On 2021-09-24 17:10:27, user Vinay K. Pathak wrote:

Schifferdecker et al. show that a new capsid labeling method efficiently labels capsids with a fluorescent membrane permeable dye and provides another tool to visualize HIV-1 cores in infected cells and increase our understanding HIV-1 replication. Importantly, this work adds to the growing body of evidence that nuclear capsids are largely intact (Burdick et al. 2020; Dharan et al. 2020; Selyutina et al. 2020; Zila et al. 2021; Müller et al. 2021, Li et al. 2021; and others). <br /> However, for two reasons, we respectfully disagree with the conclusion that the “…HIV-1*CA14SiR represents a substantial improvement compared to previous genetic labeling strategies (Campbell et al. 2008; Burdick et al. 2020; Zurnic Bönisch et al. 2020; Pereira et al. 2011).” First, like HIV-1*CA14SiR, the infectivity of virus labeled with GFP-CA as we described (1:15 ratio of GFP-CA:WT Gag) was modestly reduced 2-fold (Fig. 1B in Burdick et al. 2020), indicating that the GFP-CA labeling system does not severely reduce virus infectivity compared to the HIV-1*CA14SiR system. Second, given the “minimally invasive” strategy used to label HIV-1 CA, it was surprising that the nuclear import of capsids containing CA14SiR was severely delayed by 6-12 hours (Fig. 3; Schifferdecker et al.). In contrast, we showed that GFP-CA labeling of virions did not affect nuclear import kinetics of capsids (Fig. 2H in Burdick et al. 2020). <br /> It is not clear why the CA14SiR labeling has such a drastic effect on nuclear import kinetics; labeling most of the CA in the capsid shell with the fluorescent dye may alter the capsid structure and stability, influencing the timing of nuclear import as well as other capsid functions, such as PF74-induced disassembly. We believe it is important to show that the labeling method does not have a significant influence on the steps in HIV-1 replication that are being investigated. For this reason, we showed that GFP-CA labeling of virions did not affect the timing of loss of sensitivity to capsid inhibitor PF74 (Fig. 2G), timing of reporter gene expression (Fig. S1L), sensitivity to various HIV-1 inhibitors (Fig. S1M), capsid stability (Fig. S1E-F), association of capsids with nuclear envelope (Fig. S1G), nuclear import efficiency (Fig. S1G), and binding of nuclear capsids to CPSF6 (Fig. S4H-I; all figures in Burdick et al. 2020).

Sincerely,<br /> Ryan C. Burdick, Chenglei Li, Mohamed Husen Munshi, Wei-Shau Hu, and Vinay K. Pathak,<br /> HIV Dynamics and Replication Program, National Cancer Institute-Frederick, Frederick, Maryland 21702

On 2021-09-23 12:04:27, user Edward Emmott wrote:

This preprint has now been published in Nature Communications - please see https://www.nature.com/arti...

On 2021-09-23 09:05:28, user Dr. Nagarajan wrote:

Interesting article looks Amoxicillin has effect in gut ecology and provide beneficial effect in metabolic syndrome

On 2021-09-23 01:34:21, user Dr Erin Hahn wrote:

This article has now been published in Molecular Ecology Resources:<br /> https://onlinelibrary.wiley...

On 2021-09-22 10:23:04, user Kathy.Dibley wrote:

Hello, I have read this and the Custódio et al pre-print with much interest- thank you for sharing this research here.The finding of a Cl binding site is of particular interest. <br /> Can you please keep us updated here as to when this work has been published via peer review, as we intend to cite both in an upcoming research article on STP function.

On 2021-09-22 07:33:27, user Christoph Metzendorf wrote:

In figure 2 and following you refer to box plots and bar plots as "histograms". Histograms are diagrams that show distributions (e.g. x-axis age classes; y-axis number of people in each age class).

On 2021-09-21 15:18:07, user Christian Meesters wrote:

also, linked web page does by no means provide information on how to actually run it. Let alone any button or field where input can be given. It is henceforth dysfunctional.

On 2021-09-21 14:45:24, user Christian Meesters wrote:

nice paper, but there are a number of issues with the software:

• no versioned release on github

• no precise requirement statements (just this or that is needed, but not any (minimum) version, which means the software might work with the current versions of the given packages)

• there is a claim about HPC-compatibility, but no information about scalability. It is questionable, whether a Perl script is able to carry the weight of "HPC-compatibility" at all.

On 2021-09-21 10:36:04, user Martin R. Smith wrote:

This is an interesting approach; always good to see exploration of aspects of data that can be recovered before the alignment step.<br /> One small comment on the use of RF distances to compare to a reference topology: the RF distance has a number of biases and limitations that make ill suited to this purpose. I review and propose some alternatives in Smith, 2020, Bioinformatics: https://doi.org/10.1093/bio...

On 2021-09-21 02:14:28, user Kshitish Acharya wrote:

Published in the Journal of Biomedical Research: https://www.sciencedirect.c...

On 2021-09-20 22:39:02, user Patrick Sexton wrote:

Very interesting structure - the last of the class B1 GPCRs to be solved. However, I note from Fig. 4 that any N-terminal extension results in at least 100-fold loss of potency. Given that the construct used for the structure is N-terminally modified with purification tags, what do the authors think this means for the solved structure?

On 2021-09-20 21:44:47, user RENE wrote:

This article was published in the journal PLOS ONE:<br /> https://doi.org/10.1371/jou...<br /> Att: Rene Flores Clavo.

On 2021-09-20 16:07:37, user Rath R. Weird wrote:

Not sure that entries like that would be sufficient to offset the advertisement machine unleashed in support of the AlphaFold, but I do welcome a systematic attempt to evaluate AlphaFold performance in realistic applications. There is lots of anecdotes out there, when people turned to AlphaFold for structural info, and got gobs of disordered strings in return. Personally I compared some of the 2-3 year old models built by I-TASSER to AlphaFold output and found no discernible difference - typical homology modeling performance, none have much in looking-ahead capabilities, but at least the guys behind I-TASSER don't claim to have it. Here we have a more deliberate evaluation of the heuristic AlphaFold imbalance between physical realism and template alignment. Template alignment wins, to the detriment of physical realism.

On 2021-09-20 14:18:42, user Bo Xia wrote:

Please note that the email address of Bo Xia should be Bo.Xia@nyulangone.org

On 2021-09-20 11:39:13, user Clarissa M- maya-Monteiro wrote:

Very interesting result. It really raises the question about the distribution of the fat depots. I would like to know why the authors did not perform these comparisons. Could also check for leptin gene expression in each of the adipose tissue depots.

On 2021-09-20 04:52:35, user Cyrille Delley wrote:

Hi Vincent and Simone,<br /> Thanks for sharing this interesting preprint. I was wondering, since you are using the TSO and pT primer during the PCR, wouldn't that potentially cause your TSO primers to introduce new UMIs during each PCR cycle and thereby inflate your read counts? Having a constant spacer would presumably increase this effect. Am I missing something here?

Best,<br /> Cyrille

On 2021-09-19 08:44:21, user Aliaksei Chareshneu wrote:

In case of questions, comments or any other correspondence, please use the following email address: 479052@mail.muni.cz. Unfortunately, the corresponding author of this pre-print, professor Jaroslav Koča, recently passed away.

On 2021-09-17 23:05:52, user Larry Weisenthal wrote:

See also: https://ascopubs.org/doi/10... AND https://vimeo.com/manage/vi...

On 2021-09-17 17:36:01, user Asimbikas Das wrote:

This pre-print has been published, https://bmcmedgenomics.biom...

On 2021-09-16 22:05:04, user Dyche Mullins wrote:

Vimentin Intermediate Filaments and Filamentous Actin Form Unexpected Interpenetrating Networks That Redefine the Cell Cortex

https://doi.org/10.1101/202...

Members of the Mullins laboratory read this paper together and discussed it during a recent journal club meeting. Following the meeting, we drafted the following set of comment with the aim of helping the authors revise the work for final publication..

Briefly, this manuscript describes in vitro and live-cell experiments aimed at understanding the connection between intermediate filaments and the actin cytoskeleton. As the authors note, this is an understudied topic, with many fundamental unanswered questions. The experiments described in the paper employ a variety of approaches, including rheometry, fluorescence microscopy, and cryo-electron microscopy. The major results claimed by the authors include evidence for extensive interactions between vimentin IF and actin cytoskeletal systems in the cell periphery and effects of IF networks on actin monomer diffusion.

Specific comments/concerns:

1. In the Introduction the authors state that it is “...generally thought that F-actin and VIFs form two co-existing but separate networks.” This is not an entirely fair description of the field. There is a significant body of work on interactions between intermediate filaments and elements of the actin cytoskeleton [e.g. myosin II/IF interactions described in Svitkina et al. (1996). J Cell Biol 135(4):991-1007], and how the actin cytoskeleton can regulate IF network architecture [e.g. this review by Chang and Goldman (2004). Nat Rev Mol Cell Biol. 5(8):601-13; and numerous research papers, including Schoumacher et al. (2010) J Cell Biol. 189(3):541-56 and Serres et al. (2020) Dev Cell. 52(2):210-222]. A more inclusive discussion of previous work on the interaction of the two cytoskeletal components would improve the presentation.

2. The title mentions the cell cortex, but there is almost no mention of the cortex per se in the Results or Discussion.

3. The figure captions should contain more experimental details. For example, captions should contain information on cell types, microscopy methods, and molecular probes (e.g. is the actin in Figure 1 phalloidin stained?). They should also contain other relevant details, such as buffer conditions, temperatures, and how many times an experiment was repeated.

4. The authors should consider combining Figure 1 and 2. It is a little unclear what is being highlighted by the arrows in Figure 1, as the two networks appear to be quite separate, even in this region of the cell. Figure 2 makes a better case for overlapping network elements.

5. In Figure 2, it is unclear whether the two networks are actually interpenetrating or simply present in different focal planes. Because the raw data includes z-stacks, it would be useful to show an XZ or YZ or 3d projection of the data.

6. Figure 2 should contain some (even rough) quantification of the percentage of observed cells that displayed such unambiguously interpenetrating networks.

7. The electron microscopy in Figure 3 is beautiful and quite convincing. The minimum distance argument, however, does not rule out the possibility that the actin and intermediate filaments are linked by plectins. The crosslinks could be present in areas where the filaments are further apart. Also, to convince the reader that they can distinguish between filaments based on width, the authors should provide a histogram of all the observed filament widths. Does the histogram show a clear bimodal distribution?

8. For Figure 4, please cite some previous studies using this indenter method and/or provide further details on the method: does it apply uniaxial or isometric stretch? Some raw images before, during, and after stretching would be more useful than the recovery plot shown in B.

9. As noted above the caption (or description) of Figures 4&5 should contain the number of biological replicates. P values calculated with n=number of cells (rather than the number of replicates) are not appropriate. We recommend simply removing the P value calculations.

10. Unfortunately, the data presented in Figure 5 are not convincing:<br /> a. Firstly, P values calculated on the number of cells instead of the number of biological replicates are artificially small and should not be reported. The trend is intriguing, but does it hold up over multiple rounds of experiment?<br /> b. Secondly, the FRAP bleaches both monomers and filaments. To look at only monomers, a method like FCS would be better.<br /> c. Instead of the curves in B, raw images would be more informative.<br /> d. When vimentin is knocked out, does the rest of the cytoskeleton change to compensate? Currently the explanation for these results is that there could be direct protein-protein interactions between Vimentin and G-actin which affect G-actin diffusion. The author favored this over the model where G-actin diffusion is limited by physical/steric obstruction of Vimentin networks. However the current data is unable to fully delineate these two models as the Y117L mutant forms a sort of intermediate filament (“intermediate” in length relative to the long filament), which intuitively could physically obstruct G-actin diffusion in an intermediate fashion (which is observed by this experiment). Perhaps using another mutant form of Vimentin that is simply unable to form any filaments but is present in cellular protrusions could help clarify the mechanism of G-actin diffusion limiting.

11. It is unclear what precisely the reader is to take away from Figure 6. The concentration of actin filaments is so high that one cannot make out individual filaments or their interactions with vimentin. It does not seem very surprising that two proteins can polymerize in the presence of one another. Is the point mainly that these two proteins can mix? Are there examples of the literature of other filament-forming protein phase separating from actin, or other conditions where this mixing doesn’t occur? A negative control would make this data more convincing.

On 2021-09-16 10:23:36, user P. Routray wrote:

Excellent ms. Prediction using existing approaches are risky indeed.

On 2021-09-16 07:24:05, user Stefano Vianello wrote:

This paper describes a fascinating epithelial behaviour! For craniofacial development non-experts, would you be able to clarify the germ layer origin of the palate and of the Midline Epithelial Seam? Given that the mouth contains contributions from both ectoderm and endoderm I am wondering which of the two makes the epithelia you describe. And whether this could be a behaviour of developing epithelial cells more generally (regardless of germ layer). Thank you in advance!

On 2021-09-15 21:44:58, user Sam Lord wrote:

Really interesting work. Any thoughts about WASP's role in motility, given that CDC42 activates WASP?

I ask because we hypothesized that WASP and WAVE coordinate in neutrophil pseudopod formation and crawling, but some in the field don't believe that WASP plays no part in motility. Your data is another clue that it might.

https://doi.org/10.1083/jcb...

On 2021-09-15 12:44:15, user Mohamed Hameed Aslam A wrote:

nice work

On 2021-09-15 12:44:06, user Mohamed Hameed Aslam A wrote:

please provide supplementary table , its missing in this pre print

On 2021-09-15 10:12:30, user Xian Wu Cheng wrote:

Reviewer comments<br /> This is an animal model study of Sphingosine<br /> 1-Phosphate Mediates Adiponectin Receptor Signaling Essential for Lipid<br /> Homeostasis and Embryogenesis. In current study, using unbiased<br /> lipidomics and proteomics, the authors showed that the embryonic lethality in<br /> mice lacking the fluidity regulators Adiponectin Receptors 1 and 2 (AdipoR1/2)<br /> is associated with aberrant high saturation of the membrane phospholipids.<br /> Using MEFs derived from AdipoR1/2-KO embryos, human cell lines and the model<br /> organism C. elegans the authors found that, mechanistically, AdipoR1/2-derived<br /> sphingosine 1-phosphate (S1P) signals in parallel through S1PR3-SREBP1 and<br /> PPARγ to sustain the expression of the fatty acid desaturase SCD and maintain<br /> membrane properties. They concluded that an evolutionary conserved pathway by<br /> which cells and organism maintain membrane homeostasis and adapt to a variable<br /> environment.<br /> Overall this is a very elegant, well<br /> executed and well presented study that provides novel insights on the biological<br /> effect of Sphingosine 1-Phosphate on AdipoR1 in lipid homeostasis and embryogenesis. The<br /> paper addresses important issue with potential clinical and research. This<br /> reviewer has several comments and suggestions for changes that follow.

Specific comments:<br /> 1) As known, among AdipoR1 and R2, both show different expression pattern and activity in various cell lines (Vasiliauskaité-Brooks et al. Naure 2017 Apr6;544:120-123; Yamauchi et al. Nat Med 2007;13:332-339) . Here, there were any difference between their expression levels and activities in lipid homeostasis and embryogenesis?

2) AdipoR1 has shown to modulate cell proliferation and apoptosis (Iwabe et al. nature 2010 Apr29;464:1313-1319; Piao et al. J Am Heart Assoc. 2017 Sep 28;6(10):e006421; Int J Cardiol. 2018 Sep 15;267:150-155.). The authors did evaluate apoptosis in AdipoR1/2-KO embryos and discuss this issues in the discussion sections.

3) There were several typos in the text. The English language may be improved in whole text.

On 2021-09-14 20:40:28, user L. T. Fang wrote:

This preprint has been published in Nat Biotechnol: http://doi.org/10.1038/s415...<br /> SharedIt link: https://rdcu.be/cxASG

On 2021-09-14 15:37:23, user Karen Lange wrote:

I am very grateful that the authors shared this preprint. I checked unc-58 in several CRISPR lines that I have recently made using an unc-58 co-CRISPR strategy and found that 17% (2 of 12) had deletions in unc-58.

I can verify that the authors statement that unc-58 has a "subtle loss-of-function (LOF) not discernible by visual inspection" is true. The worms did not appear Unc. The unc-58 deletions did result in subtle phenotypes in the roaming and chemotaxis assays (which rely on worm movement).

I am glad that I found this mistake prior to publishing my findings and was able to easily outcross the unwanted mutations. In the future I will definitely be genotyping my co-CRISPR genes!!!

On 2021-09-14 14:35:27, user Donald R. Forsdyke wrote:

The final peer-reviewed version of this paper may be found in Computational Biology and Chemistry 94:107570

On 2021-09-09 17:28:47, user Donald R. Forsdyke wrote:

This paper has been peer reviewed and is formally published (Sept. 2021) by Computational Biology and Chemistry.

On 2021-09-14 14:06:02, user Donald R. Forsdyke wrote:

Further background to my 2020 commentary may be found in a recent paper, an earlier version of which had been posted on bioRxiv:<br /> Zhang, C. & Forsdyke, D. R. (2021) Potential Achilles heels of SARS-CoV-2 are best displayed by the base order-dependent component of RNA folding energy. Computational Biology and Chemistry 94:107570.

On 2021-09-14 13:39:09, user Ramon Garcia-Escudero wrote:

This is an important manuscript for the Fanconi anemia (FA) community, as it provides molecular information that would help to understand FA SCC disease. I would like to congratulate all people involved. I would also like to ask the authors if they could answer some questions that I have:

1) The mutations described in Fig 1C and Extended data Fig 1E (either SNV/indel, CNV, structural disruption…): are they normally clonal or subclonal? It is important to understand how is the intra-tumor heterogeneity in FA SCC for the most frequent genes with molecular aberrations.

2) Are there differences in mutations between<br /> BMT and non BMT patients?

Thanks a lot for sharing the manuscript before final publication.

Ramon Garcia-Escudero

On 2021-09-13 22:31:04, user tetech2 wrote:

The stem cell tumor problem is having to be addressed:<br /> Identifying alterna-<br /> tive reprogramming strategies to restore youthful gene<br /> expression with lower neoplastic risk is therefore desirable.<br /> Toward this aim, we have shown that transient reprogram-<br /> ming with multiple subsets of the Yamanaka Factors in-<br /> duces highly similar transcriptional effects to the full set,<br /> and that a distinct multipotent reprogramming system can<br /> confer youthful expression. These results suggest the fea-<br /> sibility of disentangling the rejuvenative and pluripotency<br /> inducing effects of transient reprogramming and serve as a<br /> resource for further interrogation of transient reprogram-<br /> ming effects in aged cells.

On 2021-09-13 16:52:57, user Youn Henry wrote:

Dear authors,<br /> Thanks a lot for this nice article! The topic and the questions it raises are fascinating and definitely needed to be addressed. I have few comments about method details that were absent from the manuscript, and that you may consider adding:

-You refer to the original publication by Bubly et al for the breeding methods of the different selection regimes you used (which is fine), but in this publication we have no information on parameters that can influence the microbiota. For instance, you could give some details about the opportunities for microorganisms to jump from one generation to the next (only through egg chorion? Adults could defecate in the bottle for next generation? Etc.). You could also mention the food composition and if preservatives were used (they both strongly affect the microbiota)<br /> -I missed the details of the collection of your different flies. You only indicated you sampled 20 individuals in each population or each selection regime, but we do not know if those individuals were collected 1) after the stress in a “selection generation”, 2) during the “no selection” generation, or 3) after x generations bred in identical conditions. You mention “common garden” in the abstract and in the conclusion, but there is no mention of this in the methods… Also, additional parameters such as the age of the flies, time spent in the same bottle etc. do affect a lot the microbiota composition<br /> -By not eliminating parental effects (like transgenerational transmission of microbiota), one potential issue is to measure the filtering effect of the treatment directly on bacteria rather than on the fly-microtiota system (or holobiont). This is something important, weakening the "holobiont" aspects of your discussion, and that you should discuss in my opinion. A way to test that would have been to eliminate the microbiota of the flies, and let all lines grow with the same starting microbiota. In such case, still observing different communities would indeed indicate co-evolution at the holobiont scale. I understand these flies were collected a while ago, probably without this experiment in mind, but you have to acknowledge the limits of your experimental setup.

Hope you will find my suggestions relevant. I much enjoyed reading this paper and this is why I wanted to point out some potential issues.<br /> Best regards

On 2021-09-13 13:10:09, user Anand Mayakonda wrote:

Hello Authors,<br /> Great stuff and congratulations. Just want to point out that on the page-7, last paragraph, concerning<br /> "liftover failures", reference to Figure. 1F is being made. However, there is no Fig. 1F. I could not find the relevant figure in the supplementary material as well.<br /> Best,<br /> Anand M<br /> ​

On 2021-07-14 11:39:25, user Wouter De Coster wrote:

Dear authors,

Congratulations on this fantastic paper. I am sure it will have a long-lasting impact on human genetic research, convincingly showing the limitations of an incomplete and incorrect reference genome.

Although admittedly on a smaller scale, a relevant reference to mention in this same context is https://www.ncbi.nlm.nih.go.... In this paper the authors show that the construction of a (population-) specific genome assembly leads to an improvement in both false positive and false negative variant calls from short-read sequencing from the same population.

Sincerely,<br /> Wouter De Coster

On 2021-09-13 13:06:04, user Gianluca Sigismondo wrote:

Holistic view on chromatin dynamics during the DDR

On 2021-09-13 01:49:05, user nimrat chatterjee wrote:

This preprint just got accepted at BBRC journal and a link to the accepted and published version will be available soon!

On 2021-09-13 01:25:27, user Y. Wang wrote:

This article has been accepted and published by journal of Nucleic Acids Research. Please see the article link: https://academic.oup.com/na...

On 2021-09-12 12:33:02, user Rath R. Weird wrote:

If I understand the results posted on August 2, 2021 for the clinical trial NCT04335136, comparing the injection of APN01 and saline placebo, correctly, then this intervention didn't produce any benefits at all. Noise-level variations in outcomes: a couple of percentage points benefit in [mortality + IMV], the same margin but negative for mortality alone, etc. The small size of the trial population (180 people with a few protocol violations and clerical errors) doesn't really allow to make meaningful statistical arguments, but if there were a huge clinically-relevant effect of rACE2/APN01, it would have registered.

On 2021-09-12 02:24:50, user Raghu Parthasarathy wrote:

Interesting paper! If you're going to claim a power law (such as an inverse square), however, it would be good to see the data plotted on a log-log scale, so that the scaling exponent is obvious, and also to see a robust fitting of the exponent value. Also, I don't see that the datapoints are available to the reader -- is there a supplemental data link missing? Thanks!

On 2021-09-11 01:36:10, user YiweiNiu wrote:

Very surprising but interesting results. Have you ever test the performance of paired Wilcoxon rank-sum test? Since edgeR and DESeq2 also have statistical methods for paired samples, I wonder whether Wilcoxon rank-sum test still excels in case of paired samples.

On 2021-09-10 19:17:01, user Fabrício Campos wrote:

Dear all, I would like to let you know that our preprint has been reviewed and published in the Viruses Journal: https://www.mdpi.com/1999-4.... Sincerely, Fabricio.

On 2021-09-10 08:09:18, user Robert Briddon wrote:

I have some concerns, both major and minor, about this manuscript. I will deal with the minor concerns first. <br /> The manuscript is not easy to read – it is not reader friendly. The text deals with a large number of sequences, derived from the authors own work and obtained from the databases. These are all referred to by their database accession numbers. So, for example, when the text refers to the virus phylogenetic tree saying “MYVMV tree (Figure 1b) produced two major branches. All the MYVMV isolates from Pakistan were clustered into clade I under branch A while the Indian isolates were grouped into both the branches.” the figure does not show this – it is just a collection of anonymous database accession numbers. To confirm what the authors claim the tree shows, the reader would need to refer to a supplementary table or the database. Things could be so much better. The manuscript quotes Brown et al. (2012) which first suggested the use of “isolate descriptors” with up-dates in

Brown, J.K., Zerbini, F.M., Navas-Castillo, J., Moriones, E., Ramos-Sobrinho, R., Silva, J.F., Fiallo-Olivé, E., Briddon, R.W., Hernández-Zepeda, C., Idris, A., Malathi, V.G., Martin, D.P., Rivera-Bustamante, R., Ueda, S., Varsani, A., 2015. Revision of Begomovirus taxonomy based on pairwise sequence comparisons. Arch. Virol. 160(6), 1593-1619.

So at each mention of sequence EF373060, for example, you would put “MeYVMV-BenIN:Bar:06”. This gives the reader all the information needed to know what the sequence is – so, in this case, species Mesta yellow vein mosaic virus; strain Bengal; country of origin India; place of origin Barackpore; year of isolation 2006 and the accession number. This makes it much easier for the reader. Note that similar proposals, betasatellte species and isolate descriptors, have been made for betasatellites - see here.<br /> https://talk.ictvonline .org/taxonomy/p/taxon omy-history?taxnode_id=20165 479

Note that

Briddon, R.W.; Brown, J.K.; Moriones, E.; Stanley, J.; Zerbini, M.; Zhou, X.; Fauquet, C.M. Recommendations for the classification and nomenclature of the DNA-beta satellites of begomoviruses. Arch Virol. 2008, 153(4), 763-81. doi: 10.1007/s00705-007-0013-6.

is somewhat out-of-date.

In the list of sequences used for the analysis there is a lot of duplication. All the reference sequences (sequences denoted as NC_XXXXXX) should be deleted. These duplicate the actual sequences – so for example NC_009088 is the same as EF373060.

In the introduction you say “For theses analyses, we considered all the available MYVMV and betasatellite isolates so far (isolated from mesta plants or associated with mesta plants) in GenBank including the new isolates from Bangladesh (from this study).”. This is said despite the fact that earlier you noted that a second species, Mesta yellow vein mosaic Bahraich virus, is associated with MYVMD and you then appear to include this under the name MYVMV. Mesta yellow vein mosaic Bahraich virus is far more closely related to Cotton leaf curl Multan virus and Bhendi yellow vein mosaic virus, two other malvaceous begomoviruses, than it is to MYVMV. Also you include isolates of MYVMV not “isolated from or associated with mesta plants” – MH628534 was isolated from sunflower. So, it seems that for inclusion in your analysis it is enough for the species to have been isolated from mesta, not necessarily the isolate. Unfortunately then, in selecting betasatellites for analysis, you go against this apparent rule. You ONLY include betasatelittes actually isolated from mesta, which happens to include at least five species - Kenaf leaf curl betasatellite, Cotton leaf curl Multan betasatellite, Mesta yellow vein mosaic betasatellite (previously known as “Ludwigia leaf distortion betasatellite”) Tomato leaf curl Joydebpur betasatellite, and Croton yellow vein mosaic betasatellite. However, unlike for the virus, you do not include isolates the NOT from mesta.

My question is – does this haphazard selection of sequences to analyse mean that the final results tell us anything useful?

Although there is no mention of it, the phylogenetic trees amount to species trees. The microsatellite analysis may be useful, once all the duplicate sequences are removed but can you take sequences from 5 betasatellite species and say anything useful about what is happening in mesta? Similarly, with 5 species and a small sample set, is there anything useful to be gained from a comparison of genetic diversity in Pakistan India and Bangladesh.<br /> One interesting finding overlooked by the authors is that all the betasatellites they sequenced are isolates of Cotton leaf curl Multan betasatellte. This gives strong support to the idea that, at least in Bangladesh, mesta yellow vein mosaic disease is caused by the complex Mesta yellow vein mosaic virus and Cotton leaf curl Multan betasatellte.

On 2021-09-10 06:33:15, user Maju wrote:

Very interesting. Are we finally finding the Magyar genetic legacy here? Or is it rather a mix of Magyar and Gothic (and maybe other elements)?

The Kuline twins would seem, from dates and Catalan-like origin, to have (maybe) arrived there in the Peasant's Crusade (the Occitan Knight's Crusade went via Italy, not via Hungary). A curiosity ultimately but still worth mentioning.

On 2021-09-09 22:20:34, user Jodi Schneider wrote:

In Figure 4D, you mention "QNA" - do you mean Q&A sites from Altmetric.com (e.g. StackOverflow per https://www.altmetric.com/a... )? Ideally, add a key to acronyms.

On 2021-09-09 18:15:11, user Tania Gonzalez wrote:

The final peer-reviewed version was published in Epigenomics volume 13, no. 13: https://www.futuremedicine.... with https://doi.org/10.2217/epi.... Request it for free on ResearchGate if you don't have access to the journal.

On 2021-09-09 09:35:23, user Roberto Balbontin Soria wrote:

The published version of this manuscript appeared on line the 8th of April 2021 (and later in the issue of August) in the journal Molecular Biology and Evolution, with the title "DNA Breaks-Mediated Fitness Cost Reveals RNase HI as a New Target for Selectively Eliminating Antibiotic-Resistant Bacteria", and the D.O.I. https://doi.org/10.1093/mol....

On 2021-09-08 18:30:44, user Thomas Munro wrote:

On a minor point, the text states that "The affinity of α-MSH for MC1R increases when Ca2+ concentrations are elevated (Supplementary information Fig. S5b)", but α-MSH itself is not shown there. I would suggest rephrasing this, e.g.: "Specific binding of radiolabelled afamelanotide to MC1R is strongly calcium-dependent."<br /> Yu et al 2020 also found that calcium-free buffer dramatically reduced specific binding of [125I]afamelanotide, but nonetheless found a very weak effect on afamelanotide's affinity. I find this puzzling, and it might be worth discussing. It might also help to show absolute values in Fig. S5b for Ca, Mg, and control, as in Yu's Fig. 4c, so it's clear that some specific binding is present even without calcium.

On 2021-09-08 17:25:19, user amat wrote:

You may want to consider framing this work in the context of other papers that have demonstrated patterning of motor-filament systems:

https://www.nature.com/arti...<br /> https://www.nature.com/arti...

On 2021-09-08 13:37:06, user Santiago Justo Arevalo wrote:

Article published in Scientific reports of Nature: https://doi.org/10.1038/s41...

On 2021-09-08 10:00:05, user Varun Kapoor wrote:

Hi, Nice article. I really enjoyed reading it and very much liked the idea about using slice by slice segmentation and then using tracking to create a 3D object out of it.

I just wanted to point out that in your references you cite from [7-11] all the articles that made deep learning based tracking and or track analysis softwares in Fiji/Napari. We did work in the same direction and published it in July in the proceedings of the scientific python 2021. Could you please also cite our work along with the other works you cite? The link to our paper: http://conference.scipy.org...

DOI: 10.25080/majora-1b6fd038-014<br /> The bibtex and pdf of the paper are available on the above link.

Many Thanks,<br /> Varun Kapoor

On 2021-09-08 08:19:11, user Rony wrote:

Published version: https://doi.org/10.3390/ijm...

On 2021-09-07 17:14:38, user Rohit Ruhal wrote:

Need screening of chemical library

On 2021-09-07 15:15:05, user Manickam Lab wrote:

This paper is now published in the Journal of Controlled Release: https://www.sciencedirect.c...

On 2021-09-07 15:14:27, user Manickam Lab wrote:

https://www.sciencedirect.c...

On 2021-09-07 14:57:52, user Pankaj Kumar wrote:

The preprint has been published and a link will be forthcoming. In the accepted version the primer set has been updated due to an error in the preprint version.

On 2021-09-07 00:37:51, user Monsif Shawky wrote:

Thanks to Dr. Osman she didn’t accept any unethical behavior accompanied with the submission of this manuscript and she refused to accept being a first author on a manuscript was developed and created by Mr. Shawky.

SNPs derived from the breast cancer GWAS was mapped to human genome 38 while rao et al Hi-C were mapped to human genome 37.<br /> I believe Mr. Shawky performed leftover for the SNPs and mapped them to human genome 37

This is the first manuscript to show the huge impact of the 3D structure of the genome on SNPs functions

On 2021-09-06 16:53:52, user Cedric Berney wrote:

Great to see these new data on sanchytrids!

I was wondering if you did consider the possibility that sanchytrids are actually branching inside Blastocladiomycota.<br /> There is no transcriptomic/phylogenomic data available yet for any member of the shorter-branched Physodermatales.<br /> Therefore there is a possibility that they would turn out to be basal to Blastocladiales + sanchytrids, making it premature to create a new phylum for sanchytrids.

Also there is very strong support for Blastocladiales + sanchytrids in the tree (the internal branch is actually longer than that at the base of Chytridiomycota, Zoopagomycota and Mucroromycota).<br /> So to be phylogenetically consistent across Fungi, one could argue that either the latter three should become multiple phyla, or Blastocladiales + sanchytrids should be in a single phylum, irrespective of the latter's unique traits.

In any case, whether sanchytrids deserve to be a separate phylum or not, the very strong support for their relationship to Blastocladiomycota means that this B+S clade is evolutionarily relevant and would arguably deserve a name, like Dikarya for Ascomycota + Basidiomycota + Entorrhizomycota.<br /> Any suggestion for that name?

Best wishes

On 2021-09-06 16:07:11, user son vi wrote:

Great idea. However, in Supp Figure 18, authors showed all the new versions are extremely prone to giving false positives which challenge the use of such modified enzymes for diagnostic test ? (Supp Fig 18: at 72 degree C Non Template Control can have Ct thresold as soon as 10-14 minutes; and reach full signal after appx 20 minutes; at 74 degree C the spurious activity was reduced but still the system will be less robust if one relies on controlling a 2 degree C difference)

Can you modify Bst to make it give less suprious non-specific amplification?

On 2021-09-05 15:02:51, user Leo G. wrote:

Does the position S:142 influence any enhancing or neutralizing antibodies? The mutation S:G142D appeared from nowhere, peaked to 60% of all samples, then dropped off.

Also, the virus seems to evolve in an entirely different direction.

For example, S:K417N has almost disappeared

On 2021-08-24 18:10:44, user user wrote:

That data presented in Figure 7D is intriguing. If those sera are still available, it would be useful to know the titers of antibodies against particular spike protein epitopes in each sample.

On 2021-09-05 15:00:48, user UAB BPJC wrote:

Review of Barrasso et al., “Impact of a human gut microbe on Vibrio cholerae host colonization through biofilm enhancement” by the University of Alabama at Birmingham Bacterial Pathogenesis and Physiology Journal Club

Summary

This lab previously showed that Paracoccus aminovorans could be found in higher abundance in Vibrio cholerae-infected individuals compared to non-infected individuals. This study demonstrates that V. cholerae colonization is increased by the presence of P. aminovorans in an infant murine intestinal model of infection. Through crystal violet staining and murine intestinal colonization with a ∆vpsL mutant of V. cholerae, it is shown that Vibrio exopolysaccharide (VPS) is necessary for P. aminovorans-dependent enhancement of V. cholerae biofilm formation and intestinal colonization. Microscopy also reveals VPS enrichment in areas of the pellicle with higher P. aminovorans abundance. Lastly, with mutants in accessary matrix proteins RbmA, RbmC, and Bap1, the researchers show that the ability of V. cholerae to form a structurally intact biofilm is necessary for P. aminovorans-dependent enhancement of V. cholerae colonization.

Overall, this is a very interesting paper with insightful experiments that sparked a great discussion in our journal club group. This paper gives strong evidence that P. aminovorans promotes V. cholerae colonization in a VPS-dependent manner. With that said, we have some comments that may be beneficial for the authors to address.

General comments<br /> * May be beneficial to keep y-axis scales for CFUs the same among all figures for more consistency<br /> * One-way ANOVA may be a more appropriate test for figures in which multiple comparisons are being made; we advise you to consider consulting a statistician on the appropriate statistical tests to use<br /> * The Mann Whitney U test is not a t-test, but is referred to as such in some of the figure legends. <br /> * It is mentioned multiple times that crystal violet absorbance was measured at 570nm, although measurements were made at 550nm for all crystal violet figures in the paper. <br /> * Discuss possible limitations with Wheat Germ Agglutinin; could WGA also stain GlcNAc produced by P. aminovorans?<br /> * Would be beneficial to describe in more detail the purposes of matrix proteins RbmA, RbmC, and Bap1, and why these were chosen to be studied.<br /> * One statistical test is mentioned at the end of every figure legend; is the same statistical test being formed on all panels in a given figure? If not, this needs to be clarified.<br /> * More details about how CFUs are quantified from pellicles in the results section would be good to add; the steps taken are only briefly mentioned and are a bit difficult to understand.

Figure-specific comments<br /> * Story may flow better if in vivo data from Figure 2 is added to the end of the paper along with Figure 7 in vivo data; introduce enhanced Vc colonization phenotype with in vitro data first<br /> * Would be beneficial to show single and dual species P. aminovorans CFUs in Figure 2B and 2C and also single species P. aminovorans CFUs in Figure 3B to see whether P. aminovorans colonization also increases in the presence of V. cholerae <br /> * Address the purpose of the grid in Figure 4A<br /> * Figure 5A: Title claims that P. aminovorans increases V. cholerae biofilm formation according to data in Figure 5, but can only make this claim if CFUs are quantified in the in vitro model.<br /> * Figure 6 should have a Vc single species control to compare dual species pellicle to.

On 2021-09-05 14:38:51, user Rodrigo Lorenzi wrote:

I just took a look at the article. My question is: what happens when someone vaccinated is infected by a variant. Do they produce new antibodies against this variant or the only antibodies at work are those induced by the vaccine?

On 2021-09-04 20:28:34, user peter bayley wrote:

for me the most puzzling aspect of this paper is that nowhere is it reported (or even speculated upon) whether plasma treated rats lived longer than either control rats or the average age of the rat strain used in the experiment. That would seem to be the acid test of these types of experiment. Clinically it doesn’t matter if a biological marker shows a “healthier” profile if the health or longevity of the organism, whether rat or human, doesn’t change.

On 2021-09-04 13:43:02, user Arkom Chaiwongkot wrote:

This paper is now accepted and published in PLOS ONE, can be reached via link https://journals.plos.org/p...

On 2021-09-03 19:05:45, user Christopher Muir wrote:

After review, we decided to collect more data and reanalyze. This took awhile and resulted in a quite different paper. Hence, we have decided not to revise this manuscript further and no revisions will be made. Please see this preprint that addresses similar ideas with a much broader data set:

https://www.biorxiv.org/con...

On 2021-09-02 20:36:00, user Célio Dias wrote:

The link supplied to the code just does not work

On 2021-09-02 07:24:36, user Max Gattie wrote:

This article has been split into two.. The first half is available (open access) at Frontiers in Integrative Neuroscience. https://www.frontiersin.org...

On 2021-09-01 19:27:42, user Chen Sun wrote:

This paper developed a universal cryo-EM fiducial for the study of protein-nanobody complexes and validated with two membrane proteins. The only concern is, the process of producing nanobody for membrane protein is long and expensive. A minor point is that the mask used for SFig.3f FSC is obviously too tight.

On 2021-09-01 13:41:17, user Isabel Cardoso wrote:

Hi, Our preprint has been published and a link will be forthcoming.

On 2021-09-01 08:57:30, user Dong-Ha Oh wrote:

Supplementary Figure S1-S11 can be found within the main PDF. They are presented at the end of the PDF, together with the main Figures in the order of appearance in the text. In the "Full Text" tab, they are at the end of the document.

On 2021-09-01 00:46:56, user Tom J wrote:

Please check Fig 1d relative to the text on page 4...seems contradictory. If the Alpha spike/Delta backbone replicated less efficiently than Alpha, the ratios should be >1. Is the y-axis in the figure correct?

On 2021-08-24 22:09:46, user Kelly Ten Hagen wrote:

Our recent preprint provides mechanistic insight as to why P681 is important. P681 enhances O-glycosylation in this region, which blocks furin cleavage. Mutation of P681 abrogates O-glycosylation and leads to increased furin cleavage.<br /> https://www.biorxiv.org/con...

On 2021-08-31 14:27:55, user Greg Keele wrote:

The final peer-reviewed paper is now available from Cell Genomics.

https://www.cell.com/cell-g...

On 2021-08-31 09:48:34, user Mimmo wrote:

Figure 3 is too small to see anything...

On 2021-08-30 17:49:42, user David Quain wrote:

On the one hand, I was pleased to see this preprint. On the other hand I was surprised and disappointed to see no recognition of the work published in peer reviewed brewing science journals on draught beer microbiology/quality.

The Journal of the Institute of Brewing was first published in 1895 and receives just one reference (bizarrely to the Institute of Brewing & Distilling). To my knowledge, Seton in 1912 discussed draught beer quality in the trade with publications in the 50s, 70s and 80s.

In recent years, we have published a review on the microbiological quality of draught beer (2015), the hygiene of tap nozzles (16), assessment of quality (18), survey of trade quality (19) and assessment of biofilm formation (21). None of these publications merit consideration/recognition in the preprint by Bose et al. I'm hopeful that the peer review process will identify these gaps.

On 2021-08-29 13:51:27, user Maryam Fouladvand wrote:

This is <br /> really a nice work. During skeletal muscle regeneration, cells' shape is really different from normal one. Using MyoView, help us to save time and get more solid results. well done

On 2021-08-26 23:28:45, user Laura Sanchez wrote:

Dear Willems et al, this preprint was discussed in a lab meeting and we would like to offer the following for review. Thank you for posting this very interesting manuscript. Best, The Sanchez Lab:

The manuscript by Willems et al. presents an overview of a new software, AlphaTims, which allows for fast indexing and retrieval of LC-TIMS-MS/MS data. The authors present a clear explanation of how software indexing and data matrix construction works, along with an example of how their software is used to simplify the accession of data from complex samples. This open-source program has the potential to make data more accessible without proprietary software, and has many possible applications in conjunction with further data processing software. Overall, AlphaTims looks to be an impressive piece of software, and figure 1 especially did a great job of visualizing and explaining the difficult concept of data indexing in 4 dimensions. This was a great, polished read, and very informative in elucidating the experimental process for those who are less familiar with the LC-TIMS-MS/MS workflow. It was also appreciated that the data was publicly available on PRIDE! Below please find a list of critiques that may improve the accessibility of some of the concepts and better illustrate the software’s utility.

● Figure 1 is very well done and all the terms are well-explained. It may add further clarity if the authors were to add a part (d) to help visualize what the data looks like once indexed, perhaps with number values. Additionally, the color palette is difficult to interpret when printed in black and white; the authors may wish to consult ColorBrewer.

● Some of the data on the speed of the software is difficult to conceptualize without benchmark data for comparison. There’s a brief comparison between the program and Bruker’s DataAnalysis on two different systems (one local and one Github VM) with different specifications, which doesn’t provide a lot of context as these do not seem to be directly comparable. While the speed of the software compared to others is not necessarily a major focal point, as AlphaTIMS carries out different processes to DataAnalysis, it’s still a little difficult to conceptualize the relevance of the times in figure 2, as these events are somewhat decontextualized. With that being said, it was apparent that both systems used solid state drives. Therefore, even if runtimes cannot be directly compared, it may be helpful to note whether the code is CPU-bound, storage speed bound, etc. and suggest what hardware upgrades may help increase performance.

● The documentation in general is very good! The accessibility and the included explanations for all of AlphaTims’ reading, writing, slicing, and visualization workflows are impressive. However, more examples for other included processing functions (i.e. centroiding) would be helpful.

● Some more broad data visualizations in figures 3 and 4 would be helpful. Seeing an overall LC-MS and/or TIMS-MS spectrum in figure 3 could help contextualize the complexity of the data, beyond the quality control purposes expressed in the figure. This would also help to visualize the described “polygon filter” - again, not an expressed priority of the paper, but helpful for readers to connect the software to data. Additionally, in figure 4, showing a comparison of the selected peptides between the 6 sample conditions could help to visualize the utility of the software for determining sample optimization. There’s also a slight disconnect in the captions for figure 4 - “cell 24” could refer to In [24] or Out[24]. This is worth clarifying with traditional a, b, c, d, e, f labels.

● The forward looking statement in the conclusion may provide a great opportunity to expand on future possible applications. For instance, do the authors see this being developed with additional data processing/analysis functionalities, or integrated into new/existing data analysis programs? Is there possible functionality to visualize and compare multiple datasets at once?

On 2021-08-26 12:39:17, user Kirk Overmyer wrote:

This paper has now been published in the journal Forest Research and can be accessed here:

http://www.maxapress.com/ar...

Best Regards,<br /> Kirk Overmyer

On 2021-08-26 08:36:48, user zdz wii wrote:

Where is the supplementary material?

On 2021-08-26 08:17:05, user Brian wrote:

hello can you add data/code here?

On 2021-08-25 17:35:35, user S wrote:

The Pfizer and Moderna vaccines CAN neutralize the Lambda variant! Johnson & Johnson might be less effective but can also neutralize it too!

https://www.biorxiv.org/con... if they got J&J)

On 2021-08-25 15:49:58, user Julie Hanson Ostrander wrote:

An Open Access, read-only version of the peer-reviewed article published in Oncogene can be accessed through the following link: https://rdcu.be/cv1jC . The Open Access, published article can also be accessed through the J. Willard Marriott Digital Library at the University of Utah: https://collections.lib.uta...

Additional disclosures found in the published manuscript.

This work was supported by NIH grants R01 CA236948 (JHO, CAL), R01 CA229697 (CAL), F32 CA210340 (THT), T32 HL007741 (THT), U54 CA224076 (BEW), R01 CA248158-01 (CODS), and R01 AG069727-01 (CODS). ACS Institutional Research Grant #124166-IRG-58-001-52-IRG5 (JHO), University of Minnesota Masonic Cancer Center (CAL, JHO), the Tickle Family Land Grant Endowed Chair in Breast Cancer Research (CAL), National Center for Advancing Translational Sciences of the NIH Award UL1TR000114 (JHO), and Department of Defense W81XWH14-1-0417 (BEW). We thank Bruce Lindgren for biostatistics support, and the Masonic Cancer Center Biostatistics and Bioinformatics, Analytical Biochemistry, University Imaging Core (UIC), and Flow Cytometry cores. We also thank Zohar Sachs and Michael Franklin for critical reading of this manuscript.

We disclose that CAL is a Scientific Advisory Board Member for Context Therapeutics, Inc. BEW, EC-S, KPG, and C-HY may receive financial compensation from intellectual property and tangible property licenses managed by the University of Utah. The remaining authors have no COI to disclose.

On 2021-08-24 19:42:40, user Julie Hanson Ostrander wrote:

Use this link to access a view-only version of the article for free and use Enhanced PDF features such as annotation tools, one-click supplements, citation file exports and article metrics. https://rdcu.be/cv1jC

On 2021-08-25 13:27:36, user Marc Scheetz wrote:

This has now been published in AAC. https://journals.asm.org/do...

On 2021-08-25 12:52:36, user Sergio Perez Acebron wrote:

Revised manuscript published in PNAS: https://www.pnas.org/conten...

On 2021-08-25 07:27:33, user nemo peeters wrote:

Dear Readers, A colleague has spotted a copy/paste error resulting in a yeast spot duplication in Fig1A. The new figure will be uploaded soon, together with a new supplementary material showing the raw Y2H matrices.

On 2021-08-24 23:52:42, user george mcnamara wrote:

I hope the authors read and cite Duong et al 2013 CAR library approach, before their next version.<br /> https://journals.plos.org/p...

On 2021-08-24 22:13:47, user Kelly Ten Hagen wrote:

Recent work from our lab provides mechanistic insight as to why P681 is important. P681 enhances O-glycosylation in this region, which blocks furin cleavage. Mutation of P681 abrogates O-glycosylation and leads to increased furin cleavage.<br /> https://www.biorxiv.org/con...

On 2021-08-24 22:05:29, user Kelly Ten Hagen wrote:

Our recent preprint under review provides mechanistic insight as to why P681 is important. P681 enhances O-glycosylation in this region, which blocks furin cleavage. Mutation of P681 abrogates O-glycosylation and leads to increased furin cleavage.<br /> https://www.biorxiv.org/con...

On 2021-08-24 17:44:27, user Bogdan Pasaniuc wrote:

Many thanks for the very insightful questions and the super neat related literature (as usual the breeding genetics world has made super insightful advances prior to the human genetics community!). Your comments will allow us to clarify the points below and significantly improve the quality of our manuscript!

Re Q1:<br /> Yes indeed we use standardized genotypes for the purpose of having a simple toy figure. The main point we try to convey is that multiple causal effect size configurations can lead to the same observed marginal effects in GWAS. Thus, given GWAS data only, our approach proposes to sample across these causal configurations to estimate heritabilities. As with all toy figures, there is a balance between oversimplification and leading to misinterpretations; we will clarify this better in the legend/text.

Re Q2: <br /> First, indeed we make the assumption that the true causal effects \beta are independent across SNPs; this is a standard assumption that is made across most heritability work in human genetics and likely a good approximation in real data. That being said, we can drop this assumption then an extra covariance term exists (see bottom pp17) that could potentially be estimated/investigated; here we focus only on the \beta’R\beta term (our estimand of interest).

Second, as you clarify and we are in full agreement, the posterior samples have a covariance structure that is different from identity; i.e. \beta_i and \beta_j post samples are correlated. In the most simple case of the toy example of Fig 1 with two SNPs in perfect LD and with a sparsity model that only allows 1 causal, only one of the \beta’s will have non-zero effect in any configuration; therefore the two betas in the posterior are negatively correlated (r=-1). Or in the case of full infinitesimal model with independence of beta as prior, one can also straightforwardly derive the variance of the posterior as 1/n (1/(1-h2)R + M/(Nh2) I )^-1 (with apologies for self reference see https://www.biorxiv.org/con... or multiple other previous works with similar derivations). In the more general case when there is also a sparsity prior, an analytical solution for the posterior is hard to derive; this motivated us to sample from the posterior of \beta in this work.

Third, as defined in pp 17-18, our estimand of interest is \beta’R\beta where \beta are the unknown causal effects (also denoted as h2gene). We rely on an approximation of the posterior of \beta from SuSiE to sample from posterior effects and then approximate a sampling from posterior of \beta’R\beta (pp19); our proposed estimator has the simple form of avg (\beta’R\beta), where the average is taken across samples from posterior (samples that will have correlations across SNPs, as noted above). We fully acknowledge that other estimators for \beta’R\beta can be proposed (analytical and/or sampling based) that could be potentially more efficient and/or unbiased. In this work we chose to focus on this simple estimator that works reasonably well in simulations and real data.

We will revise to clarify all these points!

On 2021-08-20 09:56:24, user Gregor Gorjanc wrote:

Thanks for this nice work!

I would like to point out that your Figure 1 can be misleading. Additive genetic variance at a single bi-allelic locus under Hardy-Weinberg equilibrium is 2pq\beta^2, not just \beta^2, where p and q are allele frequencies and \beta is allele substitution effect. In general, this is 2pq(1+F)\beta^2, where F measures deviation from Hardy-Weinberg equilibrium. So, genetic variance and heritability at a locus depend on variance of genotypes and allele effects (classic reference for this is Falconer and MacKay, 1996). Hmm, are you skipping variance of genotypes, Var(x), because you standardise your genotypes (which changes what \beta mean)?

When you expand to a region, linkage-disequilibrium between loci within the region also kicks in. Also the region will be correlated to other regions, so variance partitioning is not really that meaningful looking just one region or locus at a time. You account for linkage-disequilibrium with your R matrix. But, when working with regions, correlation between estimates of \beta_i and \beta_j also kick in, even though we assume apriori that \beta_i and \beta_j are independent. Your derivation on page 17 works on the prior side, but does this also hold when you work with posteriors of \beta - they are quite correlated and possibly also correlated with genotypes (x) too?

We have been doing something similar, but focusing on the whole genome and partitioning additive genetic variance by chromosome (=region of a genome) https://www.biorxiv.org/con.... This work of ours relied a lot on the past work of:

Sorensen, D., R. Fernando, and D. Gianola, 2001 Inferring the trajectory of genetic variance in the course of artificial selection. Genetics Research 77: 83–94.

Gianola, D., G. de los Campos, W. G. Hill, E. Manfredi, and R. Fernando, 2009 Additive genetic variability and the Bayesian alphabet. Genetics 183: 347–363.

Lehermeier, C., G. de Los Campos, V. Wimmer, and C.-C. Schön, 2017 Genomic variance estimates: With or without disequilibrium covariances? Journal of Animal Breeding and Genetics 134: 232–241.

Allier, A., S. Teyssèdre, C. Lehermeier, B. Claustres, S. Maltese, et al., 2019 Assessment of breeding programs sustainability: application of phenotypic and genomic indicators to a north european grain maize program. Theoretical and Applied Genetics 132: 1321–1334.

Schreck, N., H.-P. Piepho, and M. Schlather, 2019 Best prediction of the additive genomic variance in random-effects models. Genetics 213: 379–394.

On 2021-08-24 15:53:56, user Pedro Mendes wrote:

Nice work. Table 1 should indicate that COPASI (of which I am one of the authors) is <br /> capable of both fixed-interval output and actual time step output (which<br /> is obtained by selecting the option "automatic" in our time course <br /> settings).

On 2021-08-24 13:34:31, user Georg Pabst wrote:

The paper has been published (open access) by now. Go to https://doi.org/10.1016/j.b...

On 2021-08-24 10:28:42, user yuri wrote:

Very nice work and well done. Was wondering why using adaptive sampling and not 16S with the rapid kit from ONT. Was it for comparison with Illumina? In case, I'd just give it a try, it'd cost one kit or a couple of primers + LSK-109 and a single flowcell. Just a curiosity though. It's also help doing an unbiased analysis of bacteria, just in case you missed something new....

On 2021-08-24 08:32:04, user Steven Groot wrote:

This is a very interesting manuscript, showing the potential of low oxygen storage for prolonging seed life span, while pointing to an important critical control point. Moreover, the manuscript provide important data on the biology behind.

On 2021-08-23 15:26:46, user Crap wrote:

Elimination of flow-through - does the Receptor not breathe?<br /> 50% efficacy study was done only for coughing, and not breathing, in an environment for only filtration through the mask, not taking into account side air flow-through. The study, although controlled, has questionable results at best. <br /> Further, model assumed an open room in calculations - eliminating any barriers, and heat sources for impact on mass transfer volumetric flow.

On 2021-08-23 00:57:39, user Martin Frith wrote:

Thanks for advancing our understanding of this interesting topic!

1. The definition of W4 has a typo: line 4 duplicates line 2.

2. In Fig. 4a it would be interesting to see ry words, which have the same d=1/4, instead of (a,b,n)-words.

3. Context-dependency decreases sensitivity, but it also increases specificity, does that compensate?

On 2021-08-22 21:06:38, user Fabiane Matos dos Santos wrote:

The research article entitled "Aspirin-triggered resolvin D1 reduces parasitic cardiac load by decreasing inflammation through N-formyl peptide receptor 2 in a chronic murine model of Chagas disease" by Ileana Carrillo et al., investigates the role of Aspirin-triggered resolvin D1 (AT-RvD1) as a pro-resolving mediator of inflammation that acts through N-formyl peptide receptor 2 (FPR2) using a FPR2 knockout murine model of chronic Trypanosoma cruzi infection. The data provided in the manuscript is important and interesting in connecting a link between AT-RvD1 as an attractive therapeutic activity due to its regulatory effect on the inflammatory response at the pathophysiology to cardiac pathology during T. cruzi infection. The manuscript is an original research article and it suffers with the following minor concerns:

Materials and methods section<br /> 1. Explain the rationale for the use of Dm28c strain of T. cruzi. What is the rationale to select this strain and provide more data concerning its virulence and susceptibility level to benznidazol?

Results and discussion sections<br /> 1. Include the data of eletrocardiographic variables in the manuscript, even in the absence of diferences among the groups of mice. Discussion about eletro<br /> cardiography abnormalites in Chagas cardiomyopathy needs to explore more parameters than only QT interval, for example: PR interval (iPR) and atrial block, axis of QRS, evidences of atrial fibrillation and right bundle branch block.

On 2021-08-21 03:53:31, user Aneth David wrote:

I found this paper really interesting and comprehensive. I liked the fact that they studied fungal communities too, I hadn't come across any study that has done this for reasons I don't understand.

I thoroughly enjoyed reading this paper.

On 2021-08-19 19:16:55, user Patricia G Cipriani wrote:

Please be aware that our article describing the characterization of interactions, phenotypes and localization of MIP-1 (C38D4.4) and MIP-2 (F58G11.3) has been published on July 5th, 2021. https://elifesciences.org/a.... These names were officially approved by the WormBase curator on July 12th, 2019.

On 2021-08-19 14:35:18, user Meng Wang wrote:

We have recently reported that the Tn5-based epigenomic profiling methods, especially Stacc-seq and CoBATCH, are prone to open chromatin bias (https://www.biorxiv.org/content/10.1101/2021.07.09.451758v1). Rather than directly address this bias issue, the authors of Stacc-seq argued in this preprint that FC-I normalization (normalizing by input/IgG control) was better than FC-C (normalizing by background) for Stacc-seq etc. data analysis. Based on this, they claimed that our results had “a major analysis issue”. However, the truth is that we had already used both FC-I and FC-C normalization methods and both showed clear open chromatin bias for Stacc-seq and CoBATCH. The fact that our analyses demonstrating that CUT&Tag (5% FPR) showed much lower FPR than Stacc-seq (30% FPR) or CoBATCH (50% FPR) indicated that the high FPRs were not due to “artificially enhanced the relative enrichment of potential open chromatin bias”, but an intrinsic problem of Stacc-seq and CoBATCH. In our opinion, the preprint has several problems, which are detailed below.

1. The preprint ignored the fact that we had already used both FC-I and FC-C normalization methods. The authors assumed that we only used FC-C for Stacc-seq etc. (Fig. 1A in Liu et al.). However, in fact we used both FC-C and FC-I in our analyses. In Fig. 1c, d and Fig. S2 of our manuscript (Wang et al.), methods labeled with “with IgG” were results from FC-I normalization, and methods without such label were results from FC-C normalization. Importantly, results from both normalizing methods showed clear open chromatin bias for Stacc-seq and CoBATCH (Fig. 1c,d and Fig. S2 in Wang et al.).

2. The results of global H3K27me3 enrichment at the Polycomb targets in this preprint (Fig. 1C) was contradictory to their claim that using FC-C would cause “complete loss or dramatic reduction of enrichment at true targets for datasets generated by Tn5-based methods”. Fig. 1C of this preprint showed a clear H3K27me3 enrichment around the TSS of Polycomb targets compared to adjacent regions when using FC-C. The difference between results from FC-I and FC-C is caused by the y-scale. The fold change is a relative measurement, so the y-scale of different normalization methods is not directly comparable. If they set the y-scale of FC-C to 0~2, the enrichment pattern would be highly similar to that using FC-I.

3. The genome browser snapshots of several loci in a large scale (low resolution) could not demonstrate that the results from FC-I and FC-C normalization are globally different. This preprint provided several example loci (Fig. 1B and Fig. 2 in Liu et al.) to show that using FC-C would cause “complete loss or dramatic reduction of enrichment at true targets for datasets generated by Tn5-based methods”. However, showing browser view of very large regions are misleading as the resolution is too low. For genome browser display, the look of the signal track patterns depends on y-scale, x-scale and windowing and smoothing function. When viewing a very large region, the signals are sampled and aggregated by genome browser and are not the raw signals. Thus, the patterns may not reflect the real situation. Indeed, when zoomed-in to check these regions, we found the peak patterns from FC-I and FC-C normalization are highly similar. In addition, examples from several loci could not reflect the global pattern. The global enrichment shown in Fig. 1C of this preprint did not support their conclusion, as discussed in point 2.

In summary, our original analysis has already included the normalization method suggested by the authors of this preprint. Results from both normalization methods supported that Stacc-seq and CoBATCH had high open chromatin bias. In fact, the results from this preprint also support our conclusions. In Fig. 2 of this preprint, regardless whether FC-I, FC-C or RPKM were used, the discrete peaks from Stacc-seq etc. were more similar to ATAC-seq peaks, but were totally different from ChIP-seq peaks.

Meng Wang and Yi Zhang<br /> Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, Massachusetts 02115, USA

On 2021-08-19 13:16:56, user Michael Galko wrote:

Losick: “A previous study reported cell enlargement with loss of cell-cell junctions in the adult Drosophila ventral abdominal epithelium with age (Scherfer et al., 2013), but did not characterize the extent of multinucleation nor whether cells were becoming polyploid.”

Scherfer 2013: Fig 1D (3 days old) and especially Figure 1E (14 days old) show clear multinuclearity of the aging epidermal cells that progresses with age. Fig 2B shows by transmission EM multinucleate cells that have no intervening membranes or junctions.

It is cool that the fusion can be blocked and that Brainbow analysis<br /> confirms the continuous cytoplasm. That said, proper credit for the first<br /> observation of this multinuclearity should be given. The paper here is written as if the Scherfer study did not observe/report multinuclearity. This is not correct.

On 2021-08-18 05:58:07, user Milan Vrtílek wrote:

This work has been just published under title "Macroevolutionary foundations of a recently evolved innate immune defense" in Evolution https://onlinelibrary.wiley...

On 2021-08-17 20:22:55, user Matt wrote:

Hi authors; regarding the findings of Siberian ancestry patterns in Europe (which roughly seem to conform to a distance based pattern from the northeast to southwest), do these replicate in simpler f statistic measures? E.g. the same clinal patterns are present and they replicate without an explanation that can be found in varying proportions of ancient populations within Europe ("WHG" / "EEF" / "Steppe"). If not, isn't this a problem for the finding and if not a problem, why not?

On 2021-08-17 20:14:14, user Sue Bello wrote:

There appears to be something wrong with the pdf. When I attempt to open the downloaded file with Acrobat I get an error message "There was an error reading this document (14)".

On 2021-08-17 16:08:17, user Graham Hitman wrote:

This MS is now published in BMC endocrine disorders <br /> The link is<br /> https://rdcu.be/ct4S2

On 2021-08-17 12:11:04, user passanger lost wrote:

Not found the Supplementary Table files

On 2021-08-17 09:17:54, user passanger lost wrote:

Can not found the SUPPLEMENTARY INFORMATION files

On 2021-08-16 17:36:20, user Frank William Soveg wrote:

Figure 2 and the supplementary materials are missing from the manuscript. Can the authors please make this available? Thank you.

On 2021-08-16 15:57:24, user bric hard wrote:

Very Interesting.I did not expect the results! Take good care Joao...

On 2021-08-16 13:09:27, user Lukas Tanner wrote:

Dear authors, <br /> Thanks for this very interesting study. Similar findings have been previously described by Tabata et al in 2017. They show the same mechanism/principle for thymidine phosphorylase (https://www.cell.com/cell-r... in fueling cancer cells under nutrient deprived conditions.<br /> Thanks and best wishes, <br /> Lukas Tanner

On 2021-08-16 11:00:28, user Gregory Bix wrote:

This preprint has been published in the journal Life Sciences.<br /> https://www.sciencedirect.c...

On 2021-08-16 09:39:34, user Richard Smith Lab wrote:

Supplemental movies:<br /> https://youtu.be/q6TGjKT4lxc<br /> https://youtu.be/l-avOqrB_TI<br /> https://youtu.be/KwrwHor5p_I<br /> https://youtu.be/Bh5QEFjL1Uo<br /> https://youtu.be/31IjUtpP6os<br /> https://youtu.be/jEctM96Algo<br /> https://youtu.be/NyTcEjorXdc

On 2021-08-16 08:53:58, user Qiao-Ping Kevin Wang wrote:

This is a very interesting and elegant study. Lot of GWAS studies have revealed that a few variants like rs1421085 in FTO non-coding region are highly associated with obesity. However, none of these variants has been functionally validated in vivo due to tremendous difficulties and huge costs. In this study, the authors firstly demonstrated that a single rs1421085 variant T>C in the non-coding area was a functional point and the mutation from T to C could boost thermogenesis in global knock-in and BAT specific knock-in mice. Mechanistically, T>C mutation could enhance FTO gene expression, which in some way, boost UCP1 expression. Furthermore, based on the frequency of this mutation in different population around the world, the authors proposed a very intriguing hypothesis that this mutation with increased thermogenesis capacity help human to adapt to coldness, thus in certain way facilitating human to migrate out Africa and spread all the world. This study gives us some fresh view that the SNPs identified from GWAS are functional and that GWAS is an effective way to identify genetic factors for complex diseases.

However, there are some concerns. Since this point localizes in non-coding region, which is usually not conserved across species, how the authors could prove this be true in humans? Except FTO, does this variant affect other known important genes like IRX3 and IRX5, or more thermogenesis related genes? Is possible that the point mutation changes the local chromatin structure if it is so important?

On 2021-08-15 19:28:22, user Anand Ramachandran wrote:

HELLO has been significantly reworked with new methodologies for hybrid and stand-alone variant calling. These methodologies and results are published at:

https://bmcbioinformatics.b...

On 2021-08-15 18:03:00, user Sangeeta Nath wrote:

The paper is now published @ BBA-Mol Basis Dis<br /> https://www.sciencedirect.c...

On 2021-08-15 09:17:23, user David Pellow wrote:

Will the performance of this tool be compared to the standard tools for metagenomic plasmid assembly?

On 2021-08-13 23:33:04, user Xiaoxu Yang wrote:

The manuscript is now published online in Cell https://doi.org/10.1016/j.c....

On 2021-08-13 22:21:40, user Patricia wrote:

Many of your discussion points were addressed in the Lee and Wing preprint, surprised you didn't quote it. https://www.biorxiv.org/con...

On 2021-08-11 21:24:12, user jiarong wrote:

Just want to leave other readers a notice here: I found the accuracy or F1 score of a few gene-based viral identification tools reported in this benchmark study (<0.8) is quite different from those reported in other studies (usually >0.9, e.g. VirSorter2 and VIBRANT). I have got in contact with the authors and took a deep dive into the simulated data, and found there was a significant amount of viral sequence contamination in refseq plasmid databsae and thus in the simulated plasmid contig dataset. There were also some prophage not cleaned by prophage identification tools. The combined viral contaminants in plasmid and host set is comparable to the among of viral contigs in the viral set, which can significantly skew the performance stats. More details can be found in my report here: https://github.com/jiarong/....<br /> I have informed the issue to the authors and they are working on the issue.

On 2021-08-11 06:50:33, user Ticklicker wrote:

Are your planning to share your data? I would like to know the exact date of collection, the county & state, and map coordinates (lat, long) or approximate location (distance & directiion from nearest town) for the 4 "positive' deer samples that were collected in 2019 (1) and January 2020 (3). Also, have you considered that deer samples that tested "positive" for SARS2 may represent instead cross-reaction detection of tick-borne viruses; for example, the "Heartland Virus", which may be spreading eastward since its 2009 discovery at 2 locations in NW Missouri?

On 2021-08-11 02:19:39, user Brian Coyle wrote:

Virus don't easily infect ticks, believe it or not. Coronavirus haven't. It's because virus infect either anthropods or mammals.

On 2021-08-10 16:44:45, user hongmi wrote:

The SARS-CoV-2 sVNT can also detect SARS infection. Actually the cross reaction is stronger 17 years after infection, compared to within a year. Could your positive signal in 2019 and early 2020, and also some low-moderate signals in 2021, was due to this cross reaction?

On 2021-08-03 15:53:33, user Jessica Glasscock wrote:

I was wondering if researchers have considered, or are considering ticks, as the possible link between whitetail deer and humans. I know in the suburban and urban areas of the east coast, deer populations are highly concentrated and lead to increased tick problems and humans being infected with tick borne illnesses. Ticks might be the method in which SARS-CoV-2 was transmitted between humans and deer. Thanks for your time.

On 2021-08-09 13:14:21, user Shuaibing Ren wrote:

Equation 5: P(G) should be P(Gl)

On 2021-08-09 08:24:42, user Jiangming Sun wrote:

All values in a row (black) are 0 in Fig. 1A. Shouldn't remove such row first before any matrix operations?

On 2021-08-09 06:46:31, user Prof. T. K. Wood wrote:

Authors should also compare their directed evolution results with the 20 odd papers that have previously found beneficial mutations on this class of enzymes using directed evolution.

On 2021-08-08 23:50:11, user Chengxin Zhang wrote:

Thank you for sharing this potentially important study. There are a few questions regarding the architecture and the benchmark study.

1. What is the loss function of RGN2 (i.e. loss function for the output of the geometry module). Is it the same as RGN1, i.e. dRMSD, or a new loss function that can distinguish mirrored structures.

2. The performance of RGN1 is highly dependent on the random seed used to initialize the training. Is this still the case for RGN2? In other words, for the same testing protein, if we use two RGN2 models trained on the same training set but different random initialization, what is the GDT_TS between the two resulting structure models?

3. What is the accuracy of predicted theta and phi? This question is similar to a comment on the RGN1 paper (https://www.biorxiv.org/con... which was not fully explored. It is likely that including an auxiliary loss for theta and phi can not only improve local structure correctness but also resolve the chirality issue, which was not addressed by the dRMSD loss.

4. Both RGN1 and RGN2 construct the peptide chain in torsion space, i.e. Ramachandran angles for RGN1; a bond angle phi and a torsion angle theta for RGN2. As pointed out by a recent preprint (https://arxiv.org/abs/2105...., "One well-known problem is that internal coordinates are extremely sensitive to small deviations as the latter easily propagate through the protein, generating large errors in the reconstructed structure." Is there an attempt to address this issue?

5. RGN2 is trained on ASTRAL domains, most of which are "normal" proteins that are neither orphan nor designed proteins. Therefore, the single-sequence structure prediction performance difference between RGN2 and third-party programs (AlphaFold2, RoseTTaFold and trRosetta) should be comparable regardless of whether the testing proteins are orphan or not, provide that only a single sequence rather than MSAs is fed to the three third-party programs. On non-orphan proteins, e.g. CASP14 FM targets that are not used in RGN2 training, can RGN2 still outperform single-sequence-based AlphaFold2, RoseTTaFold and trRosetta?

On 2021-08-07 14:52:11, user Emil Kirkegaard wrote:

Contrary to what the authors say, these data are NOT publicly available. They are in fact hidden and one has to apply via some university institution. https://genomics.ut.ee/en/b...

On 2021-08-07 12:30:57, user Александр Федотов wrote:

There are 0 not predicted proteins, not 29. Please fix it.

On 2021-08-06 17:21:33, user KaAcWh wrote:

Very interesting study. I am curious to hear why the authors did not make any reference to the fact that if Spike is inducing endothelial inflammation via integrin5 and NF-KB, this means that there is a very real risk of such occurrence in people vaccinated with mRNA and vectorized vaccines that lead to the endogenous production of full length (or, even only RBD) of Spike. In other words, 2+2 should equal 4, even in these strange times. Any thoughts?

On 2021-08-05 09:34:08, user William Martin wrote:

This is really interesting. Life on geochemical H2, geochemical formate and geochemical glycine. Just barely possible, but possible, and taking place.