Top 10 Biorxiv Papers Today in Genomics


2.035 Mikeys
#1. Transposable elements drive reorganisation of 3D chromatin during early embryogenesis
Kai Kruse, Noelia Diaz, Rocio Enriquez-Gasca, Xavier Gaume, Maria-Elena Torres-Padilla, Juan M Vaquerizas
Transposable elements are abundant genetic components of eukaryotic genomes with important regulatory features affecting transcription, splicing, and recombination, among others. Here we demonstrate that the Murine Endogenous Retroviral Element (MuERV-L/MERVL) family of transposable elements drives the 3D reorganisation of the genome in the early mouse embryo. By generating Hi-C data in 2-cell-like cells, we show that MERLV elements promote the formation of insulating domain boundaries throughout the genome in vivo and in vitro. The formation of these boundaries is coupled to the upregulation of directional transcription from MERVL, which results in the activation of a subset of the gene expression programme of the 2-cell stage embryo. Domain boundaries in the 2-cell stage embryo are transient and can be remodelled without undergoing cell division. Remarkably, we find extensive inter-strain MERVL variation, suggesting multiple non-overlapping rounds of recent genome invasion and a high regulatory plasticity of genome organisation....
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generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine Endogenous Retroviral Element (MuERV-L/MERVL) promote formation of insulating domain boundaries coupled to upregulation of directional MERVL transcription https://t.co/VXwNJcrrSg
vaquerizasjm: 1/ Excited to announce our latest work looking at the role of transposable elements in regulating 3D chromatin during early mammalian development, out now in @biorxivpreprint @vaquerizas_lab #3DGenome #transposons #early_mouse_development https://t.co/M67x4vZu7D
vaquerizasjm: 1/ Excited to announce out latest work looking at the role of transposable elements in regulating 3D chromatin during early mammalian development, out now in @biorxivpreprint @vaquerizas_lab #3DGenome #transposons #early_mouse_development https://t.co/M67x4vZu7D
vaquerizas_lab: Our latest @vaquerizas_Lab results are out in @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis. Work led by Kai Kruse (@kaukrise) in collaboration with the Torres-Padilla lab. https://t.co/Gi02JnSCJA Summary below: (1/n) https://t.co/nOch6X7JYK
vaquerizas_lab: Really nice work from Kai Kruse (@kaukrise), Noelia Díaz (@NoeliaDiaz27), and Rocio Enriquez-Gasca, and a fun collaboration with the Torres-Padilla lab (@epigeneticsHMGU) (8/8) https://t.co/Gi02JnSCJA
mirimiam: “MERLV [transposable] elements promote the formation of insulating domain boundaries throughout the genome in vivo and in vitro. The formation of these boundaries is coupled to the upregulation of directional transcription from MERVL” https://t.co/uu8QtnaBbg
Dariloops: Transposable elements promoting the formation of chromatin boundaries!!! Well done @vaquerizas_lab https://t.co/CF9yeDUGcK
LlewellynGreen: A lot of interesting stuff to process in this one: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis (mouse) https://t.co/gt09mPt2aV (4)
kwartiov: Evidence for the functions of "junk DNA". Are the ancient viruses responsible for development? Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/uX1PJBwj3B
etrompouki: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis | bioRxiv https://t.co/wxYSmtu685
arianelismer: MERVL transposable elements regulate 3D chromatin conformation in the 2-cell embryo by transiently forming insulating domain boundaries. Really cool functional insight on the role of TEs during early embryogenesis!! https://t.co/O68y1zdgj2
minjaf: Really fascinating story from @vaquerizas_lab! MERVL transposable elements shape 3D genome architecture in mouse blastomeres. Waiting follow-up about how exactly Dux1 and/or MERVL induce insulation, and most important, what is it's functional meaning? https://t.co/zQomApwx4i https://t.co/FGci48h46w
PromPreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/kpcoVpWdSK
vaschetto_luis: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/Ggmd8q1yZS
BioRxivCurator: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/Yv4NOoPLhr
Julie_B92: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Alfons_Valencia: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
NatureSMB: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
3D_Genome: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
CedricFeschotte: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Team_Thomma: RT @biorxiv_genomic: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/sOKybIlfeQ #biorxi…
grawoig: RT @PromPreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/kpcoVpWdSK
grawoig: RT @etrompouki: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis | bioRxiv https://t.co/wxYSmtu685
Noncodarnia: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
timtriche: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
DonnellyCentre: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
EpigeneticsGuy: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
elenagomezdiaz: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
tylervkent: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
vaquerizasjm: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
ameliacervera: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
JuliaHorsfield: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Finnsense: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
tsubu2an: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
jsteward2930: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
laloizquierdo90: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
lambros_f: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
mirimiam: RT @Dariloops: Transposable elements promoting the formation of chromatin boundaries!!! Well done @vaquerizas_lab https://t.co/CF9yeDUGcK
PablixSil: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
marcotrizzino: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
RobKlose: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Elsie_youlater: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
StanInScience: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
GJCVeenstra: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
mate_palfy: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
nzradu: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
i_jerko: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
_diegobalboa_: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
BioGibberish: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
drosoigmm: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
drosoigmm: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
PgpMartin: RT @Dariloops: Transposable elements promoting the formation of chromatin boundaries!!! Well done @vaquerizas_lab https://t.co/CF9yeDUGcK
sudhirthakurela: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
PrecursorCell: RT @etrompouki: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis | bioRxiv https://t.co/wxYSmtu685
a_z_usa__: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
tsagakis_bio: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
awuebersohn: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Nina_CabezasW: RT @etrompouki: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis | bioRxiv https://t.co/wxYSmtu685
Moreno_AA: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
AGuleren: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
quirze92: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Milana_FM: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
CantoneIrene: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
ilyavkirov: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
the_beckhamin: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
AntoineZalc: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
Qenvio: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Chris_G_Smith1: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
cjy8709: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
ChingHua_Shih: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
psaima: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
MO_BAUDEMENT: RT @Dariloops: Transposable elements promoting the formation of chromatin boundaries!!! Well done @vaquerizas_lab https://t.co/CF9yeDUGcK
AlejoFraticelli: RT @etrompouki: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis | bioRxiv https://t.co/wxYSmtu685
Circe777: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
lunazere9: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
SaraMaciasRNA: RT @biorxivpreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/3MagNlIBUG #bioRxiv
drjaydutt: RT @biorxiv_genomic: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/sOKybIlfeQ #biorxi…
Adamu56106323: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
rozesshr: RT @PromPreprint: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/kpcoVpWdSK
Feli_Bas: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
bgbrink: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
Can_mi_lan_o: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
alexia_grasso: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
ChongjingX: RT @biorxiv_genomic: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/sOKybIlfeQ #biorxi…
StephaneBoissi1: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
WeltnerJ: RT @generegulation: Transposable elements drive reorganisation of 3D chromatin during early embryogenesis https://t.co/OxOcNccoVG Murine En…
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Sample Sizes : [15, 30, 1050000]
Authors: 6
Total Words: 13629
Unqiue Words: 3754

2.026 Mikeys
#2. Identification and mitigation of pervasive off-target activity in CRISPR-Cas9 screens for essential non-coding elements
Josh Tycko, Michael Wainberg, Georgi K Marinov, Oana Ursu, Gaelen T Hess, Braeden K Ego, Aradhana, Amy Li, Alisa Truong, Alexandro E Trevino, Kaitlyn Spees, David Yao, Irene M Kaplow, Peyton G Greenside, David W Morgens, Douglas H Phanstiel, Michael P Snyder, Lacramioara Bintu, William J Greenleaf, Anshul Kundaje, Michael C Bassik
Pooled CRISPR-Cas9 screens have recently emerged as a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we conducted a genome-scale screen for essential CTCF loop anchors in the K562 leukemia cell line. Surprisingly, the primary drivers of signal in this screen were single guide RNAs (sgRNAs) with low specificity scores. After removing these guides, we found that there were no CTCF loop anchors critical for cell growth. We also observed this effect in an independent screen fine-mapping the core motifs in enhancers of the GATA1 gene. We then conducted screens in parallel with CRISPRi and CRISPRa, which do not induce DNA damage, and found that an unexpected and distinct set of off-targets also caused strong confounding growth effects with these epigenome-editing platforms. Promisingly, strict filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and allowed...
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rnomics: Top #tweeted story in #bioscience: Identification and mitigation of pervasive off-target activity in CRISPR-Cas9 screens for essential non-coding elements | bioRxiv https://t.co/ryczfSqwVz, see more https://t.co/kME3G1o122
VidigalJoana: Great work highlighting how our https://t.co/4SBnT8ysWo can be used to design gRNAs with no off-target activity to yield high quality data! https://t.co/7gY7BT4x7q 👇 https://t.co/s1UCYiWg3i
PromPreprint: Identification and mitigation of pervasive off-target activity in CRISPR-Cas9 screens for essential non-coding elements https://t.co/lNCiwtoG10
BioRxivCurator: Identification and mitigation of pervasive off-target activity in CRISPR-Cas9 screens for essential non-coding elements https://t.co/h5MSI4R0Jg
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Sample Sizes : None.
Authors: 21
Total Words: 17685
Unqiue Words: 4880

2.022 Mikeys
#3. Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores
Sam Trejo, Benjamin W. Domingue
Summary statistics from a genome-wide association study (GWAS) can be used to generate a polygenic score (PGS). For complex, behavioral traits, the correlation between individual PGS and phenotype may contain bias alongside the causal effect of the individual's genes (due to geographic, ancestral, and/or socioeconomic confounding). We formalize the recent introduction of a different source of bias in regression models using PGSs: the effects of parental genes on offspring outcomes (i.e. genetic nurture). GWAS do not discriminate between the various pathways through which genes influence outcomes, meaning existing PGSs capture both direct genetic effects and genetic nurture effects. We construct a structural model for genetic effects and show that, unlike other sources of bias in PGSs, the presence of genetic nurture biases PGS coefficients from both naive OLS (between-family) and family fixed effects (within-family) regressions. This bias is in opposite directions; while naive OLS estimates are biased upwards, family fixed effects...
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jorsmo: Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores | bioRxiv https://t.co/ekQ5PtH6tc
pnin1957: RT @jorsmo: Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores | bioRxiv https://t.co/ekQ5PtH6tc
dccc_phd: RT @jorsmo: Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores | bioRxiv https://t.co/ekQ5PtH6tc
WDavidHill: RT @jorsmo: Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores | bioRxiv https://t.co/ekQ5PtH6tc
patrickaturley: RT @jorsmo: Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores | bioRxiv https://t.co/ekQ5PtH6tc
evogen_p: RT @biorxiv_genomic: Genetic Nature or Genetic Nurture? Quantifying Bias in Analyses Using Polygenic Scores https://t.co/W71DGCBoWm #biorx…
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Sample Sizes : None.
Authors: 2
Total Words: 8990
Unqiue Words: 2326

2.021 Mikeys
#4. LINE-1 retrotransposition impacts the genome of human pre implantation embryos and extraembryonic tissues
Martin Munoz-Lopez, Raquel Vilar, Claude Philippe, Raheleh Rahbari, Sandra R. Richardson, Miguel Andres-Anton, Thomas Widmann, David Cano, Jose L. Cortes, Alejandro Rubio-Roldan, Etienne Guichard, Sara R. Heras, Francisco J. Sanchez-Luque, Maria Morell, Elisabet Aguilar, Marta Garcia-Canadas, Laura Sanchez, Angela Macia, Pedro Vilches, Maria Concepcion Nieto-Perez, Antonio Gomez-Martin, Beatriz Gonzalez-Alzaga, Clemente Aguilar- Garduno, Adam D. Ewing, Marina Lacasana, Ignacio S. Alvarez, Richard Badge, Geoffrey J. Faulkner, Gael Cristofari, Jose L. Garcia-Perez
Long Interspersed Element 1 (LINE-1/L1) is an abundant retrotransposon that has greatly impacted human genome evolution. LINE-1s are responsible for the generation of millions of insertions in the current human population. The characterization of sporadic cases of mosaic individuals carrying pathogenic L1-insertions, suggest that heritable insertions occurs during early embryogenesis. However, the timing and potential genomic impact of LINE-1 mobilization during early embryogenesis is unknown. Here, we demonstrate that inner cell mass of human pre-implantation embryos support the expression and retrotransposition of LINE-1s. Additionally, we show that LINE-1s are expressed in trophectoderm cells of embryos, and identify placenta-restricted endogenous LINE-1 insertions in newborns. Using human embryonic stem cells as a model of postimplantation epiblast cells, we demonstrate ongoing LINE-1 retrotransposition, which can impact expression of targeted genes. Our data demonstrate that LINE-1 retrotransposition starts very shortly after...
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biorxivpreprint: LINE-1 retrotransposition impacts the genome of human pre implantation embryos and extraembryonic tissues https://t.co/cMNEvhbhS9 #bioRxiv
westr: LINE-1 #retrotransposition impacts the genome of human pre implantation embryos and extraembryonic tissues https://t.co/WbgR89Mhq7 #line1 A source of unequivocal phenotypical change. How prevalent? TBD.
biorxiv_genomic: LINE-1 retrotransposition impacts the genome of human pre implantation embryos and extraembryonic tissues https://t.co/pZAz2VLwki #biorxiv_genomic
Jeew333T: Long Interspersed Element 1 (LINE-1/L1) is an abundant retrotransposon that has greatly impacted human genome evolution. LINE-1s are responsible for the generation of millions of insertions in the current human population. https://t.co/YC3fDs5Khy
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Sample Sizes : [10, 10, 16, 10, 3, 3, 6, 10, 20, 16, 18, 5, 7, 10, 2]
Authors: 30
Total Words: 16004
Unqiue Words: 4498

2.017 Mikeys
#5. Distributed representations of protein domains and genomes and their compositionality
Adrian Viehweger, Sebastian Krautwurst, Brigitte Koenig, Manja Marz
Learning algorithms have at their disposal an ever-growing number of metagenomes for biomining and the study of microbial functions. We propose a novel representation of function called nanotext that scales to very large data sets while capturing precise functional relationships. These relationships are learned from a corpus of 32 thousand genome assemblies with 145 million protein domains. We treat the protein domains in a genome like words in a document, assuming that protein domains in a similar context have similar "meaning". This meaning can be distributed by the Word2Vec embedding algorithm over a vector of numbers. These vectors not only encode function but can be used to predict even complex genomic features and phenotypes. We apply nanotext to data from the Tara ocean expedition to predict plausible culture media and growth temperatures for microorganisms from their metagenome assembled genomes (MAGs) alone. nanotext is freely released under a BSD licence (https://github.com/phiweger/nanotext).
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phiweger: @spleonard1 ok, how about this https://t.co/TPSPkwUhKs
phiweger: Ever thought about proteins in a genome like words in a document? We did, and there’s a lot you can do with this abstraction, like taxonomy and machine learning — https://t.co/TPSPkwUhKs
rmflight: RT @biorxiv_genomic: Distributed representations of protein domains and genomes and their compositionality https://t.co/4qFc4rvTro #biorxi…
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Domains as words, genomes as documents.

Repository: nanotext
User: phiweger
Language: Python
Stargazers: 2
Subscribers: 2
Forks: 0
Open Issues: 0
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Sample Sizes : [93]
Authors: 4
Total Words: 9774
Unqiue Words: 2943

2.016 Mikeys
#6. GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes
Daniel J Wilson, The CRyPTIC Consortium
The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters such as dN/dS, but analysing very large datasets poses a major statistical challenge. Here I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: (i) it is fast no matter how large the sample size and (ii) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution...
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jennifergardy: Nice preprint out from @apemandan & the @crypticproject (including yours truly) - rapid dN/dS estimation from huge datasets, demoed here with over 10k TB genomes. For all your rapid population genomics/selection needs. https://t.co/Vg4PnCZG2T
rnomics: Top #tweeted story in #bioscience: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes | bioRxiv https://t.co/SdZyMtt51u, see more https://t.co/kME3G16pDs
osilander: looks super interesting https://t.co/jOPLOBxUMq "Among the benefits of the approach, haplotype information is not required and missing data is easily handled." https://t.co/09mInp09Up
jcamthrash: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/4OzdYMtViE
razoralign: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes: https://t.co/8iBNtJ2uB8
level3defless: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/hrtAMsKpap
BioMickWatson: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
BioRxivCurator: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/U1wsXAACQi
Triedzi: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/jAdx0CBH9v
OmicsOmicsBlog: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
msmjetten: RT @jcamthrash: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/4OzdYMtViE
BarkerLab: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
AlbertVilella: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
balcjos: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
MOUGK: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
hlcao: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
mmzbd: RT @jcamthrash: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/4OzdYMtViE
gregory_annc: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
PierisProject: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
JackieGoordial: RT @jcamthrash: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/4OzdYMtViE
TaromaedaMaedat: RT @level3defless: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/hrtAMsKpap
mehrshmali: RT @jcamthrash: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/4OzdYMtViE
perilousUnknown: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
francois_sabot: RT @biorxiv_genomic: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/pOiCsRWhyq #biorxiv_ge…
DaneshMoradi: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
vallenet: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
rbacigalupe: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
ejfresch: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
smithjac7: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
AdrianA40807461: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
ilnam_kang: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
LauraTreu: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
Xtreme_bugs: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
ChengChiangWu: RT @biorxiv_genomic: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/pOiCsRWhyq #biorxiv_ge…
evogen_p: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
genolib_19: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
christear: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
ArianeEThomas: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
vophuoctuan2: RT @biorxivpreprint: GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes https://t.co/VVCFQu88OA #bioRxiv
Github

GCAT with omegaMap library

Repository: gcat-omegaMap
User: danny-wilson
Language: C
Stargazers: 0
Subscribers: 1
Forks: 0
Open Issues: 0
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Authors: 2
Total Words: 9013
Unqiue Words: 3111

2.008 Mikeys
#7. Genome-wide epistasis and co-selection study using mutual information
Johan Pensar, Santeri Puranen, Neil MacAlasdair, Juri Kuronen, Gerry Tonkin-Hill, Maiju Pesonen, Brian Arnold, Yingying Xu, Aleksi Sipola, Leonor Sanchez-Buso, John A Lees, Claire Chewapreecha, Stephen D Bentley, Simon R Harris, Julian Parkhill, Nicholas J Croucher, Jukka Corander
Discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level co-variation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria. SpydrPick incorporates an efficient correction for population structure, which is demonstrated to maintain a very low rate of false positive findings among those SNP pairs highlighted to deviate significantly from the null hypothesis of neutral co-evolution in simulated data. We also introduce a new type of visualization of the results similar to the Manhattan plots used in genome-wide association studies, which enables rapid exploration of the identified signals of co-evolution. Application of the method to...
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biorxivpreprint: Genome-wide epistasis and co-selection study using mutual information https://t.co/OtWJQckLVb #bioRxiv
biorxiv_genomic: Genome-wide epistasis and co-selection study using mutual information https://t.co/e2O97jr9He #biorxiv_genomic
DanielFalush: Correlation based epistasis detection method from Corander and colleagues: https://t.co/5f1qLaahUk plus empirical results suggesting they work better than DCA (confirming my general experience): https://t.co/37M2LwC5CF
alanmcn1: RT @DanielFalush: Correlation based epistasis detection method from Corander and colleagues: https://t.co/5f1qLaahUk plus empirical results…
MahaFarhat: RT @DanielFalush: Correlation based epistasis detection method from Corander and colleagues: https://t.co/5f1qLaahUk plus empirical results…
AGuleren: RT @biorxivpreprint: Genome-wide epistasis and co-selection study using mutual information https://t.co/OtWJQckLVb #bioRxiv
AmineNamouchi: RT @DanielFalush: Correlation based epistasis detection method from Corander and colleagues: https://t.co/5f1qLaahUk plus empirical results…
zhenbin_hu: RT @biorxiv_genomic: Genome-wide epistasis and co-selection study using mutual information https://t.co/e2O97jr9He #biorxiv_genomic
midichloria: RT @DanielFalush: Correlation based epistasis detection method from Corander and colleagues: https://t.co/5f1qLaahUk plus empirical results…
Github

SpydrPick: mutual information based detection of pairs of genomic loci co-evolving under a shared selective pressure.

Repository: SpydrPick
User: santeripuranen
Language: C++
Stargazers: 0
Subscribers: 2
Forks: 0
Open Issues: 0
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Authors: 17
Total Words: 9784
Unqiue Words: 3250

2.002 Mikeys
#8. Comprehensive analysis of RNA-seq kits for standard, low and ultra-low quantity samples
Marie-Ange Palomares, Cyril Dalmasso, Eric Bonnet, Céline Derbois, Solène Brohard-Julien, Christophe Ambroise, Christophe Battail, Jean-François Deleuze, Robert Olaso
High-throughput RNA-sequencing has become the gold standard method for whole-transcriptome gene expression analysis, and is widely used in numerous applications to study cell and tissue transcriptomes. It is also being increasingly used in a number of clinical applications, including expression profiling for diagnostics and alternative transcript detection. However, despite its many advantages, RNA sequencing can be challenging in some situations, for instance in cases of low input amounts or degraded RNA samples. Several protocols have been proposed to overcome these challenges, and many are available as commercial kits. In this study, we comprehensively test three recent commercial technologies for RNA-seq library preparation (TruSeq, SMARTer and SMARTer Ultra-Low) on human reference tissue preparations, using standard (1ug), low (100 and 10 ng) and ultra-low (< 1 ng) input amounts, and for mRNA and total RNA, stranded or unstranded. The results are analyzed using read quality and alignment metrics, gene detection and...
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PoisonEcology: RT @biorxivpreprint: Comprehensive analysis of RNA-seq kits for standard, low and ultra-low quantity samples https://t.co/hmVFc4GM8q #bioR…
LeightonHDuncan: RT @biorxivpreprint: Comprehensive analysis of RNA-seq kits for standard, low and ultra-low quantity samples https://t.co/hmVFc4GM8q #bioR…
AgnesGenomiX: RT @biorxivpreprint: Comprehensive analysis of RNA-seq kits for standard, low and ultra-low quantity samples https://t.co/hmVFc4GM8q #bioR…
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Authors: 9
Total Words: 7196
Unqiue Words: 1804

1.998 Mikeys
#9. Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory
Aurelien Chateigner, Marie-Claude Lesage-Descauses, Odile Rogier, Veronique Jorge, Jean-Charles Leple, Veronique Brunaud, Christine Paysant-Le Roux, Ludivine Soubigou-Taconnat, Marie-Laure Martin-Magniette, Leopoldo Sanchez, Vincent Segura
The recently proposed omnigenic model makes use of network theory to distinguish central (or core) from peripheral genes underlying phenotypes. Core genes are typically few, they marginally contribute highly but altogether explain only a small part of trait heritability, while peripheral genes, each of small influence, are so numerous that they finally lead risk. In order to test this model, we collected and sequenced RNA from 459 European black poplars. We built the coexpression networks to define core and peripheral genes as the most and least connected ones. We computed the role of each of these gene sets in the prediction of phenotypes, with a linear additive model and an interactive neural network model. These analyses showed that core genes act directly and contribute additively to phenotypes, consistent with a downstream position in a biological cascade. Oppositely, peripheral genes interact to influence phenotypes, consistent with an upstream position. Overall, our work is the first empirical proof that omnigenic holds in...
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biorxivpreprint: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/DgybNtNUAR #bioRxiv
biorxiv_genomic: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/XVhTx8RMVo #biorxiv_genomic
SPS_Plant_Sci: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory (coll BioForA, BIOGECO, IPS2/SPS) | @scoopit https://t.co/08GST7lxf4
Aurelou: Our new preprint is live ! We did #predictions with #linearmodels and #NeuralNetworks to support the #omnigenic theory in trees ! https://t.co/YvYH7aHqZ7 @Vincent__Segura @jkpritch @SPS_Plant_Sci @Inra_Intl @Inra_France @InraVdl
dccc_phd: RT @biorxiv_genomic: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/XVhTx8RMVo…
gau: RT @biorxiv_genomic: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/XVhTx8RMVo…
big_data_kane: RT @biorxivpreprint: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/DgybNtNUAR…
Aurelou: RT @biorxiv_genomic: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/XVhTx8RMVo…
Aurelou: RT @biorxivpreprint: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/DgybNtNUAR…
vigocarpathian: RT @biorxiv_genomic: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/XVhTx8RMVo…
Vincent__Segura: RT @biorxivpreprint: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/DgybNtNUAR…
Vincent__Segura: RT @biorxiv_genomic: Gene Expression Predictions and Networks in Natural Populations Supports the Omnigenic Theory https://t.co/XVhTx8RMVo…
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Authors: 11
Total Words: 10709
Unqiue Words: 3007

1.998 Mikeys
#10. Physiological changes during cellular ageing in fission yeast drive non-random patterns of genome rearrangements
David A Ellis, Felix Reyes-Martin, Maria Rodriguez-Lopez, Cristina Cotobal Martin, Daniel C Jeffares, Victor A Tallada, Jurg Bahler
Aberrant repair of DNA double-strand breaks can recombine distant pairs of chromosomal breakpoints. Such chromosomal rearrangements are a hallmark of ageing and markedly compromise genome structure and function. Rearrangements are challenging to detect in genomes of non-dividing cell populations, because they reflect individually rare, heterogeneous events. The genomic distribution of de novo rearrangements in non-dividing cells, and their dynamics during ageing, remain therefore poorly characterized. Studies of genomic instability in ageing cells have focused on mitochondrial DNA, small genetic variants, or proliferating cells. To gain a better understanding of genome rearrangements during chronological ageing, we reduced their complexity to a single diagnostic measure, the DNA breakpoint junctions, allowing us to interrogate the changing genomic landscape in non-dividing cells of fission yeast ( Schizosaccharomyces pombe ). Aberrant DNA junctions that accumulated with age were associated with microhomology sequences and gene...
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Sample Sizes : [100, 18, 8, 8]
Authors: 7
Total Words: 12150
Unqiue Words: 3584

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Assert is a website where the best academic papers on arXiv (computer science, math, physics), bioRxiv (biology), BITSS (reproducibility), EarthArXiv (earth science), engrXiv (engineering), LawArXiv (law), PsyArXiv (psychology), SocArXiv (social science), and SportRxiv (sport research) bubble to the top each day.

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