Category Archives: Genome

NEW YORK An analysis of monkeypox virus (MPXV) genomes from the ongoing global outbreak has found that the samples cluster together, indicating a single origin for them.

Between the beginning of the year and the middle of June, there have been more than 2,100 laboratory-confirmed cases of monkeypox, most of which have been reported since the start of May, according to the World Health Organization. More than 80 percent of these cases have been reported in Europe and 12 percent in the Americas, where the virus is not endemic and the cases have no known links to endemic regions.

Researchers in Portugal where there have been about 300 cases, according to the European Centre for Disease Prevention and Control have now conducted a phylogenetic analysis of 2022 MPXV and found that the outbreak likely has a single source related to a 2017/2018 outbreak in Nigeria. They additionally reported in Nature Medicine on Friday that the virus samples appeared to be undergoing accelerated evolution, likely influenced by host APOBEC3, a class of mRNA-editing enzymes that help defend against viruses.

"The accelerated evolution is an observation, but we do not know yet how that happened. It was quite unexpected to find so many mutations in the 2022 MPXV," senior author Joo Paulo Gomes from the National Institute of Health Doutor Ricardo Jorge in Lisbon said in an email.

He and his colleagues analyzed the first 2022 MPXV genome from the outbreak, which they released publicly on May 19, in conjunction with 14 other MPXVgenome sequences, most of which were also from Portugal.

A phylogenetic analysis placed the 2022 outbreak samples among clade 3, within what was formerly known as the "West African" clade. All the outbreak samples clustered tightly together, indicating a single origin for the ongoing outbreak.

At the same time, the outbreak samples formed a branch that diverges from viruses linked to cases in the UK, Israel, and Singapore in 2018 and 2019, which themselves stemmed from an outbreak in Nigeria from 2017/2018. This suggested to the researchers that the 2022 outbreak could be due to the continuous circulation and evolution of the virus from the Nigeria outbreak.

However, 2022 MPXV differs from the 2018/2019 virus by an average 50 SNPs, which Gomes noted is many more than expected. For this type of virus, he said, one or two mutations would be expected to arise each year. As 2022 MPXV is likely a descendant of the 2017/2018 Nigeria outbreak which led to the UK, Israel, and Singapore cases in 2018/2019 about 5 to 10 additional mutations would be expected, not 50.

"So, unquestionably, we are facing a scenario of accelerated evolution," Gomes said.

The changes also tended to follow a certain pattern of incorporating more adenines and thymines into an already A/T-rich viral genome, which suggested that the human APOBEC3 system could be involved in this accelerated evolution.

APOBEC3 is a host antiviral mechanism that induces mutations into viruses, but that could lead to hypermutation if the enzymes do not fully restrict the viruses. Gomes noted that this mechanism has already been described in HIV and HPV.

"We do not know about the consequences but we know, for instance, that [a number] of these mutations are affecting viral proteins that are associated with the interaction with the human immune system, so, hypothetically, a mechanism of immune evasion cannot be completely discarded," he added.

In all, the researchers said that viral genome sequencing of outbreak samples may enable scientists to better understand how 2022 MPXV is spreading and provide insight into ways to control that spread. "We will focus on identifying and monitoring the mutations that will arise in real time during the ongoing transmission in order to better understand the host adaptation," Gomes said.

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Monkeypox Genome Analysis Points to Single Origin of Recent Outbreak - GenomeWeb

An illustration of Demodex folliculorum. Photo: Shutterstock (Shutterstock)

Scientists have finally unraveled the genetic secrets of humanitys coziest roommates: Demodex folliculorum, also known as the skin mite. Among other things, the findings confirm that these mites actually do have anuses, contrary to previous speculation. They also indicate that the microscopic animals may not be as potentially harmful as commonly thought and that theyre evolving into co-dependent, symbiotic creatures that might provide us some benefits to boot.

D. folliculorum is actually one of two mite species that call us home, along with Demodex brevis. Both species are arachnidsmore closely related to ticks than spidersbut D. folliculorum mites are the ones that usually reside (and mate) on our faces. These stubby worm-shaped critters live for two to three weeks, all the while embedded in our pores, clinging to our hair follicles, and primarily feeding off our sebum, the oily substance provided by our body to protect and moisturize the skin.

Despite virtually every person in the world having their own mite collection, theres still much we dont understand about them. But in a new study published Tuesday in the journal Molecular Biology and Evolution, researchers in Europe say theyve now fully sequenced the genome of D. folliculoruman accomplishment that might answer some lingering questions about their inner workings.

Some researchers have argued, for instance, that these mites lack an anus. Without an anus, the theory goes, their fecal waste simply accumulates inside them over their brief lifespan and is only released all at once when they die. Some have also speculated that an overabundance of mites can cause a skin condition known as rosacea, perhaps due to bacteria thats released from this explosion of poop upon a mites death. Other research has cast doubt on that claim, though, and the researchers behind the new study say theyve confirmed that mites do indeed have an anus.

Study author Alejandra Perotti, a researcher at the University of Reading in the UK, notes that the larger presence of mites in people who develop rosacea and other skin conditions may very well be a consequence of the condition and not its actual cause. And if mites arent leaving behind huge amounts of poop behind when they die, then theres a less clear rationale as to how they would make us sick in the first place. Other studies, for what its worth, have continued to find a link between the mites and rosacea, though they may only be one of many triggersinvolved.

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It is easier and faster to just blame the mites, she said in an email to Gizmodo.

The teams other findings show that these mites have evolved to become incredibly lazy, genetically speaking, as a result of hitching their wagon to humans. They have a very simple genome compared to other related species, and they seem to be surviving with the bare minimum of cells and proteins needed to function (Their leg pairs are even powered by a single muscle cell each). Theyve lost the ability to survive exposure to ultraviolet light, which explains why they hunker deep down into our pores and only move and mate at night, and they dont appear to even produce their own melatonin anymore, like many animals doinstead, they seem to mooch it from us. Theyre also passed down from mother to child, often through breastfeeding, meaning that populations have relatively low genetic diversity. And their lack of natural predators, host competition, and generally sheltered existence suggests that the mites are only likely to lose more genes over time.

The researchers theorize that these trends could one day lead to the end of D. folliculorum mites as a distinct entitya process thats been observed with bacteria but never an animal, they say. Eventually, the mites might no longer live externally on our skin as parasites but instead become wholly internal symbiotes. If so, then we might be seeing that transition taking place now, though this transformation likely wouldnt be finished for a long time.

Regardless of the future fate of these mites, the scientists say theyre perhaps doing some good for us now. They might help clear the skin of excess dead cells and other materials, for instance, at least when their populations are kept in check. Perotti also hopes that their research will provide people proper knowledge of these permanent companions, which have been blamed too long for our skin problems.

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The Mites That Live and Breed on Your Face Have Anuses, Genome Study Finds - Gizmodo

Breadcrumb Trail Links

Genome B.C.'s boss talks about how his agency's work helps people he and elsewhere

Author of the article:

Do you know your As, Cs, Gs and Ts?

They are the four types of bases in a DNA molecule which consists of two strands wound around each other to form an organisms complete set of DNA, called its genome.

DNA carries the instructions for making specific proteins or sets of proteins. There are about 20,000 genes in the human genome located on 23 pairs of chromosomes which are packed into the nucleus of a human cell.

Its remarkably complex and remarkably important, says Pascal Spothelfer, CEO of Genome B.C., as we move toward a future that will allow us to make informed and specific decisions about our health, the health of all other living beings, plants and the environment.

Here in Vancouver, Genome B.C. has been leading the way in the expansion of knowledge and specific beneficial advances in science and technology. COVID- 19 research was one such benefactor.

Pascal Spothelfer joined a Conversation That Matters about the role Genome B.C. is playing in our lives and in the expansion of scientific research and biomedical technology.

You can join a Conversations Live event. Sign up for advance notice about upcoming events at ohboy.ca/conversations.

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Conversations That Matter: Knowing your genome - Vancouver Sun

Index case and named contact partner epidemiology

In December 2020, researchers and public health officials in the United Kingdom identified a rapidly spreading SARS-CoV-2 variant within England, then designated as PANGO lineage B.1.1.721, now designated as the Alpha variant of concern in the WHO nomenclature. In NYC, a SARS-CoV-2 genome sequence classified as belonging to the Alpha lineage was obtained from a sample on 4 January 2021 (the index case): NYCPHL-002130 (GISAID accession number EPI_ISL_857200). Due to the potential public health importance of Alpha variant cases in NYC in early 2021, NYC DOHMH conducted a public health investigation related to the individual from which this sample had been obtained. This investigation determined that the individual had recently traveled to Ghana (late December/early January) and developed symptoms consistent with COVID-19 while in Ghana. Contact tracing in New York City identified another case of an Alpha variant infection, sampled on 14 January 2021, in a named contact with a similar travel history (the named contact partner): NYCPHL-002461 (GISAID accession EPI_ISL_883324). The named contact partner had also developed symptoms consistent with COVID-19 while in Ghana, prior to returning the United States.

Typical of the Alpha variant21, NYCPHL-002130 from the index case exhibited S gene target failure (SGTF) phenotype with the TaqPath COVID-19 RT-PCR assay (Table1). NYC PHL uses the ARTIC amplicon-based protocol V3 to sequence full viral genomes and capture intra-host diversity. All 24 mutations diagnostic of the Alpha variant were found in >90% of reads (Table2). The viral genome from this index case showed limited intra-host viral diversity (Fig.1). A single variable site was found at position 23099, with C in 20.4% of reads and A in 79.6% of reads.

Frequencies of individual alleles shown as ticks, a smoothed kernel density plot is used to highlight clustering patterns, and colors represent allele types.

During the initial PCR screening of the sample collected from the named contact partner (NYCPHL-002461-A), the SGTF characteristic of the Alpha variant was not observed (Table1). Furthermore, genome sequencing revealed substantial intra-host viral diversity within the viral genome, a possible signature of superinfection (Fig.1). To confirm that this intra-host diversity was not attributable to experimental or sequencing artifacts, the original sample was re-extracted and re-sequenced (NYCPHL-002461-B) and similar SGTF was observed. Additional extractions were then performed in duplicate from the original stock (NYCPHL-002461-C and -D) and sequenced. The same signature of intra-host diversity was confirmed in all four sequenced extractions. Four nucleotide (nt) substitutions differentiating this sequence from the reference genome were identified at >90% frequency: C241T, C3037T, C14408T, and A23403G (Fig.1; Table2). These four substitutions were all present in the lineage B.1 virus that is ancestral to the named SARS-CoV-2 variants. Numerous additional substitutions, including A23063T (S N501Y), were present, but at slightly lower frequencies. Nonetheless, this genome was classified as an Alpha variant. Notably, the 69/70 and 144 deletions were found at >97% in the sequencing reads, despite the lack of SGTF.

NYCPHL-002461-A, -B, and -D extracts exhibited low Ct values for the ORF1ab and N gene targets, ranging between 15 and 16 (Table1). The S gene target Ct values were around 2 to 3 cycles higher. The difference suggests a reduction of viral template in the S gene target region, but not SGTF. We note NYCPHL-002461-C yielded an invalid result, as the TaqPath assay showed no amplification on all targets, including the MS2 phage extraction-control target.

The presence of multiple intermediate frequency alleles and the lack of SGTF in the TaqPath assay prompted us to investigate the intra-host diversity in the named contact partner, NYCPHL-002461. Using the previously described and validated Galaxy SARS-CoV-2 allelic variation pipeline22, we identified four categories of allelic frequencies: shared, major strain, minor strain, and other (see Fig.1, interactive notebook at https://observablehq.com/@spond/nyc-superinfection). The four replicate sequencing runs for NYCPHL-002461 yielded remarkably similar patterns of these allelic frequencies.

Alleles that fell into the shared category were present at 90% allele frequency in three or more samples. Shared alleles included all four substitutions characteristic of B.1 (Table2) and two deletions in the S gene (69-70 and 144) diagnostic of the Alpha variant.

Major strain occurred at frequencies between 60 and 80% (in at least 3 samples). Major alleles included all 21 substitutions defining the Alpha variant, which we observed at a median allele frequency of 74.1%, and ORF1A deletion (Table2). The remaining major alleles are shared with genome from the index case.

Minor strain alleles occurred at frequencies between 10 and 25% (in at least 3 samples). All but one of the 12 diagnostic Epsilon mutations was found in this set: A28272T is absent in NYCPHL-002461. All remaining minor alleles have been observed in other Epsilon genomes.

The other category encompasses all other variable sites, i.e. those occurring at frequency between 25 and 60% or those found in only one or two samples. The two alleles were found in all four replicate sequences at intermediate frequencies: G7723A (30.3%) and C23099A (46.7%). These frequencies are suggestive of intra-host variation in the major strain.

In contrast to the allelic mixture detected in the named partner (NYCPHL-002461), we observed allele frequencies >90% for all Alpha defining mutations in the sequencing data for the index case, NYCPHL-002130 (Table2). The C23099A mutation, which was at intermediate frequency in NYCPHL-002461 from the named contact partner, was present at 88.1% in NYCPHL-002130 from the index case, consistent with the transmission of a mixed viral population between these individuals.

We identified sub-clades within Alpha and Epsilon that shared substitutions with the major and minor strains (Fig.2). We inferred a maximum likelihood (ML) phylogenetic tree in IQTree2 for the major strain and 3655 related Alpha (B.1.1.7) genomes containing the C2110T, C14120T, C19390T, and T7984C substitutions found in the major strain (Fig.2A). We also inferred an ML tree for the minor strain and 2275 related Epsilon (B.1.429) genomes containing the C8947T, C12100T, and C10641T substitutions found in the minor strain (Fig.2C).

A Phylogeny of Alpha variant immediate relatives. B Root-to-tip regression for Alpha variant. C Phylogeny of Epsilon variant immediate relatives. D Root-to-tip regression for Epsilon variant. NY-NYCPHL-002461 is the genome deposited in GISAID from the case of putative superinfection.NY-NYCPHL-002130 is the genome from the index case.

Root-to-tip regression analyses show that the NYCPHL-002461 sampling date is consistent with the molecular clock for both the major and minor strain sequences (Fig.2B/D), indicating that one would expect viruses of this degree of genetic divergence to have been circulating in mid-January 2021. In fact, genomes identical to the major variant were sampled in both NYC (the NYCPHL-002130 index case) and in Ghana on 8 January 2021 (EPI_ISL_944711), consistent with a scenario in which this particular Alpha virus was acquired in Ghana. These three viruses share a common ancestor around 4 January 2021 and are separated from additional viruses sampled in Ghana by two mutations: C912T and C23099A. Notably, the latter mutation appears at intermediate frequency in both NYCPHL-002130 and NYCPHL-002461.

The minor variant is genetically distinct from all other sampled genomes, including any genome sequenced by NYC DOHMH (Fig.2C). The closest relatives were sampled in California (EPI_ISL_3316023, EPI_ILS_1254173, EPI_ISL_2825578), the United Kingdom (EPI_ILS_873881), and Cameroon (EPI_ISL_1790107, EPI_ISL_1790108, EPI_ISL_1790109). The most similar of these relatives is EPI_ISL_3316023, which was sampled on 11 January 2021 in California and represents the direct ancestor of the minor variant on the phylogeny. The only mutation separating this California genome from the minor variant is T28272A, which is a reversion away from an Epsilon-defining mutation (Table2).

It is unlikely that this minor variant is a laboratory contaminant, as there are no closely related Epsilon genomes sequenced from NYC. That said, NYC represents the probable source of this Epsilon virus. Of the 145 SARS-CoV-2 genomes sequenced by NYC public health surveillance between 10 January 2020 through 16 January 2020, 4 (2.8%) were Epsilon. A similar proportion of Epsilon genomes deposited in GISAID were sampled by other labs during this same period: 11 out of 431 genomes (2.6%)23. No Epsilon genome has been reported to date from Ghana.

A preliminary inquiry of the genome sequencing data from the S gene (12 contiguous read fragments) and N gene (nucleoprotein; 3 contiguous read fragments) regions was suggestive of recombinant genome fragments within the named contact partner. To determine whether pairs of polymorphic sites within individual read fragments displayed evidence of recombination we employed three different four-gamete based recombination detection tests: PHI24, MCL, and R2 vs Dist25 (Table3). The power of each of these tests to detect recombination was seriously constrained by the short lengths of the read fragments and the low numbers of both variant-defining sites and other polymorphic sites with minor allele frequencies >1% within each of the fragments. Only three of the 15 read fragments (read fragments 6 and 8 in the S gene and read fragment 3 in the N-gene) encompassed two or more of the variant-defining sites that were expected to provide the best opportunities to detect recombination. Nevertheless, pairs of sites within four read fragments in the S gene (positions 2312324467 covering fragments 7, 8, 9 and 10) and one read fragment in the nucleoprotein gene (positions 2898629378 covering fragment 3) exhibited signals of significant phylogenetic incompatibility with at least two of the three tests (p<0.05): signals which are consistent with recombination. The only read fragment for which evidence of recombination was supported by all three tests was fragment 3 in the N gene: a fragment that was one among only three that contained multiple variant-defining substitutions. Eight of the fifteen analyzed read-fragment alignments exhibited no signals of recombination using any of the tests, which is unsurprising given the lack within these fragments of both variant-defining substitutions and polymorphic sites with minor allele frequencies greater than 1%.

The four gamete tests on genomic sequencing data is limited by the short length of amplified fragments. To obtain data from longer sequence fragments, we PCR-amplified three regions of the genome from the original nucleic acid extracts, cloned them, and then sequenced individual clones. These longer genomic fragments provide greater resolution for detecting recombination, compared with the short fragments from deep sequencing analysis, because they include more differentiating sites spread out farther across the genome.

The longest cloned region spanned 947 nt within the S gene (positions 2290423850) and contained 5 nt substitutions differentiating the major and minor strains plus a variable site in the major variant. Of the 104 clones sequenced within this region, 60 (57.7%) were major strain haplotypes, 13 (12.5%) were minor strain haplotypes, whereas the remaining 31 clones (29.8%) contained both major and minor strain mutations, consistent with recombination (Fig.3). We observed 11 distinct combinations of major and minor strain mutations across these clones, with two distinct haplotypes present in 6 clones apiece. Most recombinant haplotypes (n=24) are consistent with only a single recombination breakpoint. However, 7 clones are consistent with 2 breakpoints (representing 3 different haplotypes), and 1 clone is consistent with 3 distinct breakpoints.

Each row represents a sequenced clone (n=104). Colored markings denote mutations from the reference genome. Major strain mutations are those found in the Alpha variant. Minor strain mutations are those found in Epsilon variant. Other mutations are found at intermediate or low frequencies. Shared mutations are those shared by B.1 viruses.

The second cloned S region spanned 657 nt in the S gene (positions 2144222098) including the 6970 and 144 deletions characteristic of the major strain and two 2 substitutions in the minor strain. Of the 93 clones sequenced, 69 (74.1%) were major strain haplotypes, 17 (18.3%) were minor strain haplotypes, and 7 (7.5%) were mixed haplotypes (Fig.4). Five of these mixed haplotypes contained only one of the two deletions. One mixed haplotype was consistent with multiple recombination breakpoints. Unlike in the primary sequencing analyses where the 6970 and 144 deletions were present in >98% of sequences, 69-70 was observed in only 72 (77.4%) clones and 144 was observed in only 71 (76.3%). These frequencies are consistent with the frequency of the other major strain substitutions in the primary sequencing analysis.

Each row represents a sequenced clone (n=93). Colored markings denote mutations from the reference genome. Major strain mutations are those found in the Alpha variant. Minor strain mutations are those found in Epsilon variant. Other mutations are found at intermediate or low frequencies.

The third, and shortest, cloned region spanned 476 nt of ORF8 (positions 2779828273), surrounding 4 substitutions defining the major strain and 1 minor strain substitution. Of the 36 cloned sequences, 30 (83.3%) had the major strain haplotype, 2 (5.6%) had the minor variant haplotype, and 4 (11.1%) had mixed haplotypes consistent with a single recombination breakpoint (Fig.5). Note the discriminating substitutions only span 223 nt of this region.

Each row represents a sequenced clone (n=36). Colored markings denote mutations from the reference genome. Major strain mutations are those found in the Alpha variant. Minor strain mutations are those found in Epsilon variant. Other mutations are found at intermediate or low frequencies.

Three cloned sequences from the 947 nt S gene fragment contained single nucleotide deletions resulting in non-sense mutations. In the 657 nt S gene fragment, we observed 8 clones with similar deletions, detected in both the forward and reverse direction during sequencing. These deletions were seen in the non-recombinant Alpha and Epsilon haplotypes and likely reflect non-functional viral particles, expected to constitute a substantial fraction of genomes within an infected individual26,27.

In vitro recombination can be introduced by reverse-transcription and PCR amplification, which are part of both genome sequencing and cloning protocols28. These in vitro effects have a strong stochastic component and would result in substantially different recombinant haplotype frequencies across different extracts and PCR experiments. To determine the extent to which these protocols could have led to biased inference of recombination, we compared the haplotype frequencies across the four extracts from NYCPHL-002461, which had each independently been subjected to reverse transcription and PCR amplification, and the frequency of these haplotypes in the cloning experiment, which included PCR amplification.

Within the 947 nt cloned S gene fragment, the major haplotype was present between 76.4% and 78.6%, and the minor haplotype was between 13.7% and 15.4% (Supplementary Table1). The recombinant haplotype positions 23604A and 23709C was present at 3.9% allele frequency (standard deviation of 0.34% across extracts), whereas recombinant haplotype 23604C and 23709T was present at 4.3% (standard deviation of 0.37% across extracts). Although the haplotype frequencies among extracts were significantly different (p=0.029; chi-square test), the magnitude of these differences were unremarkable. Furthermore, there was no significant difference between the frequency of these haplotypes in cloning experiment and extracts (p=0.190 versus -A; p=0.189 versus -B; p=0.357 versus -C; p=0.206 versus -D; Fishers Exact Test).

A similar pattern was observed within the 476 nt cloned fragment in the ORF8 region, which included four discrimination sites: 27972, 28048, 28095, and 28111 (Supplementary Table2). The predominant recombinant haplotypes were consistent across the four extracts, and the frequencies differed only slightly (p=0.077; chi-square test). As in S, the frequency of these recombinant haplotypes in the cloning experiment was not significantly different from any of the extracts (p=0.405 versus -A; p=0.413 versus -B; p=0.199 versus -C; p=0.408 versus -D; Fishers exact test).

Hence, in vitro recombination induced by either reverse-transcription or PCR amplification, does not appear to have been the dominant contributor to the recombinant haplotype distribution reported here.

To determine whether there was onward transmission of a recombinant descendent of these major and minor strains, we queried the 27,806 genomes sequenced by NYC public health surveillance and deposited to GISAID through 5 September 2021. We tested these genomes for mosaicism (3SEQ29; with Dunn-Sidak correction for multiple comparisons) of the major and minor strains; however, we were unable to reject the null hypothesis of non-reticulate evolution for any of these genomes. We also did not find any genomes in the PHL dataset with a superset of the identifying substitutions present in the major and minor variants (e.g., C912T and C27406G) among the genomes in the PHL dataset. There is no evidence of an Alpha/Epsilon recombinant that circulated in New York City.

Since the Dunn-Sidak correction done in the 3SEQ analysis applies a conservative type-1 error threshold of 0.05, we reran the analysis using a more permissive threshold of 0.25 (see methods) and were able to reject the null hypothesis for a single genome (EPI_ISL_2965250; p=2.24106 and Dunn-Sidak corrected p=0.117). Although this genome (Fig.6) contains many of the mutations characteristic of the Alpha variant throughout the genome, it does not possess mutations unique to the major strain nor any Epsilon-specific mutations. Rather, within the putative recombinant regions, the EPI_ISL_2965250 genome has C8809T, C27925T, C28311T, and T28879G. All of these mutations are characteristic of the B.1.526 Iota-variant, prevalent in NYC in early 2021. Therefore, this genome is likely not a descendant of the major and minor strains. Instead it appears to be a recombinant descendant of Alpha and Iota viruses.

The distribution of the nucleotide variation found in the major, minor, Iota (B.1.526; EPI_ISL_1635735), and single putative recombinant (EPI_ISL_2965250) strains relative to the reference genome (Wuhan Hu-1; bottom gray sequence).

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Detection of SARS-CoV-2 intra-host recombination during superinfection with Alpha and Epsilon variants in New York City - Nature.com

The oversubscribed series B financing led by Healthcare Venture Partners, added SoftBank Corp. and Natera to existing investors Sequoia Capital, Foresite Capital, Founders Fund, among others

MENLO PARK, Calif., June 21, 2022 /PRNewswire/ --MyOme, a clinical whole genome platform analysis company, today announced that the company has raised $23 million in an oversubscribed series B financing round led by Healthcare Venture Partners, bringing the total raised to over $36M. MyOme plans to use the funds to begin commercialization of their clinical whole genome analysis platform technology and clinical reports to health systems. The MyOme platform will help families understand and manage their risk for inherited disease.

"Through whole genome analysis, MyOme will address the large market of predominantly healthy individuals who have known disease susceptibility in their family that can be preventatively managed or better cared for today with genetic insights, but who don't have a known rare genetic mutation," said Premal Shah, PhD, CEO of MyOme. "Moving forward, the whole genome backbone enables the delivery of future genomic reports on-demand for a lifetime of insights."

MyOme recently presented new data at the 2022 American Society of Clinical Oncology Annual Meeting on the performance of an enhanced cross-ancestry polygenic risk score (PRS) to improve breast cancer risk assessment for women across multiple ethnicities. These advanced technologies can be broadly applied across many diseases. MyOme also published data in Nature Medicine on their clinical study using whole genome reconstruction for application of PRS to in-vitro fertilization across cancers and cardiac, metabolic, and autoimmune diseases.

"The power of the whole genome has not yet been fully realized," said Matthew Rabinowitz, PhD, co-founder and chairman of MyOme. "Most common disease is not caused by single genes, but by an interaction of many genes and the environment.Whole genome analysis and PRStechnologies are accelerating and will play an increasingly crucial role in healthcare. MyOme is at the forefront of developing clinical applications to support families of all ethnicities."

"MyOme is building the future where best-in-class genomic platforms and tools can lead to a better understanding of disease with a meaningful impact on human health," said Michael Mashaal, MD, senior managing director ofHealthcare Venture Partners. "We are committed to supporting them in this endeavor and believe in their team of leading visionaries and bioinformaticians with extensive experience in developing innovative genomic products."

MyOme was founded by leaders in the field of genomics, including Matthew Rabinowitz, co-founder of Natera.

About MyOme

MyOme is a clinical whole genome analysis platform company helping families understand their risk for inherited diseases. MyOme leverages the power of the whole genome for a lifetime of actionable insights. Certified under the Clinical Laboratory Improvement Amendments (CLIA), MyOme is based in Menlo Park, California. For more information, visit myome.com.

SOURCE MyOme, Inc

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MyOme Secures $23M in Series B Funding to Deliver Clinical Whole Genome Insights to Help Families Manage Risk for Inherited Diseases - PR Newswire

10 million sequences of COVID-19s genomic code have now been organized into a phylogenetic tree in the UC Santa Cruz SARS-CoV-2 Browser, which is the largest tree of genomic sequences of a single species ever assembled. This accomplishment is impressive for both the computer engineering feat of processing such a massive amount of data and the incredible dedication and coordination of the researchers involved.

It is an astounding thing that has happened there, said Clay Fischer, Project Manager for the UCSC Genome Browser.

All of these sequences are assembled by the researchers into a phylogenetic tree that shows the evolutionary history of the virus, with different branches representing the lineages that have mutated throughout the pandemic. This tree is powered by a software tool called UShER that was developed at the UC Santa Cruz Genomics Institute and is hosted on the UCSC Genome Browser website.

Many hands from around the world have brought the Genomics Institute these 10 million sequences that live on the UShER tree. Clinicians worldwide have administered tests to be sent off to local labs, which then sent the samples on for sequencing. Once they are sequenced, they become digital files that are uploaded to databases for genomic information such as GISAID, GenBank, or the COG-UK database.

Angie Hinrichs, a senior software architect at the UCSC Genome Browser and self-described data wrangler, built a pipeline to pull these sequences into the UShER tree automatically. But this process was complicated as some databases, like GISAID, had restrictions that necessitated the manual download of sequences.

For the first half of 2021, I would download them every night before bed, Hinrichs said.

Hinrichs has worked at the UCSC Genome Browser for twenty years. She keeps a low profile, usually preferring to work behind the scenes than in the spotlight. But according to her colleagues, her work curating the tree of COVID-19 genomes and coordinating with the CDC and other health organizations has been of great importance to the pandemic relief effort. She is a part of the Pango team of volunteers who have been monitoring virus sequences to identify new variants. She takes on the ongoing, daily maintenance of updating and annotating the UShER tree, which recently became the default software used by the Pangolin tool, a system used by health officials worldwide to track the spread of variants in their community.

UShER was created early in the pandemic, when researchers at the UC Santa Cruz Genomics Institute recognized that tracing the evolution of a quickly evolving global pathogen like COVID-19 would require a phylogenetic tree that was able to handle an unprecedented amount of data. So, the Genomics Institutes scientific director David Haussler gathered together a team to focus on pathogen genomics, led by Assistant Professor of Biomolecular Engineering Russell Corbett-Detig and including then-postdoc Yatish Turakhia. Turakhia originally wrote the UShER software, which has the ability to rapidly add a new genome sequence to a very large tree of genome sequences.

Making a tree that can handle so much data is an incredible feat of computer engineering that has required herculean efforts from a number of researchers. Before the current pandemic, phylogenetic trees for comparing viral samples were relatively common, but they were built from comparatively small numbers of sequences.

As unprecedented numbers of SARS-CoV-2 sequences became available, the standard tree-building tools simply could not keep up, and researchers often struggled to make sure their analysis kept pace with the amount of samples they would receive. UShERs software and the sustained effort of the team made it possible to grow the tree apace with the pandemics flood of sequences.

Hinrichs says that her two decades of experience working with the massive amounts of data stored on the UCSC Genome Browser helped prepare her to work with the COVID-19 lineages on UShER.

This data coordination is what makes our resources really powerful, Hinrichs said. We have really great resources here, and really great people.

One of those great resources is UCSCs amazing computing hardware maintained by Jorge Garcia, Haifang Telc, and Erich Weiler. Hinrichs explained that having that computing power has been essential for this project.

Big data is our thing, so we were ready to jump on this, she said.

At the beginning of the pandemic, the UCSC pathogen genomics team made guesses as to how many COVID-19 sequences the tree would need to be able to handle. Only Corbett-Detig thought it would reach a million no one anticipated reaching 10 million.

I still get surprised at how far weve come, Turakhia said. The unimaginable amount of data we were able to handle and the fact that we are able to make sense of it quickly is mind-boggling as a computational genomicist.

As the tree has grown, it has required constant attention and updates. Cheng Ye, an undergrad in Turakhias new lab at UC San Diego, was also able to figure out a way to add new sequences faster when the tree had grown to contain millions of sequences already, and helped develop a tool called MatOptimize that moves sequences around on the tree when more data makes it apparent that the original placement was less optimal.

Accumulating reliable data has been instrumental to better understanding what we are up against in the fight against COVID-19 and all its variants. While little was known about this virus at the start of the pandemic, the tree-building tools developed at UC Santa Cruz have helped to put the history of the virus in some perspective and to predict its future, and researchers across campus have leveraged their expertise to aid in the relief efforts. The progress has been astounding; but for the researchers on the browser team, the urgency of their mission and the sheer amount of data that needs to be curated has also been overwhelming at times. Fischer acknowledges that this level of dedication comes at a cost.

It has been two years of blood, sweat, and tears, he said.

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The team behind a tree of 10 million Covid sequences - University of California, Santa Cruz

by Dr. Surendra K Chikara

Everyones DNA is as unique as their fingerprint. Information about a persons genes, environment and lifestyle factors can be used to prevent or manage disease and this is usually referred to as precision medicine. This form of personalized healthcare has been around for a few years and has been increasingly gaining popularity. Thanks to the Human Genome Project (1990-2003) that sequenced around 20,000 genes and created a breakthrough in healthcare. We are now able to use genomics to predict, prevent and manage disease better than ever.

As of today, we are experiencing a revolutionary shift towards precision medicine. We can quickly sequence DNA at a large scale and help thousands of people manage and prevent disease. Genomics has been especially valuable for identifying rare genetic diseases that had previously taken years to diagnose, ending uncertainty and suffering for many people.

In addition to reducing the risk of disease, genomic testing can serve as a source of data. Many organizations are now investing time and money into building databases of genetic biomarkers for various chronic diseases, so they can be identified early. Such databases could deliver a definitive diagnosis in seconds which could significantly bring down treatment costs at a global level.

The use of genomics in the healthcare industry has given a new perspective on managing disease; people are now focused on preventing disease rather than curing it. There are numerous start-ups that are working on utilizing genomic testing to prevent disease by helping people find the root cause of their health issues.

The need for preventive healthcareA World Economic Forum study estimates that the global economic impact of cancer, diabetes, mental illness, heart disease, and respiratory disease could reach USD 47 trillion over the next 20 years. The increased demand on healthcare systems could be lessened through breakthroughs like genomic testing because they make it possible to prevent disease.The growing prevalence of chronic diseases and demand for personalized medicine have contributed to the precision medicine market size to grow from USD 8.2 billion to 16.4 billion by 2025.

The Pandemic further proved to be an eye-opener for many people, especially those with chronic diseases, since they were prone to a higher risk for catching the virus and developing complications. This highlighted the immense need for preventing such diseases in the first place and further emphasized the importance of the need for preventive healthcare in the country.

Preventive healthcare is the future Genomics has created a shift in peoples mindset towards disease prevention. It has become increasingly clear in recent years that genomic testing and precision medicine is the wave of the future. Just like health insurance has now become commonplace in India, genomic testing would soon become the first line of defense against chronic disease. It is only a matter of time before genomic testing and thus precision medicine enters the mainstream of healthcare in India as well.

Dr. Surendra K Chikara - Founder & CEO - Bione

(DISCLAIMER: The views expressed are solely of the author and ETHealthworld does not necessarily subscribe to it. ETHealthworld.com shall not be responsible for any damage caused to any person / organisation directly or indirectly.)

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Genomics: A Revolution in Health Care? - ETHealthWorld

An appealing alternative to the Streptococcus pyogenes CRISPR nuclease SpyCas9, are Type V CRISPR Cas12a nucleases, commonly isolated from Acidaminococcus (Asp) and Lachnospiraceae (Lba). These Cas12a nucleases embody several desirable attributes that SpyCas9 lacks: they exhibit greater editing precision, recognize a thymine-rich PAM (protospacer adjacent motifa two-to-six base sequence following the nuclease target), use a single CRISPR-RNA to detect its target, cut DNA in a staggered fashion generating overhangs, process CRISPR arrays, and have been shown to function in diverse organisms ranging from plants to mammals. However, Cas12a nucleases exhibit lower editing rates than SpyCas9 in primary cells.

In a study published in GENmagazines sister journal,GEN Biotechnology (Optimization of Nuclear Localization Signal Composition Improves CRISPR-Cas12a Editing Rates in Human Primary Cells), Scot Wolfe, PhD, professor of molecular, cell and cancer biology at the University of Massachusetts Chan Medical School and his team, increased Cas12as on-target gene editing rate to nearly 100% by engineering the configuration of the enzymes nuclear localization signal (NLS). These advancements to the Cas12a editing framework could improve the use of this nuclease to uncover functions of new genes and develop new CRISPR-based treatments.

Previous work by our laboratories and others indicated that the efficiency of Cas12a editing in CD34+ hematopoietic stem and progenitor cells could potentially be improved by increasing the efficiency of its nuclear import, said Wolfe.

In earlier studies, Wolfes team had enhanced SpyCas9 gene editing in primary cells by optimizing the NLS sequence composition and number. They had found adding one NLS at the amino-terminus and two at the carboxy-terminus of the nuclease markedly improved SpyCas9s (3xNLS-SpyCas9) editing efficiency in hematopoietic stem and progenitor cells (HSPCs). They had then added two NLSs to the carboxy-terminus of Cas12a but did not achieve the same efficiency of targeted mutagenesis as the engineered SpyCas9 with three NLSs.

Ben Kleinstiver, PhD, assistant professor of pathology at Massachusetts General Hospital and Harvard Medical School, said, Genome editing efficiency is impacted by many different variables, including the concentration of a CRISPR-Cas enzyme in the nucleus where it performs its function. Researchers have previously dedicated substantial effort to improve CRISPR nuclease expression and nuclear localization for SpyCas9, but comparatively fewer optimizations have been performed for Cas12a. (Kleinstiver was not involved in the current study).

In the current study, Wolfes team developed three NLS C-terminus variants of Cas12a where they substituted the previously used simian virus NLS (SV40) with a more efficient NLS of a proto-oncogene (c-Myc). In addition, they added a third NLS to the carboxy end to achieve an editing platform at par with 3xNLS-SpyCas9 in editing efficiency. The researchers observed increased knockout efficiency in all three Cas12a orthologs (Asp, Lba, and engineered-Asp) they tested, which suggests this triple NLS strategy could be effective in improving the activity of other members of the Cas12a family, without decreasing the enzymes inherent specificity.

The study used standard electroporation to deliver the engineered Cas12a ribonucleoproteins (RNPs) into transformed human cells lines (HEK293T, Jurkat, and K562 cells) and into primary cells (natural killer cells and CD34+ HSPCs) to improve indel frequencies.

We believe that the improved NLS sequence architecture described in this paper will increase the efficiency of genome editing by Cas12a in primary cells, thus leading to increased levels of therapeutic genome editing in a variety of applications, said Wolfe. The researchers claim this strategy of enhancing the NLS sequence can be widely applied to other Cas12a orthologs and variants with similar outcomes.

The Wolfe lab and collaborators had previously demonstrated increased activity with a new NLS framework for SpyCas, so it is exciting that they demonstrated success with a new NLS for Cas12a in this publication. It is important to have additional NLSs to test in the growing list of nucleases and cell types, said Thomas Cradick, PhD, CSO at Excision BioTherapeutics. (Cradick was not involved in the current study.)

Kleinstiver said, Luk et al., demonstrated that the efficiency of editing with various Cas12a enzymes can be improved by using a more optimal configuration of NLSs. The effect of this optimization was most striking in lipid-based transfections (nucleofections) in transformed cell lines, with a more modest improvement in primary cells, the latter of which due to already high levels of editing in primary cells.

This study resurfaces a really important consideration, that you can only edit cells as efficiently as your enzyme is designed to. There are lots of knobs to turn to optimize and improve editing efficiency, and the NLS architecture clearly plays a key role in regulating the nuclear concentration, and thus the potency, of the editor, added Kleinstiver.

Nicole Gaudelli, PhD, director and head of gene editing platform technologies at Beam Therapeutics, who was not involved in the current study, said, In addition to advancing Cas12a gene editing applications, these learnings may potentially be evaluated for other gene editing tools to further increase editing efficiencies and provide greater therapeutic benefit if higher levels of gene correction or modification can be achieved.

This study was rigorously done in multiple cell types that show the robustness of the data. I liked how they delivered Cas12 as an RNP, as this is therapeutically relevant and greatly reduces off-target editing, said Alexis Komor, PhD, assistant professor of chemistry and biochemistry at the University of California, San Diego, who was not involved in the study.

I also liked this work because it uses a very universal approach to improve editing (the modifications they made to the system can be applied to any genome editing agent), and they demonstrated its utility with multiple Cas12 enzymes (which have slightly different PAMs, which is nice). Overall, its a useful and practical study, Komor continued.

As we continue the deployment of diverse CRISPR-Cas effectors in the clinic, it is important to individually engineer each molecular machine for optimal efficiency and specificity. Here, the authors show how NLS can be optimized for enhanced activity in medically relevant human primary cells, said Rodolphe Barrangou, PhD, professor of food, bioprocessing, and nutrition at North Carolina State University (NCSU), editor-in-chief of The CRISPR Journal, and CEO of TreeCo, a company that uses CRISPR to produce genetically enhanced trees. Barrangou was not part of the current study.

Optimizing on-target mutagenesis rates whilst maintaining specificity is key for successful translation to the clinic, reaffirmed Jennifer Harbottle, PhD, a senior scientist at Horizon Discovery, who was not part of this study. The Cas12a NLS variant developed by Scot Wolfes lab holds the potential to lower dosage whilst exerting therapeutic effect.

It will be of interest to see this strategy expanded to other Type V systems, and track efficiency of delivery in a wider range of cell types and tissues, added Harbottle. Comprehensively evaluating the genomic integrity of edited cells, particularly the occurrence of structural variants and chromosomal rearrangements compared to editing by canonical Cas9 systems, will be critical to push the optimized Type V variants towards in vivo use in humans.

In future studies, Wolfe intends to continue refining Cas12a nucleases to edit specific therapeutic targets. He said, We are particularly interested in applications for certain hematopoietic disorders and muscular dystrophies.

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CRISPR-Cas12a Editing Rates Improve with Better Directions to the Nucleus - Genetic Engineering & Biotechnology News

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Applications for the CAD software extend far beyond medicine and throughout the burgeoning field of synthetic biology, which involves redesigning organisms to give them new abilities. For example, we envision users designing solutions for biomanufacturing; it's possible that society could reduce its reliance on petroleum thanks to microorganisms that produce valuable chemicals and materials. And to aid the fight against climate change, users could design microorganisms that ingest and lock up carbon, thus reducing atmospheric carbon dioxide (the main driver of global warming).

Our consortium, GP-write, can be understood as a sequel to the Human Genome Project, in which scientists first learned how to "read" the entire genetic sequence of human beings. GP-write aims to take the next step in genetic literacy by enabling the routine "writing" of entire genomes, each with tens of thousands of different variations. As genome writing and editing becomes more accessible, biosafety is a top priority. We're building safeguards into our system from the start to ensure that the platform isn't used to craft dangerous or pathogenic sequences.

Need a quick refresher on genetic engineering? It starts with DNA, the double-stranded molecule that encodes the instructions for all life on our planet. DNA is composed of four types of nitrogen basesadenine (A), thymine (T), guanine (G), and cytosine (C)and the sequence of those bases determines the biological instructions in the DNA. Those bases pair up to create what look like the rungs of a long and twisted ladder. The human genome (meaning the entire DNA sequence in each human cell) is composed of approximately 3 billion base-pairs. Within the genome are sections of DNA called genes, many of which code for the production of proteins; there are more than 20,000 genes in the human genome.

The Human Genome Project, which produced the first draft of a human genome in 2000, took more than a decade and cost about $2.7 billion in total. Today, an individual's genome can be sequenced in a day for $600, with some predicting that the $100 genome is not far behind. The ease of genome sequencing has transformed both basic biological research and nearly all areas of medicine. For example, doctors have been able to precisely identify genomic variants that are correlated with certain types of cancer, helping them to establish screening regimens for early detection. However, the process of identifying and understanding variants that cause disease and developing targeted therapeutics is still in its infancy and remains a defining challenge.

Until now, genetic editing has been a matter of changing one or two genes within a massive genome; sophisticated techniques like CRISPR can create targeted edits, but at a small scale. And although many software packages exist to help with gene editing and synthesis, the scope of those software algorithms is limited to single or few gene edits. Our CAD program will be the first to enable editing and design at genome-scale, allowing users to change thousands of genes, and it will operate with a degree of abstraction and automation that allows designers to think about the big picture. As users create new genome variants and study the results in cells, each variant's traits and characteristics (called its phenotype) can be noted and added to the platform's libraries. Such a shared database could vastly speed up research on complex diseases.

What's more, current genomic design software requires human experts to predict the effect of edits. In a future version, GP-write's software will include predictions of phenotype to help scientists understand if their edits will have the desired effect. All the experimental data generated by users can feed into a machine-learning program, improving its predictions in a virtuous cycle. As more researchers leverage the CAD platform and share data (the open-source platform will be freely available to academia), its predictive power will be enhanced and refined.

Our first version of the CAD software will feature a user-friendly graphical interface enabling researchers to upload a species' genome, make thousands of edits throughout the genome, and output a file that can go directly to a DNA synthesis company for manufacture. The platform will also enable design sharing, an important feature in the collaborative efforts required for large-scale genome-writing initiatives.

There are clear parallels between CAD programs for electronic and genome design. To make a gadget with four transistors, you wouldn't need the help of a computer. But today's systems may have billions of transistors and other components, and designing them would be impossible without design-automation software. Likewise, designing just a snippet of DNA can be a manual process. But sophisticated genomic designwith thousands to tens of thousands of edits across a genomeis simply not feasible without something like the CAD program we're developing. Users must be able to input high-level directives that are executed across the genome in a matter of seconds.

Our CAD program will be the first to enable editing at genome-scale, with a degree of abstraction and automation that allows designers to think about the big picture.

A good CAD program for electronics includes certain design rules to prevent a user from spending a lot of time on a design, only to discover that it can't be built. For example, a good program won't let the user put down transistors in patterns that can't be manufactured or put in a logic that doesn't make sense. We want the same sort of design-for-manufacture rules for our genomic CAD program. Ultimately, our system will alert users if they're creating sequences that can't be manufactured by synthesis companies, which currently have limitations such as trouble with certain repetitive DNA sequences. It will also inform users if their biological logic is faulty; for example, if the gene sequence they added to code for the production of a protein won't work, because they've mistakenly included a "stop production" signal halfway through.

But other aspects of our enterprise seem unique. For one thing, our users may import huge files containing billions of base-pairs. The genome of the Polychaos dubium, a freshwater amoeboid, clocks in at 670 billion base-pairsthat's over 200 times larger than the human genome! As our CAD program will be hosted on the cloud and run on any Internet browser, we need to think about efficiency in the user experience. We don't want a user to click the "save" button and then wait ten minutes for results. We may employ the technique of lazy loading, in which the program only uploads the portion of the genome that the user is working on, or implement other tricks with caching.

Getting a DNA sequence into the CAD program is just the first step, because the sequence, on its own, doesn't tell you much. What's needed is another layer of annotation to indicate the structure and function of that sequence. For example, a gene that codes for the production of a protein is composed of three regions: the promoter that turns the gene on, the coding region that contains instructions for synthesizing RNA (the next step in protein production), and the termination sequence that indicates the end of the gene. Within the coding region, there are "exons," which are directly translated into the amino acids that make up proteins and "introns," intervening sequences of nucleotides that are removed during the process of gene expression. There are existing standards for this annotation that we want to improve on, so our standardized interface language will be readily interpretable by people all over the world.

The CAD program from GP-write will enable users to apply high-level directives to edit a genome, including inserting, deleting, modifying, and replacing certain parts of the sequence. GP-write

Once a user imports the genome, the editing engine will enable the user to make changes throughout the genome. Right now, we're exploring different ways to efficiently make these changes and keep track of them. One idea is an approach we call genome algebra, which is analogous to the algebra we all learned in school. In mathematics, if you want to get from the number 1 to the number 10, there are infinite ways to do it. You could add 1 million and then subtract almost all of it, or you could get there by repeatedly adding tiny amounts. In algebra, you have a set of operations, costs for each of those operations, and tools that help organize everything.

In genome algebra, we have four operations: we can insert, delete, invert, or edit sequences of nucleotides. The CAD program can execute these operations based on certain rules of genomics, without the user having to get into the details. Similar to the "PEMDAS rule" that defines the order of operations in arithmetic, the genome editing engine must order the user's operations correctly to get the desired outcome. The software could also compare sequences against each other, essentially checking their math to determine similarities and differences in the resulting genomes.

In a later version of the software, we'll also have algorithms that advise users on how best to create the genomes they have in mind. Some altered genomes can most efficiently be produced by creating the DNA sequence from scratch, while others are more suited to large-scale edits of an existing genome. Users will be able to input their design objectives and get recommendations on whether to use a synthesis or editing strategyor a combination of the two.

Users can import any genome (here, the E. coli bacteria genome), and create many edited versions; the CAD program will automatically annotate each version to show the changes made. GP-write

Our goal is to make the CAD program a "one-stop shop" for users, with the help of the members of our Industry Advisory Board: Agilent Technologies, a global leader in life sciences, diagnostics and applied chemical markets; the DNA synthesis companies Ansa Biotechnologies, DNA Script, and Twist Bioscience; and the gene editing automation companies Inscripta and Lattice Automation. (Lattice was founded by coauthor Douglas Densmore). We are also partnering with biofoudries such as the Edinburgh Genome Foundry that can take synthetic DNA fragments, assemble them, and validate them before the genome is sent to a lab for testing in cells.

Users can most readily benefit from our connections to DNA synthesis companies; when possible, we'll use these companies' APIs to allow CAD users to place orders and send their sequences off to be synthesized. (In the case of DNA Script, when a user places an order it would be quickly printed on the company's DNA printers; some dedicated users might even buy their own printers for more rapid turnaround.) In the future, we'd like to make the ordering step even more user-friendly by suggesting the company best suited to the manufacture of a particular sequence, or perhaps by creating a marketplace where the user can see prices from multiple manufacturers, the way people do on airfare sites.

We've recently added two new members to our Industrial Advisory Board, each of which brings interesting new capabilities to our users. Catalog Technologies is the first commercially viable platform to use synthetic DNA for massive digital storage and computation, and could eventually help users store vast amounts of genomic data generated on GP-write software. The other new board member is SOSV's IndieBio, the leader in biotech startup development. It will work with GP-write to select, fund, and launch companies advancing genome-writing science from IndieBio's New York office. Naturally, all those startups will have access to our CAD software.

We're motivated by a desire to make genome editing and synthesis more accessible than ever before. Imagine if high-school kids who don't have access to a wet lab could find their way to genetic research via a computer in their school library; this scenario could enable outreach to future genome design engineers and could lead to a more diverse workforce. Our CAD program could also entice people with engineering or computational backgroundsbut with no knowledge of biologyto contribute their skills to genetic research.

Because of this new level of accessibility, biosafety is a top priority. We're planning to build several different levels of safety checks into our system. There will be user authentication, so we'll know who's using our technology. We'll have biosecurity checks upon the import and export of any sequence, basing our "prohibited" list on the standards devised by the International Gene Synthesis Consortium (IGSC), and updated in accordance with their evolving database of pathogens and potentially dangerous sequences. In addition to hard checkpoints that prevent a user from moving forward with something dangerous, we may also develop a softer system of warnings.

Imagine if high-school kids who don't have access to a lab could find their way to genetic research via a computer in their school library.

We'll also keep a permanent record of redesigned genomes for tracing and tracking purposes. This record will serve as a unique identifier for each new genome and will enable proper attribution to further encourage sharing and collaboration. The goal is to create a broadly accessible resource for researchers, philanthropies, pharmaceutical companies, and funders to share their designs and lessons learned, helping all of them identify fruitful pathways for advancing R&D on genetic diseases and environmental health. We believe that the authentication of users and annotated tracking of their designs will serve two complementary goals: It will enhance biosecurity while also engendering a safer environment for collaborative exchange by creating a record for attribution.

One project that will put the CAD program to the test is a grand challenge adopted by GP-write, the Ultra-Safe Cell Project. This effort, led by coauthor Farren Isaacs and Harvard professor George Church, aims to create a human cell line that is resistant to viral infection. Such virus-resistant cells could be a huge boon to the biomanufacturing and pharmaceutical industry by enabling the production of more robust and stable products, potentially driving down the cost of biomanufacturing and passing along the savings to patients.

The Ultra-Safe Cell Project relies on a technique called recoding. To build proteins, cells use combinations of three DNA bases, called codons, to code for each amino acid building block. For example, the triplet 'GGC' represents the amino acid glycine, TTA represents leucine, GTC represents valine, and so on. Because there are 64 possible codons but only 20 amino acids, many of the codons are redundant. For example, four different codons can code for glycine: GGT, GGC, GGA, and GGG. If you replaced a redundant codon in all genes (or 'recode' the genes), the human cell could still make all of its proteins. But viruseswhose genes would still include the redundant codons and which rely on the host cell to replicatewould not be able to translate their genes into proteins. Think of a key that no longer fits into the lock; viruses trying to replicate would be unable to do so in the cells' machinery, rendering the recoded cells virus-resistant.

This concept of recoding for viral resistance has already been demonstrated. Isaacs, Church, and their colleagues reported in a 2013 paper in Science that, by removing all 321 instances of a single codon from the genome of the E. coli bacterium, they could impart resistance to viruses which use that codon. But the ultra-safe cell line requires edits on a much grander scale. We estimate that it would entail thousands to tens of thousands of edits across the human genome (for example, removing specific redundant codons from all 20,000 human genes). Such an ambitious undertaking can only be achieved with the help of the CAD program, which can automate much of the drudge work and let researchers focus on high-level design.

The famed physicist Richard Feynman once said, "What I cannot create, I do not understand." With our CAD program, we hope geneticists become creators who understand life on an entirely new level.

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