Discover and read the best of Twitter Threads about #ASHG20
Most recents (24)
#ASHG20 OSR Want to understand gene expression in eukaryotic cells. Especially coupling of translation and mRNA decay.
#ASHG20 OSR Two main avenues. 1) mechanistic studies. 2) regulation of mRNA decay and translation during development.
#ASHG20 XX How do you go from genotype to phenotypes with so much genetic data? Long way to go to tackle this challenge. Many different players from genotypes - phenotypes. Complex, interacting pathways lead to final phenotype.
#ASHG20 XX Many steps exist between RNA expression to degradation. Alternative polyadenylation. Alternative isoforms. RNA editing. From same DNA sequence diverse spectrum of RNA molecules can be produced.
#ASHG20 HYC RNA localizatin is both a prevalent phenomenon and an important one. Variation that affects RNA localization can lead to phenotypic differences.
#ASHG20 HYC If you understand where RNA is going you can understand more about what it does.
Finally, Margot Cousin presents on "Impairment of the mitochondrial one-carbon metabolism enzyme SHMT2 causes a novel brain and heart developmental syndrome" #ASHG20
SHMT2 - encodes mitochondrial serine hydroxymethyltransferase 2. Key roles in amino acid metabolism and folic acid pathways, as well as mitochondrial respiration and protein translocation #ASHG20
Identified 4 individuals with biallelic SHMT2 variants. One individual has a variant disrupting a splice site. Other variants are missense on highly conserved residues, and are absent/extremely rare in gnoMAD. Variable dysmorphic features. Others incl. developmental delay #ASHG20
#ASHG20 MAC
Impairment of the mitochondrial one-carbon metabolism enzyme SHMT2 causes a novel brain and heart developmental syndrome.
Margot A. Cousin.
Impairment of the mitochondrial one-carbon metabolism enzyme SHMT2 causes a novel brain and heart developmental syndrome.
Margot A. Cousin.
#ASHG20 MAC SHMT2 encodes the mitochrondrial serine hydroxymethyltransferase 2. Loss embryonic lethal in mice. Both mitochondrial and cytosolic functions.
#ASHG20 MAC [ primarily mitochondrial though. ] Individuals with biallelic SHMT2 variants - 5 individuals with similar phenotypes from 4 families.
#ASHG20 HCM
Increased p4EBP1 underlies ALS pathology associated to P56S mutant VAPB.
Helen Cristina Miranda.
Increased p4EBP1 underlies ALS pathology associated to P56S mutant VAPB.
Helen Cristina Miranda.
#ASHG20 HCM Amyotrophic lateral sclerosis (ALS). Most common type of adult-onset motor neuron disease. About 50% survive past 3rd year diagnosis. 10% familial. 90% sporadic.
#ASHG20 HCM Involves both upper and lower motor neurons. Many genes associated with ALS. >25 genes associated with familial, sporadic, or both versions.
Next up is Helen Miranda discussing "Increased p4EBP1 underlies ALS pathology associated to P56S mutant VAPB" #ASHG20
ALS is the most common adult-onset neurodegenerative disorder. 50% of patients do not survive beyond third year of diagnosis. Pathophysiology across upper and lower motor neurones. 90% of cases are sporadic in presentation. #ASHG20
Mutations in >25 genes have been associated in ALS. Focus on VAPB. Highly conserved gene that is ubiquitously expression. P56S mutation is the causative gene for ALS type 8 - mostly identified in Brazilian population, but has been identified globally. #ASHG20
#ASHG20 VF
Impaired eIF5A function causes a craniofacial-neurodevelopmental syndrome that is partially rescued in model systems by spermidine.
Victor Faundes.
Impaired eIF5A function causes a craniofacial-neurodevelopmental syndrome that is partially rescued in model systems by spermidine.
Victor Faundes.
#ASHG20 VF by trio whole exome find de novo heterozygous frameshift in EF15A in a patient with a syndrome similar to Kabuki syndrome.
#ASHG20 VF Used Gene Matcher to find additional patients with similar phenotypic featurs. Find additional EIF5A variants in these patients. Developmental delay. Microcephaly, micrognathia.
Next up is Victor Faundes, who will talk about Impaired eIF5A function causes a craniofacial-neurodevelopmental syndrome that is partially rescued in model systems by spermidine #ASHG20
EIF5A was identified as a candidate developmental disorder gene through WES. Used the DDD resource to identify a further 6 individuals with EIF5A variants, defined a novel syndrome of developmental delay and other features #ASHG20
EIF5A resolves ribosomal stalling caused by polyproline tracts. Aimed to understand how this is disrupted by the variants seen in patients. Haploinsufficiency is the most likely mechanism #ASHG20
Slightly late into the fourth plenary: David Blair discussing "Common genetic variants associated with Mendelian disease severity revealed through cryptic phenotype analysis" #ASHG20
Cryptic phenotypes are phenotypes that underlie mendelian diseases, but which are not observed. For some, this will be a liability-threshold model (mendelian as extreme of normal range), but for others it will be a phenotypic outlier model (mendelian as truly separate) #ASHG20
Need models that differentiate between the models. May be morbidity-dependent genetic modifiers - e.g. may not see effects looking at the average of the population, but may see it at the extreme percentiles of severity #ASHG20
#ASHG20 DB
Common genetic variants associated with Mendelian disease severity revealed through cryptic phenotype analysis.
David Blair.
Common genetic variants associated with Mendelian disease severity revealed through cryptic phenotype analysis.
David Blair.
#ASHG20 DB Clinical heterogeneity is common rare Mendelian-like diseases. [ I'd go further and say that variation is rule. Just blanket variability is the rule. ]
#ASHG20 DB Looked at morbidity-dependent model for quantitative traits (MDGM). Cryptic phenotype inference (CPA).
#ASHG20 EDF
Transcription factor regulation of genetic variant effects across tissues and individuals.
Elise D. Flynn.
@EliseScience
Transcription factor regulation of genetic variant effects across tissues and individuals.
Elise D. Flynn.
@EliseScience
#ASHG20 EDF Know that eQTLS are enriched in cis-regulatory elements. Can be context specific, where effect is only seen with certain stimulations. May be seen in many contexts with variable effects.
#ASHG20 EDF eQTLs may be exerting effects by transcription factor binding. i.e. some alleles have higher affinity for binding to TFs. Can also think about this effect at different expression levels of transcription factors. i.e. minimum threshold of TF expression to see effect.
Elise Flynn will end the session, talking about "Transcription factor regulation of genetic variant effects across tissues and individuals" #ASHG20
Genetic variants associated with gene expression = eQTL #ASHG20
eQTLs can be context specific, whether in terms of effect size or the presence/absence of an effect. Know that eQTLs are enriched in TF binding sites. Suggests that modifications to TF binding are a major mechanism by which genetic variation regulates gene expression #ASHG20
Next is Xiaolei Zhang, discussing "Annotating high-impact 5'UTR variants with the UTRannotator"
The translation of upstream open reading frames can reduce the expression of genes considerably. Can have overlapping uORF, out of frame or in frame depending on where the stop coding of the uORF lies #ASHG20
uORF perturbing variants can be disease-causing. they are under strong negative selection and appear to cause disease through LoF of genes. #ASHG20
#ASHG20 XZ
Annotating high-impact 5 prime untranslated region variants with the UTRannotator.
Xiaolei Zhang.
@xiaolei_gene
GitHub repo:
bit.ly/34EHExc
Annotating high-impact 5 prime untranslated region variants with the UTRannotator.
Xiaolei Zhang.
@xiaolei_gene
GitHub repo:
bit.ly/34EHExc
#ASHG20 XZ Upstream open reading frames (uORFs) can exist upstream of the main coding sequence of a protein. Interested in variants that perturb upstream open reading frames, bc uORFs have been shown to affect expression of the protein-coding gene they are associated with.
#ASHG20 XZ Overlapping uORFs have a STOP after the start of the protein coding gene (oORFs). uORF variants can be disease causing. uORFs are under strong negative selection. Stronger selection over oORFs. Match in the Kozak consensus is important and can cause LoF when altered.
#ASHG20 BH
Inference of fitness effects of short tandem repeat polymorphisms improves functional categorization.
Bonnie Huang.
Inference of fitness effects of short tandem repeat polymorphisms improves functional categorization.
Bonnie Huang.
#ASHG20 BH
@b_b_huang
Looking at short tandem repeats (STRs). 1-6 bp repeat unit. 1.6 M loci in human genome. Implicated in >40 disorders.
@b_b_huang
Looking at short tandem repeats (STRs). 1-6 bp repeat unit. 1.6 M loci in human genome. Implicated in >40 disorders.
#ASHG20 BH STRs are highly polymorphic. Hard to distinguish from benign and de novo STR mutations. Harder to interpret than SNVs in general.
Next is Bonnie Huang discussing "Inference of fitness effects of short tandem repeat polymorphisms improves functional categorisation" #ASHG20
STRS are DNA sequences with repeated 1-6 base pair motifs. About 1.6M in human genome. Repeat number differs between individuals #ASHG20
Discussing the logic underlying the SISTR method. Challenging to determine the pathogenicity of STR mutations. STRs harder to interpret than (coding) SNVs - adding extra amino acids has less clear an effect than removing or altering them #ASHG20
#ASHG20 EM
Personalized regulatory genomics: Identifying gene dysregulation to solve undiagnosed rare disease cases.
Evonne McArthur.
Personalized regulatory genomics: Identifying gene dysregulation to solve undiagnosed rare disease cases.
Evonne McArthur.
#ASHG20 EM Most patients with a rare genetic disease have no diagnosis. The undiagnosed disease network (UDN) helps to solve some of these cases. About 35% solved.
#ASHG20 EM Commonly think that coding changes lead to alterations in protein structure. But how to you identify and interpret variants that are not coding? Gene regulatory mutations are harder. May have tissue and time-specific effect. Can you skip some of these challenges?
Next Evonne McArthur will discuss "Personalised regulatory genomics: identifying gene dysregulation to solve undiagnosed rare disease cases" #ASHG20
UDM - undiagnosed diseases network. Genetic diagnosis approach resolves ~35% of diagnosis. These lead to changes in patient treatment and understanding of their diseases #ASHG20
Most genetic diagnosis is done through examining coding mutation, but increasingly interested in understanding (non-coding) variant effects on the transcriptome #ASHG20
Next up is Jill Moore - talking about "Cell type-specific regulatory landscapes defined across murine brain development reveal novel biological insights for genetic variants associated with neuropsychiatric disorders" #ASHG20
ENCODE consortium recently published a dataset of candidate cis-regulatory elements across mouse and human genomes. Mouse data is unique because it was a coordinated effort across labs for 8 developmental stages and 12 tissues - enables integrative analysis #ASHG20
Mouse data matrix is much richer than for human. Keen to use mouse data to inform studies of human. See homologous CCREs, CCREs that map only, and CCREs that don't map. Most PLS[?] CCREs map to human genome. Distal enhancers map more poorly #ASHG20
#ASHG20 VAY
The added value of RNA sequencing over WES for variant interpretation and diagnosis of patients with rare genetic disorders.
Vicente A. Yepez.
The added value of RNA sequencing over WES for variant interpretation and diagnosis of patients with rare genetic disorders.
Vicente A. Yepez.
#ASHG20 VAY 50-75% of rare genetic disease patients don't get a diagnosis after whole exome. Either not found reasonable variants, or variants are of uncertain significance.
#ASHG20 VAY Example of mitochondrial disease. Prevalence ~1/5000. Disruptions in energy metabolism.
I'm in the Computational Methods... session on the final day of #ASHG20 The first speaker is Vincente Yepez, who will talk about "The added value of RNA sequencing over WES for variant interpretation and diagnosis of patient with rare genetic disorders"
50-75% of patients with rare diseases remain undiagnosed after WES. WGS gives all the variants, but not interpretable. VY will talk about using RNAseq to help diagnose. Focusses particularly on mitochondrial disorders #ASHG20
RNAseq can be used to resolve diagnoses in 10-15% of individuals with WES-undiagnosed mitochondrial disorders. Use a method called OUTRIDER to identify outlying gene expression signatures. Outliers are enriched for genes with rare LoF and aberrant splicing variants #ASHG20
Survived another ASHG plenary talk :)
In case you missed it, I presented results on behalf of @Regeneron from a trans-ancestry #COVID19 meta-analysis of common and rare variants + gene burden tests in >883k imputed samples and >592k exomes.
#ASHG20
In case you missed it, I presented results on behalf of @Regeneron from a trans-ancestry #COVID19 meta-analysis of common and rare variants + gene burden tests in >883k imputed samples and >592k exomes.
#ASHG20
Using REGENIE developed by @joellembatchou and @marchini (SAIGE gave us some bizarre results with rare variants) to run our common and rare variant GWASes, we found 2 loci associated with susceptibility and 3 loci with hospitalization. #ASHG20
Curiously, despite losing ~75% of the cases, we found more loci with hospitalization than using all COVID19 positive individuals - @covid19_hgi sees the same pattern.
One might suspect a severe COVID19 GWAS would be even more powerful at the same sample size
#ASHG20
One might suspect a severe COVID19 GWAS would be even more powerful at the same sample size
#ASHG20
Up next in the first #ASHG20 plenary session is my former Daly lab colleague, @HHeyne, presenting work from @FinnGen_FI on "Recessive effects of 82,516 coding variants in 176,899 Finns."
Bottleneck in Finland makes the Finnish population and @FinnGen_FI ideal for understanding ultra-rare variants that stochastically rose in frequency #ASHG20
Using SAIGE, ran GWAS using 1) a recessive model and 2) additive model on all coding variants in @FinnGen_FI.
For the majority of coding variants, additive model performs better. However, the recessive model performed 2x better for some variants. #ASHG20
For the majority of coding variants, additive model performs better. However, the recessive model performed 2x better for some variants. #ASHG20
