538(7625), 336343 (2016).

Article ADS CAS PubMed PubMed Central Google Scholar

Pollard, M. O. et al. Long reads: Their purpose and place. Hum. Mol. Genet. 27(R2), R234-r241 (2018).

Article CAS PubMed PubMed Central Google Scholar

Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326(5950), 289293 (2009).

Article ADS CAS PubMed PubMed Central Google Scholar

Streicher, J. W. The genome sequence of the common frog, Rana temporaria Linnaeus 1758. Wellcome Open Res. 6, 286 (2021).

Article PubMed PubMed Central Google Scholar

Wang, G., Li, X. & Wang, Z. APD3: The antimicrobial peptide database as a tool for research and education. Nucleic Acids Res. 44(D1), D1087D1093 (2016).

Article CAS PubMed Google Scholar

Huan, Y. C. et al. Antimicrobial peptides: Classification, design, application and research progress in multiple fields. Front. Microbiol. 11, 582779 (2020).

Article PubMed PubMed Central Google Scholar

Hanson, M. A., Lemaitre, B. & Unckless, R. L. Dynamic evolution of antimicrobial peptides underscores trade-offs between immunity and ecological fitness. Front. Immunol. 10, 2620 (2019).

Article CAS PubMed PubMed Central Google Scholar

Mercer, D. K. et al. NP213 (Novexatin): A unique therapy candidate for onychomycosis with a differentiated safety and efficacy profile. Med. Mycol. 58(8), 10641072 (2020).

Article CAS PubMed PubMed Central Google Scholar

Ridyard, K. E. & Overhage, J. The potential of human peptide LL-37 as an antimicrobial and anti-biofilm agent. Antibiotics 10(6), 650 (2021).

Article CAS PubMed PubMed Central Google Scholar

Wang, Q. et al. Diversity of antimicrobial peptides in three partially sympatric frog species in Northeast Asia and implications for evolution. Genes (Basel) 11(2), 158 (2020).

Article MathSciNet PubMed PubMed Central Google Scholar

Varga, J. F. A., Bui-Marinos, M. P. & Katzenback, B. A. Frog skin innate immune defences: Sensing and surviving pathogens. Front. Immunol. 9, 3128 (2018).

Article CAS PubMed Google Scholar

Ladram, A. & Nicolas, P. Antimicrobial peptides from frog skin: Biodiversity and therapeutic promises. Front. Biosci. Landmark 21, 13411371 (2016).

Article CAS Google Scholar

Novkovi, M. et al. DADP: The database of anuran defense peptides. Bioinformatics 28(10), 14061407 (2012).

Article PubMed Google Scholar

Yang, Y. et al. A non-bactericidal cathelicidin provides prophylactic efficacy against bacterial infection by driving phagocyte influx. eLife 11, e72849 (2022).

Article CAS PubMed PubMed Central Google Scholar

Hao, X. et al. Amphibian cathelicidin fills the evolutionary gap of cathelicidin in vertebrate. Amino Acids 43(2), 677685 (2012).

Article CAS PubMed Google Scholar

He, X. et al. A frog-derived immunomodulatory peptide promotes cutaneous wound healing by regulating cellular response. Front. Immunol. 10, 2421 (2019).

Article CAS PubMed PubMed Central Google Scholar

Peel, E. et al. Cathelicidins in the Tasmanian devil (Sarcophilus harrisii). Sci. Rep. 6, 35019 (2016).

Article ADS CAS PubMed PubMed Central Google Scholar

Dalla Valle, L. et al. Bioinformatic and molecular characterization of beta-defensins-like peptides isolated from the green lizard Anolis carolinensis. Dev. Comp. Immunol. 36(1), 222229 (2012).

Article CAS PubMed Google Scholar

Wang, M. et al. Identification and characterization of antimicrobial peptides from butterflies: An integrated bioinformatics and experimental study. Front. Microbiol. 12, 720381 (2021).

Article ADS PubMed PubMed Central Google Scholar

Prez de la Lastra, J. M. et al. Bioinformatic analysis of genome-predicted bat cathelicidins. Molecules 26(6), 1811 (2021).

Article PubMed PubMed Central Google Scholar

Yoo, W. G. et al. Genome-wide identification of antimicrobial peptides in the liver fluke, Clonorchis sinensis. Bioinformation 11(1), 1720 (2015).

Article PubMed PubMed Central Google Scholar

Brennan, I. G. et al. Populating a continent: Phylogenomics reveal the timing of Australian frog diversification. Syst. Biol. https://doi.org/10.1093/sysbio/syad048 (2023).

Article PubMed Google Scholar

Irisarri, I. et al. The origin of modern frogs (Neobatrachia) was accompanied by acceleration in mitochondrial and nuclear substitution rates. BMC Genomics 13(1), 626 (2012).

Article PubMed PubMed Central Google Scholar

Mahony, M. et al. A new species of barred frog, Mixophyes (Anura: Myobatrachidae) from south-eastern Australia identified by molecular genetic analyses. Zootaxa 5297, 301336 (2023).

Article PubMed Google Scholar

Barker, J., Grigg, G. & Tyler, M. J. A Field Guide to Australian frogs (Surrey Beatty and Sons, 1995).

Google Scholar

Cogger, H. G. Reptiles and Amphibians of Australia 6th edn. (Reed New Holland, 2000).

Google Scholar

Murray, B. R. & Hose, G. C. Life-history and ecological correlates of decline and extinction in the endemic Australian frog fauna. Austral Ecol. 30(5), 564571 (2005).

Article Google Scholar

Woodhams, D. C. et al. Resistance to chytridiomycosis varies among amphibian species and is correlated with skin peptide defenses. Anim. Conserv. 10(4), 409417 (2007).

Article Google Scholar

Hollanders, M. et al. Recovered frog populations coexist with endemic Batrachochytrium dendrobatidis despite load-dependent mortality. Ecol. Appl. 33(1), e2724 (2023).

Article PubMed Google Scholar

Grant, J. R. et al. Proksee: In-depth characterization and visualization of bacterial genomes. Nucleic Acids Res. 51(W1), W484-w492 (2023).

Article PubMed PubMed Central Google Scholar

Simo, F. A. et al. BUSCO: Assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31(19), 32103212 (2015).

Article PubMed Google Scholar

Donnellan, S. C., Mahony, M. J. & Davies, M. A new species of mixophyes (Anura: Leptodactylidae) and first record of the genus in New Guinea. Herpetologica 46(3), 266274 (1990).

Google Scholar

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