nirantk/geneticsQA-train huggingface dataset:
Question: What is the role of neurexins in forming transsynaptic interactions at the presynapse?

Context:
Neurexins and neuroligins are two distinct families of single-pass transmembrane proteins localized at pre- and postsynapses, respectively. 
presynaptic neurexins
best-characterized transsynaptic interactions are formed by presynaptic neurexins, which bind to diverse postsynaptic ligands.
presynaptic neurexin

Answer: Neurexins play a key role in forming transsynaptic interactions at the presynapse by binding to diverse postsynaptic ligands, making them the best-characterized transsynaptic interactions.
Question: What is the methodological principle of ChIA-PET?

Context:
Overall we show that ChIA-PET is the cornerstone to explore the three-dimensional (3D) chromatin structure, and certainly will lead the forthcoming wave of 3D genomics studies.
Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) is a new technology to study genome-wide long-range chromatin interactions bound by protein factors. 
Chromatin Interaction Analysis using Paired-End Tag sequencing (ChIA-PET) is a method which converts functional chromatin structure into millions of short tag sequences. Combining Chromatin Immunoprecipitation (ChIP), proximity ligation and high-throughput sequencing, ChIA-PET provides a global and unbiased interrogation of higher-order chromatin structures associated with specific protein factors.
Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) was developed to identify these higher-order chromatin structures
 ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. 
Proximity ligation assays commonly known as chromosome conformation capture (3C) and 3C based methodologies (e.g., GCC, HiC and ChIA-Pet) are increasingly being incorporated into empirical studies to investigate the role that three-dimensional genome structure plays in the regulation of phenotype.

Answer: Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) is a new technology to study genome-wide long-range chromatin interactions bound by protein factors. To minimize non-specific noise and reduce complexity, as well as to increase the specificity of the chromatin interaction analysis, chromatin immunoprecipitation (ChIP) is used against specific protein factors to enrich chromatin fragments of interest before proximity ligation. Combining Chromatin Immunoprecipitation (ChIP), proximity ligation and high-throughput sequencing, ChIA-PET provides a global and unbiased interrogation of higher-order chromatin structures associated with specific protein factors. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall.
Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET) is a new technology to study genome-wide long-range chromatin interactions bound by protein factors. It converts functional chromatin structure into millions of short tag sequences. By combining Chromatin Immunoprecipitation (ChIP), proximity ligation and high-throughput sequencing, ChIA-PET provides a global and unbiased interrogation of higher-order chromatin structures associated with specific protein factors.
Question: Which dediodinases are present in kidney?

Context:
Iodothyronine deiodinase in vitro activity studies in the chicken showed the presence of type I and type III iodothyronine deiodinase activity in both liver and kidney.
Co-expression of the deiodinases was also found in the kidney.
high ID-I activities were found in liver, kidney
the kidney microsome 5'-deiodinase is type I.

Answer: Type 1 and  Type 3 deiodinases are both present in liver
Exact answer: Type 1 deiodinase, Tipe 3 deiodinase
Question: Is there any algorithm for enhancer identification from chromatin state?

Context:
RFECS: a random-forest based algorithm for enhancer identification from chromatin state.
However, only a limited number of cell types or chromatin marks have previously been investigated for this purpose, leaving the question unanswered whether there exists an optimal set of histone modifications for enhancer prediction in different cell types. Here, we address this issue by exploring genome-wide profiles of 24 histone modifications in two distinct human cell types, embryonic stem cells and lung fibroblasts. We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin States) to integrate histone modification profiles for identification of enhancers, and used it to identify enhancers in a number of cell-types. We show that RFECS not only leads to more accurate and precise prediction of enhancers than previous methods, but also helps identify the most informative and robust set of three chromatin marks for enhancer prediction.
We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin States) to integrate histone modification profiles for identification of enhancers, and used it to identify enhancers in a number of cell-types.
Here, we address this issue by exploring genome-wide profiles of 24 histone modifications in two distinct human cell types, embryonic stem cells and lung fibroblasts. We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin States) to integrate histone modification profiles for identification of enhancers, and used it to identify enhancers in a number of cell-types. 
ChromaGenSVM selects optimum combinations of specific histone epigenetic marks to predict enhancers. 
We developed a Random-Forest based algorithm, RFECS (Random Forest based Enhancer identification from Chromatin States) to integrate histone modification profiles for identification of enhancers, and used it to identify enhancers in a number of cell-types.

Answer: yes
Yes. RFECS is a random-forest based algorithm for enhancer identification from chromatin state. It integrates histone modification profiles for the identification of enhancers, and can be used to identify enhancers in a number of cell-types. RFECS not only leads to more accurate and precise prediction of enhancers than previous methods, but also helps identify the most informative and robust set of three chromatin marks for enhancer prediction.
Exact answer: yes
Question: Are mutations in the C9orf72  gene associated with macular degeneration?

Context:
Over the years, however, growing evidence from clinical, pathological and genetic findings has suggested that ALS and FTD belong to the same clinic-pathological spectrum disorder. This concept has been further supported by the identification of the most common genetic cause for both diseases, an aberrantly expanded hexanucleotide repeat GGGGCC/ CCCCGG sequence located in a non-coding region of the gene C9orf72.
Amyotrophic lateral sclerosis (ALS) is characterized by motor neurone loss resulting in muscle weakness, spasticity and ultimately death. 5-10% are caused by inherited mutations, most commonly C9ORF72, SOD1, TARDBP and FUS.
In this article, we will review the brief characterizations of the C9ORF72 gene, the expansion mutations, the related disorders, and their features, followed by a discussion of the deficiency knowledge of C9ORF72 mutations.
Mutations in the C9ORF72 gene may be a major cause not only of frontotemporal dementia with motor neuron disease but also of late onset psychosis.
Frontotemporal lobar degeneration (FTLD) is a genetically heterogenous syndrome and has been associated most recently with a hexanucleotide repeat expansion within the C9ORF72 gene.
An expanded GGGGCC hexanucleotide repeat in C9ORF72 is the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal lobar degeneration associated with TDP-43 pathology (FTLD-TDP).
Novel TARDBP sequence variant and C9ORF72 repeat expansion in a family with frontotemporal dementia.
There was, as expected, a significant association between C9ORF72 mutations and presence of motor neuron disease.
Expansion of a hexanucleotide repeat in the C9ORF72 gene has been identified as the most common pathogenic mutation in families with autosomal dominant frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis.
C9ORF72 hexanucleotide repeat number in frontotemporal lobar degeneration: a genotype-phenotype correlation study.
Hexanucleotide repeat expansions in chromosome 9 open reading frame 72 (C9orf72) have recently been linked to frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis, and may be the most common genetic cause of both neurodegenerative diseases.
studies recently identified a GGGGCC hexanucleotide repeat expansion in a non-coding region of the chromosome 9 open-reading frame 72 gene (C9ORF72) as the cause of chromosome 9p-linked amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD).
GGGGCC hexanucleotide repeat expansion in the C9ORF72 gene was recently identified as an important cause of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia in Caucasian populations.

Answer: Amyotrophic lateral sclerosis (ALS) is characterized by motor neurone loss resulting in muscle weakness, spasticity and ultimately death. 5-10% are caused by inherited mutations, most commonly C9ORF72, SOD1, TARDBP and FUS.
Exact answer: no
Question: Is there an association between TERT promoter mutation and survival of glioblastoma patients?

Context:
Glioblastoma patients with TERT mutations showed a shorter survival than those without TERT mutations in univariate analysis (median, 9.3 vs. 10.5 months; P = 0.015) and multivariate analysis after adjusting for age and gender (HR 1.38, 95 % CI 1.01-1.88, P = 0.041). However, TERT mutations had no significant impact on patients' survival in multivariate analysis after further adjusting for other genetic alterations, or when primary and secondary glioblastomas were separately analysed. These results suggest that the prognostic value of TERT mutations for poor survival is largely due to their inverse correlation with IDH1 mutations, which are a significant prognostic marker of better survival in patients with secondary glioblastomas.
Patients with tumors lacking hTERT expression/TA showed a significant survival benefit (Kaplan-Meier test, both P < .01), which, however, was based exclusively on the younger patient subgroup (≤60 y, both P < .005; >60 y, both ns). 
Glioblastoma patients with TERT mutations showed a shorter survival than those without TERT mutations in univariate analysis (median, 9.3 vs

Answer: Telomerase reverse transcriptase (TERT) promoter are associated with shorter survival of glioblastoma patients. Prognostic value of TERT mutations for poor survival is largely due to their inverse correlation with IDH1 mutations.
Exact answer: yes
Question: What is the biological role of expansins in fungi?

Context:
interactions with alpha-expansin in cell wall extension and polysaccharide degradation
cell wall swelling may not be a significant event during the action of expansin and hydrolases
To evaluate a putative implication of three newly identified expansin/family 45 endoglucanase-like (EEL) proteins in lignocellulose degradation
Our results show that EglD is a conidial cell wall localized expansin-like protein, which could be involved in cell wall remodeling during germination
Swollenin, a protein first characterized in the saprophytic fungus Trichoderma reesei, contains an N-terminal carbohydrate-binding module family 1 domain (CBD) with cellulose-binding function and a C-terminal expansin-like domain
alpha-Expansins are extracellular proteins that increase plant cell-wall extensibility
these wall-loosening proteins are directly involved in the accommodation of the fungus by infected cortical cells

Answer: Expansins are extracellular proteins that increase plant cell-wall extensibility. These wall-loosening proteins are involved in cell wall extension and polysaccharide degradation. In fungi expansins and expansin-like proteins have been found to localize in the conidial cell wall and are probably involved in cell wall remodeling during germination.
Question: What is the association between proBNP serum concentrations and stroke outcomes?

Context:
N-terminal probrain natriuretic peptide levels as a predictor of functional outcomes in patients with ischemic stroke.
There was a strong positive correlation between the plasma level of NT-proBNP and the National Institutes of Health Stroke Scale score (r=0.415, P=0.000). Plasma levels of NT-proBNP in patients with an unfavorable outcome were significantly higher than those in patients with a favorable outcome [3432 (interquartile range, 1100-54991) vs. 978 (interquartile range, 123-1705) pg/ml; P=0.000]. In multivariate analyses, after adjusting for all other significant outcome predictors, the NT-proBNP level that remained can be seen as an independent unfavorable outcome predictor, with an adjusted odds ratios of 4.14 (95% confidence interval, 2.72-7.99; P=0.000). Our results show that plasma NT-proBNP levels were significantly elevated in patients with an unfavorable outcome and might be of clinical importance as a supplementary tool for the assessment of functional outcomes in patients with AIS.
Plasma levels of BNP, NT-proBNP, cortisol and copeptin were associated with stroke severity, as well as short-term functional outcomes. After adjusting for all other significant outcome predictors, NT-proBNP, cortisol and copeptin remained as independent outcome predictors. In the receiver operating characteristic curve analysis, the biomarker panel (including BNP, NT-proBNP, cortisol and copeptin) predicted functional outcome and death within 90 days significantly more efficiently than the National Institute of Health Stroke Scale (NIHSS) or the biomarker alone.
The NT-proBNP levels were significantly higher at 4 intervals after ischemic stroke than in healthy and at-risk control subjects (all p<0.001). 
Multivariate analysis demonstrated that age and NIH Stroke Scale were the 2 strongest independent predictors of increased NT-proBNP levels (all p<0.01). Furthermore, increased NT-proBNP (> or = 150 pg/ml) was the strongest independent predictor of long-term (mean follow-up: 24 months) UFCO (26 patients) (all p<0.05). CONCLUSIONS: The NT-proBNP level was markedly elevated after acute ischemic stroke and declined substantially thereafter. An increased NT-proBNP level was strongly and independently correlated with UFCO in patients after ischemic stroke.

Answer: ProBNP serum concentrations are elevated in stroke patients relative to healthy controls. Greater proBNP serum concentrations are associated with greater stroke severity and with increased risk for unfvorable functional outcomes.
Question: Is CD84 genetically associated with arthritis?

Context:
The SNP is predicted to disrupt transcription factor binding site motifs in the 3' UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1 × 10(-11) in 228 non-RA patients and P = 0.004 in 132 RA patients)
Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity
 Three members of this gene family, Ly108, Ly9, and CD84, exhibit polymorphisms that strongly influence susceptibility to systemic autoimmunity, notably in mice, but also in some human populations

Answer: Three members of this gene family, Ly108, Ly9, and CD84, exhibit polymorphisms that strongly influence susceptibility to systemic autoimmunity, notably in mice, but also in some human populations. Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with Rheumatoid Arthritis disease activity.
Exact answer: yes
Question: Which R package is used for the analysis of genome-wide DNA methylation profiles?

Context:
methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles.
 Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation.
Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments.
methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles
Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation
Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation.
methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles.

Answer: MethylKit is a comprehensive R package for the analysis of genome-wide DNA methylation profiles. MethylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation.
Exact answer: methylKit
Question: Which genes were found to be methylated in bladder cancer cells?

Context:
CpG island in promoter of hepaCAM gene was hyper-methylated both in bladder carcinoma tissues and cell lines (T24 and BIU-87). Otherwise, aberrant methylation of its promoter was associated with its decreased expression.
Abnormal hypermethylation in CpG island of hepaCAM promoter is involved in absence of hepaCAM gene expression when bladder cancer occurs.
Methylated RARβ(2) and APC were significantly higher in bladder cancer patients (62.8%, 59.5%) than benign (16.4%, 5%) but not detected in healthy volunteers (0%) at (P < 0.0001).
Among the 128 patients with bilharzial bladder cancer, 94 (73.4%) showed methylated RARβ(2) and 86 (67.2%) showed methylated APC.
Thus, methylated RARβ(2) and APC genes might be valuable urinary molecular markers for early detection of bilharzial and nonbilharzial bladder cancer.
Exon 2 methylation inhibits hepaCAM expression in transitional cell carcinoma of the bladder
the expression of hepaCAM was absent in T24 and BIU-87 cells, and we found that exon 2 of hepaCAM was methylated in the 2 cells.
hepaCAM mRNA was re-expressed and the methylation status of hepaCAM exon 2 was reversed after treatment with 5-Aza-CdR.
The methylation rate of hepaCAM exon 2 was significantly higher in bladder cancer tissues than in adjacent tissues.
Recently, methylation of the TPEF (transmembrane protein containing epidermal growth factor and follistatin domain) gene was reported in human colon, gastric, and bladder cancer cells.
Hypermethylation of at least one of three suppressor genes (APC, RASSF1A, and p14(ARF)) was found in all 45 tumor DNAs (100% diagnostic coverage).
Methylation of the CpG island in the promoter of the p16 gene in human bladder cancer cells did not stop the formation of a transcript initiated 20 kb upstream by the p19 promoter but did prevent the expression of a p16 transcript.
We also present the first functional evidence that methylation of only a small number of CpG sites can significantly down-regulate p16 promoter activity, thus providing support for the model of progressive inactivation of this tumor suppressor gene by DNA methylation.
Hypermethylation of hepaCAM gene was reversed and expression of its mRNA and protein were re-activated in two cell lines by DNA methyltransferases inhibitor 5-aza-CdR

Answer: In bladder cancer, hepaCAM (hepatocyte cell adhesion molecule), RARβ(2), APC, TPEF (transmembrane protein containing epidermal growth factor and follistatin domain), RASSF1A, p14(ARF) and p16 genes were found to be methylated. These methylation events were demostrated to associate with downregulation of gene expression.
Exact answer: hepaCAM (hepatocyte cell adhesion molecule)
RARβ(2)
APC
TPEF (transmembrane protein containing epidermal growth factor and follistatin domain)
RASSF1A
p14(ARF)
p16
Question: Which signaling pathway is activating the dishevelled proteins?

Context:
Wnt signaling is known to be important for diverse embryonic and post-natal cellular events and be regulated by the proteins Dishevelled and Axin. Although Dishevelled is activated by Wnt and involved in signal transduction, it is not clear how Dishevelled-mediated signaling is turned off. 
The Dishevelled protein mediates several diverse biological processes. Intriguingly, within the same tissues where Xenopus Dishevelled (Xdsh) controls cell fate via canonical Wnt signaling,
Dishevelled (DVL) proteins, three of which have been identified in humans, are highly conserved components of canonical and noncanonical Wnt signaling pathways.

Answer: Dishevelled (Xdsh) controls cell fate via canonical Wnt signaling
Exact answer: Wnt signaling
Question: Which is the physiological target for LeuRS translational quality control?

Context:
The physiological target for LeuRS translational quality control is norvaline.
The physiological target for LeuRS translational quality control is norvaline
Rather, as shown by kinetic, structural and in vivo approaches, the prime biological function of LeuRS editing is to prevent mis-incorporation of the non-standard amino acid norvaline

Answer: QUALITY CONTROL
The physiological target for LeuRS translational quality control is norvaline.
The fidelity of protein synthesis depends on the capacity of aminoacyl-tRNA synthetases (AARSs) to couple only cognate amino acid-tRNA pairs. If amino acid selectivity is compromised, fidelity can be ensured by an inherent AARS editing activity that hydrolyses mischarged tRNAs. Rather, as shown by kinetic, structural and in vivo approaches, the prime biological function of LeuRS editing is to prevent mis-incorporation of the non-standard amino acid norvaline.
Exact answer: Norvaline